diff --git a/.github/workflows/namespace_exports.yml b/.github/workflows/namespace_exports.yml index bc4fe0da079f..0ef90162b160 100644 --- a/.github/workflows/namespace_exports.yml +++ b/.github/workflows/namespace_exports.yml @@ -21,6 +21,12 @@ name: namespace_exports # Workflow triggers: on: + pull_request_target: + branches: + - develop + types: + - closed + # Allow the workflow to be manually run: workflow_dispatch: diff --git a/.mailmap b/.mailmap index 6b3543971592..7b5a845ca611 100644 --- a/.mailmap +++ b/.mailmap @@ -76,9 +76,6 @@ Matt Cochrane Mihir Pandit <129577900+MSP20086@users.noreply.github.com> MSP20086 -Muhammad Haris <101793258+headlessNode@users.noreply.github.com> -Muhammad Haris headlessNode - # N Naresh Jagadeesan <37257700+Infinage@users.noreply.github.com> diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 12e6f49663dd..b637fec9ecab 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -118,17 +118,7 @@ Create a [GitHub account][github-signup]. The project uses GitHub exclusively fo $ git clone https://github.com//stdlib.git ``` -where `` is your GitHub username. When cloning, avoid cloning to a directory having spaces in its path. Because this project relies heavily on `make`, any spaces in the directory path will lead to errors and inevitable frustration. - -```text -// Bad: -/home/foo/bar/beep boop/stdlib - -// Good: -/home/foo/bar/beep_boop/stdlib -``` - -The repository has a large commit history, leading to slow download times. You can reduce the download time by limiting the clone [depth][git-clone-depth]. +where `` is your GitHub username. The repository has a large commit history, leading to slow download times. You can reduce the download time by limiting the clone [depth][git-clone-depth]. @@ -162,27 +152,7 @@ And finally, add an `upstream` [remote][git-remotes] to allow syncing changes be $ git remote add upstream git://github.com/stdlib-js/stdlib.git ``` -#### Step 2: Initial Setup - -Install dependencies. - - - -```bash -$ make install -``` - -Initialize Git hooks to enable automated development processes to run prior to authoring commits and pushing changes. - - - -```bash -$ make init -``` - -Note that `make init` only needs to be run once; however, we repeat it below as **not** running it is a common omission by new contributors. - -#### Step 3: Branch +#### Step 2: Branch For modifications intended to be included in stdlib, create a new local branch. @@ -194,11 +164,11 @@ $ git checkout -b where `` is the branch name. Both the `master` and `develop` branches for the main stdlib project are protected, and direct modifications to these branches will **not** be accepted. Instead, all contributions should be made on non-master and non-develop local branches, including documentation changes and other non-code modifications. See the project [branching guide][stdlib-branching] for additional guidance. -#### Step 4: Write +#### Step 3: Write Start making your changes and/or implementing the new feature. Any text you write should follow the [text style guide][stdlib-style-guides-text], including comments and API documentation. -#### Step 5: Commit +#### Step 4: Commit Ensure that you have configured [Git][git] to know your name and email address. @@ -220,7 +190,7 @@ $ git commit When writing commit messages, follow the Git [style guide][stdlib-style-guides-git]. Adherence to project commit conventions is necessary for project automation which automatically generates release notes and changelogs from commit messages. -#### Step 6: Sync +#### Step 5: Sync To incorporate recent changes from the `upstream` repository during development, you should [rebase][git-rebase] your local branch, reapplying your local commits on top of the current upstream `HEAD`. This procedure is in contrast to performing a standard [merge][git-merge], which may interleave development histories. The rationale is twofold: @@ -236,13 +206,11 @@ $ git fetch upstream $ git rebase upstream/develop ``` -#### Step 7: Test +#### Step 6: Test Tests should accompany **all** bug fixes and features. For guidance on how to write tests, consult existing tests within the project. -**Before** submitting a [pull request][github-pull-request] to the `upstream` repository, ensure that all tests pass, including linting. To run tests locally, consult the guidance [below](#writing-tests). - -If [Git][git] hooks have been enabled, +**Before** submitting a [pull request][github-pull-request] to the `upstream` repository, ensure that all tests pass, including linting. If [Git][git] hooks have been enabled, @@ -254,7 +222,7 @@ linting should be automatically triggered prior to each commit, and test executi Any [pull requests][github-pull-request] which include failing tests and/or lint errors will **not** be accepted. -#### Step 8: Push +#### Step 7: Push Push your changes to your remote GitHub repository. @@ -266,7 +234,7 @@ $ git push origin where `` is the name of your branch. -#### Step 9: Pull Request +#### Step 8: Pull Request Once your contribution is ready to be incorporated in the `upstream` repository, open a [pull request][github-pull-request] against the `develop` branch. One or more project contributors will review the contribution, provide feedback, and potentially request changes. @@ -312,13 +280,13 @@ $ git commit -m "fixup! feat: add support for computing the absolute value" If the history needs modification, a contributor will modify the history during the merge process. The rationale for **not** rewriting public history is that doing so invalidates the commit history for anyone else who has pulled your changes, thus imposing additional burdens on collaborators to ensure that their local versions match the modified history. -#### Step 10: Land +#### Step 9: Land After any changes have been resolved and continuous integration tests have passed, a contributor will approve a [pull request][github-pull-request] for inclusion in the project. Once merged, the [pull request][github-pull-request] will be updated with the merge commit, and the [pull request][github-pull-request] will be closed. Note that, during the merge process, multiple commits will often be [squashed][git-rewriting-history]. -#### Step 11: Celebrate +#### Step 10: Celebrate **Congratulations**! You are an official contributor to stdlib! Thank you for your hard work and patience! @@ -348,7 +316,7 @@ The project can **never** have enough tests. To address areas lacking sufficient ```bash - $ make TESTS_FILTER=".*//.*" test + $ make TESTS_FILTER=.*//.* test ``` where `` is a pattern matching a particular path. For example, to test the base math `sin` package @@ -356,7 +324,7 @@ The project can **never** have enough tests. To address areas lacking sufficient ```bash - $ make TESTS_FILTER=".*/math/base/special/sin/.*" test + $ make TESTS_FILTER=.*/math/base/special/sin/.* test ``` where the pattern `.*/math/base/special/sin/.*` matches any test file whose absolute path contains `math/base/special/sin`. @@ -366,7 +334,7 @@ The project can **never** have enough tests. To address areas lacking sufficient ```bash - $ make TESTS_FILTER=".*//.*" test-cov + $ make TESTS_FILTER=.*//.* test-cov $ make view-cov ``` @@ -374,16 +342,6 @@ The project can **never** have enough tests. To address areas lacking sufficient 7. Submit the test as a [pull request][github-pull-request]. -Note that, for contributions targeting C implementations, you'll need to first compile the native add-on which provides the bridge between JavaScript and C (assuming that the package has a native add-on binding). - -```bash -$ make install-node-addons NODE_ADDONS_PATTERN="math/base/special/sin" -``` - -where the pattern `math/base/special/sin` (note the differences from the filter pattern above!) matches any add-on whose absolute path contains `math/base/special/sin`. - -Once the add-on is compiled, you can follow steps 5-7 above. - ### Writing Documentation > By contributing documentation to the project, you are agreeing to release it under the project [license][stdlib-license]. diff --git a/CONTRIBUTORS b/CONTRIBUTORS index bfb0b09e3720..6917be2bd659 100644 --- a/CONTRIBUTORS +++ b/CONTRIBUTORS @@ -10,10 +10,8 @@ Aman Bhansali Amit Jimiwal Anudeep Sanapala Athan Reines -Ayaka <73595362+USERSATOSHI@users.noreply.github.com> Brendan Graetz Bruno Fenzl -Bryan Elee Chinmay Joshi <86140365+JawHawk@users.noreply.github.com> Christopher Dambamuromo Dan Rose @@ -43,7 +41,6 @@ Matt Cochrane Mihir Pandit <129577900+MSP20086@users.noreply.github.com> Milan Raj Momtchil Momtchev -Muhammad Haris Naresh Jagadeesan Nithin Katta <88046362+nithinkatta@users.noreply.github.com> Ognjen Jevremović @@ -69,13 +66,10 @@ Shubham Mishra Snehil Shah <130062020+Snehil-Shah@users.noreply.github.com> Spandan Barve Stephannie Jiménez Gacha -Suraj kumar <125961509+kumarsuraj212003@users.noreply.github.com> -Tirtadwipa Manunggal Utkarsh Utkarsh Raj Varad Gupta Yernar Yergaziyev -naveen nishant-s7 <97207366+nishant-s7@users.noreply.github.com> orimiles5 <97595296+orimiles5@users.noreply.github.com> rei2hu diff --git a/lib/node_modules/@stdlib/array/mostly-safe-casts/README.md b/lib/node_modules/@stdlib/array/mostly-safe-casts/README.md index d6f682fab026..eef5ec369abc 100644 --- a/lib/node_modules/@stdlib/array/mostly-safe-casts/README.md +++ b/lib/node_modules/@stdlib/array/mostly-safe-casts/README.md @@ -121,17 +121,6 @@ for ( i = 0; i < DTYPES.length; i++ ) {
-* * * - -## See Also - -- [`@stdlib/array/convert`][@stdlib/array/convert]: convert an array to an array of a different data type. -- [`@stdlib/array/convert-same`][@stdlib/array/convert-same]: convert an array to the same data type as a second input array. -- [`@stdlib/array/dtypes`][@stdlib/array/dtypes]: list of array data types. -- [`@stdlib/array/safe-casts`][@stdlib/array/safe-casts]: return a list of array data types to which a provided array data type can be safely cast. -- [`@stdlib/array/same-kind-casts`][@stdlib/array/same-kind-casts]: return a list of array data types to which a provided array data type can be safely cast or cast within the same kind. -- [`@stdlib/ndarray/mostly-safe-casts`][@stdlib/ndarray/mostly-safe-casts]: return a list of ndarray data types to which a provided ndarray data type can be safely cast and, for floating-point data types, can be downcast. -
@@ -142,20 +131,6 @@ for ( i = 0; i < DTYPES.length; i++ ) { [@stdlib/array/dtypes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/dtypes - - -[@stdlib/array/convert]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/convert - -[@stdlib/array/convert-same]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/convert-same - -[@stdlib/array/safe-casts]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/safe-casts - -[@stdlib/array/same-kind-casts]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/same-kind-casts - -[@stdlib/ndarray/mostly-safe-casts]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/mostly-safe-casts - - - diff --git a/lib/node_modules/@stdlib/assert/is-nonnegative-integer/README.md b/lib/node_modules/@stdlib/assert/is-nonnegative-integer/README.md index c1ae53d42dfb..ffeb509b5e8a 100644 --- a/lib/node_modules/@stdlib/assert/is-nonnegative-integer/README.md +++ b/lib/node_modules/@stdlib/assert/is-nonnegative-integer/README.md @@ -138,8 +138,6 @@ bool = isNonNegativeInteger( null ); ## See Also - [`@stdlib/assert/is-integer`][@stdlib/assert/is-integer]: test if a value is a number having an integer value. -- [`@stdlib/assert/is-nonnegative-number`][@stdlib/assert/is-nonnegative-number]: test if a value is a number having a nonnegative value. -- [`@stdlib/assert/is-number`][@stdlib/assert/is-number]: test if a value is a number. @@ -153,10 +151,6 @@ bool = isNonNegativeInteger( null ); [@stdlib/assert/is-integer]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/assert/is-integer -[@stdlib/assert/is-nonnegative-number]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/assert/is-nonnegative-number - -[@stdlib/assert/is-number]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/assert/is-number - diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/README.md b/lib/node_modules/@stdlib/blas/ext/base/dapx/README.md index 1aadc282dbc5..3449170450a5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapx/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/README.md @@ -32,7 +32,7 @@ var dapx = require( '@stdlib/blas/ext/base/dapx' ); #### dapx( N, alpha, x, stride ) -Adds a constant `alpha` to each element in a double-precision floating-point strided array. +Adds a constant `alpha` to each element in a double-precision floating-point strided array `x`. ```javascript var Float64Array = require( '@stdlib/array/float64' ); @@ -50,14 +50,16 @@ The function has the following parameters: - **x**: input [`Float64Array`][@stdlib/array/float64]. - **stride**: index increment. -The `N` and `stride` parameters determine which elements in the strided array are accessed at runtime. For example, to add a constant to every other element +The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to add a constant to every other element ```javascript var Float64Array = require( '@stdlib/array/float64' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] ); +var N = floor( x.length / 2 ); -dapx( 4, 5.0, x, 2 ); +dapx( N, 5.0, x, 2 ); // x => [ 3.0, 1.0, 8.0, -5.0, 9.0, 0.0, 4.0, -3.0 ] ``` @@ -65,21 +67,23 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); +var floor = require( '@stdlib/math/base/special/floor' ); // Initial array... var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] ); // Create an offset view... var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var N = floor( x0.length/2 ); // Add a constant to every other element... -dapx( 3, 5.0, x1, 2 ); +dapx( N, 5.0, x1, 2 ); // x0 => [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ] ``` #### dapx.ndarray( N, alpha, x, stride, offset ) -Adds a constant `alpha` to each element in a double-precision floating-point strided array using alternative indexing semantics. +Adds a constant `alpha` to each element in a double-precision floating-point strided array `x` using alternative indexing semantics. ```javascript var Float64Array = require( '@stdlib/array/float64' ); @@ -94,7 +98,7 @@ The function has the following additional parameters: - **offset**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access only the last three elements of the strided array +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access only the last three elements of `x` ```javascript var Float64Array = require( '@stdlib/array/float64' ); @@ -113,7 +117,7 @@ dapx.ndarray( 3, 5.0, x, 1, x.length-3 ); ## Notes -- If `N <= 0`, both functions return the strided array unchanged. +- If `N <= 0`, both functions return `x` unchanged. @@ -126,11 +130,27 @@ dapx.ndarray( 3, 5.0, x, 1, x.length-3 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var round = require( '@stdlib/math/base/special/round' ); +var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); var dapx = require( '@stdlib/blas/ext/base/dapx' ); -var x = filledarrayBy( 10, 'float64', discreteUniform( -100, 100 ) ); +var rand; +var sign; +var x; +var i; + +x = new Float64Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + rand = round( randu()*100.0 ); + sign = randu(); + if ( sign < 0.5 ) { + sign = -1.0; + } else { + sign = 1.0; + } + x[ i ] = sign * rand; +} console.log( x ); dapx( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dapx/benchmark/benchmark.js index 1e2ec3f90065..a8b1105782cd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapx/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/benchmark/benchmark.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dapx = require( './../lib/dapx.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -45,8 +40,12 @@ var rand = uniform( -10.0, 10.0 ); */ function createBenchmark( len ) { var x; + var i; - x = filledarrayBy( len, 'float64', rand ); + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dapx/benchmark/benchmark.native.js index bec331f17271..c96243119938 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapx/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/benchmark/benchmark.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var dapx = tryRequire( resolve( __dirname, './../lib/dapx.native.js' ) ); var opts = { 'skip': ( dapx instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -50,8 +49,12 @@ var rand = uniform( -10.0, 10.0 ); */ function createBenchmark( len ) { var x; + var i; - x = filledarrayBy( len, 'float64', rand ); + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dapx/benchmark/benchmark.ndarray.js index 0a0fd5418756..7fccdbcd49bf 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapx/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/benchmark/benchmark.ndarray.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dapx = require( './../lib/ndarray.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -45,8 +40,12 @@ var rand = uniform( -10.0, 10.0 ); */ function createBenchmark( len ) { var x; + var i; - x = filledarrayBy( len, 'float64', rand ); + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dapx/benchmark/benchmark.ndarray.native.js index 77d9e12eeb14..ea4007141b3e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapx/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var dapx = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dapx instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -50,8 +49,12 @@ var rand = uniform( -10.0, 10.0 ); */ function createBenchmark( len ) { var x; + var i; - x = filledarrayBy( len, 'float64', rand ); + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/dapx/docs/repl.txt index 2f77bbf08b29..80e0c0b9d3aa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapx/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/docs/repl.txt @@ -3,13 +3,13 @@ Adds a constant to each element in a double-precision floating-point strided array. - The `N` and stride parameters determine which elements in the strided array - are accessed at runtime. + The `N` and `stride` parameters determine which elements in `x` are accessed + at runtime. Indexing is relative to the first index. To introduce an offset, use typed array views. - If `N <= 0`, the function returns the strided array unchanged. + If `N <= 0`, the function returns `x` unchanged. Parameters ---------- @@ -23,34 +23,40 @@ Input array. stride: integer - Index increment. + Index increment for `x`. Returns ------- x: Float64Array - Input array. + Input array `x`. Examples -------- // Standard Usage: > var x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] ); - > {{alias}}( x.length, 5.0, x, 1 ) + > var alpha = 5.0; + > {{alias}}( x.length, alpha, x, 1 ) [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ] // Using `N` and `stride` parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] ); - > {{alias}}( 3, 5.0, x, 2 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > alpha = 5.0; + > var stride = 2; + > {{alias}}( N, alpha, x, stride ) [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ] // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > {{alias}}( 3, 5.0, x1, 2 ) + > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); + > alpha = 5.0; + > stride = 2; + > {{alias}}( N, alpha, x1, stride ) [ 3.0, 3.0, 1.0, 5.0, -1.0 ] > x0 [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ] - {{alias}}.ndarray( N, alpha, x, stride, offset ) Adds a constant to each element in a double-precision floating-point strided array using alternative indexing semantics. @@ -71,26 +77,30 @@ Input array. stride: integer - Index increment. + Index increment for `x`. offset: integer - Starting index. + Starting index of `x`. Returns ------- x: Float64Array - Input array. + Input array `x`. Examples -------- // Standard Usage: > var x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] ); - > {{alias}}.ndarray( x.length, 5.0, x, 1, 0 ) + > var alpha = 5.0; + > {{alias}}.ndarray( x.length, alpha, x, 1, 0 ) [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ] // Using an index offset: > x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] ); - > {{alias}}.ndarray( 3, 5.0, x, 2, 1 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > alpha = 5.0; + > var stride = 2; + > {{alias}}.ndarray( N, alpha, x, stride, 1 ) [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ] See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/dapx/docs/types/index.d.ts index 1211a0d34637..99f90326ef7f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapx/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/docs/types/index.d.ts @@ -29,7 +29,7 @@ interface Routine { * @param alpha - constant * @param x - input array * @param stride - stride length - * @returns input array + * @returns `x` * * @example * var Float64Array = require( '@stdlib/array/float64' ); @@ -49,7 +49,7 @@ interface Routine { * @param x - input array * @param stride - stride length * @param offset - starting index - * @returns input array + * @returns `x` * * @example * var Float64Array = require( '@stdlib/array/float64' ); @@ -69,7 +69,7 @@ interface Routine { * @param alpha - constant * @param x - input array * @param stride - stride length -* @returns input array +* @returns `x` * * @example * var Float64Array = require( '@stdlib/array/float64' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/dapx/examples/index.js index 58d039e922be..55c571652632 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapx/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/examples/index.js @@ -18,11 +18,27 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var round = require( '@stdlib/math/base/special/round' ); +var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); var dapx = require( './../lib' ); -var x = filledarrayBy( 10, 'float64', discreteUniform( -100, 100 ) ); +var rand; +var sign; +var x; +var i; + +x = new Float64Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + rand = round( randu()*100.0 ); + sign = randu(); + if ( sign < 0.5 ) { + sign = -1.0; + } else { + sign = 1.0; + } + x[ i ] = sign * rand; +} console.log( x ); dapx( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/dapx/include.gypi index 26476a8c2655..868c5c12e852 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapx/include.gypi +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.c', + '<(src_dir)/addon.cpp', ' - -/** -* Receives JavaScript callback invocation data. -* -* @private -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value node_dapx( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_DOUBLE( env, alpha, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 2 ); - c_dapx( N, alpha, X, stride ); - return NULL; -} - -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/src/addon.cpp b/lib/node_modules/@stdlib/blas/ext/base/dapx/src/addon.cpp new file mode 100644 index 000000000000..7280d7e21b67 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/src/addon.cpp @@ -0,0 +1,128 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dapx.h" +#include +#include +#include +#include +#include + +/** +* Add-on namespace. +*/ +namespace stdlib_blas_ext_base_dapx { + + /** + * Adds a constant to each element in a double-precision floating-point strided array. + * + * ## Notes + * + * - When called from JavaScript, the function expects four arguments: + * + * - `N`: number of indexed elements + * - `alpha`: scalar + * - `X`: input array + * - `strideX`: `X` stride length + */ + napi_value node_dapx( napi_env env, napi_callback_info info ) { + napi_status status; + + size_t argc = 4; + napi_value argv[ 4 ]; + status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); + assert( status == napi_ok ); + + if ( argc < 4 ) { + napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); + return nullptr; + } + + napi_valuetype vtype0; + status = napi_typeof( env, argv[ 0 ], &vtype0 ); + assert( status == napi_ok ); + if ( vtype0 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); + return nullptr; + } + + napi_valuetype vtype1; + status = napi_typeof( env, argv[ 1 ], &vtype1 ); + assert( status == napi_ok ); + if ( vtype1 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); + return nullptr; + } + + bool res2; + status = napi_is_typedarray( env, argv[ 2 ], &res2 ); + assert( status == napi_ok ); + if ( res2 == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); + return nullptr; + } + + napi_valuetype vtype3; + status = napi_typeof( env, argv[ 3 ], &vtype3 ); + assert( status == napi_ok ); + if ( vtype3 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); + return nullptr; + } + + int64_t N; + status = napi_get_value_int64( env, argv[ 0 ], &N ); + assert( status == napi_ok ); + + double alpha; + status = napi_get_value_double( env, argv[ 1 ], &alpha ); + assert( status == napi_ok ); + + int64_t strideX; + status = napi_get_value_int64( env, argv[ 3 ], &strideX ); + assert( status == napi_ok ); + + napi_typedarray_type vtype2; + size_t xlen; + void *X; + status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype2 != napi_float64_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); + return nullptr; + } + if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + c_dapx( N, alpha, (double *)X, strideX ); + + return nullptr; + } + + napi_value Init( napi_env env, napi_value exports ) { + napi_status status; + napi_value fcn; + status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dapx, NULL, &fcn ); + assert( status == napi_ok ); + return fcn; + } + + NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) +} // end namespace stdlib_blas_ext_base_dapx diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/test/test.dapx.js b/lib/node_modules/@stdlib/blas/ext/base/dapx/test/test.dapx.js index 539c980f43f1..1ad083a0c40f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapx/test/test.dapx.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/test/test.dapx.js @@ -86,7 +86,7 @@ tape( 'the function returns a reference to the input array', function test( t ) t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { var expected; var x; @@ -102,7 +102,7 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu t.end(); }); -tape( 'if `alpha` equals `0`, the function returns the output array unchanged', function test( t ) { +tape( 'if `alpha` equals `0`, the function returns `x` unchanged', function test( t ) { var expected; var x; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/test/test.dapx.native.js b/lib/node_modules/@stdlib/blas/ext/base/dapx/test/test.dapx.native.js index 21e7a2240082..c90f015cb356 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapx/test/test.dapx.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/test/test.dapx.native.js @@ -95,7 +95,7 @@ tape( 'the function returns a reference to the input array', opts, function test t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', opts, function test( t ) { var expected; var x; @@ -111,7 +111,7 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu t.end(); }); -tape( 'if `alpha` equals `0`, the function returns the output array unchanged', opts, function test( t ) { +tape( 'if `alpha` equals `0`, the function returns `x` unchanged', opts, function test( t ) { var expected; var x; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dapx/test/test.ndarray.js index db2e07f0f97a..2cdbdfb45b20 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapx/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/test/test.ndarray.js @@ -86,7 +86,7 @@ tape( 'the function returns a reference to the input array', function test( t ) t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { var expected; var x; @@ -102,7 +102,7 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu t.end(); }); -tape( 'if `alpha` equals `0`, the function returns the output array unchanged', function test( t ) { +tape( 'if `alpha` equals `0`, the function returns `x` unchanged', function test( t ) { var expected; var x; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dapx/test/test.ndarray.native.js index d68862de0c82..b7bce4bd8cca 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapx/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/test/test.ndarray.native.js @@ -95,7 +95,7 @@ tape( 'the function returns a reference to the input array', opts, function test t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', opts, function test( t ) { var expected; var x; @@ -111,7 +111,7 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu t.end(); }); -tape( 'if `alpha` equals `0`, the function returns the output array unchanged', opts, function test( t ) { +tape( 'if `alpha` equals `0`, the function returns `x` unchanged', opts, function test( t ) { var expected; var x; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/README.md b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/README.md index 7ef97e680803..4ae499991c8e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/README.md @@ -44,8 +44,9 @@ Adds a constant to each double-precision floating-point strided array element an var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +var N = x.length; -var v = dapxsumkbn( 3, 5.0, x, 1 ); +var v = dapxsumkbn( N, 5.0, x, 1 ); // returns 16.0 ``` @@ -55,14 +56,16 @@ The function has the following parameters: - **x**: input [`Float64Array`][@stdlib/array/float64]. - **stride**: index increment for `x`. -The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to access every other element in `x`, +The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to access every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); +var N = floor( x.length / 2 ); -var v = dapxsumkbn( 4, 5.0, x, 2 ); +var v = dapxsumkbn( N, 5.0, x, 2 ); // returns 25.0 ``` @@ -72,11 +75,14 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var v = dapxsumkbn( 4, 5.0, x1, 2 ); +var N = floor( x0.length / 2 ); + +var v = dapxsumkbn( N, 5.0, x1, 2 ); // returns 25.0 ``` @@ -88,8 +94,9 @@ Adds a constant to each double-precision floating-point strided array element an var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +var N = x.length; -var v = dapxsumkbn.ndarray( 3, 5.0, x, 1, 0 ); +var v = dapxsumkbn.ndarray( N, 5.0, x, 1, 0 ); // returns 16.0 ``` @@ -101,10 +108,12 @@ While [`typed array`][mdn-typed-array] views mandate a view offset based on the ```javascript var Float64Array = require( '@stdlib/array/float64' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +var N = floor( x.length / 2 ); -var v = dapxsumkbn.ndarray( 4, 5.0, x, 2, 1 ); +var v = dapxsumkbn.ndarray( N, 5.0, x, 2, 1 ); // returns 25.0 ``` @@ -129,11 +138,18 @@ var v = dapxsumkbn.ndarray( 4, 5.0, x, 2, 1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float64Array = require( '@stdlib/array/float64' ); var dapxsumkbn = require( '@stdlib/blas/ext/base/dapxsumkbn' ); -var x = filledarrayBy( 10, 'float64', discreteUniform( 0, 100 ) ); +var x; +var i; + +x = new Float64Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); var v = dapxsumkbn( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/benchmark/benchmark.js index 4ff50f16bf0a..6872da33c834 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/benchmark/benchmark.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dapxsumkbn = require( './../lib/dapxsumkbn.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -44,7 +39,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x; + var i; + + x = new Float64Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/benchmark/benchmark.native.js index eda73b750834..5c0f4dc5fbc1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/benchmark/benchmark.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var dapxsumkbn = tryRequire( resolve( __dirname, './../lib/dapxsumkbn.native.js' var opts = { 'skip': ( dapxsumkbn instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -49,7 +48,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x; + var i; + + x = new Float64Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/benchmark/benchmark.ndarray.js index be58cad1369c..36a0f01dd907 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/benchmark/benchmark.ndarray.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dapxsumkbn = require( './../lib/ndarray.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -44,7 +39,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x; + var i; + + x = new Float64Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/benchmark/benchmark.ndarray.native.js index 9d41530d4779..aac2aa92684e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var dapxsumkbn = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) var opts = { 'skip': ( dapxsumkbn instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -49,7 +48,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x; + var i; + + x = new Float64Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/docs/repl.txt index e4b352bfc7da..3e7d1f3b33c3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/docs/repl.txt @@ -3,8 +3,8 @@ Adds a constant to each double-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. - The `N` and stride parameters determine which elements in the strided - array are accessed at runtime. + The `N` and `stride` parameters determine which elements in `x` are accessed + at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -39,16 +39,19 @@ // Using `N` and `stride` parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > {{alias}}( 3, 5.0, x, 2 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > var stride = 2; + > {{alias}}( N, 5.0, x, stride ) 16.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > {{alias}}( 3, 5.0, x1, 2) + > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); + > stride = 2; + > {{alias}}( N, 5.0, x1, stride ) 14.0 - {{alias}}.ndarray( N, alpha, x, stride, offset ) Adds a constant to each double-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm and @@ -89,7 +92,8 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > {{alias}}.ndarray( 3, 5.0, x, 2, 1 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > {{alias}}.ndarray( N, 5.0, x, 2, 1 ) 14.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/examples/index.js index a7f4a0041261..1d2888396a02 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/examples/index.js @@ -18,11 +18,18 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float64Array = require( '@stdlib/array/float64' ); var dapxsumkbn = require( './../lib' ); -var x = filledarrayBy( 10, 'float64', discreteUniform( 0.0, 100.0 ) ); +var x; +var i; + +x = new Float64Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); var v = dapxsumkbn( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/include.gypi index 26476a8c2655..868c5c12e852 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/include.gypi +++ b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.c', + '<(src_dir)/addon.cpp', ' -#include - -/** -* Receives JavaScript callback invocation data. -* -* @private -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_DOUBLE( env, alpha, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 2 ); - - napi_value v; - napi_status status = napi_create_double( env, stdlib_strided_dapxsumkbn( N, alpha, X, stride ), &v ); - assert( status == napi_ok ); - - return v; -} - -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/src/addon.cpp b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/src/addon.cpp new file mode 100644 index 000000000000..28c85ad76ebc --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/src/addon.cpp @@ -0,0 +1,130 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dapxsumkbn.h" +#include +#include +#include +#include +#include + +/** +* Add-on namespace. +*/ +namespace stdlib_blas_ext_base_dapxsumkbn { + + /** + * Adds a constant to each double-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. + * + * ## Notes + * + * - When called from JavaScript, the function expects four arguments: + * + * - `N`: number of indexed elements + * - `alpha`: constant + * - `X`: input array + * - `stride`: stride length + */ + napi_value node_dapxsumkbn( napi_env env, napi_callback_info info ) { + napi_status status; + + size_t argc = 4; + napi_value argv[ 4 ]; + status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); + assert( status == napi_ok ); + + if ( argc < 4 ) { + napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); + return nullptr; + } + + napi_valuetype vtype0; + status = napi_typeof( env, argv[ 0 ], &vtype0 ); + assert( status == napi_ok ); + if ( vtype0 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); + return nullptr; + } + + napi_valuetype vtype1; + status = napi_typeof( env, argv[ 1 ], &vtype1 ); + assert( status == napi_ok ); + if ( vtype1 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); + return nullptr; + } + + bool res; + status = napi_is_typedarray( env, argv[ 2 ], &res ); + assert( status == napi_ok ); + if ( res == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); + return nullptr; + } + + napi_valuetype vtype3; + status = napi_typeof( env, argv[ 3 ], &vtype3 ); + assert( status == napi_ok ); + if ( vtype3 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); + return nullptr; + } + + int64_t N; + status = napi_get_value_int64( env, argv[ 0 ], &N ); + assert( status == napi_ok ); + + double alpha; + status = napi_get_value_double( env, argv[ 1 ], &alpha ); + assert( status == napi_ok ); + + int64_t stride; + status = napi_get_value_int64( env, argv[ 3 ], &stride ); + assert( status == napi_ok ); + + napi_typedarray_type vtype2; + size_t xlen; + void *X; + status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype2 != napi_float64_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); + return nullptr; + } + if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + napi_value v; + status = napi_create_double( env, stdlib_strided_dapxsumkbn( N, alpha, (double *)X, stride ), &v ); + assert( status == napi_ok ); + + return v; + } + + napi_value Init( napi_env env, napi_value exports ) { + napi_status status; + napi_value fcn; + status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dapxsumkbn, NULL, &fcn ); + assert( status == napi_ok ); + return fcn; + } + + NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) +} // end namespace stdlib_blas_ext_base_dapxsumkbn diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/test/test.dapxsumkbn.js b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/test/test.dapxsumkbn.js index d77d6e304bfb..ccd84e860586 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/test/test.dapxsumkbn.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/test/test.dapxsumkbn.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dapxsumkbn = require( './../lib/dapxsumkbn.js' ); @@ -35,7 +36,7 @@ tape( 'main export is a function', function test( t ) { }); tape( 'the function has an arity of 4', function test( t ) { - t.strictEqual( dapxsumkbn.length, 4, 'returns expected value' ); + t.strictEqual( dapxsumkbn.length, 4, 'has expected arity' ); t.end(); }); @@ -94,6 +95,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { + var N; var x; var v; @@ -108,13 +110,15 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - v = dapxsumkbn( 4, 5.0, x, 2 ); + N = floor( x.length / 2 ); + v = dapxsumkbn( N, 5.0, x, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { + var N; var x; var v; @@ -129,7 +133,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - v = dapxsumkbn( 4, 5.0, x, -2 ); + N = floor( x.length / 2 ); + v = dapxsumkbn( N, 5.0, x, -2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); @@ -150,6 +155,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; + var N; var v; x0 = new Float64Array([ @@ -165,7 +171,9 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - v = dapxsumkbn( 4, 5.0, x1, 2 ); + N = floor(x1.length / 2); + + v = dapxsumkbn( N, 5.0, x1, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/test/test.dapxsumkbn.native.js b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/test/test.dapxsumkbn.native.js index 9b5276b82135..e8215ed13549 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/test/test.dapxsumkbn.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/test/test.dapxsumkbn.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -44,7 +45,7 @@ tape( 'main export is a function', opts, function test( t ) { }); tape( 'the function has an arity of 4', opts, function test( t ) { - t.strictEqual( dapxsumkbn.length, 4, 'returns expected value' ); + t.strictEqual( dapxsumkbn.length, 4, 'has expected arity' ); t.end(); }); @@ -212,6 +213,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -226,13 +228,15 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - v = dapxsumkbn( 4, 5.0, x, 2 ); + N = floor( x.length / 2 ); + v = dapxsumkbn( N, 5.0, x, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -247,7 +251,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - v = dapxsumkbn( 4, 5.0, x, -2 ); + N = floor( x.length / 2 ); + v = dapxsumkbn( N, 5.0, x, -2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); @@ -268,6 +273,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; + var N; var v; x0 = new Float64Array([ @@ -283,7 +289,9 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - v = dapxsumkbn( 4, 5.0, x1, 2 ); + N = floor(x1.length / 2); + + v = dapxsumkbn( N, 5.0, x1, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/test/test.ndarray.js index 2ba7edc195fa..2a526c76e4c6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/test/test.ndarray.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dapxsumkbn = require( './../lib/ndarray.js' ); @@ -35,7 +36,7 @@ tape( 'main export is a function', function test( t ) { }); tape( 'the function has an arity of 5', function test( t ) { - t.strictEqual( dapxsumkbn.length, 5, 'returns expected value' ); + t.strictEqual( dapxsumkbn.length, 5, 'has expected arity' ); t.end(); }); @@ -94,6 +95,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { + var N; var x; var v; @@ -108,13 +110,15 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - v = dapxsumkbn( 4, 5.0, x, 2, 0 ); + N = floor( x.length / 2 ); + v = dapxsumkbn( N, 5.0, x, 2, 0 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { + var N; var x; var v; @@ -129,7 +133,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - v = dapxsumkbn( 4, 5.0, x, -2, 6 ); + N = floor( x.length / 2 ); + v = dapxsumkbn( N, 5.0, x, -2, 6 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); @@ -148,6 +153,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { + var N; var x; var v; @@ -161,8 +167,9 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); + N = floor( x.length / 2 ); - v = dapxsumkbn( 4, 5.0, x, 2, 1 ); + v = dapxsumkbn( N, 5.0, x, 2, 1 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/test/test.ndarray.native.js index 179476d28604..85d8ad4003fb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/test/test.ndarray.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -44,7 +45,7 @@ tape( 'main export is a function', opts, function test( t ) { }); tape( 'the function has an arity of 5', opts, function test( t ) { - t.strictEqual( dapxsumkbn.length, 5, 'returns expected value' ); + t.strictEqual( dapxsumkbn.length, 5, 'has expected arity' ); t.end(); }); @@ -103,6 +104,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -117,13 +119,15 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - v = dapxsumkbn( 4, 5.0, x, 2, 0 ); + N = floor( x.length / 2 ); + v = dapxsumkbn( N, 5.0, x, 2, 0 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -138,7 +142,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - v = dapxsumkbn( 4, 5.0, x, -2, 6 ); + N = floor( x.length / 2 ); + v = dapxsumkbn( N, 5.0, x, -2, 6 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); @@ -157,6 +162,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { + var N; var x; var v; @@ -170,8 +176,9 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); + N = floor( x.length / 2 ); - v = dapxsumkbn( 4, 5.0, x, 2, 1 ); + v = dapxsumkbn( N, 5.0, x, 2, 1 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/docs/types/index.d.ts index 93cc7a29073f..e47c736c52eb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/docs/types/index.d.ts @@ -146,7 +146,7 @@ interface Namespace { * @param alpha - constant * @param x - input array * @param stride - stride length - * @returns input array + * @returns `x` * * @example * var Float64Array = require( '@stdlib/array/float64' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/README.md b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/README.md index f145d06db915..406a7dca47af 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/README.md @@ -44,8 +44,9 @@ Adds a constant to each single-precision floating-point strided array element an var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); +var N = x.length; -var v = dsapxsum( 3, 5.0, x, 1 ); +var v = dsapxsum( N, 5.0, x, 1 ); // returns 16.0 ``` @@ -55,14 +56,16 @@ The function has the following parameters: - **x**: input [`Float32Array`][@stdlib/array/float32]. - **stride**: index increment for `x`. -The `N` and `stride` parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element in the strided array, +The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to access every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); +var N = floor( x.length / 2 ); -var v = dsapxsum( 4, 5.0, x, 2 ); +var v = dsapxsum( N, 5.0, x, 2 ); // returns 25.0 ``` @@ -72,11 +75,14 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var v = dsapxsum( 4, 5.0, x1, 2 ); +var N = floor( x0.length / 2 ); + +var v = dsapxsum( N, 5.0, x1, 2 ); // returns 25.0 ``` @@ -88,8 +94,9 @@ Adds a constant to each single-precision floating-point strided array element an var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); +var N = x.length; -var v = dsapxsum.ndarray( 3, 5.0, x, 1, 0 ); +var v = dsapxsum.ndarray( N, 5.0, x, 1, 0 ); // returns 16.0 ``` @@ -97,14 +104,16 @@ The function has the following additional parameters: - **offset**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the offset parameter supports indexing semantics based on a starting index. For example, to access every other value in the strided array starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access every other value in `x` starting from the second value ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +var N = floor( x.length / 2 ); -var v = dsapxsum.ndarray( 4, 5.0, x, 2, 1 ); +var v = dsapxsum.ndarray( N, 5.0, x, 2, 1 ); // returns 25.0 ``` @@ -130,11 +139,18 @@ var v = dsapxsum.ndarray( 4, 5.0, x, 2, 1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float32Array = require( '@stdlib/array/float32' ); var dsapxsum = require( '@stdlib/blas/ext/base/dsapxsum' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x; +var i; + +x = new Float32Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); var v = dsapxsum( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.js index 87bf2ee909fc..1bc8431b4ccd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var dsapxsum = require( './../lib/dsapxsum.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -44,7 +39,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.native.js index 66defd69e513..4877ac1f68e8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var dsapxsum = tryRequire( resolve( __dirname, './../lib/dsapxsum.native.js' ) ) var opts = { 'skip': ( dsapxsum instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -49,7 +48,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.ndarray.js index 6299c00494a9..0a646c147af4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.ndarray.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var dsapxsum = require( './../lib/ndarray.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -44,7 +39,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.ndarray.native.js index 28c13c39de37..6bc4c27d0abc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var dsapxsum = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dsapxsum instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -49,7 +48,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/docs/repl.txt index dc49fe91b05b..a8ef3a367711 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/docs/repl.txt @@ -4,8 +4,8 @@ element and computes the sum using extended accumulation and returning an extended precision result. - The `N` and `stride` parameters determine which elements in the strided - array are accessed at runtime. + The `N` and `stride` parameters determine which elements in `x` are accessed + at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -40,16 +40,19 @@ // Using `N` and `stride` parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > {{alias}}( 3, 5.0, x, 2 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > var stride = 2; + > {{alias}}( N, 5.0, x, stride ) 16.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > {{alias}}( 3, 5.0, x1, 2 ) + > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); + > stride = 2; + > {{alias}}( N, 5.0, x1, stride ) 14.0 - {{alias}}.ndarray( N, alpha, x, stride, offset ) Adds a constant to each single-precision floating-point strided array element and computes the sum using extended accumulation and alternative @@ -89,8 +92,9 @@ 16.0 // Using offset parameter: - > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > {{alias}}.ndarray( 3, 5.0, x, 2, 1 ) + > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > {{alias}}.ndarray( N, 5.0, x, 2, 1 ) 14.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/examples/index.js index b3278a6935c5..5cc9839becc2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/examples/index.js @@ -18,11 +18,18 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float32Array = require( '@stdlib/array/float32' ); var dsapxsum = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x; +var i; + +x = new Float32Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); var v = dsapxsum( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/include.gypi index 26476a8c2655..868c5c12e852 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/include.gypi +++ b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.c', + '<(src_dir)/addon.cpp', ' -#include - -/** -* Receives JavaScript callback invocation data. -* -* @private -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_FLOAT( env, N, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); - - napi_value v; - status = napi_create_double( env, stdlib_strided_dsapxsum( N, alpha, X, stride ), &v ); - assert( status == napi_ok ); - return v; -} - -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/src/addon.cpp b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/src/addon.cpp new file mode 100644 index 000000000000..be1bbe59606a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/src/addon.cpp @@ -0,0 +1,130 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dsapxsum.h" +#include +#include +#include +#include +#include + +/** +* Add-on namespace. +*/ +namespace stdlib_blas_ext_base_dsapxsum { + + /** + * Adds a constant to each single-precision floating-point strided array element and computes the sum using extended accumulation and returning an extended precision result. + * + * ## Notes + * + * - When called from JavaScript, the function expects four arguments: + * + * - `N`: number of indexed elements + * - `alpha`: constant + * - `X`: input array + * - `stride`: stride length + */ + napi_value node_dsapxsum( napi_env env, napi_callback_info info ) { + napi_status status; + + size_t argc = 4; + napi_value argv[ 4 ]; + status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); + assert( status == napi_ok ); + + if ( argc < 4 ) { + napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); + return nullptr; + } + + napi_valuetype vtype0; + status = napi_typeof( env, argv[ 0 ], &vtype0 ); + assert( status == napi_ok ); + if ( vtype0 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); + return nullptr; + } + + napi_valuetype vtype1; + status = napi_typeof( env, argv[ 1 ], &vtype1 ); + assert( status == napi_ok ); + if ( vtype1 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); + return nullptr; + } + + bool res; + status = napi_is_typedarray( env, argv[ 2 ], &res ); + assert( status == napi_ok ); + if ( res == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + + napi_valuetype vtype3; + status = napi_typeof( env, argv[ 3 ], &vtype3 ); + assert( status == napi_ok ); + if ( vtype3 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); + return nullptr; + } + + int64_t N; + status = napi_get_value_int64( env, argv[ 0 ], &N ); + assert( status == napi_ok ); + + double alpha; + status = napi_get_value_double( env, argv[ 1 ], &alpha ); + assert( status == napi_ok ); + + int64_t stride; + status = napi_get_value_int64( env, argv[ 3 ], &stride ); + assert( status == napi_ok ); + + napi_typedarray_type vtype2; + size_t xlen; + void *X; + status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype2 != napi_float32_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + napi_value v; + status = napi_create_double( env, stdlib_strided_dsapxsum( N, (float)alpha, (float *)X, stride ), &v ); + assert( status == napi_ok ); + + return v; + } + + napi_value Init( napi_env env, napi_value exports ) { + napi_status status; + napi_value fcn; + status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dsapxsum, NULL, &fcn ); + assert( status == napi_ok ); + return fcn; + } + + NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) +} // end namespace stdlib_blas_ext_base_dsapxsum diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/test/test.dsapxsum.js b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/test/test.dsapxsum.js index 017eaf731d73..035e7d40d230 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/test/test.dsapxsum.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/test/test.dsapxsum.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var dsapxsum = require( './../lib/dsapxsum.js' ); @@ -35,7 +36,7 @@ tape( 'main export is a function', function test( t ) { }); tape( 'the function has an arity of 4', function test( t ) { - t.strictEqual( dsapxsum.length, 4, 'returns expected value' ); + t.strictEqual( dsapxsum.length, 4, 'has expected arity' ); t.end(); }); @@ -102,6 +103,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { + var N; var x; var v; @@ -116,13 +118,15 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - v = dsapxsum( 4, 5.0, x, 2 ); + N = floor( x.length / 2 ); + v = dsapxsum( N, 5.0, x, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { + var N; var x; var v; var i; @@ -138,7 +142,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - v = dsapxsum( 4, 5.0, x, -2 ); + N = floor( x.length / 2 ); + v = dsapxsum( N, 5.0, x, -2 ); t.strictEqual( v, 25.0, 'returns expected value' ); @@ -167,6 +172,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; + var N; var v; x0 = new Float32Array([ @@ -182,8 +188,9 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + N = floor(x1.length / 2); - v = dsapxsum( 4, 5.0, x1, 2 ); + v = dsapxsum( N, 5.0, x1, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/test/test.dsapxsum.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/test/test.dsapxsum.native.js index 49f2fc85faca..927c98c898a2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/test/test.dsapxsum.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/test/test.dsapxsum.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -44,7 +45,7 @@ tape( 'main export is a function', opts, function test( t ) { }); tape( 'the function has an arity of 4', opts, function test( t ) { - t.strictEqual( dsapxsum.length, 4, 'returns expected value' ); + t.strictEqual( dsapxsum.length, 4, 'has expected arity' ); t.end(); }); @@ -220,6 +221,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -234,13 +236,15 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - v = dsapxsum( 4, 5.0, x, 2 ); + N = floor( x.length / 2 ); + v = dsapxsum( N, 5.0, x, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var N; var x; var v; var i; @@ -256,7 +260,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - v = dsapxsum( 4, 5.0, x, -2 ); + N = floor( x.length / 2 ); + v = dsapxsum( N, 5.0, x, -2 ); t.strictEqual( v, 25.0, 'returns expected value' ); @@ -285,6 +290,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; + var N; var v; x0 = new Float32Array([ @@ -300,8 +306,9 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + N = floor(x1.length / 2); - v = dsapxsum( 4, 5.0, x1, 2 ); + v = dsapxsum( N, 5.0, x1, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/test/test.ndarray.js index a09095020213..53762d5de58e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/test/test.ndarray.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var dsapxsum = require( './../lib/ndarray.js' ); @@ -35,7 +36,7 @@ tape( 'main export is a function', function test( t ) { }); tape( 'the function has an arity of 5', function test( t ) { - t.strictEqual( dsapxsum.length, 5, 'returns expected value' ); + t.strictEqual( dsapxsum.length, 5, 'has expected arity' ); t.end(); }); @@ -102,6 +103,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { + var N; var x; var v; @@ -116,13 +118,15 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - v = dsapxsum( 4, 5.0, x, 2, 0 ); + N = floor( x.length / 2 ); + v = dsapxsum( N, 5.0, x, 2, 0 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { + var N; var x; var v; var i; @@ -138,7 +142,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - v = dsapxsum( 4, 5.0, x, -2, 6 ); + N = floor( x.length / 2 ); + v = dsapxsum( N, 5.0, x, -2, 6 ); t.strictEqual( v, 25.0, 'returns expected value' ); @@ -165,6 +170,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { + var N; var x; var v; @@ -178,8 +184,9 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); + N = floor( x.length / 2 ); - v = dsapxsum( 4, 5.0, x, 2, 1 ); + v = dsapxsum( N, 5.0, x, 2, 1 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/test/test.ndarray.native.js index 59fb184148a8..35bbebbfc1ee 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsapxsum/test/test.ndarray.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -44,7 +45,7 @@ tape( 'main export is a function', opts, function test( t ) { }); tape( 'the function has an arity of 5', opts, function test( t ) { - t.strictEqual( dsapxsum.length, 5, 'returns expected value' ); + t.strictEqual( dsapxsum.length, 5, 'has expected arity' ); t.end(); }); @@ -111,6 +112,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -125,13 +127,15 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - v = dsapxsum( 4, 5.0, x, 2, 0 ); + N = floor( x.length / 2 ); + v = dsapxsum( N, 5.0, x, 2, 0 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var N; var x; var v; var i; @@ -147,7 +151,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - v = dsapxsum( 4, 5.0, x, -2, 6 ); + N = floor( x.length / 2 ); + v = dsapxsum( N, 5.0, x, -2, 6 ); t.strictEqual( v, 25.0, 'returns expected value' ); @@ -174,6 +179,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { + var N; var x; var v; @@ -187,8 +193,9 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); + N = floor( x.length / 2 ); - v = dsapxsum( 4, 5.0, x, 2, 1 ); + v = dsapxsum( N, 5.0, x, 2, 1 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dssum/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/dssum/manifest.json index a27f5053aae0..8a60f30e0d0a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dssum/manifest.json +++ b/lib/node_modules/@stdlib/blas/ext/base/dssum/manifest.json @@ -1,82 +1,42 @@ { - "options": { - "task": "build" - }, - "fields": [ - { - "field": "src", - "resolve": true, - "relative": true - }, - { - "field": "include", - "resolve": true, - "relative": true - }, - { - "field": "libraries", - "resolve": false, - "relative": false - }, - { - "field": "libpath", - "resolve": true, - "relative": false - } - ], - "confs": [ - { - "task": "build", - "src": [ - "./src/dssum.c" - ], - "include": [ - "./include" - ], - "libraries": [ - "-lm" - ], - "libpath": [], - "dependencies": [ - "@stdlib/blas/ext/base/dssumpw", - "@stdlib/napi/argv", - "@stdlib/napi/export", - "@stdlib/napi/argv-int64", - "@stdlib/napi/argv-strided-float32array" - - ] - }, - { - "task": "benchmark", - "src": [ - "./src/dssum.c" - ], - "include": [ - "./include" - ], - "libraries": [ - "-lm" - ], - "libpath": [], - "dependencies": [ - "@stdlib/blas/ext/base/dssumpw" - ] - }, - { - "task": "examples", - "src": [ - "./src/dssum.c" - ], - "include": [ - "./include" - ], - "libraries": [ - "-lm" - ], - "libpath": [], - "dependencies": [ - "@stdlib/blas/ext/base/dssumpw" - ] - } - ] + "options": {}, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "src": [ + "./src/dssum.c" + ], + "include": [ + "./include" + ], + "libraries": [ + "-lm" + ], + "libpath": [], + "dependencies": [ + "@stdlib/blas/ext/base/dssumpw" + ] + } + ] } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dssum/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/dssum/src/addon.c index 3904a53fad15..db151490d609 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dssum/src/addon.c +++ b/lib/node_modules/@stdlib/blas/ext/base/dssum/src/addon.c @@ -35,13 +35,12 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); napi_value v; - napi_status status = napi_create_double( env, stdlib_strided_dssum( N, X, stride ), &v ); + status = napi_create_double( env, stdlib_strided_dssum( N, (float *)X, stride ), &v ); assert( status == napi_ok ); - return v; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsum/README.md b/lib/node_modules/@stdlib/blas/ext/base/dsum/README.md index febeda650931..433f55b71bf8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsum/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/dsum/README.md @@ -56,14 +56,16 @@ The function has the following parameters: - **x**: input [`Float64Array`][@stdlib/array/float64]. - **stride**: index increment for `x`. -The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of every other element in the strided array, +The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the sum of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); +var N = floor( x.length / 2 ); -var v = dsum( 4, x, 2 ); +var v = dsum( N, x, 2 ); // returns 5.0 ``` @@ -73,11 +75,14 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var v = dsum( 4, x1, 2 ); +var N = floor( x0.length / 2 ); + +var v = dsum( N, x1, 2 ); // returns 5.0 ``` @@ -89,8 +94,9 @@ Computes the sum of double-precision floating-point strided array elements using var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +var N = x.length; -var v = dsum.ndarray( 3, x, 1, 0 ); +var v = dsum.ndarray( N, x, 1, 0 ); // returns 1.0 ``` @@ -98,14 +104,16 @@ The function has the following additional parameters: - **offset**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other value in the strided array starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other value in `x` starting from the second value ```javascript var Float64Array = require( '@stdlib/array/float64' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +var N = floor( x.length / 2 ); -var v = dsum.ndarray( 4, x, 2, 1 ); +var v = dsum.ndarray( N, x, 2, 1 ); // returns 5.0 ``` @@ -130,11 +138,18 @@ var v = dsum.ndarray( 4, x, 2, 1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float64Array = require( '@stdlib/array/float64' ); var dsum = require( '@stdlib/blas/ext/base/dsum' ); -var x = filledarrayBy( 10, 'float64', discreteUniform( 0, 100 ) ); +var x; +var i; + +x = new Float64Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); var v = dsum( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.js index 4cea809eacf3..8ac3515ecccc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dsum = require( './../lib/dsum.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -44,7 +39,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x; + var i; + + x = new Float64Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*10.0 ) - 20.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.native.js index a5cdc68d94f8..5e221895b4de 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var dsum = tryRequire( resolve( __dirname, './../lib/dsum.native.js' ) ); var opts = { 'skip': ( dsum instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -49,7 +48,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x; + var i; + + x = new Float64Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*10.0 ) - 20.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.ndarray.js index 26b8ec1af487..81fad361bd13 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.ndarray.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dsum = require( './../lib/ndarray.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -44,7 +39,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x; + var i; + + x = new Float64Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*10.0 ) - 20.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.ndarray.native.js index eff365899b03..df4cb59656d7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsum/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var dsum = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dsum instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -49,7 +48,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x; + var i; + + x = new Float64Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*10.0 ) - 20.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsum/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/dsum/docs/repl.txt index 377feb1ce2d3..1aa6e0bc1f97 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsum/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/dsum/docs/repl.txt @@ -2,8 +2,8 @@ {{alias}}( N, x, stride ) Computes the sum of double-precision floating-point strided array elements. - The `N` and stride parameters determine which elements in the strided array - are accessed at runtime. + The `N` and `stride` parameters determine which elements in `x` are accessed + at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -33,18 +33,21 @@ > {{alias}}( x.length, x, 1 ) 1.0 - // Using `N` and stride parameters: + // Using `N` and `stride` parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > {{alias}}( 3, x, 2 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > var stride = 2; + > {{alias}}( N, x, stride ) 1.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > {{alias}}( 3, x1, 2 ) + > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); + > stride = 2; + > {{alias}}( N, x1, stride ) -1.0 - {{alias}}.ndarray( N, x, stride, offset ) Computes the sum of double-precision floating-point strided array elements using alternative indexing semantics. @@ -80,8 +83,9 @@ 1.0 // Using offset parameter: - > x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > {{alias}}.ndarray( 3, x, 2, 1 ) + > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > {{alias}}.ndarray( N, x, 2, 1 ) -1.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsum/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/dsum/examples/index.js index a04aad391efe..f4ed3bde00d2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsum/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsum/examples/index.js @@ -18,11 +18,18 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float64Array = require( '@stdlib/array/float64' ); var dsum = require( './../lib' ); -var x = filledarrayBy( 10, 'float64', discreteUniform( -100, 100 ) ); +var x; +var i; + +x = new Float64Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); var v = dsum( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsum/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/dsum/include.gypi index 26476a8c2655..868c5c12e852 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsum/include.gypi +++ b/lib/node_modules/@stdlib/blas/ext/base/dsum/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.c', + '<(src_dir)/addon.cpp', ' - -/** -* Receives JavaScript callback invocation data. -* -* @private -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 1 ); - - napi_value v; - napi_status status = napi_create_double( env, stdlib_strided_dsum( N, X, stride ), &v ); - assert( status == napi_ok ); - - return v; -} - -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsum/src/addon.cpp b/lib/node_modules/@stdlib/blas/ext/base/dsum/src/addon.cpp new file mode 100644 index 000000000000..3dfacd120852 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dsum/src/addon.cpp @@ -0,0 +1,117 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dsum.h" +#include +#include +#include +#include +#include + +/** +* Add-on namespace. +*/ +namespace stdlib_blas_ext_base_dsum { + + /** + * Computes the sum of double-precision floating-point strided array elements. + * + * ## Notes + * + * - When called from JavaScript, the function expects three arguments: + * + * - `N`: number of indexed elements + * - `X`: input array + * - `stride`: stride length + */ + napi_value node_dsum( napi_env env, napi_callback_info info ) { + napi_status status; + + size_t argc = 3; + napi_value argv[ 3 ]; + status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); + assert( status == napi_ok ); + + if ( argc < 3 ) { + napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); + return nullptr; + } + + napi_valuetype vtype0; + status = napi_typeof( env, argv[ 0 ], &vtype0 ); + assert( status == napi_ok ); + if ( vtype0 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); + return nullptr; + } + + bool res; + status = napi_is_typedarray( env, argv[ 1 ], &res ); + assert( status == napi_ok ); + if ( res == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." ); + return nullptr; + } + + napi_valuetype vtype2; + status = napi_typeof( env, argv[ 2 ], &vtype2 ); + assert( status == napi_ok ); + if ( vtype2 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); + return nullptr; + } + + int64_t N; + status = napi_get_value_int64( env, argv[ 0 ], &N ); + assert( status == napi_ok ); + + int64_t stride; + status = napi_get_value_int64( env, argv[ 2 ], &stride ); + assert( status == napi_ok ); + + napi_typedarray_type vtype1; + size_t xlen; + void *X; + status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype1 != napi_float64_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." ); + return nullptr; + } + if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + napi_value v; + status = napi_create_double( env, stdlib_strided_dsum( N, (double *)X, stride ), &v ); + assert( status == napi_ok ); + + return v; + } + + napi_value Init( napi_env env, napi_value exports ) { + napi_status status; + napi_value fcn; + status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dsum, NULL, &fcn ); + assert( status == napi_ok ); + return fcn; + } + + NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) +} // end namespace stdlib_blas_ext_base_dsum diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsum/test/test.dsum.js b/lib/node_modules/@stdlib/blas/ext/base/dsum/test/test.dsum.js index 2dfc3d5be1c2..829371758c1d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsum/test/test.dsum.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsum/test/test.dsum.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dsum = require( './../lib/dsum.js' ); @@ -35,7 +36,7 @@ tape( 'main export is a function', function test( t ) { }); tape( 'the function has an arity of 3', function test( t ) { - t.strictEqual( dsum.length, 3, 'returns expected value' ); + t.strictEqual( dsum.length, 3, 'has expected arity' ); t.end(); }); @@ -109,7 +110,7 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = 4; + N = floor( x.length / 2 ); v = dsum( N, x, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); @@ -132,7 +133,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = 4; + N = floor( x.length / 2 ); v = dsum( N, x, -2 ); t.strictEqual( v, 5.0, 'returns expected value' ); @@ -170,7 +171,7 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = 4; + N = floor(x1.length / 2); v = dsum( N, x1, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsum/test/test.dsum.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsum/test/test.dsum.native.js index bdcb51522b5e..caf5beda25b7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsum/test/test.dsum.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsum/test/test.dsum.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -44,7 +45,7 @@ tape( 'main export is a function', opts, function test( t ) { }); tape( 'the function has an arity of 3', opts, function test( t ) { - t.strictEqual( dsum.length, 3, 'returns expected value' ); + t.strictEqual( dsum.length, 3, 'has expected arity' ); t.end(); }); @@ -200,7 +201,7 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = 4; + N = floor( x.length / 2 ); v = dsum( N, x, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); @@ -223,7 +224,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = 4; + N = floor( x.length / 2 ); v = dsum( N, x, -2 ); t.strictEqual( v, 5.0, 'returns expected value' ); @@ -261,7 +262,7 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = 4; + N = floor(x1.length / 2); v = dsum( N, x1, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsum/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsum/test/test.ndarray.js index 69b88a66fa92..2e2169aacac7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsum/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsum/test/test.ndarray.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dsum = require( './../lib/ndarray.js' ); @@ -35,7 +36,7 @@ tape( 'main export is a function', function test( t ) { }); tape( 'the function has an arity of 4', function test( t ) { - t.strictEqual( dsum.length, 4, 'returns expected value' ); + t.strictEqual( dsum.length, 4, 'has expected arity' ); t.end(); }); @@ -109,7 +110,7 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = 4; + N = floor( x.length / 2 ); v = dsum( N, x, 2, 0 ); t.strictEqual( v, 5.0, 'returns expected value' ); @@ -132,7 +133,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = 4; + N = floor( x.length / 2 ); v = dsum( N, x, -2, 6 ); t.strictEqual( v, 5.0, 'returns expected value' ); @@ -166,7 +167,7 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = 4; + N = floor( x.length / 2 ); v = dsum( N, x, 2, 1 ); t.strictEqual( v, 5.0, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsum/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsum/test/test.ndarray.native.js index ced60d19a7b4..e6ffc27b6e9b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsum/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsum/test/test.ndarray.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -44,7 +45,7 @@ tape( 'main export is a function', opts, function test( t ) { }); tape( 'the function has an arity of 4', opts, function test( t ) { - t.strictEqual( dsum.length, 4, 'returns expected value' ); + t.strictEqual( dsum.length, 4, 'has expected arity' ); t.end(); }); @@ -118,7 +119,7 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = 4; + N = floor( x.length / 2 ); v = dsum( N, x, 2, 0 ); t.strictEqual( v, 5.0, 'returns expected value' ); @@ -141,7 +142,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = 4; + N = floor( x.length / 2 ); v = dsum( N, x, -2, 6 ); t.strictEqual( v, 5.0, 'returns expected value' ); @@ -175,7 +176,7 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = 4; + N = floor( x.length / 2 ); v = dsum( N, x, 2, 1 ); t.strictEqual( v, 5.0, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/README.md b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/README.md index 20ea8a24b5db..245aa6c28fd5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/README.md @@ -44,8 +44,9 @@ Computes the sum of double-precision floating-point strided array elements using var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +var N = x.length; -var v = dsumkbn2( 3, x, 1 ); +var v = dsumkbn2( N, x, 1 ); // returns 1.0 ``` @@ -59,10 +60,12 @@ The `N` and `stride` parameters determine which elements in `x` are accessed at ```javascript var Float64Array = require( '@stdlib/array/float64' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); +var N = floor( x.length / 2 ); -var v = dsumkbn2( 4, x, 2 ); +var v = dsumkbn2( N, x, 2 ); // returns 5.0 ``` @@ -72,11 +75,14 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var v = dsumkbn2( 4, x1, 2 ); +var N = floor( x0.length / 2 ); + +var v = dsumkbn2( N, x1, 2 ); // returns 5.0 ``` @@ -88,8 +94,9 @@ Computes the sum of double-precision floating-point strided array elements using var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +var N = x.length; -var v = dsumkbn2.ndarray( 3, x, 1, 0 ); +var v = dsumkbn2.ndarray( N, x, 1, 0 ); // returns 1.0 ``` @@ -104,8 +111,9 @@ var Float64Array = require( '@stdlib/array/float64' ); var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +var N = floor( x.length / 2 ); -var v = dsumkbn2.ndarray( 4, x, 2, 1 ); +var v = dsumkbn2.ndarray( N, x, 2, 1 ); // returns 5.0 ``` @@ -130,11 +138,18 @@ var v = dsumkbn2.ndarray( 4, x, 2, 1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float64Array = require( '@stdlib/array/float64' ); var dsumkbn2 = require( '@stdlib/blas/ext/base/dsumkbn2' ); -var x = filledarrayBy( 10, 'float64', discreteUniform( -100, 100 ) ); +var x; +var i; + +x = new Float64Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); var v = dsumkbn2( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.js index 66237dbf6082..afec7cc9c189 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dsumkbn2 = require( './../lib/dsumkbn2.js' ); -// VARIABLES // - -var rand = uniform( -100.0, 100.0 ); - - // FUNCTIONS // /** @@ -44,7 +39,13 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x; + var i; + + x = new Float64Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*10.0 ) - 20.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.native.js index 1eb8239f0d78..493ad09a311e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var dsumkbn2 = tryRequire( resolve( __dirname, './../lib/dsumkbn2.native.js' ) ) var opts = { 'skip': ( dsumkbn2 instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); // FUNCTIONS // @@ -49,7 +48,13 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x; + var i; + + x = new Float64Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*10.0 ) - 20.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.ndarray.js index 88a1b89b76ed..98158b67b5ef 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.ndarray.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dsumkbn2 = require( './../lib/ndarray.js' ); -// VARIABLES // - -var rand = uniform( -100.0, 100.0 ); - - // FUNCTIONS // /** @@ -44,7 +39,13 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x; + var i; + + x = new Float64Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*10.0 ) - 20.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.ndarray.native.js index b587ad2fde9b..7d229a4c8bbc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var dsumkbn2 = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dsumkbn2 instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); // FUNCTIONS // @@ -49,7 +48,13 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x; + var i; + + x = new Float64Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*10.0 ) - 20.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/examples/index.js index c3b802e07f38..f0a9b781d101 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/examples/index.js @@ -18,11 +18,18 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float64Array = require( '@stdlib/array/float64' ); var dsumkbn2 = require( './../lib' ); -var x = filledarrayBy( 10, 'float64', discreteUniform( -100, 100 ) ); +var x; +var i; + +x = new Float64Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); var v = dsumkbn2( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/include.gypi index 26476a8c2655..868c5c12e852 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/include.gypi +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.c', + '<(src_dir)/addon.cpp', ' -#include - -/** -* Receives JavaScript callback invocation data. -* -* @private -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - - napi_value v; - napi_create_double( env, stdlib_strided_dsumkbn2( N, X, strideX ), &v ); - - return v; -} - -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/src/addon.cpp b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/src/addon.cpp new file mode 100644 index 000000000000..924413149a5e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/src/addon.cpp @@ -0,0 +1,117 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dsumkbn2.h" +#include +#include +#include +#include +#include + +/** +* Add-on namespace. +*/ +namespace stdlib_blas_ext_base_dsumkbn2 { + + /** + * Computes the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm. + * + * ## Notes + * + * - When called from JavaScript, the function expects three arguments: + * + * - `N`: number of indexed elements + * - `X`: input array + * - `stride`: stride length + */ + napi_value node_dsumkbn2( napi_env env, napi_callback_info info ) { + napi_status status; + + size_t argc = 3; + napi_value argv[ 3 ]; + status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); + assert( status == napi_ok ); + + if ( argc < 3 ) { + napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); + return nullptr; + } + + napi_valuetype vtype0; + status = napi_typeof( env, argv[ 0 ], &vtype0 ); + assert( status == napi_ok ); + if ( vtype0 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); + return nullptr; + } + + bool res; + status = napi_is_typedarray( env, argv[ 1 ], &res ); + assert( status == napi_ok ); + if ( res == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." ); + return nullptr; + } + + napi_valuetype vtype2; + status = napi_typeof( env, argv[ 2 ], &vtype2 ); + assert( status == napi_ok ); + if ( vtype2 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); + return nullptr; + } + + int64_t N; + status = napi_get_value_int64( env, argv[ 0 ], &N ); + assert( status == napi_ok ); + + int64_t stride; + status = napi_get_value_int64( env, argv[ 2 ], &stride ); + assert( status == napi_ok ); + + napi_typedarray_type vtype1; + size_t xlen; + void *X; + status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype1 != napi_float64_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." ); + return nullptr; + } + if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + napi_value v; + status = napi_create_double( env, stdlib_strided_dsumkbn2( N, (double *)X, stride ), &v ); + assert( status == napi_ok ); + + return v; + } + + napi_value Init( napi_env env, napi_value exports ) { + napi_status status; + napi_value fcn; + status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dsumkbn2, NULL, &fcn ); + assert( status == napi_ok ); + return fcn; + } + + NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) +} // end namespace stdlib_blas_ext_base_dsumkbn2 diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.dsumkbn2.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.dsumkbn2.js index 0e74cf92c7cb..3ec0e00165e4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.dsumkbn2.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.dsumkbn2.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dsumkbn2 = require( './../lib/dsumkbn2.js' ); @@ -109,7 +110,7 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = 4; + N = floor( x.length / 2 ); v = dsumkbn2( N, x, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); @@ -132,7 +133,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = 4; + N = floor( x.length / 2 ); v = dsumkbn2( N, x, -2 ); t.strictEqual( v, 5.0, 'returns expected value' ); @@ -170,7 +171,7 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = 4; + N = floor(x1.length / 2); v = dsumkbn2( N, x1, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.dsumkbn2.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.dsumkbn2.native.js index 09a7a5b243f5..520d987d2e6a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.dsumkbn2.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.dsumkbn2.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -200,7 +201,7 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = 4; + N = floor( x.length / 2 ); v = dsumkbn2( N, x, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); @@ -223,7 +224,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = 4; + N = floor( x.length / 2 ); v = dsumkbn2( N, x, -2 ); t.strictEqual( v, 5.0, 'returns expected value' ); @@ -261,7 +262,7 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = 4; + N = floor(x1.length / 2); v = dsumkbn2( N, x1, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.ndarray.js index 6eaad80ee38d..2408d52ef7f1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.ndarray.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dsumkbn2 = require( './../lib/ndarray.js' ); @@ -109,7 +110,7 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = 4; + N = floor( x.length / 2 ); v = dsumkbn2( N, x, 2, 0 ); t.strictEqual( v, 5.0, 'returns expected value' ); @@ -132,7 +133,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = 4; + N = floor( x.length / 2 ); v = dsumkbn2( N, x, -2, 6 ); t.strictEqual( v, 5.0, 'returns expected value' ); @@ -166,7 +167,7 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = 4; + N = floor( x.length / 2 ); v = dsumkbn2( N, x, 2, 1 ); t.strictEqual( v, 5.0, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.ndarray.native.js index 668f399f2ab6..ec94ebb36d3b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.ndarray.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -118,7 +119,7 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = 4; + N = floor( x.length / 2 ); v = dsumkbn2( N, x, 2, 0 ); t.strictEqual( v, 5.0, 'returns expected value' ); @@ -141,7 +142,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = 4; + N = floor( x.length / 2 ); v = dsumkbn2( N, x, -2, 6 ); t.strictEqual( v, 5.0, 'returns expected value' ); @@ -175,7 +176,7 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = 4; + N = floor( x.length / 2 ); v = dsumkbn2( N, x, 2, 1 ); t.strictEqual( v, 5.0, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/README.md b/lib/node_modules/@stdlib/blas/ext/base/sapx/README.md index 4c14fd5482e7..f5d6a80ae23c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/README.md @@ -50,14 +50,16 @@ The function has the following parameters: - **x**: input [`Float32Array`][@stdlib/array/float32]. - **stride**: index increment. -The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to add a constant to every other element +The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to add a constant to every other element ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] ); +var N = floor( x.length / 2 ); -sapx( 4, 5.0, x, 2 ); +sapx( N, 5.0, x, 2 ); // x => [ 3.0, 1.0, 8.0, -5.0, 9.0, 0.0, 4.0, -3.0 ] ``` @@ -65,15 +67,17 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); // Initial array... var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] ); // Create an offset view... var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var N = floor( x0.length/2 ); // Add a constant to every other element... -sapx( 3, 5.0, x1, 2 ); +sapx( N, 5.0, x1, 2 ); // x0 => [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ] ``` @@ -94,7 +98,7 @@ The function has the following additional parameters: - **offset**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access only the last three elements of the strided array +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access only the last three elements of `x` ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -113,7 +117,7 @@ sapx.ndarray( 3, 5.0, x, 1, x.length-3 ); ## Notes -- If `N <= 0`, both functions return the input array unchanged. +- If `N <= 0`, both functions return `x` unchanged. @@ -126,11 +130,27 @@ sapx.ndarray( 3, 5.0, x, 1, x.length-3 ); ```javascript -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var round = require( '@stdlib/math/base/special/round' ); +var randu = require( '@stdlib/random/base/randu' ); +var Float32Array = require( '@stdlib/array/float32' ); var sapx = require( '@stdlib/blas/ext/base/sapx' ); -var x = filledarrayBy( 10, 'float32', uniform( -100.0, 100.0 ) ); +var rand; +var sign; +var x; +var i; + +x = new Float32Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + rand = round( randu()*100.0 ); + sign = randu(); + if ( sign < 0.5 ) { + sign = -1.0; + } else { + sign = 1.0; + } + x[ i ] = sign * rand; +} console.log( x ); sapx( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.js index ffd0ff4adca6..fc8f88420392 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var sapx = require( './../lib/sapx.js' ); -// VARIABLES // - -var rand = uniform( -100.0, 100.0 ); - - // FUNCTIONS // /** @@ -44,7 +39,13 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.native.js index c0d5da977159..ec66fd0dc0cd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var sapx = tryRequire( resolve( __dirname, './../lib/sapx.native.js' ) ); var opts = { 'skip': ( sapx instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); // FUNCTIONS // @@ -49,7 +48,13 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.js index b98d981d2b07..29b81da77048 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var sapx = require( './../lib/ndarray.js' ); -// VARIABLES // - -var rand = uniform( -100.0, 100.0 ); - - // FUNCTIONS // /** @@ -44,7 +39,13 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.native.js index 650ac428642a..cd198d07eff6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var sapx = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( sapx instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); // FUNCTIONS // @@ -49,7 +48,13 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/sapx/docs/repl.txt index 42e084cc080c..0c12d6d9d792 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/docs/repl.txt @@ -3,13 +3,13 @@ Adds a constant to each element in a single-precision floating-point strided array. - The `N` and stride parameters determine which elements in the strided array - are accessed at runtime. + The `N` and `stride` parameters determine which elements in `x` are accessed + at runtime. Indexing is relative to the first index. To introduce an offset, use typed array views. - If `N <= 0`, the function returns the strided array unchanged. + If `N <= 0`, the function returns `x` unchanged. Parameters ---------- @@ -23,34 +23,40 @@ Input array. stride: integer - Index increment. + Index increment for `x`. Returns ------- x: Float32Array - Input array. + Input array `x`. Examples -------- // Standard Usage: > var x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] ); - > {{alias}}( x.length, 5.0, x, 1 ) + > var alpha = 5.0; + > {{alias}}( x.length, alpha, x, 1 ) [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ] // Using `N` and `stride` parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] ); - > {{alias}}( 3, 5.0, x, 2 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > alpha = 5.0; + > var stride = 2; + > {{alias}}( N, alpha, x, stride ) [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ] // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > {{alias}}( 3, 5.0, x1, 2 ) + > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); + > alpha = 5.0; + > stride = 2; + > {{alias}}( N, alpha, x1, stride ) [ 3.0, 3.0, 1.0, 5.0, -1.0 ] > x0 [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ] - {{alias}}.ndarray( N, alpha, x, stride, offset ) Adds a constant to each element in a single-precision floating-point strided array using alternative indexing semantics. @@ -71,26 +77,30 @@ Input array. stride: integer - Index increment. + Index increment for `x`. offset: integer - Starting index. + Starting index of `x`. Returns ------- x: Float32Array - Input array. + Input array `x`. Examples -------- // Standard Usage: > var x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] ); - > {{alias}}.ndarray( x.length, 5.0, x, 1, 0 ) + > var alpha = 5.0; + > {{alias}}.ndarray( x.length, alpha, x, 1, 0 ) [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ] // Using an index offset: > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] ); - > {{alias}}.ndarray( 3, 5.0, x, 2, 1 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > alpha = 5.0; + > var stride = 2; + > {{alias}}.ndarray( N, alpha, x, stride, 1 ) [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ] See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/examples/index.js index 3e9bf3a73c87..650232f9d8e2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/examples/index.js @@ -18,12 +18,27 @@ 'use strict'; -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var round = require( '@stdlib/math/base/special/round' ); +var randu = require( '@stdlib/random/base/randu' ); +var Float32Array = require( '@stdlib/array/float32' ); var sapx = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', uniform( -100.0, 100.0 ) ); +var rand; +var sign; +var x; +var i; +x = new Float32Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + rand = round( randu()*100.0 ); + sign = randu(); + if ( sign < 0.5 ) { + sign = -1.0; + } else { + sign = 1.0; + } + x[ i ] = sign * rand; +} console.log( x ); sapx( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/sapx/include.gypi index 26476a8c2655..868c5c12e852 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/include.gypi +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.c', + '<(src_dir)/addon.cpp', ' - -/** -* Receives JavaScript callback invocation data. -* -* @private -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ) - c_sapx( N, alpha, X, strideX ); - return NULL; -} - -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/src/addon.cpp b/lib/node_modules/@stdlib/blas/ext/base/sapx/src/addon.cpp new file mode 100644 index 000000000000..2d511f5f5af3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/src/addon.cpp @@ -0,0 +1,128 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sapx.h" +#include +#include +#include +#include +#include + +/** +* Add-on namespace. +*/ +namespace stdlib_blas_ext_base_sapx { + + /** + * Adds a constant to each element in a single-precision floating-point strided array. + * + * ## Notes + * + * - When called from JavaScript, the function expects four arguments: + * + * - `N`: number of indexed elements + * - `alpha`: scalar + * - `X`: input array + * - `strideX`: `X` stride length + */ + napi_value node_sapx( napi_env env, napi_callback_info info ) { + napi_status status; + + size_t argc = 4; + napi_value argv[ 4 ]; + status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); + assert( status == napi_ok ); + + if ( argc < 4 ) { + napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); + return nullptr; + } + + napi_valuetype vtype0; + status = napi_typeof( env, argv[ 0 ], &vtype0 ); + assert( status == napi_ok ); + if ( vtype0 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); + return nullptr; + } + + napi_valuetype vtype1; + status = napi_typeof( env, argv[ 1 ], &vtype1 ); + assert( status == napi_ok ); + if ( vtype1 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); + return nullptr; + } + + bool res2; + status = napi_is_typedarray( env, argv[ 2 ], &res2 ); + assert( status == napi_ok ); + if ( res2 == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + + napi_valuetype vtype3; + status = napi_typeof( env, argv[ 3 ], &vtype3 ); + assert( status == napi_ok ); + if ( vtype3 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); + return nullptr; + } + + int64_t N; + status = napi_get_value_int64( env, argv[ 0 ], &N ); + assert( status == napi_ok ); + + double alpha; + status = napi_get_value_double( env, argv[ 1 ], &alpha ); + assert( status == napi_ok ); + + int64_t strideX; + status = napi_get_value_int64( env, argv[ 3 ], &strideX ); + assert( status == napi_ok ); + + napi_typedarray_type vtype2; + size_t xlen; + void *X; + status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype2 != napi_float32_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + c_sapx( N, (float)alpha, (float *)X, strideX ); + + return nullptr; + } + + napi_value Init( napi_env env, napi_value exports ) { + napi_status status; + napi_value fcn; + status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_sapx, NULL, &fcn ); + assert( status == napi_ok ); + return fcn; + } + + NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) +} // end namespace stdlib_blas_ext_base_sapx diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/test/test.ndarray.js index d0413321a0c2..d6af1182cc72 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/test/test.ndarray.js @@ -86,7 +86,7 @@ tape( 'the function returns a reference to the input array', function test( t ) t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the input array unchanged', function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { var expected; var x; @@ -102,7 +102,7 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu t.end(); }); -tape( 'if `alpha` equals `0`, the function returns the input array unchanged', function test( t ) { +tape( 'if `alpha` equals `0`, the function returns `x` unchanged', function test( t ) { var expected; var x; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/test/test.ndarray.native.js index 0b99f94efe61..4936985b82af 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/test/test.ndarray.native.js @@ -95,7 +95,7 @@ tape( 'the function returns a reference to the input array', opts, function test t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the input array unchanged', opts, function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', opts, function test( t ) { var expected; var x; @@ -111,7 +111,7 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu t.end(); }); -tape( 'if `alpha` equals `0`, the function returns the input array unchanged', opts, function test( t ) { +tape( 'if `alpha` equals `0`, the function returns `x` unchanged', opts, function test( t ) { var expected; var x; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/test/test.sapx.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/test/test.sapx.js index 014e47e5ad8a..462982a68478 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/test/test.sapx.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/test/test.sapx.js @@ -86,7 +86,7 @@ tape( 'the function returns a reference to the input array', function test( t ) t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the input array unchanged', function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { var expected; var x; @@ -102,7 +102,7 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu t.end(); }); -tape( 'if `alpha` equals `0`, the function returns the input array unchanged', function test( t ) { +tape( 'if `alpha` equals `0`, the function returns `x` unchanged', function test( t ) { var expected; var x; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/test/test.sapx.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/test/test.sapx.native.js index 9f97b9f87a7c..88f1b8126580 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/test/test.sapx.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/test/test.sapx.native.js @@ -95,7 +95,7 @@ tape( 'the function returns a reference to the input array', opts, function test t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the input array unchanged', opts, function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', opts, function test( t ) { var expected; var x; @@ -111,7 +111,7 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu t.end(); }); -tape( 'if `alpha` equals `0`, the function returns the input array unchanged', opts, function test( t ) { +tape( 'if `alpha` equals `0`, the function returns `x` unchanged', opts, function test( t ) { var expected; var x; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/README.md b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/README.md index 7c7e27ae3ca7..effe09603735 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/README.md @@ -56,14 +56,16 @@ The function has the following parameters: - **x**: input [`Float32Array`][@stdlib/array/float32]. - **stride**: index increment for `x`. -The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element in `x`, +The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to access every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); +var N = floor( x.length / 2 ); -var v = sapxsum( 4, 5.0, x, 2 ); +var v = sapxsum( N, 5.0, x, 2 ); // returns 25.0 ``` @@ -73,11 +75,14 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var v = sapxsum( 4, 5.0, x1, 2 ); +var N = floor( x0.length / 2 ); + +var v = sapxsum( N, 5.0, x1, 2 ); // returns 25.0 ``` @@ -99,14 +104,16 @@ The function has the following additional parameters: - **offset**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the offset parameter supports indexing semantics based on a starting index. For example, to access every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access every other value in `x` starting from the second value ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +var N = floor( x.length / 2 ); -var v = sapxsum.ndarray( 4, 5.0, x, 2, 1 ); +var v = sapxsum.ndarray( N, 5.0, x, 2, 1 ); // returns 25.0 ``` @@ -131,12 +138,22 @@ var v = sapxsum.ndarray( 4, 5.0, x, 2, 1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float32Array = require( '@stdlib/array/float32' ); var sapxsum = require( '@stdlib/blas/ext/base/sapxsum' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x; +var i; + +x = new Float32Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); + +var v = sapxsum( x.length, 5.0, x, 1 ); +console.log( v ); ``` diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.js index a3794363584e..7c7093df3de5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var sapxsum = require( './../lib/sapxsum.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -44,7 +39,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.native.js index f850b14b21dc..d3efad2eac3f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var sapxsum = tryRequire( resolve( __dirname, './../lib/sapxsum.native.js' ) ); var opts = { 'skip': ( sapxsum instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -49,7 +48,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.js index 8197e74a9950..2a7a6dddc356 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var sapxsum = require( './../lib/ndarray.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -44,7 +39,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.native.js index ad9b898716e7..4c3571eeb841 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var sapxsum = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( sapxsum instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -49,7 +48,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/docs/repl.txt index b277320a58d3..645a563ce6ef 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/docs/repl.txt @@ -3,8 +3,8 @@ Adds a constant to each single-precision floating-point strided array element and computes the sum. - The `N` and stride parameters determine which elements in the strided - array are accessed at runtime. + The `N` and `stride` parameters determine which elements in `x` are accessed + at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -37,24 +37,27 @@ > {{alias}}( x.length, 5.0, x, 1 ) 16.0 - // Using `N` and stride parameters: + // Using `N` and `stride` parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > {{alias}}( 3, 5.0, x, 2 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > var stride = 2; + > {{alias}}( N, 5.0, x, stride ) 16.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > {{alias}}( 3, 5.0, x1, 2 ) + > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); + > stride = 2; + > {{alias}}( N, 5.0, x1, stride ) 14.0 - {{alias}}.ndarray( N, alpha, x, stride, offset ) Adds a constant to each single-precision floating-point strided array element and computes the sum using alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the offset parameter supports indexing semantics based on a + buffer, the `offset` parameter supports indexing semantics based on a starting index. Parameters @@ -87,8 +90,9 @@ 16.0 // Using offset parameter: - > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > {{alias}}.ndarray( 3, 5.0, x, 2, 1 ) + > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > {{alias}}.ndarray( N, 5.0, x, 2, 1 ) 14.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/examples/index.js index 9dffd93b0fc8..7124ce61ec87 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/examples/index.js @@ -18,11 +18,18 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float32Array = require( '@stdlib/array/float32' ); var sapxsum = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x; +var i; + +x = new Float32Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); var v = sapxsum( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/include.gypi index 26476a8c2655..868c5c12e852 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/include.gypi +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.c', + '<(src_dir)/addon.cpp', ' -#include - -/** -* Receives JavaScript callback invocation data. -* -* @private -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_sapxsum( N, alpha, X, stride ), &v ); - assert( status == napi_ok ); - - return v; -} - -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/src/addon.cpp b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/src/addon.cpp new file mode 100644 index 000000000000..76b29f8d478a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/src/addon.cpp @@ -0,0 +1,130 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sapxsum.h" +#include +#include +#include +#include +#include + +/** +* Add-on namespace. +*/ +namespace stdlib_blas_ext_base_sapxsum { + + /** + * Adds a constant to each single-precision floating-point strided array element and computes the sum. + * + * ## Notes + * + * - When called from JavaScript, the function expects four arguments: + * + * - `N`: number of indexed elements + * - `alpha`: constant + * - `X`: input array + * - `stride`: stride length + */ + napi_value node_sapxsum( napi_env env, napi_callback_info info ) { + napi_status status; + + size_t argc = 4; + napi_value argv[ 4 ]; + status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); + assert( status == napi_ok ); + + if ( argc < 4 ) { + napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); + return nullptr; + } + + napi_valuetype vtype0; + status = napi_typeof( env, argv[ 0 ], &vtype0 ); + assert( status == napi_ok ); + if ( vtype0 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); + return nullptr; + } + + napi_valuetype vtype1; + status = napi_typeof( env, argv[ 1 ], &vtype1 ); + assert( status == napi_ok ); + if ( vtype1 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); + return nullptr; + } + + bool res; + status = napi_is_typedarray( env, argv[ 2 ], &res ); + assert( status == napi_ok ); + if ( res == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + + napi_valuetype vtype3; + status = napi_typeof( env, argv[ 3 ], &vtype3 ); + assert( status == napi_ok ); + if ( vtype3 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); + return nullptr; + } + + int64_t N; + status = napi_get_value_int64( env, argv[ 0 ], &N ); + assert( status == napi_ok ); + + double alpha; + status = napi_get_value_double( env, argv[ 1 ], &alpha ); + assert( status == napi_ok ); + + int64_t stride; + status = napi_get_value_int64( env, argv[ 3 ], &stride ); + assert( status == napi_ok ); + + napi_typedarray_type vtype2; + size_t xlen; + void *X; + status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype2 != napi_float32_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + napi_value v; + status = napi_create_double( env, (double)stdlib_strided_sapxsum( N, (float)alpha, (float *)X, stride ), &v ); + assert( status == napi_ok ); + + return v; + } + + napi_value Init( napi_env env, napi_value exports ) { + napi_status status; + napi_value fcn; + status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_sapxsum, NULL, &fcn ); + assert( status == napi_ok ); + return fcn; + } + + NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) +} // end namespace stdlib_blas_ext_base_sapxsum diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.ndarray.js index 6b1841d188ca..61fc59e77d03 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.ndarray.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var sapxsum = require( './../lib/ndarray.js' ); @@ -35,7 +36,7 @@ tape( 'main export is a function', function test( t ) { }); tape( 'the function has an arity of 5', function test( t ) { - t.strictEqual( sapxsum.length, 5, 'returns expected value' ); + t.strictEqual( sapxsum.length, 5, 'has expected arity' ); t.end(); }); @@ -94,6 +95,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { + var N; var x; var v; @@ -108,13 +110,15 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - v = sapxsum( 4, 5.0, x, 2, 0 ); + N = floor( x.length / 2 ); + v = sapxsum( N, 5.0, x, 2, 0 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { + var N; var x; var v; @@ -129,7 +133,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - v = sapxsum( 4, 5.0, x, -2, 6 ); + N = floor( x.length / 2 ); + v = sapxsum( N, 5.0, x, -2, 6 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); @@ -148,6 +153,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { + var N; var x; var v; @@ -161,8 +167,9 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); + N = floor( x.length / 2 ); - v = sapxsum( 4, 5.0, x, 2, 1 ); + v = sapxsum( N, 5.0, x, 2, 1 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.ndarray.native.js index 6d6e3d7349d3..70b804ddb7cf 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.ndarray.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -44,7 +45,7 @@ tape( 'main export is a function', opts, function test( t ) { }); tape( 'the function has an arity of 5', opts, function test( t ) { - t.strictEqual( sapxsum.length, 5, 'returns expected value' ); + t.strictEqual( sapxsum.length, 5, 'has expected arity' ); t.end(); }); @@ -103,6 +104,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -117,13 +119,15 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - v = sapxsum( 4, 5.0, x, 2, 0 ); + N = floor( x.length / 2 ); + v = sapxsum( N, 5.0, x, 2, 0 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -138,7 +142,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - v = sapxsum( 4, 5.0, x, -2, 6 ); + N = floor( x.length / 2 ); + v = sapxsum( N, 5.0, x, -2, 6 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); @@ -157,6 +162,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { + var N; var x; var v; @@ -170,8 +176,9 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); + N = floor( x.length / 2 ); - v = sapxsum( 4, 5.0, x, 2, 1 ); + v = sapxsum( N, 5.0, x, 2, 1 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.sapxsum.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.sapxsum.js index e69c204bcc8f..45232ed52350 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.sapxsum.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.sapxsum.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var sapxsum = require( './../lib/sapxsum.js' ); @@ -94,6 +95,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { + var N; var x; var v; @@ -108,13 +110,15 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - v = sapxsum( 4, 5.0, x, 2 ); + N = floor( x.length / 2 ); + v = sapxsum( N, 5.0, x, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { + var N; var x; var v; @@ -129,7 +133,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - v = sapxsum( 4, 5.0, x, -2 ); + N = floor( x.length / 2 ); + v = sapxsum( N, 5.0, x, -2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); @@ -150,6 +155,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; + var N; var v; x0 = new Float32Array([ @@ -165,8 +171,9 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + N = floor(x1.length / 2); - v = sapxsum( 4, 5.0, x1, 2 ); + v = sapxsum( N, 5.0, x1, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.sapxsum.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.sapxsum.native.js index 5776424c10a5..81a46607b045 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.sapxsum.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.sapxsum.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -44,7 +45,7 @@ tape( 'main export is a function', opts, function test( t ) { }); tape( 'the function has an arity of 4', opts, function test( t ) { - t.strictEqual( sapxsum.length, 4, 'returns expected value' ); + t.strictEqual( sapxsum.length, 4, 'has expected arity' ); t.end(); }); @@ -212,6 +213,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -226,13 +228,15 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - v = sapxsum( 4, 5.0, x, 2 ); + N = floor( x.length / 2 ); + v = sapxsum( N, 5.0, x, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -247,7 +251,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - v = sapxsum( 4, 5.0, x, -2 ); + N = floor( x.length / 2 ); + v = sapxsum( N, 5.0, x, -2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); @@ -268,6 +273,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; + var N; var v; x0 = new Float32Array([ @@ -283,8 +289,9 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + N = floor(x1.length / 2); - v = sapxsum( 4, 5.0, x1, 2 ); + v = sapxsum( N, 5.0, x1, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/README.md b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/README.md index 6029f851c8dc..cac3a4097cf2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/README.md @@ -44,26 +44,28 @@ Adds a constant to each single-precision floating-point strided array element an var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); +var N = x.length; -var v = sapxsumkbn( 3, 5.0, x, 1 ); +var v = sapxsumkbn( N, 5.0, x, 1 ); // returns 16.0 ``` The function has the following parameters: - **N**: number of indexed elements. -- **alpha**: scalar constant. - **x**: input [`Float32Array`][@stdlib/array/float32]. - **stride**: index increment for `x`. -The `N` and `stride` parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element in the strided array, +The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to access every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); +var N = floor( x.length / 2 ); -var v = sapxsumkbn( 4, 5.0, x, 2 ); +var v = sapxsumkbn( N, 5.0, x, 2 ); // returns 25.0 ``` @@ -73,11 +75,14 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var v = sapxsumkbn( 4, 5.0, x1, 2 ); +var N = floor( x0.length / 2 ); + +var v = sapxsumkbn( N, 5.0, x1, 2 ); // returns 25.0 ``` @@ -89,8 +94,9 @@ Adds a constant to each single-precision floating-point strided array element an var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); +var N = x.length; -var v = sapxsumkbn.ndarray( 3, 5.0, x, 1, 0 ); +var v = sapxsumkbn.ndarray( N, 5.0, x, 1, 0 ); // returns 16.0 ``` @@ -98,14 +104,16 @@ The function has the following additional parameters: - **offset**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the offset parameter supports indexing semantics based on a starting index. For example, to access every other value in the strided array starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access every other value in `x` starting from the second value ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +var N = floor( x.length / 2 ); -var v = sapxsumkbn.ndarray( 4, 5.0, x, 2, 1 ); +var v = sapxsumkbn.ndarray( N, 5.0, x, 2, 1 ); // returns 25.0 ``` @@ -130,11 +138,18 @@ var v = sapxsumkbn.ndarray( 4, 5.0, x, 2, 1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float32Array = require( '@stdlib/array/float32' ); var sapxsumkbn = require( '@stdlib/blas/ext/base/sapxsumkbn' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x; +var i; + +x = new Float32Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); var v = sapxsumkbn( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.js index 436b3c5fd9b3..99ead31c8a14 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var sapxsumkbn = require( './../lib/sapxsumkbn.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -44,7 +39,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.native.js index 6533d38d9263..d0bdfbe68feb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var sapxsumkbn = tryRequire( resolve( __dirname, './../lib/sapxsumkbn.native.js' var opts = { 'skip': ( sapxsumkbn instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -49,7 +48,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.js index 2468257ec2fe..5d514a5dc971 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var sapxsumkbn = require( './../lib/ndarray.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -44,7 +39,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.native.js index bcaf22fbf17a..f02a01b905b1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var sapxsumkbn = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) var opts = { 'skip': ( sapxsumkbn instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -49,7 +48,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/docs/repl.txt index c19a98e099c9..7200ddeac7d0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/docs/repl.txt @@ -3,8 +3,8 @@ Adds a constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. - The `N` and `stride` parameters determine which elements in the strided - array are accessed at runtime. + The `N` and `stride` parameters determine which elements in `x` are accessed + at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -39,16 +39,19 @@ // Using `N` and `stride` parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > {{alias}}( 3, 5.0, x, 2 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > var stride = 2; + > {{alias}}( N, 5.0, x, stride ) 16.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > {{alias}}( 3, 5.0, x1, 2 ) + > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); + > stride = 2; + > {{alias}}( N, 5.0, x1, stride ) 14.0 - {{alias}}.ndarray( N, alpha, x, stride, offset ) Adds a constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm and @@ -88,8 +91,9 @@ 16.0 // Using offset parameter: - > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > {{alias}}.ndarray( 3, 5.0, x, 2, 1 ) + > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > {{alias}}.ndarray( N, 5.0, x, 2, 1 ) 14.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/examples/index.js index 085e247e5682..9cf270e76a68 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/examples/index.js @@ -18,11 +18,18 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float32Array = require( '@stdlib/array/float32' ); var sapxsumkbn = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x; +var i; + +x = new Float32Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); var v = sapxsumkbn( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/include.gypi index 26476a8c2655..868c5c12e852 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/include.gypi +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.c', + '<(src_dir)/addon.cpp', ' -#include - -/** -* Receives JavaScript callback invocation data. -* -* @private -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); - - napi_value v; - napi_status status; - status = napi_create_double( env, (double)stdlib_strided_sapxsumkbn( N, alpha, X, stride ), &v ); - assert( status == napi_ok ); - return v; -} - -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/src/addon.cpp b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/src/addon.cpp new file mode 100644 index 000000000000..0ea997785adc --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/src/addon.cpp @@ -0,0 +1,130 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sapxsumkbn.h" +#include +#include +#include +#include +#include + +/** +* Add-on namespace. +*/ +namespace stdlib_blas_ext_base_sapxsumkbn { + + /** + * Adds a constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. + * + * ## Notes + * + * - When called from JavaScript, the function expects four arguments: + * + * - `N`: number of indexed elements + * - `alpha`: constant + * - `X`: input array + * - `stride`: stride length + */ + napi_value node_sapxsumkbn( napi_env env, napi_callback_info info ) { + napi_status status; + + size_t argc = 4; + napi_value argv[ 4 ]; + status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); + assert( status == napi_ok ); + + if ( argc < 4 ) { + napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); + return nullptr; + } + + napi_valuetype vtype0; + status = napi_typeof( env, argv[ 0 ], &vtype0 ); + assert( status == napi_ok ); + if ( vtype0 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); + return nullptr; + } + + napi_valuetype vtype1; + status = napi_typeof( env, argv[ 1 ], &vtype1 ); + assert( status == napi_ok ); + if ( vtype1 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); + return nullptr; + } + + bool res; + status = napi_is_typedarray( env, argv[ 2 ], &res ); + assert( status == napi_ok ); + if ( res == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + + napi_valuetype vtype3; + status = napi_typeof( env, argv[ 3 ], &vtype3 ); + assert( status == napi_ok ); + if ( vtype3 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); + return nullptr; + } + + int64_t N; + status = napi_get_value_int64( env, argv[ 0 ], &N ); + assert( status == napi_ok ); + + double alpha; + status = napi_get_value_double( env, argv[ 1 ], &alpha ); + assert( status == napi_ok ); + + int64_t stride; + status = napi_get_value_int64( env, argv[ 3 ], &stride ); + assert( status == napi_ok ); + + napi_typedarray_type vtype2; + size_t xlen; + void *X; + status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype2 != napi_float32_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + napi_value v; + status = napi_create_double( env, (double)stdlib_strided_sapxsumkbn( N, (float)alpha, (float *)X, stride ), &v ); + assert( status == napi_ok ); + + return v; + } + + napi_value Init( napi_env env, napi_value exports ) { + napi_status status; + napi_value fcn; + status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_sapxsumkbn, NULL, &fcn ); + assert( status == napi_ok ); + return fcn; + } + + NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) +} // end namespace stdlib_blas_ext_base_sapxsumkbn diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.ndarray.js index 9168b052806c..d2ddaba88f7c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.ndarray.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var sapxsumkbn = require( './../lib/ndarray.js' ); @@ -35,7 +36,7 @@ tape( 'main export is a function', function test( t ) { }); tape( 'the function has an arity of 5', function test( t ) { - t.strictEqual( sapxsumkbn.length, 5, 'returns expected value' ); + t.strictEqual( sapxsumkbn.length, 5, 'has expected arity' ); t.end(); }); @@ -94,6 +95,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { + var N; var x; var v; @@ -108,13 +110,15 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - v = sapxsumkbn( 4, 5.0, x, 2, 0 ); + N = floor( x.length / 2 ); + v = sapxsumkbn( N, 5.0, x, 2, 0 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { + var N; var x; var v; @@ -129,7 +133,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - v = sapxsumkbn( 4, 5.0, x, -2, 6 ); + N = floor( x.length / 2 ); + v = sapxsumkbn( N, 5.0, x, -2, 6 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); @@ -148,6 +153,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { + var N; var x; var v; @@ -161,8 +167,9 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); + N = floor( x.length / 2 ); - v = sapxsumkbn( 4, 5.0, x, 2, 1 ); + v = sapxsumkbn( N, 5.0, x, 2, 1 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.ndarray.native.js index 845e5a7d30ce..5be62cd27f8e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.ndarray.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -44,7 +45,7 @@ tape( 'main export is a function', opts, function test( t ) { }); tape( 'the function has an arity of 5', opts, function test( t ) { - t.strictEqual( sapxsumkbn.length, 5, 'returns expected value' ); + t.strictEqual( sapxsumkbn.length, 5, 'has expected arity' ); t.end(); }); @@ -103,6 +104,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -117,13 +119,15 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - v = sapxsumkbn( 4, 5.0, x, 2, 0 ); + N = floor( x.length / 2 ); + v = sapxsumkbn( N, 5.0, x, 2, 0 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -138,7 +142,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - v = sapxsumkbn( 4, 5.0, x, -2, 6 ); + N = floor( x.length / 2 ); + v = sapxsumkbn( N, 5.0, x, -2, 6 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); @@ -157,6 +162,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { + var N; var x; var v; @@ -170,8 +176,9 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); + N = floor( x.length / 2 ); - v = sapxsumkbn( 4, 5.0, x, 2, 1 ); + v = sapxsumkbn( N, 5.0, x, 2, 1 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.sapxsumkbn.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.sapxsumkbn.js index 7f1726ee0230..b428132469c2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.sapxsumkbn.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.sapxsumkbn.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var sapxsumkbn = require( './../lib/sapxsumkbn.js' ); @@ -35,7 +36,7 @@ tape( 'main export is a function', function test( t ) { }); tape( 'the function has an arity of 4', function test( t ) { - t.strictEqual( sapxsumkbn.length, 4, 'returns expected value' ); + t.strictEqual( sapxsumkbn.length, 4, 'has expected arity' ); t.end(); }); @@ -94,6 +95,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { + var N; var x; var v; @@ -108,13 +110,15 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - v = sapxsumkbn( 4, 5.0, x, 2 ); + N = floor( x.length / 2 ); + v = sapxsumkbn( N, 5.0, x, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { + var N; var x; var v; @@ -129,7 +133,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - v = sapxsumkbn( 4, 5.0, x, -2 ); + N = floor( x.length / 2 ); + v = sapxsumkbn( N, 5.0, x, -2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); @@ -150,6 +155,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; + var N; var v; x0 = new Float32Array([ @@ -165,8 +171,9 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + N = floor(x1.length / 2); - v = sapxsumkbn( 4, 5.0, x1, 2 ); + v = sapxsumkbn( N, 5.0, x1, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.sapxsumkbn.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.sapxsumkbn.native.js index 34b37df19ff3..a3543c1580bb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.sapxsumkbn.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.sapxsumkbn.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -44,7 +45,7 @@ tape( 'main export is a function', opts, function test( t ) { }); tape( 'the function has an arity of 4', opts, function test( t ) { - t.strictEqual( sapxsumkbn.length, 4, 'returns expected value' ); + t.strictEqual( sapxsumkbn.length, 4, 'has expected arity' ); t.end(); }); @@ -212,6 +213,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -226,13 +228,15 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - v = sapxsumkbn( 4, 5.0, x, 2 ); + N = floor( x.length / 2 ); + v = sapxsumkbn( N, 5.0, x, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -247,7 +251,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - v = sapxsumkbn( 4, 5.0, x, -2 ); + N = floor( x.length / 2 ); + v = sapxsumkbn( N, 5.0, x, -2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); @@ -268,6 +273,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; + var N; var v; x0 = new Float32Array([ @@ -283,8 +289,9 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + N = floor(x1.length / 2); - v = sapxsumkbn( 4, 5.0, x1, 2 ); + v = sapxsumkbn( N, 5.0, x1, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/README.md b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/README.md index 2ea223b640e5..84439e5654c7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/README.md @@ -56,14 +56,16 @@ The function has the following parameters: - **x**: input [`Float32Array`][@stdlib/array/float32]. - **stride**: index increment for `x`. -The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element in `x`, +The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to access every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); +var N = floor( x.length / 2 ); -var v = sapxsumpw( 4, 5.0, x, 2 ); +var v = sapxsumpw( N, 5.0, x, 2 ); // returns 25.0 ``` @@ -73,11 +75,14 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var v = sapxsumpw( 4, 5.0, x1, 2 ); +var N = floor( x0.length / 2 ); + +var v = sapxsumpw( N, 5.0, x1, 2 ); // returns 25.0 ``` @@ -103,10 +108,12 @@ While [`typed array`][mdn-typed-array] views mandate a view offset based on the ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +var N = floor( x.length / 2 ); -var v = sapxsumpw.ndarray( 4, 5.0, x, 2, 1 ); +var v = sapxsumpw.ndarray( N, 5.0, x, 2, 1 ); // returns 25.0 ``` @@ -131,12 +138,18 @@ var v = sapxsumpw.ndarray( 4, 5.0, x, 2, 1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float32Array = require( '@stdlib/array/float32' ); var sapxsumpw = require( '@stdlib/blas/ext/base/sapxsumpw' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x; +var i; +x = new Float32Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); var v = sapxsumpw( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.js index 1e03ab275c86..b493f7547089 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.js @@ -21,10 +21,10 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var sapxsumpw = require( './../lib/sapxsumpw.js' ); @@ -40,9 +40,12 @@ var sapxsumpw = require( './../lib/sapxsumpw.js' ); */ function createBenchmark( len ) { var x; + var i; - x = filledarrayBy( len, 'float32', uniform( -10.0, 10.0 ) ); - + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.native.js index 756d5a078148..93db52a1f7a0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -49,9 +49,12 @@ var opts = { */ function createBenchmark( len ) { var x; + var i; - x = filledarrayBy( len, 'float32', uniform( -10.0, 10.0 ) ); - + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.js index e680e6575f61..b6b6daac4c36 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.js @@ -21,10 +21,10 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var sapxsumpw = require( './../lib/ndarray.js' ); @@ -40,9 +40,12 @@ var sapxsumpw = require( './../lib/ndarray.js' ); */ function createBenchmark( len ) { var x; + var i; - x = filledarrayBy( len, 'float32', uniform( -10.0, 10.0 ) ); - + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.native.js index 00d203a97740..677788064f7f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -49,9 +49,12 @@ var opts = { */ function createBenchmark( len ) { var x; + var i; - x = filledarrayBy( len, 'float32', uniform( -10.0, 10.0 ) ); - + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/docs/repl.txt index 469b9b207f4f..acb1305e4683 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/docs/repl.txt @@ -3,7 +3,7 @@ Adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. - The `N` and stride parameters determine which elements in `x` are accessed + The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed @@ -39,18 +39,19 @@ // Using `N` and `stride` parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); > var stride = 2; - > {{alias}}( 3, 5.0, x, stride ) + > {{alias}}( N, 5.0, x, stride ) 16.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); > stride = 2; - > {{alias}}( 3, 5.0, x1, stride ) + > {{alias}}( N, 5.0, x1, stride ) 14.0 - {{alias}}.ndarray( N, alpha, x, stride, offset ) Adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation and alternative @@ -91,7 +92,8 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > {{alias}}.ndarray( 3, 5.0, x, 2, 1 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > {{alias}}.ndarray( N, 5.0, x, 2, 1 ) 14.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/examples/index.js index ce7accccd889..69d0d6f8ef97 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/examples/index.js @@ -18,14 +18,18 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float32Array = require( '@stdlib/array/float32' ); var sapxsumpw = require( './../lib' ); var x; +var i; -x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); - +x = new Float32Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); var v = sapxsumpw( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/include.gypi index 26476a8c2655..868c5c12e852 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/include.gypi +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.c', + '<(src_dir)/addon.cpp', ' - -/** -* Receives JavaScript callback invocation data. -* -* @private -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); - - napi_value v; - napi_status status = napi_create_double( env, (double)stdlib_strided_sapxsumpw( N, alpha, X, stride ), &v ); - assert( status == napi_ok ); - - return v; -} - -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) \ No newline at end of file diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/src/addon.cpp b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/src/addon.cpp new file mode 100644 index 000000000000..7bcbc23495e5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/src/addon.cpp @@ -0,0 +1,130 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sapxsumpw.h" +#include +#include +#include +#include +#include + +/** +* Add-on namespace. +*/ +namespace stdlib_blas_ext_base_sapxsumpw { + + /** + * Adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. + * + * ## Notes + * + * - When called from JavaScript, the function expects four arguments: + * + * - `N`: number of indexed elements + * - `alpha`: constant + * - `X`: input array + * - `stride`: stride length + */ + napi_value node_sapxsumpw( napi_env env, napi_callback_info info ) { + napi_status status; + + size_t argc = 4; + napi_value argv[ 4 ]; + status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); + assert( status == napi_ok ); + + if ( argc < 4 ) { + napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); + return nullptr; + } + + napi_valuetype vtype0; + status = napi_typeof( env, argv[ 0 ], &vtype0 ); + assert( status == napi_ok ); + if ( vtype0 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); + return nullptr; + } + + napi_valuetype vtype1; + status = napi_typeof( env, argv[ 1 ], &vtype1 ); + assert( status == napi_ok ); + if ( vtype1 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); + return nullptr; + } + + bool res; + status = napi_is_typedarray( env, argv[ 2 ], &res ); + assert( status == napi_ok ); + if ( res == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + + napi_valuetype vtype3; + status = napi_typeof( env, argv[ 3 ], &vtype3 ); + assert( status == napi_ok ); + if ( vtype3 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); + return nullptr; + } + + int64_t N; + status = napi_get_value_int64( env, argv[ 0 ], &N ); + assert( status == napi_ok ); + + double alpha; + status = napi_get_value_double( env, argv[ 1 ], &alpha ); + assert( status == napi_ok ); + + int64_t stride; + status = napi_get_value_int64( env, argv[ 3 ], &stride ); + assert( status == napi_ok ); + + napi_typedarray_type vtype2; + size_t xlen; + void *X; + status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype2 != napi_float32_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + napi_value v; + status = napi_create_double( env, (double)stdlib_strided_sapxsumpw( N, (float)alpha, (float *)X, stride ), &v ); + assert( status == napi_ok ); + + return v; + } + + napi_value Init( napi_env env, napi_value exports ) { + napi_status status; + napi_value fcn; + status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_sapxsumpw, NULL, &fcn ); + assert( status == napi_ok ); + return fcn; + } + + NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) +} // end namespace stdlib_blas_ext_base_sapxsumpw diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.ndarray.js index c16278d1610d..b3019ad0c618 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.ndarray.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var sapxsumpw = require( './../lib/ndarray.js' ); @@ -102,6 +103,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { + var N; var x; var v; @@ -116,13 +118,15 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - v = sapxsumpw( 4, 5.0, x, 2, 0 ); + N = floor( x.length / 2 ); + v = sapxsumpw( N, 5.0, x, 2, 0 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { + var N; var x; var v; var i; @@ -138,7 +142,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - v = sapxsumpw( 4, 5.0, x, -2, 6 ); + N = floor( x.length / 2 ); + v = sapxsumpw( N, 5.0, x, -2, 6 ); t.strictEqual( v, 25.0, 'returns expected value' ); @@ -165,6 +170,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { + var N; var x; var v; @@ -178,8 +184,9 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); + N = floor( x.length / 2 ); - v = sapxsumpw( 4, 5.0, x, 2, 1 ); + v = sapxsumpw( N, 5.0, x, 2, 1 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.ndarray.native.js index 22fa27a4bbd8..c8f11b8df159 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.ndarray.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -111,6 +112,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -125,13 +127,15 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - v = sapxsumpw( 4, 5.0, x, 2, 0 ); + N = floor( x.length / 2 ); + v = sapxsumpw( N, 5.0, x, 2, 0 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var N; var x; var v; var i; @@ -147,7 +151,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - v = sapxsumpw( 4, 5.0, x, -2, 6 ); + N = floor( x.length / 2 ); + v = sapxsumpw( N, 5.0, x, -2, 6 ); t.strictEqual( v, 25.0, 'returns expected value' ); @@ -174,6 +179,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { + var N; var x; var v; @@ -187,8 +193,9 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); + N = floor( x.length / 2 ); - v = sapxsumpw( 4, 5.0, x, 2, 1 ); + v = sapxsumpw( N, 5.0, x, 2, 1 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.sapxsumpw.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.sapxsumpw.js index 4b9c1dedbbec..0c4717aa057c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.sapxsumpw.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.sapxsumpw.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var sapxsumpw = require( './../lib/sapxsumpw.js' ); @@ -102,6 +103,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { + var N; var x; var v; @@ -116,13 +118,15 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - v = sapxsumpw( 4, 5.0, x, 2 ); + N = floor( x.length / 2 ); + v = sapxsumpw( N, 5.0, x, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { + var N; var x; var v; var i; @@ -138,7 +142,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - v = sapxsumpw( 4, 5.0, x, -2 ); + N = floor( x.length / 2 ); + v = sapxsumpw( N, 5.0, x, -2 ); t.strictEqual( v, 25.0, 'returns expected value' ); @@ -167,6 +172,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; + var N; var v; x0 = new Float32Array([ @@ -182,8 +188,9 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + N = floor(x1.length / 2); - v = sapxsumpw( 4, 5.0, x1, 2 ); + v = sapxsumpw( N, 5.0, x1, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.sapxsumpw.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.sapxsumpw.native.js index ea0af9baf524..232f3a74259f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.sapxsumpw.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.sapxsumpw.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -220,6 +221,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -234,13 +236,15 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - v = sapxsumpw( 4, 5.0, x, 2 ); + N = floor( x.length / 2 ); + v = sapxsumpw( N, 5.0, x, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var N; var x; var v; var i; @@ -256,7 +260,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - v = sapxsumpw( 4, 5.0, x, -2 ); + N = floor( x.length / 2 ); + v = sapxsumpw( N, 5.0, x, -2 ); t.strictEqual( v, 25.0, 'returns expected value' ); @@ -285,6 +290,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; + var N; var v; x0 = new Float32Array([ @@ -300,8 +306,9 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + N = floor(x1.length / 2); - v = sapxsumpw( 4, 5.0, x1, 2 ); + v = sapxsumpw( N, 5.0, x1, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/README.md b/lib/node_modules/@stdlib/blas/ext/base/scusum/README.md index fc090f8e6bf8..198ec8975cf3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/README.md @@ -65,15 +65,18 @@ The function has the following parameters: - **y**: output [`Float32Array`][@stdlib/array/float32]. - **strideY**: index increment for `y`. -The `N` and `stride` parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative sum of every other element in the strided input array, +The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to compute the cumulative sum of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); var y = new Float32Array( x.length ); -var v = scusum( 4, 0.0, x, 2, y, 1 ); +var N = floor( x.length / 2 ); + +var v = scusum( N, 0.0, x, 2, y, 1 ); // y => [ 1.0, 3.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] ``` @@ -83,6 +86,7 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); // Initial arrays... var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); @@ -92,7 +96,9 @@ var y0 = new Float32Array( x0.length ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element -scusum( 4, 0.0, x1, -2, y1, 1 ); +var N = floor( x0.length / 2 ); + +scusum( N, 0.0, x1, -2, y1, 1 ); // y0 => [ 0.0, 0.0, 0.0, 4.0, 6.0, 4.0, 5.0, 0.0 ] ``` @@ -115,15 +121,18 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: starting index for `y`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, offsetX and offsetY parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative sum of every other value in the strided input array starting from the second value and to store in the last `N` elements of the strided output array starting from the last element +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, `offsetX` and `offsetY` parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative sum of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var y = new Float32Array( x.length ); -scusum.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 ); +var N = floor( x.length / 2 ); + +scusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ); // y => [ 0.0, 0.0, 0.0, 0.0, 5.0, 1.0, -1.0, 1.0 ] ``` @@ -148,13 +157,20 @@ scusum.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); var Float32Array = require( '@stdlib/array/float32' ); var scusum = require( '@stdlib/blas/ext/base/scusum' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); -var y = new Float32Array( x.length ); +var y; +var x; +var i; + +x = new Float32Array( 10 ); +y = new Float32Array( x.length ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); console.log( y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.js index 69c251af827c..962e406fa06b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.js @@ -21,20 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); -var Float32Array = require( '@stdlib/array/float32' ); +var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var scusum = require( './../lib/scusum.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -45,8 +39,15 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = new Float32Array( len ); + var y; + var x; + var i; + + x = new Float32Array( len ); + y = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.native.js index 942a4ddda88a..02c902ea4406 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -37,7 +36,6 @@ var scusum = tryRequire( resolve( __dirname, './../lib/scusum.native.js' ) ); var opts = { 'skip': ( scusum instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -50,8 +48,15 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = new Float32Array( len ); + var x; + var y; + var i; + + x = new Float32Array( len ); + y = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.js index 00e014a1fe5e..125ca2e4786d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -30,11 +29,6 @@ var pkg = require( './../package.json' ).name; var scusum = require( './../lib/ndarray.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -45,8 +39,15 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = new Float32Array( len ); + var x; + var y; + var i; + + x = new Float32Array( len ); + y = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.native.js index 0a920dce4110..df723354c058 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -37,7 +36,6 @@ var scusum = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( scusum instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -50,8 +48,15 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = new Float32Array( len ); + var x; + var y; + var i; + + x = new Float32Array( len ); + y = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/scusum/docs/repl.txt index d6e5e3124514..568765828a01 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/docs/repl.txt @@ -3,8 +3,8 @@ Computes the cumulative sum of single-precision floating-point strided array elements. - The `N` and `stride` parameters determine which elements in the strided - arrays are accessed at runtime. + The `N` and `stride` parameters determine which elements in `x` and `y` are + accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -47,7 +47,8 @@ // Using `N` and `stride` parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); > y = new {{alias:@stdlib/array/float32}}( x.length ); - > {{alias}}( 3, 0.0, x, 2, y, 2 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > {{alias}}( N, 0.0, x, 2, y, 2 ) [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ] // Using view offsets: @@ -55,12 +56,12 @@ > var y0 = new {{alias:@stdlib/array/float32}}( x0.length ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); > var y1 = new {{alias:@stdlib/array/float32}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); - > {{alias}}( 3, 0.0, x1, 2, y1, 1 ) + > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); + > {{alias}}( N, 0.0, x1, 2, y1, 1 ) [ -2.0, 0.0, -1.0 ] > y0 [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ] - {{alias}}.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY ) Computes the cumulative sum of single-precision floating-point strided array elements using alternative indexing semantics. @@ -111,7 +112,8 @@ // Advanced indexing: > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > y = new {{alias:@stdlib/array/float32}}( x.length ); - > {{alias}}.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > {{alias}}.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ) [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ] See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/examples/index.js index 6a92d6ab1267..15f6a4e1c3ef 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/examples/index.js @@ -18,14 +18,20 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); var Float32Array = require( '@stdlib/array/float32' ); var scusum = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); -var y = new Float32Array( x.length ); +var y; +var x; +var i; +x = new Float32Array( 10 ); +y = new Float32Array( x.length ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); console.log( y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/scusum/include.gypi index 26476a8c2655..868c5c12e852 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/include.gypi +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.c', + '<(src_dir)/addon.cpp', ' [ 1.0, -1.0, 1.0 ] * * @example * var Float32Array = require( '@stdlib/array/float32' ); +* var floor = require( '@stdlib/math/base/special/floor' ); * var scusum = require( '@stdlib/blas/ext/base/scusum' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); +* var N = floor( x.length / 2 ); * -* scusum.ndarray( 4, 0.0, x, 2, 1, y, 1, 0 ); +* scusum.ndarray( N, 0.0, x, 2, 1, y, 1, 0 ); * // y => [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/ndarray.js index fc8c631d22b0..0b13094e661b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/ndarray.js @@ -40,11 +40,13 @@ var scusumkbn = require( '@stdlib/blas/ext/base/scusumkbn' ).ndarray; * * @example * var Float32Array = require( '@stdlib/array/float32' ); +* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); +* var N = floor( x.length / 2 ); * -* var v = scusum( 4, 0.0, x, 2, 1, y, 1, 0 ); +* var v = scusum( N, 0.0, x, 2, 1, y, 1, 0 ); * // returns [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ function scusum( N, sum, x, strideX, offsetX, y, strideY, offsetY ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/ndarray.native.js index 3f05e52ab35a..a5595b017394 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var minViewBufferIndex = require( '@stdlib/strided/base/min-view-buffer-index' ); -var offsetView = require( '@stdlib/strided/base/offset-view' ); +var Float32Array = require( '@stdlib/array/float32' ); var addon = require( './scusum.native.js' ); @@ -42,21 +41,26 @@ var addon = require( './scusum.native.js' ); * * @example * var Float32Array = require( '@stdlib/array/float32' ); +* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); +* var N = floor( x.length / 2 ); * -* var v = scusum( 4, 0.0, x, 2, 1, y, 1, 0 ); +* var v = scusum( N, 0.0, x, 2, 1, y, 1, 0 ); * // returns [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ function scusum( N, sum, x, strideX, offsetX, y, strideY, offsetY ) { var viewX; var viewY; - - offsetX = minViewBufferIndex( N, strideX, offsetX ); - viewX = offsetView( x, offsetX ); - offsetY = minViewBufferIndex( N, strideY, offsetY ); - viewY = offsetView( y, offsetY ); + if ( strideX < 0 ) { + offsetX += (N-1) * strideX; + } + if ( strideY < 0 ) { + offsetY += (N-1) * strideY; + } + viewX = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offsetX), x.length-offsetX ); // eslint-disable-line max-len + viewY = new Float32Array( y.buffer, y.byteOffset+(y.BYTES_PER_ELEMENT*offsetY), y.length-offsetY ); // eslint-disable-line max-len addon( N, sum, viewX, strideX, viewY, strideY ); return y; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/scusum.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/scusum.js index 6c0613927f8e..8e1e046d9304 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/scusum.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/scusum.js @@ -41,8 +41,9 @@ var scusumkbn = require( '@stdlib/blas/ext/base/scusumkbn' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); +* var N = x.length; * -* var v = scusum( 3, 0.0, x, 1, y, 1 ); +* var v = scusum( N, 0.0, x, 1, y, 1 ); * // returns [ 1.0, -1.0, 1.0 ] */ function scusum( N, sum, x, strideX, y, strideY ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/scusum.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/scusum.native.js index 96b9f767476f..804e5fb5590a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/scusum.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/scusum.native.js @@ -41,8 +41,9 @@ var addon = require( './../src/addon.node' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); +* var N = x.length; * -* var v = scusum( 3, 0.0, x, 1, y, 1 ); +* var v = scusum( N, 0.0, x, 1, y, 1 ); * // returns [ 1.0, -1.0, 1.0 ] */ function scusum( N, sum, x, strideX, y, strideY ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/scusum/manifest.json index 9f852154bd20..0c7e02a28ec0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/manifest.json +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/manifest.json @@ -1,78 +1,42 @@ { - "options": { - "task": "build" - }, - "fields": [ - { - "field": "src", - "resolve": true, - "relative": true - }, - { - "field": "include", - "resolve": true, - "relative": true - }, - { - "field": "libraries", - "resolve": false, - "relative": false - }, - { - "field": "libpath", - "resolve": true, - "relative": false - } - ], - "confs": [ - { - "task": "build", - "src": [ - "./src/scusum.c" - ], - "include": [ - "./include" - ], - "libraries": [ - "-lm" - ], - "libpath": [], - "dependencies": [ - "@stdlib/blas/ext/base/scusumkbn", - "stdlib/napi/export", - "stdlib/napi/argv", - "stdlib/napi/argv-int64", - "stdlib/napi/argv-float", - "stdlib/napi/argv-strided-float32array" - ] - }, - { - "task": "benchmark", - "src": [ - "./src/scusum.c" - ], - "include": [ - "./include" - ], - "libraries": [ - "-lm" - ], - "libpath": [], - "dependencies": [] - }, - { - "task": "examples", - "src": [ - "./src/scusum.c" - ], - "include": [ - "./include" - ], - "libraries": [ - "-lm" - ], - "libpath": [], - "dependencies": [] - } - ] + "options": {}, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "src": [ + "./src/scusum.c" + ], + "include": [ + "./include" + ], + "libraries": [ + "-lm" + ], + "libpath": [], + "dependencies": [ + "@stdlib/blas/ext/base/scusumkbn" + ] + } + ] } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/package.json b/lib/node_modules/@stdlib/blas/ext/base/scusum/package.json index bb44b07c32ff..0dcc765d7ae8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/package.json @@ -75,7 +75,5 @@ "single", "float32array" ], - "__stdlib__": { - "wasm": false - } + "__stdlib__": {} } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/scusum/src/addon.c deleted file mode 100644 index 93edb179b7c5..000000000000 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/src/addon.c +++ /dev/null @@ -1,48 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/blas/ext/base/scusum.h" -#include "stdlib/napi/export.h" -#include "stdlib/napi/argv.h" -#include "stdlib/napi/argv_int64.h" -#include "stdlib/napi/argv_float.h" -#include "stdlib/napi/argv_strided_float32array.h" -#include -#include - -/** -* Receives JavaScript callback invocation data. -* -* @private -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_FLOAT( env, N, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); - STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideY, argv, 4 ); - stdlib_strided_scusum( N, sum, X, strideX, Y, strideY ); - return NULL; -} - -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/src/addon.cpp b/lib/node_modules/@stdlib/blas/ext/base/scusum/src/addon.cpp new file mode 100644 index 000000000000..6a1382842289 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/src/addon.cpp @@ -0,0 +1,164 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/scusum.h" +#include +#include +#include +#include +#include + +/** +* Add-on namespace. +*/ +namespace stdlib_blas_ext_base_scusum { + + /** + * Computes the cumulative sum of single-precision floating-point strided array elements. + * + * ## Notes + * + * - When called from JavaScript, the function expects six arguments: + * + * - `N`: number of indexed elements + * - `sum`: initial sum + * - `X`: input array + * - `strideX`: `X` stride length + * - `Y`: output array + * - `strideY`: `Y` stride length + */ + napi_value node_scusum( napi_env env, napi_callback_info info ) { + napi_status status; + + size_t argc = 6; + napi_value argv[ 6 ]; + status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); + assert( status == napi_ok ); + + if ( argc < 6 ) { + napi_throw_error( env, nullptr, "invalid invocation. Must provide 6 arguments." ); + return nullptr; + } + + napi_valuetype vtype0; + status = napi_typeof( env, argv[ 0 ], &vtype0 ); + assert( status == napi_ok ); + if ( vtype0 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); + return nullptr; + } + + napi_valuetype vtype1; + status = napi_typeof( env, argv[ 1 ], &vtype1 ); + assert( status == napi_ok ); + if ( vtype1 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); + return nullptr; + } + + bool res2; + status = napi_is_typedarray( env, argv[ 2 ], &res2 ); + assert( status == napi_ok ); + if ( res2 == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + + napi_valuetype vtype3; + status = napi_typeof( env, argv[ 3 ], &vtype3 ); + assert( status == napi_ok ); + if ( vtype3 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); + return nullptr; + } + + bool res4; + status = napi_is_typedarray( env, argv[ 4 ], &res4 ); + assert( status == napi_ok ); + if ( res4 == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a Float32Array." ); + return nullptr; + } + + napi_valuetype vtype5; + status = napi_typeof( env, argv[ 5 ], &vtype5 ); + assert( status == napi_ok ); + if ( vtype5 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Sixth argument must be a number." ); + return nullptr; + } + + int64_t N; + status = napi_get_value_int64( env, argv[ 0 ], &N ); + assert( status == napi_ok ); + + double sum; + status = napi_get_value_double( env, argv[ 1 ], &sum ); + assert( status == napi_ok ); + + int64_t strideX; + status = napi_get_value_int64( env, argv[ 3 ], &strideX ); + assert( status == napi_ok ); + + int64_t strideY; + status = napi_get_value_int64( env, argv[ 5 ], &strideY ); + assert( status == napi_ok ); + + napi_typedarray_type vtype2; + size_t xlen; + void *X; + status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype2 != napi_float32_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + napi_typedarray_type vtype4; + size_t ylen; + void *Y; + status = napi_get_typedarray_info( env, argv[ 4 ], &vtype4, &ylen, &Y, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype4 != napi_float32_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a Float32Array." ); + return nullptr; + } + if ( (N-1)*llabs(strideY) >= (int64_t)ylen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Fifth argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + stdlib_strided_scusum( N, (float)sum, (float *)X, strideX, (float *)Y, strideY ); + + return nullptr; + } + + napi_value Init( napi_env env, napi_value exports ) { + napi_status status; + napi_value fcn; + status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_scusum, NULL, &fcn ); + assert( status == napi_ok ); + return fcn; + } + + NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) +} // end namespace stdlib_blas_ext_base_scusum diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/test/test.ndarray.js index da0034ad3831..ffcae20fc948 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/test/test.ndarray.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var Float32Array = require( '@stdlib/array/float32' ); var scusum = require( './../lib/ndarray.js' ); @@ -163,6 +164,7 @@ tape( 'the function supports an `x` stride', function test( t ) { var expected; var x; var y; + var N; x = new Float32Array([ 1.0, // 0 @@ -178,8 +180,9 @@ tape( 'the function supports an `x` stride', function test( t ) { 0.0, 0.0 ]); + N = 3; - scusum( 3, 0.0, x, 2, 0, y, 1, 0 ); + scusum( N, 0.0, x, 2, 0, y, 1, 0 ); expected = new Float32Array( [ 1.0, 4.0, 9.0, 0.0, 0.0 ] ); @@ -191,6 +194,7 @@ tape( 'the function supports a `y` stride', function test( t ) { var expected; var x; var y; + var N; x = new Float32Array([ 1.0, // 0 @@ -206,8 +210,9 @@ tape( 'the function supports a `y` stride', function test( t ) { 0.0, 0.0 // 2 ]); + N = 3; - scusum( 3, 0.0, x, 1, 0, y, 2, 0 ); + scusum( N, 0.0, x, 1, 0, y, 2, 0 ); expected = new Float32Array( [ 1.0, 0.0, 3.0, 0.0, 6.0 ] ); @@ -219,6 +224,7 @@ tape( 'the function supports negative strides', function test( t ) { var expected; var x; var y; + var N; x = new Float32Array([ 1.0, // 2 @@ -234,8 +240,9 @@ tape( 'the function supports negative strides', function test( t ) { 0.0, 0.0 ]); + N = 3; - scusum( 3, 0.0, x, -2, x.length-1, y, -1, 2 ); + scusum( N, 0.0, x, -2, x.length-1, y, -1, 2 ); expected = new Float32Array( [ 9.0, 8.0, 5.0, 0.0, 0.0 ] ); @@ -245,6 +252,7 @@ tape( 'the function supports negative strides', function test( t ) { tape( 'the function supports an `x` offset', function test( t ) { var expected; + var N; var x; var y; @@ -268,8 +276,9 @@ tape( 'the function supports an `x` offset', function test( t ) { 0.0, 0.0 ]); + N = floor( x.length / 2 ); - scusum( 4, 0.0, x, 2, 1, y, 1, 0 ); + scusum( N, 0.0, x, 2, 1, y, 1, 0 ); expected = new Float32Array( [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] ); @@ -279,6 +288,7 @@ tape( 'the function supports an `x` offset', function test( t ) { tape( 'the function supports a `y` offset', function test( t ) { var expected; + var N; var x; var y; @@ -302,8 +312,9 @@ tape( 'the function supports a `y` offset', function test( t ) { 0.0, 0.0 // 3 ]); + N = floor( x.length / 2 ); - scusum( 4, 0.0, x, 1, 0, y, 2, 1 ); + scusum( N, 0.0, x, 1, 0, y, 2, 1 ); expected = new Float32Array( [ 0.0, 2.0, 0.0, 3.0, 0.0, 5.0, 0.0, 3.0 ] ); @@ -315,6 +326,7 @@ tape( 'the function supports complex access patterns', function test( t ) { var expected; var x; var y; + var N; x = new Float32Array([ 1.0, // 0 @@ -332,8 +344,9 @@ tape( 'the function supports complex access patterns', function test( t ) { 0.0, 0.0 ]); + N = 3; - scusum( 3, 0.0, x, 2, 0, y, -1, 2 ); + scusum( N, 0.0, x, 2, 0, y, -1, 2 ); expected = new Float32Array( [ 9.0, 4.0, 1.0, 0.0, 0.0, 0.0 ] ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/test/test.ndarray.native.js index 3ae5cb53505c..ad957b847d10 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/test/test.ndarray.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -172,6 +173,7 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { var expected; var x; var y; + var N; x = new Float32Array([ 1.0, // 0 @@ -187,8 +189,9 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { 0.0, 0.0 ]); + N = 3; - scusum( 3, 0.0, x, 2, 0, y, 1, 0 ); + scusum( N, 0.0, x, 2, 0, y, 1, 0 ); expected = new Float32Array( [ 1.0, 4.0, 9.0, 0.0, 0.0 ] ); @@ -200,6 +203,7 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { var expected; var x; var y; + var N; x = new Float32Array([ 1.0, // 0 @@ -215,8 +219,9 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { 0.0, 0.0 // 2 ]); + N = 3; - scusum( 3, 0.0, x, 1, 0, y, 2, 0 ); + scusum( N, 0.0, x, 1, 0, y, 2, 0 ); expected = new Float32Array( [ 1.0, 0.0, 3.0, 0.0, 6.0 ] ); @@ -228,6 +233,7 @@ tape( 'the function supports negative strides', opts, function test( t ) { var expected; var x; var y; + var N; x = new Float32Array([ 1.0, // 2 @@ -243,8 +249,9 @@ tape( 'the function supports negative strides', opts, function test( t ) { 0.0, 0.0 ]); + N = 3; - scusum( 3, 0.0, x, -2, x.length-1, y, -1, 2 ); + scusum( N, 0.0, x, -2, x.length-1, y, -1, 2 ); expected = new Float32Array( [ 9.0, 8.0, 5.0, 0.0, 0.0 ] ); @@ -254,6 +261,7 @@ tape( 'the function supports negative strides', opts, function test( t ) { tape( 'the function supports an `x` offset', opts, function test( t ) { var expected; + var N; var x; var y; @@ -277,8 +285,9 @@ tape( 'the function supports an `x` offset', opts, function test( t ) { 0.0, 0.0 ]); + N = floor( x.length / 2 ); - scusum( 3, 0.0, x, 2, 1, y, 1, 0 ); + scusum( N, 0.0, x, 2, 1, y, 1, 0 ); expected = new Float32Array( [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] ); @@ -288,6 +297,7 @@ tape( 'the function supports an `x` offset', opts, function test( t ) { tape( 'the function supports a `y` offset', opts, function test( t ) { var expected; + var N; var x; var y; @@ -311,8 +321,9 @@ tape( 'the function supports a `y` offset', opts, function test( t ) { 0.0, 0.0 // 3 ]); + N = floor( x.length / 2 ); - scusum( 3, 0.0, x, 1, 0, y, 2, 1 ); + scusum( N, 0.0, x, 1, 0, y, 2, 1 ); expected = new Float32Array( [ 0.0, 2.0, 0.0, 3.0, 0.0, 5.0, 0.0, 3.0 ] ); @@ -324,6 +335,7 @@ tape( 'the function supports complex access patterns', opts, function test( t ) var expected; var x; var y; + var N; x = new Float32Array([ 1.0, // 0 @@ -341,8 +353,9 @@ tape( 'the function supports complex access patterns', opts, function test( t ) 0.0, 0.0 ]); + N = 3; - scusum( 3, 0.0, x, 2, 0, y, -1, 2 ); + scusum( N, 0.0, x, 2, 0, y, -1, 2 ); expected = new Float32Array( [ 9.0, 4.0, 1.0, 0.0, 0.0, 0.0 ] ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/test/test.scusum.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/test/test.scusum.js index 85badd1053d9..b1973a63519a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/test/test.scusum.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/test/test.scusum.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var Float32Array = require( '@stdlib/array/float32' ); var scusum = require( './../lib/scusum.js' ); @@ -35,7 +36,7 @@ tape( 'main export is a function', function test( t ) { }); tape( 'the function has an arity of 6', function test( t ) { - t.strictEqual( scusum.length, 6, 'returns expected value' ); + t.strictEqual( scusum.length, 6, 'has expected arity' ); t.end(); }); @@ -163,6 +164,7 @@ tape( 'the function supports an `x` stride', function test( t ) { var expected; var x; var y; + var N; x = new Float32Array([ 1.0, // 0 @@ -178,8 +180,9 @@ tape( 'the function supports an `x` stride', function test( t ) { 0.0, 0.0 ]); + N = 3; - scusum( 3, 0.0, x, 2, y, 1 ); + scusum( N, 0.0, x, 2, y, 1 ); expected = new Float32Array( [ 1.0, 4.0, 9.0, 0.0, 0.0 ] ); @@ -191,6 +194,7 @@ tape( 'the function supports a `y` stride', function test( t ) { var expected; var x; var y; + var N; x = new Float32Array([ 1.0, // 0 @@ -206,8 +210,9 @@ tape( 'the function supports a `y` stride', function test( t ) { 0.0, 0.0 // 2 ]); + N = 3; - scusum( 3, 0.0, x, 1, y, 2 ); + scusum( N, 0.0, x, 1, y, 2 ); expected = new Float32Array( [ 1.0, 0.0, 3.0, 0.0, 6.0 ] ); @@ -219,6 +224,7 @@ tape( 'the function supports negative strides', function test( t ) { var expected; var x; var y; + var N; x = new Float32Array([ 1.0, // 2 @@ -234,8 +240,9 @@ tape( 'the function supports negative strides', function test( t ) { 0.0, 0.0 ]); + N = 3; - scusum( 3, 0.0, x, -2, y, -1 ); + scusum( N, 0.0, x, -2, y, -1 ); expected = new Float32Array( [ 9.0, 8.0, 5.0, 0.0, 0.0 ] ); @@ -247,6 +254,7 @@ tape( 'the function supports complex access patterns', function test( t ) { var expected; var x; var y; + var N; x = new Float32Array([ 1.0, // 0 @@ -264,8 +272,9 @@ tape( 'the function supports complex access patterns', function test( t ) { 0.0, 0.0 ]); + N = 3; - scusum( 3, 0.0, x, 2, y, -1 ); + scusum( N, 0.0, x, 2, y, -1 ); expected = new Float32Array( [ 9.0, 4.0, 1.0, 0.0, 0.0, 0.0 ] ); @@ -279,6 +288,7 @@ tape( 'the function supports view offsets', function test( t ) { var y0; var x1; var y1; + var N; // Initial arrays... x0 = new Float32Array([ @@ -302,7 +312,9 @@ tape( 'the function supports view offsets', function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element - scusum( 3, 0.0, x1, -2, y1, 1 ); + N = floor( x0.length / 2 ); + + scusum( N, 0.0, x1, -2, y1, 1 ); expected = new Float32Array( [ 0.0, 0.0, 0.0, 6.0, 10.0, 12.0 ] ); t.deepEqual( y0, expected, 'deep equal' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/test/test.scusum.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/test/test.scusum.native.js index ac0a872c7e72..e5b184951519 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/test/test.scusum.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/test/test.scusum.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -44,7 +45,7 @@ tape( 'main export is a function', opts, function test( t ) { }); tape( 'the function has an arity of 6', opts, function test( t ) { - t.strictEqual( scusum.length, 6, 'returns expected value' ); + t.strictEqual( scusum.length, 6, 'has expected arity' ); t.end(); }); @@ -172,6 +173,7 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { var expected; var x; var y; + var N; x = new Float32Array([ 1.0, // 0 @@ -187,8 +189,9 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { 0.0, 0.0 ]); + N = 3; - scusum( 3, 0.0, x, 2, y, 1 ); + scusum( N, 0.0, x, 2, y, 1 ); expected = new Float32Array( [ 1.0, 4.0, 9.0, 0.0, 0.0 ] ); @@ -200,6 +203,7 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { var expected; var x; var y; + var N; x = new Float32Array([ 1.0, // 0 @@ -215,8 +219,9 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { 0.0, 0.0 // 2 ]); + N = 3; - scusum( 3, 0.0, x, 1, y, 2 ); + scusum( N, 0.0, x, 1, y, 2 ); expected = new Float32Array( [ 1.0, 0.0, 3.0, 0.0, 6.0 ] ); @@ -228,6 +233,7 @@ tape( 'the function supports negative strides', opts, function test( t ) { var expected; var x; var y; + var N; x = new Float32Array([ 1.0, // 2 @@ -243,8 +249,9 @@ tape( 'the function supports negative strides', opts, function test( t ) { 0.0, 0.0 ]); + N = 3; - scusum( 3, 0.0, x, -2, y, -1 ); + scusum( N, 0.0, x, -2, y, -1 ); expected = new Float32Array( [ 9.0, 8.0, 5.0, 0.0, 0.0 ] ); @@ -256,6 +263,7 @@ tape( 'the function supports complex access patterns', opts, function test( t ) var expected; var x; var y; + var N; x = new Float32Array([ 1.0, // 0 @@ -273,8 +281,9 @@ tape( 'the function supports complex access patterns', opts, function test( t ) 0.0, 0.0 ]); + N = 3; - scusum( 3, 0.0, x, 2, y, -1 ); + scusum( N, 0.0, x, 2, y, -1 ); expected = new Float32Array( [ 9.0, 4.0, 1.0, 0.0, 0.0, 0.0 ] ); @@ -288,6 +297,7 @@ tape( 'the function supports view offsets', opts, function test( t ) { var y0; var x1; var y1; + var N; // Initial arrays... x0 = new Float32Array([ @@ -311,7 +321,9 @@ tape( 'the function supports view offsets', opts, function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element - scusum( 3, 0.0, x1, -2, y1, 1 ); + N = floor( x0.length / 2 ); + + scusum( N, 0.0, x1, -2, y1, 1 ); expected = new Float32Array( [ 0.0, 0.0, 0.0, 6.0, 10.0, 12.0 ] ); t.deepEqual( y0, expected, 'deep equal' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/README.md b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/README.md index 9959aa54cf6a..52fb29f21720 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/README.md @@ -65,14 +65,18 @@ The function has the following parameters: - **y**: output [`Float32Array`][@stdlib/array/float32]. - **strideY**: index increment for `y`. -The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative sum of every other element in `x`, +The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to compute the cumulative sum of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); + var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); var y = new Float32Array( x.length ); -var v = scusumkbn( 4, 0.0, x, 2, y, 1 ); +var N = floor( x.length / 2 ); + +var v = scusumkbn( N, 0.0, x, 2, y, 1 ); // y => [ 1.0, 3.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] ``` @@ -82,6 +86,7 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); // Initial arrays... var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); @@ -91,7 +96,9 @@ var y0 = new Float32Array( x0.length ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element -scusumkbn( 4, 0.0, x1, -2, y1, 1 ); +var N = floor( x0.length / 2 ); + +scusumkbn( N, 0.0, x1, -2, y1, 1 ); // y0 => [ 0.0, 0.0, 0.0, 4.0, 6.0, 4.0, 5.0, 0.0 ] ``` @@ -103,9 +110,9 @@ Computes the cumulative sum of single-precision floating-point strided array ele var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var y = new Float32Array( 3 ); +var y = new Float32Array( x.length ); -scusumkbn.ndarray( 3, 0.0, x, 1, 0, y, 1, 0 ); +scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 ); // y => [ 1.0, -1.0, 1.0 ] ``` @@ -114,15 +121,18 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: starting index for `y`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, offset parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative sum of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, `offsetX` and `offsetY` parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative sum of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var y = new Float32Array( x.length ); -scusumkbn.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 ); +var N = floor( x.length / 2 ); + +scusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ); // y => [ 0.0, 0.0, 0.0, 0.0, 5.0, 1.0, -1.0, 1.0 ] ``` @@ -147,14 +157,21 @@ scusumkbn.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float32Array = require( '@stdlib/array/float32' ); var scusumkbn = require( '@stdlib/blas/ext/base/scusumkbn' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); -console.log( x ); +var y; +var x; +var i; -var y = filledarrayBy( x.length, 'float32', discreteUniform( 0, 10 ) ); +x = new Float32Array( 10 ); +y = new Float32Array( x.length ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} +console.log( x ); console.log( y ); scusumkbn( x.length, 0.0, x, 1, y, -1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.js index d3306232854f..ca32b4ad981b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var scusumkbn = require( './../lib/scusumkbn.js' ); -// VARIABLES // - -var rand = uniform( -100.0, 100.0 ); - - // FUNCTIONS // /** @@ -44,8 +39,15 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = filledarrayBy( len, 'float32', rand ); + var y; + var x; + var i; + + x = new Float32Array( len ); + y = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.native.js index 5ec896713745..a3bb22085569 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var scusumkbn = tryRequire( resolve( __dirname, './../lib/scusumkbn.native.js' ) var opts = { 'skip': ( scusumkbn instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); // FUNCTIONS // @@ -49,8 +48,15 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = filledarrayBy( len, 'float32', rand ); + var x; + var y; + var i; + + x = new Float32Array( len ); + y = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.js index b515bb63eec5..9e68c42d396a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var scusumkbn = require( './../lib/ndarray.js' ); -// VARIABLES // - -var rand = uniform( -100.0, 100.0 ); - - // FUNCTIONS // /** @@ -44,8 +39,15 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = filledarrayBy( len, 'float32', rand ); + var x; + var y; + var i; + + x = new Float32Array( len ); + y = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.native.js index a9ac4955e25a..793fe23e7e48 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var scusumkbn = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ) var opts = { 'skip': ( scusumkbn instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); // FUNCTIONS // @@ -49,8 +48,15 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = filledarrayBy( len, 'float32', rand ); + var x; + var y; + var i; + + x = new Float32Array( len ); + y = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/docs/repl.txt index a64a884cd6b1..470a0986b764 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/docs/repl.txt @@ -3,8 +3,8 @@ Computes the cumulative sum of single-precision floating-point strided array elements using an improved Kahan–Babuška algorithm. - The `N` and stride parameters determine which elements in the strided arrays - are accessed at runtime. + The `N` and `stride` parameters determine which elements in `x` and `y` are + accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -44,10 +44,11 @@ > {{alias}}( x.length, 0.0, x, 1, y, 1 ) [ 1.0, -1.0, 1.0 ] - // Using `N` and stride parameters: + // Using `N` and `stride` parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); > y = new {{alias:@stdlib/array/float32}}( x.length ); - > {{alias}}( 3, 0.0, x, 2, y, 2 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > {{alias}}( N, 0.0, x, 2, y, 2 ) [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ] // Using view offsets: @@ -61,15 +62,14 @@ > y0 [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ] - {{alias}}.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY ) Computes the cumulative sum of single-precision floating-point strided array elements using an improved Kahan–Babuška algorithm and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the offset parameters support indexing semantics based on - starting indices. + buffer, the `offset` parameter supports indexing semantics based on a + starting index. Parameters ---------- @@ -113,7 +113,8 @@ // Advanced indexing: > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > y = new {{alias:@stdlib/array/float32}}( x.length ); - > {{alias}}.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > {{alias}}.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ) [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ] See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/examples/index.js index c3c81e53b3b9..d7a9f78e0502 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/examples/index.js @@ -18,14 +18,21 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float32Array = require( '@stdlib/array/float32' ); var scusumkbn = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); -console.log( x ); +var y; +var x; +var i; -var y = filledarrayBy( x.length, 'float32', discreteUniform( 0, 10 ) ); +x = new Float32Array( 10 ); +y = new Float32Array( x.length ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} +console.log( x ); console.log( y ); scusumkbn( x.length, 0.0, x, 1, y, -1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/include.gypi index 26476a8c2655..868c5c12e852 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/include.gypi +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.c', + '<(src_dir)/addon.cpp', ' - -/** -* Receives JavaScript callback invocation data. -* -* @private -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_FLOAT( env, sum, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); - STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 4 ); - stdlib_strided_scusumkbn( N, sum, X, strideX, Y, strideY ); - return NULL; -} - -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/src/addon.cpp b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/src/addon.cpp new file mode 100644 index 000000000000..22e1547fbbcf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/src/addon.cpp @@ -0,0 +1,164 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/scusumkbn.h" +#include +#include +#include +#include +#include + +/** +* Add-on namespace. +*/ +namespace stdlib_blas_ext_base_scusumkbn { + + /** + * Computes the cumulative sum of single-precision floating-point strided array elements using an improved Kahan–Babuška algorithm. + * + * ## Notes + * + * - When called from JavaScript, the function expects six arguments: + * + * - `N`: number of indexed elements + * - `sum`: initial sum + * - `X`: input array + * - `strideX`: `X` stride length + * - `Y`: output array + * - `strideY`: `Y` stride length + */ + napi_value node_scusumkbn( napi_env env, napi_callback_info info ) { + napi_status status; + + size_t argc = 6; + napi_value argv[ 6 ]; + status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); + assert( status == napi_ok ); + + if ( argc < 6 ) { + napi_throw_error( env, nullptr, "invalid invocation. Must provide 6 arguments." ); + return nullptr; + } + + napi_valuetype vtype0; + status = napi_typeof( env, argv[ 0 ], &vtype0 ); + assert( status == napi_ok ); + if ( vtype0 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); + return nullptr; + } + + napi_valuetype vtype1; + status = napi_typeof( env, argv[ 1 ], &vtype1 ); + assert( status == napi_ok ); + if ( vtype1 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); + return nullptr; + } + + bool res2; + status = napi_is_typedarray( env, argv[ 2 ], &res2 ); + assert( status == napi_ok ); + if ( res2 == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + + napi_valuetype vtype3; + status = napi_typeof( env, argv[ 3 ], &vtype3 ); + assert( status == napi_ok ); + if ( vtype3 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); + return nullptr; + } + + bool res4; + status = napi_is_typedarray( env, argv[ 4 ], &res4 ); + assert( status == napi_ok ); + if ( res4 == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a Float32Array." ); + return nullptr; + } + + napi_valuetype vtype5; + status = napi_typeof( env, argv[ 5 ], &vtype5 ); + assert( status == napi_ok ); + if ( vtype5 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Sixth argument must be a number." ); + return nullptr; + } + + int64_t N; + status = napi_get_value_int64( env, argv[ 0 ], &N ); + assert( status == napi_ok ); + + double sum; + status = napi_get_value_double( env, argv[ 1 ], &sum ); + assert( status == napi_ok ); + + int64_t strideX; + status = napi_get_value_int64( env, argv[ 3 ], &strideX ); + assert( status == napi_ok ); + + int64_t strideY; + status = napi_get_value_int64( env, argv[ 5 ], &strideY ); + assert( status == napi_ok ); + + napi_typedarray_type vtype2; + size_t xlen; + void *X; + status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype2 != napi_float32_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + napi_typedarray_type vtype4; + size_t ylen; + void *Y; + status = napi_get_typedarray_info( env, argv[ 4 ], &vtype4, &ylen, &Y, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype4 != napi_float32_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a Float32Array." ); + return nullptr; + } + if ( (N-1)*llabs(strideY) >= (int64_t)ylen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Fifth argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + stdlib_strided_scusumkbn( N, (float)sum, (float *)X, strideX, (float *)Y, strideY ); + + return nullptr; + } + + napi_value Init( napi_env env, napi_value exports ) { + napi_status status; + napi_value fcn; + status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_scusumkbn, NULL, &fcn ); + assert( status == napi_ok ); + return fcn; + } + + NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) +} // end namespace stdlib_blas_ext_base_scusumkbn diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/test/test.ndarray.js index 4601130a1bc1..62706d6e2918 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/test/test.ndarray.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var Float32Array = require( '@stdlib/array/float32' ); var scusumkbn = require( './../lib/ndarray.js' ); @@ -140,7 +141,7 @@ tape( 'the function returns a reference to the output array', function test( t ) t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { var expected; var x; var y; @@ -151,10 +152,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); scusumkbn( -1, 0.0, x, 1, 0, y, 1, 0 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); scusumkbn( 0, 0.0, x, 1, 0, y, 1, 0 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); t.end(); }); @@ -275,7 +276,7 @@ tape( 'the function supports an `x` offset', function test( t ) { 0.0, 0.0 ]); - N = 4; + N = floor( x.length / 2 ); scusumkbn( N, 0.0, x, 2, 1, y, 1, 0 ); @@ -311,7 +312,7 @@ tape( 'the function supports a `y` offset', function test( t ) { 0.0, 0.0 // 3 ]); - N = 4; + N = floor( x.length / 2 ); scusumkbn( N, 0.0, x, 1, 0, y, 2, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/test/test.ndarray.native.js index 19a253895cd2..5c83a10832dd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/test/test.ndarray.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -149,7 +150,7 @@ tape( 'the function returns a reference to the output array', opts, function tes t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', opts, function test( t ) { var expected; var x; var y; @@ -160,10 +161,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); scusumkbn( -1, 0.0, x, 1, 0, y, 1, 0 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); scusumkbn( 0, 0.0, x, 1, 0, y, 1, 0 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); t.end(); }); @@ -284,7 +285,7 @@ tape( 'the function supports an `x` offset', opts, function test( t ) { 0.0, 0.0 ]); - N = 4; + N = floor( x.length / 2 ); scusumkbn( N, 0.0, x, 2, 1, y, 1, 0 ); @@ -320,7 +321,7 @@ tape( 'the function supports a `y` offset', opts, function test( t ) { 0.0, 0.0 // 3 ]); - N = 4; + N = floor( x.length / 2 ); scusumkbn( N, 0.0, x, 1, 0, y, 2, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/test/test.scusumkbn.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/test/test.scusumkbn.js index facea33903bb..f83c515697d7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/test/test.scusumkbn.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/test/test.scusumkbn.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var Float32Array = require( '@stdlib/array/float32' ); var scusumkbn = require( './../lib/scusumkbn.js' ); @@ -140,7 +141,7 @@ tape( 'the function returns a reference to the output array', function test( t ) t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { var expected; var x; var y; @@ -151,10 +152,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); scusumkbn( -1, 0.0, x, 1, y, 1 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); scusumkbn( 0, 0.0, x, 1, y, 1 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); t.end(); }); @@ -311,7 +312,7 @@ tape( 'the function supports view offsets', function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element - N = 3; + N = floor( x0.length / 2 ); scusumkbn( N, 0.0, x1, -2, y1, 1 ); expected = new Float32Array( [ 0.0, 0.0, 0.0, 6.0, 10.0, 12.0 ] ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/test/test.scusumkbn.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/test/test.scusumkbn.native.js index 7b9c97bec979..9f5e939cca86 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/test/test.scusumkbn.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/test/test.scusumkbn.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -149,7 +150,7 @@ tape( 'the function returns a reference to the output array', opts, function tes t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', opts, function test( t ) { var expected; var x; var y; @@ -160,10 +161,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); scusumkbn( -1, 0.0, x, 1, y, 1 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); scusumkbn( 0, 0.0, x, 1, y, 1 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); t.end(); }); @@ -320,7 +321,7 @@ tape( 'the function supports view offsets', opts, function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element - N = 3; + N = floor( x0.length / 2 ); scusumkbn( N, 0.0, x1, -2, y1, 1 ); expected = new Float32Array( [ 0.0, 0.0, 0.0, 6.0, 10.0, 12.0 ] ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/README.md b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/README.md index 76711bfe20aa..157068603988 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/README.md @@ -65,15 +65,18 @@ The function has the following parameters: - **y**: output [`Float32Array`][@stdlib/array/float32]. - **strideY**: index increment for `y`. -The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative sum of every other element in `x`, +The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to compute the cumulative sum of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); var y = new Float32Array( x.length ); -var v = scusumkbn2( 4, 0.0, x, 2, y, 1 ); +var N = floor( x.length / 2 ); + +var v = scusumkbn2( N, 0.0, x, 2, y, 1 ); // y => [ 1.0, 3.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] ``` @@ -83,6 +86,7 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); // Initial arrays... var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); @@ -92,7 +96,9 @@ var y0 = new Float32Array( x0.length ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element -scusumkbn2( 4, 0.0, x1, -2, y1, 1 ); +var N = floor( x0.length / 2 ); + +scusumkbn2( N, 0.0, x1, -2, y1, 1 ); // y0 => [ 0.0, 0.0, 0.0, 4.0, 6.0, 4.0, 5.0, 0.0 ] ``` @@ -104,9 +110,9 @@ Computes the cumulative sum of single-precision floating-point strided array ele var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var y = new Float32Array( 3 ); +var y = new Float32Array( x.length ); -scusumkbn2.ndarray( 3, 0.0, x, 1, 0, y, 1, 0 ); +scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 ); // y => [ 1.0, -1.0, 1.0 ] ``` @@ -115,15 +121,18 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: starting index for `y`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, offset parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative sum of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, `offsetX` and `offsetY` parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative sum of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var y = new Float32Array( x.length ); -scusumkbn2.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 ); +var N = floor( x.length / 2 ); + +scusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ); // y => [ 0.0, 0.0, 0.0, 0.0, 5.0, 1.0, -1.0, 1.0 ] ``` @@ -148,16 +157,21 @@ scusumkbn2.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float32Array = require( '@stdlib/array/float32' ); var scusumkbn2 = require( '@stdlib/blas/ext/base/scusumkbn2' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var y; +var x; +var i; +x = new Float32Array( 10 ); +y = new Float32Array( x.length ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); - -var y = filledarrayBy( x.length, 'float32', discreteUniform( 0, 10 ) ); - console.log( y ); scusumkbn2( x.length, 0.0, x, 1, y, -1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.js index 4a8201013ca1..0af540bf80dc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var scusumkbn2 = require( './../lib/scusumkbn2.js' ); -// VARIABLES // - -var rand = uniform( -100.0, 100.0 ); - - // FUNCTIONS // /** @@ -44,8 +39,15 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = filledarrayBy( len, 'float32', rand ); + var y; + var x; + var i; + + x = new Float32Array( len ); + y = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.native.js index b19255d0b9af..e8aab4db618a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var scusumkbn2 = tryRequire( resolve( __dirname, './../lib/scusumkbn2.native.js' var opts = { 'skip': ( scusumkbn2 instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); // FUNCTIONS // @@ -49,8 +48,15 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = filledarrayBy( len, 'float32', rand ); + var x; + var y; + var i; + + x = new Float32Array( len ); + y = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.js index 99eaa0a272b4..5d7eaf750b0a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var scusumkbn2 = require( './../lib/ndarray.js' ); -// VARIABLES // - -var rand = uniform( -100.0, 100.0 ); - - // FUNCTIONS // /** @@ -44,8 +39,15 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = filledarrayBy( len, 'float32', rand ); + var x; + var y; + var i; + + x = new Float32Array( len ); + y = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.native.js index 138307c744d3..e9d2dbdff513 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var scusumkbn2 = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) var opts = { 'skip': ( scusumkbn2 instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); // FUNCTIONS // @@ -49,8 +48,15 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = filledarrayBy( len, 'float32', rand ); + var x; + var y; + var i; + + x = new Float32Array( len ); + y = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/docs/repl.txt index 1994b0296f7d..18cb152928c2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/docs/repl.txt @@ -1,13 +1,13 @@ {{alias}}( N, sum, x, strideX, y, strideY ) - Computes the cumulative sum of single-precision floating-point strided - array elements using a second-order iterative Kahan–Babuška algorithm. + Computes the cumulative sum of single-precision floating-point strided array + elements using a second-order iterative Kahan–Babuška algorithm. - The `N` and stride parameters determine which elements in the strided - arrays are accessed at runtime. + The `N` and `stride` parameters determine which elements in `x` and `y` are + accessed at runtime. - Indexing is relative to the first index. To introduce an offset, use - a typed array view. + Indexing is relative to the first index. To introduce an offset, use a typed + array view. If `N <= 0`, the function returns `y` unchanged. @@ -44,10 +44,11 @@ > {{alias}}( x.length, 0.0, x, 1, y, 1 ) [ 1.0, -1.0, 1.0 ] - // Using `N` and stride parameters: + // Using `N` and `stride` parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); > y = new {{alias:@stdlib/array/float32}}( x.length ); - > {{alias}}( 3, 0.0, x, 2, y, 2 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > {{alias}}( N, 0.0, x, 2, y, 2 ) [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ] // Using view offsets: @@ -61,16 +62,14 @@ > y0 [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ] - {{alias}}.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY ) - Computes the cumulative sum of single-precision floating-point strided - array elements using a second-order iterative Kahan–Babuška algorithm and + Computes the cumulative sum of single-precision floating-point strided array + elements using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offsetX` and `offsetY` parameter supports indexing semantics - based on starting indices. - + buffer, the `offset` parameter supports indexing semantics based on a + starting index. Parameters ---------- @@ -98,13 +97,11 @@ offsetY: integer Starting index for `y`. - Returns ------- out: Float32Array Output array. - Examples -------- // Standard Usage: @@ -116,10 +113,10 @@ // Advanced indexing: > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > y = new {{alias:@stdlib/array/float32}}( x.length ); - > {{alias}}.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > {{alias}}.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ) [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ] - See Also -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/examples/index.js index 4f33d6985df7..20c325bb0ba9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/examples/index.js @@ -18,14 +18,21 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float32Array = require( '@stdlib/array/float32' ); var scusumkbn2 = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); -console.log( x ); +var y; +var x; +var i; -var y = filledarrayBy( x.length, 'float32', discreteUniform( 0, 10 ) ); +x = new Float32Array( 10 ); +y = new Float32Array( x.length ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} +console.log( x ); console.log( y ); scusumkbn2( x.length, 0.0, x, 1, y, -1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/include.gypi index 26476a8c2655..868c5c12e852 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/include.gypi +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.c', + '<(src_dir)/addon.cpp', ' - -/** -* Receives JavaScript callback invocation data. -* -* @private -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_FLOAT( env, sum, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); - STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 4 ); - stdlib_strided_scusumkbn2( N, sum, X, strideX, Y, strideY ); - return NULL; -} - -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) \ No newline at end of file diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/src/addon.cpp b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/src/addon.cpp new file mode 100644 index 000000000000..80986dfd402a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/src/addon.cpp @@ -0,0 +1,164 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/scusumkbn2.h" +#include +#include +#include +#include +#include + +/** +* Add-on namespace. +*/ +namespace stdlib_blas_ext_base_scusumkbn2 { + + /** + * Computes the cumulative sum of single-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm. + * + * ## Notes + * + * - When called from JavaScript, the function expects six arguments: + * + * - `N`: number of indexed elements + * - `sum`: initial sum + * - `X`: input array + * - `strideX`: `X` stride length + * - `Y`: output array + * - `strideY`: `Y` stride length + */ + napi_value node_scusumkbn2( napi_env env, napi_callback_info info ) { + napi_status status; + + size_t argc = 6; + napi_value argv[ 6 ]; + status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); + assert( status == napi_ok ); + + if ( argc < 6 ) { + napi_throw_error( env, nullptr, "invalid invocation. Must provide 6 arguments." ); + return nullptr; + } + + napi_valuetype vtype0; + status = napi_typeof( env, argv[ 0 ], &vtype0 ); + assert( status == napi_ok ); + if ( vtype0 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); + return nullptr; + } + + napi_valuetype vtype1; + status = napi_typeof( env, argv[ 1 ], &vtype1 ); + assert( status == napi_ok ); + if ( vtype1 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); + return nullptr; + } + + bool res2; + status = napi_is_typedarray( env, argv[ 2 ], &res2 ); + assert( status == napi_ok ); + if ( res2 == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + + napi_valuetype vtype3; + status = napi_typeof( env, argv[ 3 ], &vtype3 ); + assert( status == napi_ok ); + if ( vtype3 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); + return nullptr; + } + + bool res4; + status = napi_is_typedarray( env, argv[ 4 ], &res4 ); + assert( status == napi_ok ); + if ( res4 == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a Float32Array." ); + return nullptr; + } + + napi_valuetype vtype5; + status = napi_typeof( env, argv[ 5 ], &vtype5 ); + assert( status == napi_ok ); + if ( vtype5 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Sixth argument must be a number." ); + return nullptr; + } + + int64_t N; + status = napi_get_value_int64( env, argv[ 0 ], &N ); + assert( status == napi_ok ); + + double sum; + status = napi_get_value_double( env, argv[ 1 ], &sum ); + assert( status == napi_ok ); + + int64_t strideX; + status = napi_get_value_int64( env, argv[ 3 ], &strideX ); + assert( status == napi_ok ); + + int64_t strideY; + status = napi_get_value_int64( env, argv[ 5 ], &strideY ); + assert( status == napi_ok ); + + napi_typedarray_type vtype2; + size_t xlen; + void *X; + status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype2 != napi_float32_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + napi_typedarray_type vtype4; + size_t ylen; + void *Y; + status = napi_get_typedarray_info( env, argv[ 4 ], &vtype4, &ylen, &Y, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype4 != napi_float32_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a Float32Array." ); + return nullptr; + } + if ( (N-1)*llabs(strideY) >= (int64_t)ylen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Fifth argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + stdlib_strided_scusumkbn2( N, (float)sum, (float *)X, strideX, (float *)Y, strideY ); + + return nullptr; + } + + napi_value Init( napi_env env, napi_value exports ) { + napi_status status; + napi_value fcn; + status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_scusumkbn2, NULL, &fcn ); + assert( status == napi_ok ); + return fcn; + } + + NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) +} // end namespace stdlib_blas_ext_base_scusumkbn2 diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/test/test.ndarray.js index ac063f99514e..d20010cc70aa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/test/test.ndarray.js @@ -141,7 +141,7 @@ tape( 'the function returns a reference to the output array', function test( t ) t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { var expected; var x; var y; @@ -152,10 +152,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); scusumkbn2( -1, 0.0, x, 1, 0, y, 1, 0 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); scusumkbn2( 0, 0.0, x, 1, 0, y, 1, 0 ); - t.deepEqual( y, expected, 'returns `expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/test/test.ndarray.native.js index 276b557a13f7..2429e597281e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/test/test.ndarray.native.js @@ -150,7 +150,7 @@ tape( 'the function returns a reference to the output array', opts, function tes t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', opts, function test( t ) { var expected; var x; var y; @@ -161,10 +161,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); scusumkbn2( -1, 0.0, x, 1, 0, y, 1, 0 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); scusumkbn2( 0, 0.0, x, 1, 0, y, 1, 0 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/test/test.scusumkbn2.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/test/test.scusumkbn2.js index 713316d3568e..56a1e6437516 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/test/test.scusumkbn2.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/test/test.scusumkbn2.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var Float32Array = require( '@stdlib/array/float32' ); var scusumkbn2 = require( './../lib/scusumkbn2.js' ); @@ -140,7 +141,7 @@ tape( 'the function returns a reference to the output array', function test( t ) t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { var expected; var x; var y; @@ -151,10 +152,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); scusumkbn2( -1, 0.0, x, 1, y, 1 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); scusumkbn2( 0, 0.0, x, 1, y, 1 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); t.end(); }); @@ -327,7 +328,7 @@ tape( 'the function supports view offsets', function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element - N = 3; + N = floor( x0.length / 2 ); scusumkbn2( N, 0.0, x1, -2, y1, 1 ); expected = new Float32Array( [ 0.0, 0.0, 0.0, 6.0, 10.0, 12.0 ] ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/test/test.scusumkbn2.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/test/test.scusumkbn2.native.js index 705537999ddc..bca6a9b6cc4f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/test/test.scusumkbn2.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/test/test.scusumkbn2.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -149,7 +150,7 @@ tape( 'the function returns a reference to the output array', opts, function tes t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', opts, function test( t ) { var expected; var x; var y; @@ -160,10 +161,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); scusumkbn2( -1, 0.0, x, 1, y, 1 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); scusumkbn2( 0, 0.0, x, 1, y, 1 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); t.end(); }); @@ -336,7 +337,7 @@ tape( 'the function supports view offsets', opts, function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element - N = 3; + N = floor( x0.length / 2 ); scusumkbn2( N, 0.0, x1, -2, y1, 1 ); expected = new Float32Array( [ 0.0, 0.0, 0.0, 6.0, 10.0, 12.0 ] ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/README.md b/lib/node_modules/@stdlib/blas/ext/base/scusumors/README.md index bc247cf7aae6..6cd5c5951743 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/README.md @@ -65,15 +65,18 @@ The function has the following parameters: - **y**: output [`Float32Array`][@stdlib/array/float32]. - **strideY**: index increment for `y`. -The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative sum of every other element in `x`, +The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to compute the cumulative sum of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); var y = new Float32Array( x.length ); -var v = scusumors( 4, 0.0, x, 2, y, 1 ); +var N = floor( x.length / 2 ); + +var v = scusumors( N, 0.0, x, 2, y, 1 ); // y => [ 1.0, 3.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] ``` @@ -83,6 +86,7 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); // Initial arrays... var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); @@ -92,7 +96,9 @@ var y0 = new Float32Array( x0.length ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element -scusumors( 4, 0.0, x1, -2, y1, 1 ); +var N = floor( x0.length / 2 ); + +scusumors( N, 0.0, x1, -2, y1, 1 ); // y0 => [ 0.0, 0.0, 0.0, 4.0, 6.0, 4.0, 5.0, 0.0 ] ``` @@ -115,15 +121,18 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: starting index for `y`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, offset parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative sum of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, `offsetX` and `offsetY` parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative sum of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var y = new Float32Array( x.length ); -scusumors.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 ); +var N = floor( x.length / 2 ); + +scusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ); // y => [ 0.0, 0.0, 0.0, 0.0, 5.0, 1.0, -1.0, 1.0 ] ``` @@ -135,7 +144,7 @@ scusumors.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 ); ## Notes -- If `N <= 0`, both functions return the output array unchanged. +- If `N <= 0`, both functions return `y` unchanged. - Ordinary recursive summation (i.e., a "simple" sum) is performant, but can incur significant numerical error. If performance is paramount and error tolerated, using ordinary recursive summation is acceptable; in all other cases, exercise due caution. @@ -149,14 +158,20 @@ scusumors.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); var Float32Array = require( '@stdlib/array/float32' ); var scusumors = require( '@stdlib/blas/ext/base/scusumors' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); -var y = new Float32Array( x.length ); +var y; +var x; +var i; +x = new Float32Array( 10 ); +y = new Float32Array( x.length ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); console.log( y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.js index 2f42a28b2db3..0cd850d46e76 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -42,10 +41,13 @@ var scusumors = require( './../lib/scusumors.js' ); function createBenchmark( len ) { var y; var x; + var i; - x = filledarrayBy( len, 'float32', uniform( -10.0, 10.0 ) ); + x = new Float32Array( len ); y = new Float32Array( len ); - + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.native.js index 4256c5fc0c77..1b3f1a4e25b3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -51,10 +50,13 @@ var opts = { function createBenchmark( len ) { var x; var y; + var i; - x = filledarrayBy( len, 'float32', uniform( -10.0, 10.0 ) ); + x = new Float32Array( len ); y = new Float32Array( len ); - + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.js index 2c987c262a8a..e4c8659972a1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -42,10 +41,13 @@ var scusumors = require( './../lib/ndarray.js' ); function createBenchmark( len ) { var x; var y; + var i; - x = filledarrayBy( len, 'float32', uniform( -10.0, 10.0 ) ); + x = new Float32Array( len ); y = new Float32Array( len ); - + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.native.js index 37cc520539ab..c90db53814c7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -51,10 +50,13 @@ var opts = { function createBenchmark( len ) { var x; var y; + var i; - x = filledarrayBy( len, 'float32', uniform( -10.0, 10.0 ) ); + x = new Float32Array( len ); y = new Float32Array( len ); - + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/scusumors/docs/repl.txt index c16d450b275c..86553568a61b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/docs/repl.txt @@ -3,8 +3,8 @@ Computes the cumulative sum of single-precision floating-point strided array elements using ordinary recursive summation. - The `N` and stride parameters determine which elements in the strided arrays - are accessed at runtime. + The `N` and `stride` parameters determine which elements in `x` and `y` are + accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -44,10 +44,11 @@ > {{alias}}( x.length, 0.0, x, 1, y, 1 ) [ 1.0, -1.0, 1.0 ] - // Using `N` and stride parameters: + // Using `N` and `stride` parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); > y = new {{alias:@stdlib/array/float32}}( x.length ); - > {{alias}}( 3, 0.0, x, 2, y, 2 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > {{alias}}( N, 0.0, x, 2, y, 2 ) [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ] // Using view offsets: @@ -55,12 +56,12 @@ > var y0 = new {{alias:@stdlib/array/float32}}( x0.length ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); > var y1 = new {{alias:@stdlib/array/float32}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); - > {{alias}}( 3, 0.0, x1, 2, y1, 1 ) + > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); + > {{alias}}( N, 0.0, x1, 2, y1, 1 ) [ -2.0, 0.0, -1.0 ] > y0 [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ] - {{alias}}.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY ) Computes the cumulative sum of single-precision floating-point strided array elements using ordinary recursive summation and alternative indexing @@ -112,7 +113,8 @@ // Advanced indexing: > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > y = new {{alias:@stdlib/array/float32}}( x.length ); - > {{alias}}.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > {{alias}}.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ) [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ] See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/examples/index.js index 7bb9a381a349..cc8eb5a7773c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/examples/index.js @@ -18,14 +18,20 @@ 'use strict'; +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); var Float32Array = require( '@stdlib/array/float32' ); -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); var scusumors = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); -var y = new Float32Array( x.length ); +var y; +var x; +var i; +x = new Float32Array( 10 ); +y = new Float32Array( x.length ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); console.log( y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/scusumors/include.gypi index 26476a8c2655..868c5c12e852 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/include.gypi +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.c', + '<(src_dir)/addon.cpp', ' [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/ndarray.js index 210f8a30aa55..f05bb342b5ba 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/ndarray.js @@ -40,11 +40,13 @@ var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); * * @example * var Float32Array = require( '@stdlib/array/float32' ); +* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); +* var N = floor( x.length / 2 ); * -* var v = scusumors( 4, 0.0, x, 2, 1, y, 1, 0 ); +* var v = scusumors( N, 0.0, x, 2, 1, y, 1, 0 ); * // returns [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ function scusumors( N, sum, x, strideX, offsetX, y, strideY, offsetY ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/ndarray.native.js index 1e5087b5aa64..7edd250e3ee3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var minViewBufferIndex = require( '@stdlib/strided/base/min-view-buffer-index' ); -var offsetView = require( '@stdlib/strided/base/offset-view' ); +var Float32Array = require( '@stdlib/array/float32' ); var addon = require( './scusumors.native.js' ); @@ -42,23 +41,26 @@ var addon = require( './scusumors.native.js' ); * * @example * var Float32Array = require( '@stdlib/array/float32' ); +* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); +* var N = floor( x.length / 2 ); * -* var v = scusumors( 4, 0.0, x, 2, 1, y, 1, 0 ); +* var v = scusumors( N, 0.0, x, 2, 1, y, 1, 0 ); * // returns [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ function scusumors( N, sum, x, strideX, offsetX, y, strideY, offsetY ) { var viewX; var viewY; - - offsetX = minViewBufferIndex( N, strideX, offsetX ); - offsetY = minViewBufferIndex( N, strideY, offsetY ); - - viewX = offsetView( x, offsetX ); - viewY = offsetView( y, offsetY ); - + if ( strideX < 0 ) { + offsetX += (N-1) * strideX; + } + if ( strideY < 0 ) { + offsetY += (N-1) * strideY; + } + viewX = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offsetX), x.length-offsetX ); // eslint-disable-line max-len + viewY = new Float32Array( y.buffer, y.byteOffset+(y.BYTES_PER_ELEMENT*offsetY), y.length-offsetY ); // eslint-disable-line max-len addon( N, sum, viewX, strideX, viewY, strideY ); return y; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/scusumors/manifest.json index 17c6d6c978f5..dd9cf0d5f8f5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/manifest.json +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/manifest.json @@ -1,77 +1,40 @@ { - "options": { - "task": "build" - }, - "fields": [ - { - "field": "src", - "resolve": true, - "relative": true - }, - { - "field": "include", - "resolve": true, - "relative": true - }, - { - "field": "libraries", - "resolve": false, - "relative": false - }, - { - "field": "libpath", - "resolve": true, - "relative": false - } - ], - "confs": [ - { - "task": "build", - "src": [ - "./src/scusumors.c" - ], - "include": [ - "./include" - ], - "libraries": [ - "-lm" - ], - "libpath": [], - "dependencies": [ - "@stdlib/napi/export", - "@stdlib/napi/argv", - "@stdlib/napi/argv-float", - "@stdlib/napi/argv-int64", - "@stdlib/napi/argv-strided-float32array" - ] - }, - { - "task": "benchmark", - "src": [ - "./src/scusumors.c" - ], - "include": [ - "./include" - ], - "libraries": [ - "-lm" - ], - "libpath": [], - "dependencies": [] - }, - { - "task": "examples", - "src": [ - "./src/scusumors.c" - ], - "include": [ - "./include" - ], - "libraries": [ - "-lm" - ], - "libpath": [], - "dependencies": [] - } - ] + "options": {}, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "src": [ + "./src/scusumors.c" + ], + "include": [ + "./include" + ], + "libraries": [ + "-lm" + ], + "libpath": [], + "dependencies": [] + } + ] } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/package.json b/lib/node_modules/@stdlib/blas/ext/base/scusumors/package.json index 304a98bca137..5c17c6a8bd56 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/package.json @@ -76,7 +76,5 @@ "single", "float32array" ], - "__stdlib__": { - "wasm": false - } + "__stdlib__": {} } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/scusumors/src/addon.c deleted file mode 100644 index ace217d1c331..000000000000 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/src/addon.c +++ /dev/null @@ -1,51 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/blas/ext/base/scusumors.h" -#include "stdlib/napi/export.h" -#include "stdlib/napi/argv.h" -#include "stdlib/napi/argv_float.h" -#include "stdlib/napi/argv_int64.h" -#include "stdlib/napi/argv_strided_float32array.h" -#include - -/** -* Receives JavaScript callback invocation data. -* -* @private -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_FLOAT( env, sum, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); - STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 4 ); - - stdlib_strided_scusumors( N, sum, X, strideX, Y, strideY ); - - return NULL; -} - - -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) - diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/src/addon.cpp b/lib/node_modules/@stdlib/blas/ext/base/scusumors/src/addon.cpp new file mode 100644 index 000000000000..d3152f5005fa --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/src/addon.cpp @@ -0,0 +1,164 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/scusumors.h" +#include +#include +#include +#include +#include + +/** +* Add-on namespace. +*/ +namespace stdlib_blas_ext_base_scusumors { + + /** + * Computes the cumulative sum of single-precision floating-point strided array elements using ordinary recursive summation. + * + * ## Notes + * + * - When called from JavaScript, the function expects six arguments: + * + * - `N`: number of indexed elements + * - `sum`: initial sum + * - `X`: input array + * - `strideX`: `X` stride length + * - `Y`: output array + * - `strideY`: `Y` stride length + */ + napi_value node_scusumors( napi_env env, napi_callback_info info ) { + napi_status status; + + size_t argc = 6; + napi_value argv[ 6 ]; + status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); + assert( status == napi_ok ); + + if ( argc < 6 ) { + napi_throw_error( env, nullptr, "invalid invocation. Must provide 6 arguments." ); + return nullptr; + } + + napi_valuetype vtype0; + status = napi_typeof( env, argv[ 0 ], &vtype0 ); + assert( status == napi_ok ); + if ( vtype0 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); + return nullptr; + } + + napi_valuetype vtype1; + status = napi_typeof( env, argv[ 1 ], &vtype1 ); + assert( status == napi_ok ); + if ( vtype1 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); + return nullptr; + } + + bool res2; + status = napi_is_typedarray( env, argv[ 2 ], &res2 ); + assert( status == napi_ok ); + if ( res2 == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + + napi_valuetype vtype3; + status = napi_typeof( env, argv[ 3 ], &vtype3 ); + assert( status == napi_ok ); + if ( vtype3 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); + return nullptr; + } + + bool res4; + status = napi_is_typedarray( env, argv[ 4 ], &res4 ); + assert( status == napi_ok ); + if ( res4 == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a Float32Array." ); + return nullptr; + } + + napi_valuetype vtype5; + status = napi_typeof( env, argv[ 5 ], &vtype5 ); + assert( status == napi_ok ); + if ( vtype5 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Sixth argument must be a number." ); + return nullptr; + } + + int64_t N; + status = napi_get_value_int64( env, argv[ 0 ], &N ); + assert( status == napi_ok ); + + double sum; + status = napi_get_value_double( env, argv[ 1 ], &sum ); + assert( status == napi_ok ); + + int64_t strideX; + status = napi_get_value_int64( env, argv[ 3 ], &strideX ); + assert( status == napi_ok ); + + int64_t strideY; + status = napi_get_value_int64( env, argv[ 5 ], &strideY ); + assert( status == napi_ok ); + + napi_typedarray_type vtype2; + size_t xlen; + void *X; + status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype2 != napi_float32_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + napi_typedarray_type vtype4; + size_t ylen; + void *Y; + status = napi_get_typedarray_info( env, argv[ 4 ], &vtype4, &ylen, &Y, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype4 != napi_float32_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a Float32Array." ); + return nullptr; + } + if ( (N-1)*llabs(strideY) >= (int64_t)ylen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Fifth argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + stdlib_strided_scusumors( N, (float)sum, (float *)X, strideX, (float *)Y, strideY ); + + return nullptr; + } + + napi_value Init( napi_env env, napi_value exports ) { + napi_status status; + napi_value fcn; + status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_scusumors, NULL, &fcn ); + assert( status == napi_ok ); + return fcn; + } + + NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) +} // end namespace stdlib_blas_ext_base_scusumors diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/test/test.ndarray.js index fd828a164066..5137803a2b94 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/test/test.ndarray.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var Float32Array = require( '@stdlib/array/float32' ); var scusumors = require( './../lib/ndarray.js' ); @@ -140,7 +141,7 @@ tape( 'the function returns a reference to the output array', function test( t ) t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { var expected; var x; var y; @@ -151,10 +152,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); scusumors( -1, 0.0, x, 1, 0, y, 1, 0 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); scusumors( 0, 0.0, x, 1, 0, y, 1, 0 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); t.end(); }); @@ -267,6 +268,7 @@ tape( 'the function supports negative strides', function test( t ) { tape( 'the function supports an `x` offset', function test( t ) { var expected; + var N; var x; var y; @@ -290,8 +292,9 @@ tape( 'the function supports an `x` offset', function test( t ) { 0.0, 0.0 ]); + N = floor( x.length / 2 ); - scusumors( 4, 0.0, x, 2, 1, y, 1, 0 ); + scusumors( N, 0.0, x, 2, 1, y, 1, 0 ); expected = new Float32Array( [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] ); @@ -301,6 +304,7 @@ tape( 'the function supports an `x` offset', function test( t ) { tape( 'the function supports a `y` offset', function test( t ) { var expected; + var N; var x; var y; @@ -324,8 +328,9 @@ tape( 'the function supports a `y` offset', function test( t ) { 0.0, 0.0 // 3 ]); + N = floor( x.length / 2 ); - scusumors( 4, 0.0, x, 1, 0, y, 2, 1 ); + scusumors( N, 0.0, x, 1, 0, y, 2, 1 ); expected = new Float32Array( [ 0.0, 2.0, 0.0, 3.0, 0.0, 5.0, 0.0, 3.0 ] ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/test/test.ndarray.native.js index e62212021968..6afb73a6a122 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/test/test.ndarray.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -149,7 +150,7 @@ tape( 'the function returns a reference to the output array', opts, function tes t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', opts, function test( t ) { var expected; var x; var y; @@ -160,10 +161,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); scusumors( -1, 0.0, x, 1, 0, y, 1, 0 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); scusumors( 0, 0.0, x, 1, 0, y, 1, 0 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); t.end(); }); @@ -276,6 +277,7 @@ tape( 'the function supports negative strides', opts, function test( t ) { tape( 'the function supports an `x` offset', opts, function test( t ) { var expected; + var N; var x; var y; @@ -299,8 +301,9 @@ tape( 'the function supports an `x` offset', opts, function test( t ) { 0.0, 0.0 ]); + N = floor( x.length / 2 ); - scusumors( 4, 0.0, x, 2, 1, y, 1, 0 ); + scusumors( N, 0.0, x, 2, 1, y, 1, 0 ); expected = new Float32Array( [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] ); @@ -310,6 +313,7 @@ tape( 'the function supports an `x` offset', opts, function test( t ) { tape( 'the function supports a `y` offset', opts, function test( t ) { var expected; + var N; var x; var y; @@ -333,8 +337,9 @@ tape( 'the function supports a `y` offset', opts, function test( t ) { 0.0, 0.0 // 3 ]); + N = floor( x.length / 2 ); - scusumors( 4, 0.0, x, 1, 0, y, 2, 1 ); + scusumors( N, 0.0, x, 1, 0, y, 2, 1 ); expected = new Float32Array( [ 0.0, 2.0, 0.0, 3.0, 0.0, 5.0, 0.0, 3.0 ] ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/test/test.scusumors.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/test/test.scusumors.js index eaec9e782bce..5cdc4875ad20 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/test/test.scusumors.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/test/test.scusumors.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var Float32Array = require( '@stdlib/array/float32' ); var scusumors = require( './../lib/scusumors.js' ); @@ -140,7 +141,7 @@ tape( 'the function returns a reference to the output array', function test( t ) t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { var expected; var x; var y; @@ -151,10 +152,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); scusumors( -1, 0.0, x, 1, y, 1 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); scusumors( 0, 0.0, x, 1, y, 1 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); t.end(); }); @@ -303,6 +304,7 @@ tape( 'the function supports view offsets', function test( t ) { var y0; var x1; var y1; + var N; // Initial arrays... x0 = new Float32Array([ @@ -326,7 +328,9 @@ tape( 'the function supports view offsets', function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element - scusumors( 3, 0.0, x1, -2, y1, 1 ); + N = floor( x0.length / 2 ); + + scusumors( N, 0.0, x1, -2, y1, 1 ); expected = new Float32Array( [ 0.0, 0.0, 0.0, 6.0, 10.0, 12.0 ] ); t.deepEqual( y0, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/test/test.scusumors.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/test/test.scusumors.native.js index f8241221beb7..7a32188b0b38 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/test/test.scusumors.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/test/test.scusumors.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -149,7 +150,7 @@ tape( 'the function returns a reference to the output array', opts, function tes t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', opts, function test( t ) { var expected; var x; var y; @@ -160,10 +161,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); scusumors( -1, 0.0, x, 1, y, 1 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); scusumors( 0, 0.0, x, 1, y, 1 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); t.end(); }); @@ -312,6 +313,7 @@ tape( 'the function supports view offsets', opts, function test( t ) { var y0; var x1; var y1; + var N; // Initial arrays... x0 = new Float32Array([ @@ -335,7 +337,9 @@ tape( 'the function supports view offsets', opts, function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element - scusumors( 3, 0.0, x1, -2, y1, 1 ); + N = floor( x0.length / 2 ); + + scusumors( N, 0.0, x1, -2, y1, 1 ); expected = new Float32Array( [ 0.0, 0.0, 0.0, 6.0, 10.0, 12.0 ] ); t.deepEqual( y0, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/README.md b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/README.md index 99de471245d3..1254ee178fb2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/README.md @@ -65,15 +65,18 @@ The function has the following parameters: - **y**: output [`Float32Array`][@stdlib/array/float32]. - **strideY**: index increment for `y`. -The `N` and `stride` parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative sum of every other element in `x`, +The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to compute the cumulative sum of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); var y = new Float32Array( x.length ); -var v = scusumpw( 4, 0.0, x, 2, y, 1 ); +var N = floor( x.length / 2 ); + +var v = scusumpw( N, 0.0, x, 2, y, 1 ); // y => [ 1.0, 3.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] ``` @@ -83,6 +86,7 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); // Initial arrays... var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); @@ -92,7 +96,9 @@ var y0 = new Float32Array( x0.length ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element -scusumpw( 4, 0.0, x1, -2, y1, 1 ); +var N = floor( x0.length / 2 ); + +scusumpw( N, 0.0, x1, -2, y1, 1 ); // y0 => [ 0.0, 0.0, 0.0, 4.0, 6.0, 4.0, 5.0, 0.0 ] ``` @@ -119,11 +125,14 @@ While [`typed array`][mdn-typed-array] views mandate a view offset based on the ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var y = new Float32Array( x.length ); -scusumpw.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 ); +var N = floor( x.length / 2 ); + +scusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ); // y => [ 0.0, 0.0, 0.0, 0.0, 5.0, 1.0, -1.0, 1.0 ] ``` @@ -149,14 +158,20 @@ scusumpw.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); var Float32Array = require( '@stdlib/array/float32' ); var scusumpw = require( '@stdlib/blas/ext/base/scusumpw' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); -var y = new Float32Array( x.length ); +var y; +var x; +var i; +x = new Float32Array( 10 ); +y = new Float32Array( x.length ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); console.log( y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.js index 9140d18b1123..b38a94746a16 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -30,11 +29,6 @@ var pkg = require( './../package.json' ).name; var scusumpw = require( './../lib/scusumpw.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -45,9 +39,15 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var y = new Float32Array( len ); - var x = filledarrayBy( len, 'float32', rand ); + var y; + var x; + var i; + x = new Float32Array( len ); + y = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.native.js index e63e3363000e..504c1bcae895 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -37,7 +36,6 @@ var scusumpw = tryRequire( resolve( __dirname, './../lib/scusumpw.native.js' ) ) var opts = { 'skip': ( scusumpw instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -50,9 +48,15 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = new Float32Array( len ); + var x; + var y; + var i; + x = new Float32Array( len ); + y = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.js index 0a6f1bc6c736..f030f41e30ef 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -30,11 +29,6 @@ var pkg = require( './../package.json' ).name; var scusumpw = require( './../lib/ndarray.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -45,9 +39,15 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = new Float32Array( len ); + var x; + var y; + var i; + x = new Float32Array( len ); + y = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.native.js index 0a386bb1269e..ee290adbeb36 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -37,7 +36,6 @@ var scusumpw = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( scusumpw instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -50,9 +48,15 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = new Float32Array( len ); + var x; + var y; + var i; + x = new Float32Array( len ); + y = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/docs/repl.txt index 70e9f3b55348..cfb10565541b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/docs/repl.txt @@ -3,8 +3,8 @@ Computes the cumulative sum of single-precision floating-point strided array elements using pairwise summation. - The `N` and stride parameters determine which elements in the strided arrays - are accessed at runtime. + The `N` and `stride` parameters determine which elements in `x` and `y` are + accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -44,10 +44,11 @@ > {{alias}}( x.length, 0.0, x, 1, y, 1 ) [ 1.0, -1.0, 1.0 ] - // Using `N` and stride parameters: + // Using `N` and `stride` parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); > y = new {{alias:@stdlib/array/float32}}( x.length ); - > {{alias}}( 3, 0.0, x, 2, y, 2 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > {{alias}}( N, 0.0, x, 2, y, 2 ) [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ] // Using view offsets: @@ -55,12 +56,12 @@ > var y0 = new {{alias:@stdlib/array/float32}}( x0.length ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); > var y1 = new {{alias:@stdlib/array/float32}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); - > {{alias}}( 3, 0.0, x1, 2, y1, 1 ) + > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); + > {{alias}}( N, 0.0, x1, 2, y1, 1 ) [ -2.0, 0.0, -1.0 ] > y0 [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ] - {{alias}}.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY ) Computes the cumulative sum of single-precision floating-point strided array elements using pairwise summation and alternative indexing semantics. @@ -111,7 +112,8 @@ // Advanced indexing: > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > y = new {{alias:@stdlib/array/float32}}( x.length ); - > {{alias}}.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > {{alias}}.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ) [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ] See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/examples/index.js index 64d24e25349a..0e176b0a14f9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/examples/index.js @@ -18,14 +18,20 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); var Float32Array = require( '@stdlib/array/float32' ); var scusumpw = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); -var y = new Float32Array( x.length ); +var y; +var x; +var i; +x = new Float32Array( 10 ); +y = new Float32Array( x.length ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); console.log( y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/include.gypi index 26476a8c2655..868c5c12e852 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/include.gypi +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.c', + '<(src_dir)/addon.cpp', ' - - -/** -* Receives JavaScript callback invocation data. -* -* @private -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_FLOAT( env, sum, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); - STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 4 ); - - stdlib_strided_scusumpw( N, sum, X, strideX, Y, strideY ); - - return NULL; -} - -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/src/addon.cpp b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/src/addon.cpp new file mode 100644 index 000000000000..6cb8c89e466f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/src/addon.cpp @@ -0,0 +1,164 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/scusumpw.h" +#include +#include +#include +#include +#include + +/** +* Add-on namespace. +*/ +namespace stdlib_blas_ext_base_scusumpw { + + /** + * Computes the cumulative sum of single-precision floating-point strided array elements using pairwise summation. + * + * ## Notes + * + * - When called from JavaScript, the function expects six arguments: + * + * - `N`: number of indexed elements + * - `sum`: initial sum + * - `X`: input array + * - `strideX`: `X` stride length + * - `Y`: output array + * - `strideY`: `Y` stride length + */ + napi_value node_scusumpw( napi_env env, napi_callback_info info ) { + napi_status status; + + size_t argc = 6; + napi_value argv[ 6 ]; + status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); + assert( status == napi_ok ); + + if ( argc < 6 ) { + napi_throw_error( env, nullptr, "invalid invocation. Must provide 6 arguments." ); + return nullptr; + } + + napi_valuetype vtype0; + status = napi_typeof( env, argv[ 0 ], &vtype0 ); + assert( status == napi_ok ); + if ( vtype0 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); + return nullptr; + } + + napi_valuetype vtype1; + status = napi_typeof( env, argv[ 1 ], &vtype1 ); + assert( status == napi_ok ); + if ( vtype1 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); + return nullptr; + } + + bool res2; + status = napi_is_typedarray( env, argv[ 2 ], &res2 ); + assert( status == napi_ok ); + if ( res2 == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + + napi_valuetype vtype3; + status = napi_typeof( env, argv[ 3 ], &vtype3 ); + assert( status == napi_ok ); + if ( vtype3 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); + return nullptr; + } + + bool res4; + status = napi_is_typedarray( env, argv[ 4 ], &res4 ); + assert( status == napi_ok ); + if ( res4 == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a Float32Array." ); + return nullptr; + } + + napi_valuetype vtype5; + status = napi_typeof( env, argv[ 5 ], &vtype5 ); + assert( status == napi_ok ); + if ( vtype5 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Sixth argument must be a number." ); + return nullptr; + } + + int64_t N; + status = napi_get_value_int64( env, argv[ 0 ], &N ); + assert( status == napi_ok ); + + double sum; + status = napi_get_value_double( env, argv[ 1 ], &sum ); + assert( status == napi_ok ); + + int64_t strideX; + status = napi_get_value_int64( env, argv[ 3 ], &strideX ); + assert( status == napi_ok ); + + int64_t strideY; + status = napi_get_value_int64( env, argv[ 5 ], &strideY ); + assert( status == napi_ok ); + + napi_typedarray_type vtype2; + size_t xlen; + void *X; + status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype2 != napi_float32_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + napi_typedarray_type vtype4; + size_t ylen; + void *Y; + status = napi_get_typedarray_info( env, argv[ 4 ], &vtype4, &ylen, &Y, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype4 != napi_float32_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a Float32Array." ); + return nullptr; + } + if ( (N-1)*llabs(strideY) >= (int64_t)ylen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Fifth argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + stdlib_strided_scusumpw( N, (float)sum, (float *)X, strideX, (float *)Y, strideY ); + + return nullptr; + } + + napi_value Init( napi_env env, napi_value exports ) { + napi_status status; + napi_value fcn; + status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_scusumpw, NULL, &fcn ); + assert( status == napi_ok ); + return fcn; + } + + NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) +} // end namespace stdlib_blas_ext_base_scusumpw diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/test/test.ndarray.js index b72e1617dde9..8f4b774d068a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/test/test.ndarray.js @@ -141,7 +141,7 @@ tape( 'the function returns a reference to the output array', function test( t ) t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns output array unchanged', function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { var expected; var x; var y; @@ -152,10 +152,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); scusumpw( -1, 0.0, x, 1, 0, y, 1, 0 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); scusumpw( 0, 0.0, x, 1, 0, y, 1, 0 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/test/test.ndarray.native.js index aae46fd36e56..5b481f1bfc2f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/test/test.ndarray.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -149,7 +150,7 @@ tape( 'the function returns a reference to the output array', opts, function tes t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns output array unchanged', opts, function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', opts, function test( t ) { var expected; var x; var y; @@ -160,10 +161,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); scusumpw( -1, 0.0, x, 1, 0, y, 1, 0 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); scusumpw( 0, 0.0, x, 1, 0, y, 1, 0 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); t.end(); }); @@ -276,6 +277,7 @@ tape( 'the function supports negative strides', opts, function test( t ) { tape( 'the function supports an `x` offset', opts, function test( t ) { var expected; + var N; var x; var y; @@ -299,8 +301,9 @@ tape( 'the function supports an `x` offset', opts, function test( t ) { 0.0, 0.0 ]); + N = floor( x.length / 2 ); - scusumpw( 4, 0.0, x, 2, 1, y, 1, 0 ); + scusumpw( N, 0.0, x, 2, 1, y, 1, 0 ); expected = new Float32Array( [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] ); @@ -310,6 +313,7 @@ tape( 'the function supports an `x` offset', opts, function test( t ) { tape( 'the function supports a `y` offset', opts, function test( t ) { var expected; + var N; var x; var y; @@ -333,8 +337,9 @@ tape( 'the function supports a `y` offset', opts, function test( t ) { 0.0, 0.0 // 3 ]); + N = floor( x.length / 2 ); - scusumpw( 4, 0.0, x, 1, 0, y, 2, 1 ); + scusumpw( N, 0.0, x, 1, 0, y, 2, 1 ); expected = new Float32Array( [ 0.0, 2.0, 0.0, 3.0, 0.0, 5.0, 0.0, 3.0 ] ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/test/test.scusumpw.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/test/test.scusumpw.js index ab929b774d78..b1a31f637e07 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/test/test.scusumpw.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/test/test.scusumpw.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var Float32Array = require( '@stdlib/array/float32' ); var scusumpw = require( './../lib/scusumpw.js' ); @@ -140,7 +141,7 @@ tape( 'the function returns a reference to the output array', function test( t ) t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns output array unchanged', function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { var expected; var x; var y; @@ -151,10 +152,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); scusumpw( -1, 0.0, x, 1, y, 1 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); scusumpw( 0, 0.0, x, 1, y, 1 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); t.end(); }); @@ -303,6 +304,7 @@ tape( 'the function supports view offsets', function test( t ) { var y0; var x1; var y1; + var N; // Initial arrays... x0 = new Float32Array([ @@ -326,7 +328,9 @@ tape( 'the function supports view offsets', function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element - scusumpw( 3, 0.0, x1, -2, y1, 1 ); + N = floor( x0.length / 2 ); + + scusumpw( N, 0.0, x1, -2, y1, 1 ); expected = new Float32Array( [ 0.0, 0.0, 0.0, 6.0, 10.0, 12.0 ] ); t.deepEqual( y0, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/test/test.scusumpw.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/test/test.scusumpw.native.js index 38fe431978f3..a37a8aaf8619 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/test/test.scusumpw.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/test/test.scusumpw.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -149,7 +150,7 @@ tape( 'the function returns a reference to the output array', opts, function tes t.end(); }); -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', opts, function test( t ) { var expected; var x; var y; @@ -160,10 +161,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); scusumpw( -1, 0.0, x, 1, y, 1 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); scusumpw( 0, 0.0, x, 1, y, 1 ); - t.deepEqual( y, expected, 'returns expected value' ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); t.end(); }); @@ -312,6 +313,7 @@ tape( 'the function supports view offsets', opts, function test( t ) { var y0; var x1; var y1; + var N; // Initial arrays... x0 = new Float32Array([ @@ -335,7 +337,9 @@ tape( 'the function supports view offsets', opts, function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element - scusumpw( 3, 0.0, x1, -2, y1, 1 ); + N = floor( x0.length / 2 ); + + scusumpw( N, 0.0, x1, -2, y1, 1 ); expected = new Float32Array( [ 0.0, 0.0, 0.0, 6.0, 10.0, 12.0 ] ); t.deepEqual( y0, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/README.md b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/README.md index d432f453d087..3a45d4b0de1d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/README.md @@ -44,8 +44,9 @@ Adds a constant to each single-precision floating-point strided array element an var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); +var N = x.length; -var v = sdsapxsum( 3, 5.0, x, 1 ); +var v = sdsapxsum( N, 5.0, x, 1 ); // returns 16.0 ``` @@ -55,14 +56,16 @@ The function has the following parameters: - **x**: input [`Float32Array`][@stdlib/array/float32]. - **stride**: index increment for `x`. -The `N` and `stride` parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element in the strided array, +The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to access every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); +var N = floor( x.length / 2 ); -var v = sdsapxsum( 4, 5.0, x, 2 ); +var v = sdsapxsum( N, 5.0, x, 2 ); // returns 25.0 ``` @@ -72,11 +75,14 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var v = sdsapxsum( 4, 5.0, x1, 2 ); +var N = floor( x0.length / 2 ); + +var v = sdsapxsum( N, 5.0, x1, 2 ); // returns 25.0 ``` @@ -88,8 +94,9 @@ Adds a constant to each single-precision floating-point strided array element an var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); +var N = x.length; -var v = sdsapxsum.ndarray( 3, 5.0, x, 1, 0 ); +var v = sdsapxsum.ndarray( N, 5.0, x, 1, 0 ); // returns 16.0 ``` @@ -97,14 +104,16 @@ The function has the following additional parameters: - **offset**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the offset parameter supports indexing semantics based on a starting index. For example, to access every other value in the strided array starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access every other value in `x` starting from the second value ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +var N = floor( x.length / 2 ); -var v = sdsapxsum.ndarray( 4, 5.0, x, 2, 1 ); +var v = sdsapxsum.ndarray( N, 5.0, x, 2, 1 ); // returns 25.0 ``` @@ -130,11 +139,18 @@ var v = sdsapxsum.ndarray( 4, 5.0, x, 2, 1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float32Array = require( '@stdlib/array/float32' ); var sdsapxsum = require( '@stdlib/blas/ext/base/sdsapxsum' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x; +var i; + +x = new Float32Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); var v = sdsapxsum( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.js index 372fe933ceff..a2216c9fe4ef 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var sdsapxsum = require( './../lib/sdsapxsum.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -44,7 +39,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.native.js index 6418d272348d..c86bd9d82530 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var sdsapxsum = tryRequire( resolve( __dirname, './../lib/sdsapxsum.native.js' ) var opts = { 'skip': ( sdsapxsum instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -49,7 +48,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.ndarray.js index 17115bfd96f1..e5efd5fb39d5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.ndarray.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var sdsapxsum = require( './../lib/ndarray.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -44,7 +39,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.ndarray.native.js index 9cfb7bdda60a..a8e4edcfa61a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var sdsapxsum = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ) var opts = { 'skip': ( sdsapxsum instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -49,7 +48,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/docs/repl.txt index 9dca6b853208..2a238f9e8187 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/docs/repl.txt @@ -3,8 +3,8 @@ Adds a constant to each single-precision floating-point strided array element and computes the sum using extended accumulation. - The `N` and `stride` parameters determine which elements in the strided - array are accessed at runtime. + The `N` and `stride` parameters determine which elements in `x` are accessed + at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -39,16 +39,19 @@ // Using `N` and `stride` parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > {{alias}}( 3, 5.0, x, 2 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > var stride = 2; + > {{alias}}( N, 5.0, x, stride ) 16.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > {{alias}}( 3, 5.0, x1, 2 ) + > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); + > stride = 2; + > {{alias}}( N, 5.0, x1, stride ) 14.0 - {{alias}}.ndarray( N, alpha, x, stride, offset ) Adds a constant to each single-precision floating-point strided array element and computes the sum using extended accumulation and alternative @@ -88,8 +91,9 @@ 16.0 // Using offset parameter: - > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > {{alias}}.ndarray( 3, 5.0, x, 2, 1 ) + > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > {{alias}}.ndarray( N, 5.0, x, 2, 1 ) 14.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/examples/index.js index 9aa890c47fca..36f9176e4dc3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/examples/index.js @@ -18,11 +18,18 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float32Array = require( '@stdlib/array/float32' ); var sdsapxsum = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x; +var i; + +x = new Float32Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); var v = sdsapxsum( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/include.gypi index 26476a8c2655..868c5c12e852 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/include.gypi +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.c', + '<(src_dir)/addon.cpp', ' -#include - -/** -* Receives JavaScript callback invocation data. -* -* @private -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_FLOAT( env, N, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_sdsapxsum( N, alpha, X, stride ), &v ); - assert( status == napi_ok ); - return v; -} - -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/src/addon.cpp b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/src/addon.cpp new file mode 100644 index 000000000000..8628e66eb144 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/src/addon.cpp @@ -0,0 +1,130 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sdsapxsum.h" +#include +#include +#include +#include +#include + +/** +* Add-on namespace. +*/ +namespace stdlib_blas_ext_base_sdsapxsum { + + /** + * Adds a constant to each single-precision floating-point strided array element and computes the sum using extended accumulation. + * + * ## Notes + * + * - When called from JavaScript, the function expects four arguments: + * + * - `N`: number of indexed elements + * - `alpha`: constant + * - `X`: input array + * - `stride`: stride length + */ + napi_value node_sdsapxsum( napi_env env, napi_callback_info info ) { + napi_status status; + + size_t argc = 4; + napi_value argv[ 4 ]; + status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); + assert( status == napi_ok ); + + if ( argc < 4 ) { + napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); + return nullptr; + } + + napi_valuetype vtype0; + status = napi_typeof( env, argv[ 0 ], &vtype0 ); + assert( status == napi_ok ); + if ( vtype0 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); + return nullptr; + } + + napi_valuetype vtype1; + status = napi_typeof( env, argv[ 1 ], &vtype1 ); + assert( status == napi_ok ); + if ( vtype1 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); + return nullptr; + } + + bool res; + status = napi_is_typedarray( env, argv[ 2 ], &res ); + assert( status == napi_ok ); + if ( res == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + + napi_valuetype vtype3; + status = napi_typeof( env, argv[ 3 ], &vtype3 ); + assert( status == napi_ok ); + if ( vtype3 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); + return nullptr; + } + + int64_t N; + status = napi_get_value_int64( env, argv[ 0 ], &N ); + assert( status == napi_ok ); + + double alpha; + status = napi_get_value_double( env, argv[ 1 ], &alpha ); + assert( status == napi_ok ); + + int64_t stride; + status = napi_get_value_int64( env, argv[ 3 ], &stride ); + assert( status == napi_ok ); + + napi_typedarray_type vtype2; + size_t xlen; + void *X; + status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype2 != napi_float32_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + napi_value v; + status = napi_create_double( env, (double)stdlib_strided_sdsapxsum( N, (float)alpha, (float *)X, stride ), &v ); + assert( status == napi_ok ); + + return v; + } + + napi_value Init( napi_env env, napi_value exports ) { + napi_status status; + napi_value fcn; + status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_sdsapxsum, NULL, &fcn ); + assert( status == napi_ok ); + return fcn; + } + + NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) +} // end namespace stdlib_blas_ext_base_sdsapxsum diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/test/test.ndarray.js index d00f354b1e98..5981265509bf 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/test/test.ndarray.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var sdsapxsum = require( './../lib/ndarray.js' ); @@ -35,7 +36,7 @@ tape( 'main export is a function', function test( t ) { }); tape( 'the function has an arity of 5', function test( t ) { - t.strictEqual( sdsapxsum.length, 5, 'returns expected value' ); + t.strictEqual( sdsapxsum.length, 5, 'has expected arity' ); t.end(); }); @@ -102,6 +103,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { + var N; var x; var v; @@ -116,13 +118,15 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - v = sdsapxsum( 4, 5.0, x, 2, 0 ); + N = floor( x.length / 2 ); + v = sdsapxsum( N, 5.0, x, 2, 0 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { + var N; var x; var v; var i; @@ -138,7 +142,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - v = sdsapxsum( 4, 5.0, x, -2, 6 ); + N = floor( x.length / 2 ); + v = sdsapxsum( N, 5.0, x, -2, 6 ); t.strictEqual( v, 25.0, 'returns expected value' ); @@ -165,6 +170,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { + var N; var x; var v; @@ -178,8 +184,9 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); + N = floor( x.length / 2 ); - v = sdsapxsum( 4, 5.0, x, 2, 1 ); + v = sdsapxsum( N, 5.0, x, 2, 1 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/test/test.ndarray.native.js index 68d3e1ad68e6..3d3f07d13981 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/test/test.ndarray.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -44,7 +45,7 @@ tape( 'main export is a function', opts, function test( t ) { }); tape( 'the function has an arity of 5', opts, function test( t ) { - t.strictEqual( sdsapxsum.length, 5, 'returns expected value' ); + t.strictEqual( sdsapxsum.length, 5, 'has expected arity' ); t.end(); }); @@ -111,6 +112,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -125,13 +127,15 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - v = sdsapxsum( 4, 5.0, x, 2, 0 ); + N = floor( x.length / 2 ); + v = sdsapxsum( N, 5.0, x, 2, 0 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var N; var x; var v; var i; @@ -147,7 +151,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - v = sdsapxsum( 4, 5.0, x, -2, 6 ); + N = floor( x.length / 2 ); + v = sdsapxsum( N, 5.0, x, -2, 6 ); t.strictEqual( v, 25.0, 'returns expected value' ); @@ -174,6 +179,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { + var N; var x; var v; @@ -187,8 +193,9 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); + N = floor( x.length / 2 ); - v = sdsapxsum( 4, 5.0, x, 2, 1 ); + v = sdsapxsum( N, 5.0, x, 2, 1 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/test/test.sdsapxsum.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/test/test.sdsapxsum.js index dfea74599972..ec903a47ba3e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/test/test.sdsapxsum.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/test/test.sdsapxsum.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var sdsapxsum = require( './../lib/sdsapxsum.js' ); @@ -35,7 +36,7 @@ tape( 'main export is a function', function test( t ) { }); tape( 'the function has an arity of 4', function test( t ) { - t.strictEqual( sdsapxsum.length, 4, 'returns expected value' ); + t.strictEqual( sdsapxsum.length, 4, 'has expected arity' ); t.end(); }); @@ -102,6 +103,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { + var N; var x; var v; @@ -116,13 +118,15 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - v = sdsapxsum( 4, 5.0, x, 2 ); + N = floor( x.length / 2 ); + v = sdsapxsum( N, 5.0, x, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { + var N; var x; var v; var i; @@ -138,7 +142,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - v = sdsapxsum( 4, 5.0, x, -2 ); + N = floor( x.length / 2 ); + v = sdsapxsum( N, 5.0, x, -2 ); t.strictEqual( v, 25.0, 'returns expected value' ); @@ -167,6 +172,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; + var N; var v; x0 = new Float32Array([ @@ -182,8 +188,9 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + N = floor(x1.length / 2); - v = sdsapxsum( 4, 5.0, x1, 2 ); + v = sdsapxsum( N, 5.0, x1, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/test/test.sdsapxsum.native.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/test/test.sdsapxsum.native.js index 2a5c5be8791e..9432146dd898 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/test/test.sdsapxsum.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsum/test/test.sdsapxsum.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -44,7 +45,7 @@ tape( 'main export is a function', opts, function test( t ) { }); tape( 'the function has an arity of 4', opts, function test( t ) { - t.strictEqual( sdsapxsum.length, 4, 'returns expected value' ); + t.strictEqual( sdsapxsum.length, 4, 'has expected arity' ); t.end(); }); @@ -220,6 +221,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -234,13 +236,15 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - v = sdsapxsum( 4, 5.0, x, 2 ); + N = floor( x.length / 2 ); + v = sdsapxsum( N, 5.0, x, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var N; var x; var v; var i; @@ -256,7 +260,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - v = sdsapxsum( 4, 5.0, x, -2 ); + N = floor( x.length / 2 ); + v = sdsapxsum( N, 5.0, x, -2 ); t.strictEqual( v, 25.0, 'returns expected value' ); @@ -285,6 +290,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; + var N; var v; x0 = new Float32Array([ @@ -300,8 +306,9 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + N = floor(x1.length / 2); - v = sdsapxsum( 4, 5.0, x1, 2 ); + v = sdsapxsum( N, 5.0, x1, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/README.md b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/README.md index 2e81b95e5a86..92d2dbf3ca44 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/README.md @@ -44,26 +44,28 @@ Adds a constant to each single-precision floating-point strided array element an var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); +var N = x.length; -var v = sdsapxsumpw( 3, 5.0, x, 1 ); +var v = sdsapxsumpw( N, 5.0, x, 1 ); // returns 16.0 ``` The function has the following parameters: - **N**: number of indexed elements. -- **alpha**: scalar constant. - **x**: input [`Float32Array`][@stdlib/array/float32]. - **stride**: index increment for `x`. -The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of every other element in the strided array, +The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to access every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); +var N = floor( x.length / 2 ); -var v = sdsapxsumpw( 4, 5.0, x, 2 ); +var v = sdsapxsumpw( N, 5.0, x, 2 ); // returns 25.0 ``` @@ -73,11 +75,14 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var v = sdsapxsumpw( 4, 5.0, x1, 2 ); +var N = floor( x0.length / 2 ); + +var v = sdsapxsumpw( N, 5.0, x1, 2 ); // returns 25.0 ``` @@ -89,8 +94,9 @@ Adds a constant to each single-precision floating-point strided array element an var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); +var N = x.length; -var v = sdsapxsumpw.ndarray( 3, 5.0, x, 1, 0 ); +var v = sdsapxsumpw.ndarray( N, 5.0, x, 1, 0 ); // returns 16.0 ``` @@ -98,14 +104,16 @@ The function has the following additional parameters: - **offset**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the offset parameter supports indexing semantics based on a starting index. For example, to access every other value in the strided array starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access every other value in `x` starting from the second value ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +var N = floor( x.length / 2 ); -var v = sdsapxsumpw.ndarray( 4, 5.0, x, 2, 1 ); +var v = sdsapxsumpw.ndarray( N, 5.0, x, 2, 1 ); // returns 25.0 ``` @@ -131,11 +139,18 @@ var v = sdsapxsumpw.ndarray( 4, 5.0, x, 2, 1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float32Array = require( '@stdlib/array/float32' ); var sdsapxsumpw = require( '@stdlib/blas/ext/base/sdsapxsumpw' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x; +var i; + +x = new Float32Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); var v = sdsapxsumpw( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.js index 628e2e1b421c..f5da2ba3722b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var sdsapxsumpw = require( './../lib/sdsapxsumpw.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -44,7 +39,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.native.js index e74c78320c40..71f43a2bd63d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var sdsapxsumpw = tryRequire( resolve( __dirname, './../lib/sdsapxsumpw.native.j var opts = { 'skip': ( sdsapxsumpw instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -49,7 +48,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.ndarray.js index 12ad6958b2ed..143d69637931 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.ndarray.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var sdsapxsumpw = require( './../lib/ndarray.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -44,7 +39,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.ndarray.native.js index 9cfd9de3a1a1..f2830827f9d7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var sdsapxsumpw = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) var opts = { 'skip': ( sdsapxsumpw instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -49,7 +48,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*20.0 ) - 10.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/docs/repl.txt index 8159c3b7a159..1f8a87d66ffa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/docs/repl.txt @@ -4,8 +4,8 @@ element and computes the sum using pairwise summation with extended accumulation. - The `N` and stride parameters determine which elements in the strided array - are accessed at runtime. + The `N` and `stride` parameters determine which elements in `x` are accessed + at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -40,16 +40,19 @@ // Using `N` and `stride` parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > {{alias}}( 3, 5.0, x, 2 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > var stride = 2; + > {{alias}}( N, 5.0, x, stride ) 16.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > {{alias}}( 3, 5.0, x1, 2 ) + > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); + > stride = 2; + > {{alias}}( N, 5.0, x1, stride ) 14.0 - {{alias}}.ndarray( N, alpha, x, stride, offset ) Adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation with extended @@ -89,9 +92,11 @@ 16.0 // Using offset parameter: - > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > {{alias}}.ndarray( 3, 5.0, x, 2, 1 ) + > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > {{alias}}.ndarray( N, 5.0, x, 2, 1 ) 14.0 See Also -------- + diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/examples/c/example.c index cb3499d52896..2f6283c56361 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/examples/c/example.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/examples/c/example.c @@ -22,7 +22,7 @@ int main( void ) { // Create a strided array: - const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + const float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: const int64_t N = 4; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/examples/index.js index 3557cd7adbd9..dcefd402bd3e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/examples/index.js @@ -18,11 +18,18 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float32Array = require( '@stdlib/array/float32' ); var sdsapxsumpw = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( -100.0, 100.0 ) ); +var x; +var i; + +x = new Float32Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); var v = sdsapxsumpw( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/include.gypi index 26476a8c2655..868c5c12e852 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/include.gypi +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.c', + '<(src_dir)/addon.cpp', ' -#include - -/** -* Receives JavaScript callback invocation data. -* -* @private -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); - - napi_value v; - napi_status status = napi_create_double( env, (double)stdlib_strided_sdsapxsumpw( N, alpha, X, stride ), &v ); - assert( status == napi_ok ); - - return v; -} - -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/src/addon.cpp b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/src/addon.cpp new file mode 100644 index 000000000000..879e6f6cdf5e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/src/addon.cpp @@ -0,0 +1,130 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sdsapxsumpw.h" +#include +#include +#include +#include +#include + +/** +* Add-on namespace. +*/ +namespace stdlib_blas_ext_base_sdsapxsumpw { + + /** + * Adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation with extended accumulation. + * + * ## Notes + * + * - When called from JavaScript, the function expects four arguments: + * + * - `N`: number of indexed elements + * - `alpha`: constant + * - `X`: input array + * - `stride`: stride length + */ + napi_value node_sdsapxsumpw( napi_env env, napi_callback_info info ) { + napi_status status; + + size_t argc = 4; + napi_value argv[ 4 ]; + status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); + assert( status == napi_ok ); + + if ( argc < 4 ) { + napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); + return nullptr; + } + + napi_valuetype vtype0; + status = napi_typeof( env, argv[ 0 ], &vtype0 ); + assert( status == napi_ok ); + if ( vtype0 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); + return nullptr; + } + + napi_valuetype vtype1; + status = napi_typeof( env, argv[ 1 ], &vtype1 ); + assert( status == napi_ok ); + if ( vtype1 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); + return nullptr; + } + + bool res; + status = napi_is_typedarray( env, argv[ 2 ], &res ); + assert( status == napi_ok ); + if ( res == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + + napi_valuetype vtype3; + status = napi_typeof( env, argv[ 3 ], &vtype3 ); + assert( status == napi_ok ); + if ( vtype3 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); + return nullptr; + } + + int64_t N; + status = napi_get_value_int64( env, argv[ 0 ], &N ); + assert( status == napi_ok ); + + double alpha; + status = napi_get_value_double( env, argv[ 1 ], &alpha ); + assert( status == napi_ok ); + + int64_t stride; + status = napi_get_value_int64( env, argv[ 3 ], &stride ); + assert( status == napi_ok ); + + napi_typedarray_type vtype2; + size_t xlen; + void *X; + status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype2 != napi_float32_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); + return nullptr; + } + if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + napi_value v; + status = napi_create_double( env, (double)stdlib_strided_sdsapxsumpw( N, (float)alpha, (float *)X, stride ), &v ); + assert( status == napi_ok ); + + return v; + } + + napi_value Init( napi_env env, napi_value exports ) { + napi_status status; + napi_value fcn; + status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_sdsapxsumpw, NULL, &fcn ); + assert( status == napi_ok ); + return fcn; + } + + NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) +} // end namespace stdlib_blas_ext_base_sdsapxsumpw diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/test/test.ndarray.js index b4b46f9bc3aa..473c556734fa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/test/test.ndarray.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var sdsapxsumpw = require( './../lib/ndarray.js' ); @@ -35,7 +36,7 @@ tape( 'main export is a function', function test( t ) { }); tape( 'the function has an arity of 5', function test( t ) { - t.strictEqual( sdsapxsumpw.length, 5, 'returns expected value' ); + t.strictEqual( sdsapxsumpw.length, 5, 'has expected arity' ); t.end(); }); @@ -102,6 +103,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { + var N; var x; var v; @@ -116,13 +118,15 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - v = sdsapxsumpw( 4, 5.0, x, 2, 0 ); + N = floor( x.length / 2 ); + v = sdsapxsumpw( N, 5.0, x, 2, 0 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { + var N; var x; var v; var i; @@ -138,7 +142,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - v = sdsapxsumpw( 4, 5.0, x, -2, 6 ); + N = floor( x.length / 2 ); + v = sdsapxsumpw( N, 5.0, x, -2, 6 ); t.strictEqual( v, 25.0, 'returns expected value' ); @@ -165,6 +170,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { + var N; var x; var v; @@ -178,8 +184,9 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); + N = floor( x.length / 2 ); - v = sdsapxsumpw( 4, 5.0, x, 2, 1 ); + v = sdsapxsumpw( N, 5.0, x, 2, 1 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/test/test.ndarray.native.js index f16fc008f44a..416d2a1a87cb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/test/test.ndarray.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -44,7 +45,7 @@ tape( 'main export is a function', opts, function test( t ) { }); tape( 'the function has an arity of 5', opts, function test( t ) { - t.strictEqual( sdsapxsumpw.length, 5, 'returns expected value' ); + t.strictEqual( sdsapxsumpw.length, 5, 'has expected arity' ); t.end(); }); @@ -111,6 +112,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -125,13 +127,15 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - v = sdsapxsumpw( 4, 5.0, x, 2, 0 ); + N = floor( x.length / 2 ); + v = sdsapxsumpw( N, 5.0, x, 2, 0 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var N; var x; var v; var i; @@ -147,7 +151,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - v = sdsapxsumpw( 4, 5.0, x, -2, 6 ); + N = floor( x.length / 2 ); + v = sdsapxsumpw( N, 5.0, x, -2, 6 ); t.strictEqual( v, 25.0, 'returns expected value' ); @@ -174,6 +179,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { + var N; var x; var v; @@ -187,8 +193,9 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); + N = floor( x.length / 2 ); - v = sdsapxsumpw( 4, 5.0, x, 2, 1 ); + v = sdsapxsumpw( N, 5.0, x, 2, 1 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/test/test.sdsapxsumpw.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/test/test.sdsapxsumpw.js index 0d9f9d1f3555..1f91f94e14c4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/test/test.sdsapxsumpw.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/test/test.sdsapxsumpw.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var sdsapxsumpw = require( './../lib/sdsapxsumpw.js' ); @@ -35,7 +36,7 @@ tape( 'main export is a function', function test( t ) { }); tape( 'the function has an arity of 4', function test( t ) { - t.strictEqual( sdsapxsumpw.length, 4, 'returns expected value' ); + t.strictEqual( sdsapxsumpw.length, 4, 'has expected arity' ); t.end(); }); @@ -102,6 +103,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { + var N; var x; var v; @@ -116,13 +118,15 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - v = sdsapxsumpw( 4, 5.0, x, 2 ); + N = floor( x.length / 2 ); + v = sdsapxsumpw( N, 5.0, x, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { + var N; var x; var v; var i; @@ -138,7 +142,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - v = sdsapxsumpw( 4, 5.0, x, -2 ); + N = floor( x.length / 2 ); + v = sdsapxsumpw( N, 5.0, x, -2 ); t.strictEqual( v, 25.0, 'returns expected value' ); @@ -167,6 +172,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; + var N; var v; x0 = new Float32Array([ @@ -182,8 +188,9 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + N = floor(x1.length / 2); - v = sdsapxsumpw( 4, 5.0, x1, 2 ); + v = sdsapxsumpw( N, 5.0, x1, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/test/test.sdsapxsumpw.native.js b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/test/test.sdsapxsumpw.native.js index 29a8b8fec72c..17eb088bcc75 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/test/test.sdsapxsumpw.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sdsapxsumpw/test/test.sdsapxsumpw.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -44,7 +45,7 @@ tape( 'main export is a function', opts, function test( t ) { }); tape( 'the function has an arity of 4', opts, function test( t ) { - t.strictEqual( sdsapxsumpw.length, 4, 'returns expected value' ); + t.strictEqual( sdsapxsumpw.length, 4, 'has expected arity' ); t.end(); }); @@ -220,6 +221,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -234,13 +236,15 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - v = sdsapxsumpw( 4, 5.0, x, 2 ); + N = floor( x.length / 2 ); + v = sdsapxsumpw( N, 5.0, x, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var N; var x; var v; var i; @@ -256,7 +260,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - v = sdsapxsumpw( 4, 5.0, x, -2 ); + N = floor( x.length / 2 ); + v = sdsapxsumpw( N, 5.0, x, -2 ); t.strictEqual( v, 25.0, 'returns expected value' ); @@ -285,6 +290,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; + var N; var v; x0 = new Float32Array([ @@ -300,8 +306,9 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + N = floor(x1.length / 2); - v = sdsapxsumpw( 4, 5.0, x1, 2 ); + v = sdsapxsumpw( N, 5.0, x1, 2 ); t.strictEqual( v, 25.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn/src/addon.c index 92fad314939d..9e9eb48f64b8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn/src/addon.c +++ b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn/src/addon.c @@ -39,7 +39,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 ); napi_value v; - napi_status status = napi_create_double( env, (double)stdlib_strided_ssumkbn( N, X, stride ), &v ); + napi_status status = napi_create_double( env, (double)stdlib_strided_ssumkbn( N, (float *)X, stride ), &v ); assert( status == napi_ok ); return v; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/README.md b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/README.md index 559b9b5ba945..437751242871 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/README.md @@ -44,8 +44,9 @@ Computes the sum of single-precision floating-point strided array elements using var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); +var N = x.length; -var v = ssumkbn2( 3, x, 1 ); +var v = ssumkbn2( N, x, 1 ); // returns 1.0 ``` @@ -55,14 +56,16 @@ The function has the following parameters: - **x**: input [`Float32Array`][@stdlib/array/float32]. - **stride**: index increment for `x`. -The `N` and `stride` parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of every other element in the strided array, +The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the sum of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); +var N = floor( x.length / 2 ); -var v = ssumkbn2( 4, x, 2 ); +var v = ssumkbn2( N, x, 2 ); // returns 5.0 ``` @@ -72,11 +75,14 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var v = ssumkbn2( 4, x1, 2 ); +var N = floor( x0.length / 2 ); + +var v = ssumkbn2( N, x1, 2 ); // returns 5.0 ``` @@ -88,8 +94,9 @@ Computes the sum of single-precision floating-point strided array elements using var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); +var N = x.length; -var v = ssumkbn2.ndarray( 3, x, 1, 0 ); +var v = ssumkbn2.ndarray( N, x, 1, 0 ); // returns 1.0 ``` @@ -97,14 +104,16 @@ The function has the following additional parameters: - **offset**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other value in the strided array starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other value in `x` starting from the second value ```javascript var Float32Array = require( '@stdlib/array/float32' ); +var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +var N = floor( x.length / 2 ); -var v = ssumkbn2.ndarray( 4, x, 2, 1 ); +var v = ssumkbn2.ndarray( N, x, 2, 1 ); // returns 5.0 ``` @@ -129,11 +138,18 @@ var v = ssumkbn2.ndarray( 4, x, 2, 1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float32Array = require( '@stdlib/array/float32' ); var ssumkbn2 = require( '@stdlib/blas/ext/base/ssumkbn2' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x; +var i; + +x = new Float32Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); var v = ssumkbn2( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/benchmark/benchmark.js index 60bdbb4563cd..394665f62bf2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/benchmark/benchmark.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var ssumkbn2 = require( './../lib/ssumkbn2.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -44,7 +39,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*10.0 ) - 20.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/benchmark/benchmark.native.js index a1eaec4f45c1..2feafbee87e2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/benchmark/benchmark.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var ssumkbn2 = tryRequire( resolve( __dirname, './../lib/ssumkbn2.native.js' ) ) var opts = { 'skip': ( ssumkbn2 instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -49,7 +48,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*10.0 ) - 20.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/benchmark/benchmark.ndarray.js index 98e5b5a90024..062fd192be69 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/benchmark/benchmark.ndarray.js @@ -21,19 +21,14 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var ssumkbn2 = require( './../lib/ndarray.js' ); -// VARIABLES // - -var rand = uniform( -10.0, 10.0 ); - - // FUNCTIONS // /** @@ -44,7 +39,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*10.0 ) - 20.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/benchmark/benchmark.ndarray.native.js index dbec12a0f3ce..76397613a614 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +36,6 @@ var ssumkbn2 = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( ssumkbn2 instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); // FUNCTIONS // @@ -49,7 +48,13 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x; + var i; + + x = new Float32Array( len ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = ( randu()*10.0 ) - 20.0; + } return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/docs/repl.txt index 8f336b417db4..a8be18cc3450 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/docs/repl.txt @@ -3,8 +3,8 @@ Computes the sum of single-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm. - The `N` and `stride` parameters determine which elements in the strided - array are accessed at runtime. + The `N` and `stride` parameters determine which elements in `x` are accessed + at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -36,16 +36,19 @@ // Using `N` and `stride` parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > {{alias}}( 3, x, 2 ) + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > var stride = 2; + > {{alias}}( N, x, stride ) 1.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > {{alias}}( 3, x1, 2 ) + > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); + > stride = 2; + > {{alias}}( N, x1, stride ) -1.0 - {{alias}}.ndarray( N, x, stride, offset ) Computes the sum of single-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm and alternative @@ -82,8 +85,9 @@ 1.0 // Using offset parameter: - > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > {{alias}}.ndarray( 3, x, 2, 1 ) + > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); + > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); + > {{alias}}.ndarray( N, x, 2, 1 ) -1.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/examples/index.js index bbee99dcd2c7..5b24e5f8b704 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/examples/index.js @@ -18,11 +18,18 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float32Array = require( '@stdlib/array/float32' ); var ssumkbn2 = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x; +var i; + +x = new Float32Array( 10 ); +for ( i = 0; i < x.length; i++ ) { + x[ i ] = round( randu()*100.0 ); +} console.log( x ); var v = ssumkbn2( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/include.gypi index 26476a8c2655..868c5c12e852 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/include.gypi +++ b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.c', + '<(src_dir)/addon.cpp', ' -#include - -/** -* Receives JavaScript callback invocation data. -* -* @private -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 ); - - napi_value v; - napi_status status = napi_create_double( env, (double)stdlib_strided_ssumkbn2( N, X, stride ), &v ); - assert( status == napi_ok ); - - return v; -} - -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/src/addon.cpp b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/src/addon.cpp new file mode 100644 index 000000000000..5d81667e5c7d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/src/addon.cpp @@ -0,0 +1,117 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/ssumkbn2.h" +#include +#include +#include +#include +#include + +/** +* Add-on namespace. +*/ +namespace stdlib_blas_ext_base_ssumkbn2 { + + /** + * Computes the sum of single-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm. + * + * ## Notes + * + * - When called from JavaScript, the function expects three arguments: + * + * - `N`: number of indexed elements + * - `X`: input array + * - `stride`: stride length + */ + napi_value node_ssumkbn2( napi_env env, napi_callback_info info ) { + napi_status status; + + size_t argc = 3; + napi_value argv[ 3 ]; + status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); + assert( status == napi_ok ); + + if ( argc < 3 ) { + napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); + return nullptr; + } + + napi_valuetype vtype0; + status = napi_typeof( env, argv[ 0 ], &vtype0 ); + assert( status == napi_ok ); + if ( vtype0 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); + return nullptr; + } + + bool res; + status = napi_is_typedarray( env, argv[ 1 ], &res ); + assert( status == napi_ok ); + if ( res == false ) { + napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); + return nullptr; + } + + napi_valuetype vtype2; + status = napi_typeof( env, argv[ 2 ], &vtype2 ); + assert( status == napi_ok ); + if ( vtype2 != napi_number ) { + napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); + return nullptr; + } + + int64_t N; + status = napi_get_value_int64( env, argv[ 0 ], &N ); + assert( status == napi_ok ); + + int64_t stride; + status = napi_get_value_int64( env, argv[ 2 ], &stride ); + assert( status == napi_ok ); + + napi_typedarray_type vtype1; + size_t xlen; + void *X; + status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); + assert( status == napi_ok ); + if ( vtype1 != napi_float32_array ) { + napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); + return nullptr; + } + if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { + napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); + return nullptr; + } + + napi_value v; + status = napi_create_double( env, (double)stdlib_strided_ssumkbn2( N, (float *)X, stride ), &v ); + assert( status == napi_ok ); + + return v; + } + + napi_value Init( napi_env env, napi_value exports ) { + napi_status status; + napi_value fcn; + status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_ssumkbn2, NULL, &fcn ); + assert( status == napi_ok ); + return fcn; + } + + NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) +} // end namespace stdlib_blas_ext_base_ssumkbn2 diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/test/test.ndarray.js index dfcae8688377..8306f677fa00 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/test/test.ndarray.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var ssumkbn2 = require( './../lib/ndarray.js' ); @@ -94,6 +95,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { + var N; var x; var v; @@ -108,13 +110,15 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - v = ssumkbn2( 4, x, 2, 0 ); + N = floor( x.length / 2 ); + v = ssumkbn2( N, x, 2, 0 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { + var N; var x; var v; @@ -129,7 +133,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - v = ssumkbn2( 4, x, -2, 6 ); + N = floor( x.length / 2 ); + v = ssumkbn2( N, x, -2, 6 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); @@ -148,6 +153,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { + var N; var x; var v; @@ -161,8 +167,9 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); + N = floor( x.length / 2 ); - v = ssumkbn2( 4, x, 2, 1 ); + v = ssumkbn2( N, x, 2, 1 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/test/test.ndarray.native.js index 3e618933ed7c..bd682835479f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/test/test.ndarray.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -103,6 +104,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -117,13 +119,15 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - v = ssumkbn2( 4, x, 2, 0 ); + N = floor( x.length / 2 ); + v = ssumkbn2( N, x, 2, 0 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -138,7 +142,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - v = ssumkbn2( 4, x, -2, 6 ); + N = floor( x.length / 2 ); + v = ssumkbn2( N, x, -2, 6 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); @@ -157,6 +162,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { + var N; var x; var v; @@ -170,8 +176,9 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); + N = floor( x.length / 2 ); - v = ssumkbn2( 4, x, 2, 1 ); + v = ssumkbn2( N, x, 2, 1 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/test/test.ssumkbn2.js b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/test/test.ssumkbn2.js index 090bb4c85990..382dbb43d231 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/test/test.ssumkbn2.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/test/test.ssumkbn2.js @@ -21,6 +21,7 @@ // MODULES // var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var ssumkbn2 = require( './../lib/ssumkbn2.js' ); @@ -94,6 +95,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { + var N; var x; var v; @@ -108,13 +110,15 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - v = ssumkbn2( 4, x, 2 ); + N = floor( x.length / 2 ); + v = ssumkbn2( N, x, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { + var N; var x; var v; @@ -129,7 +133,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - v = ssumkbn2( 4, x, -2 ); + N = floor( x.length / 2 ); + v = ssumkbn2( N, x, -2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); @@ -150,6 +155,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; + var N; var v; x0 = new Float32Array([ @@ -165,8 +171,9 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + N = floor(x1.length / 2); - v = ssumkbn2( 4, x1, 2 ); + v = ssumkbn2( N, x1, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/test/test.ssumkbn2.native.js b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/test/test.ssumkbn2.native.js index d86d11fbda9d..c975280fdf76 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/test/test.ssumkbn2.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ssumkbn2/test/test.ssumkbn2.native.js @@ -22,6 +22,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -185,6 +186,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -199,13 +201,15 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - v = ssumkbn2( 4, x, 2 ); + N = floor( x.length / 2 ); + v = ssumkbn2( N, x, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { + var N; var x; var v; @@ -220,7 +224,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - v = ssumkbn2( 4, x, -2 ); + N = floor( x.length / 2 ); + v = ssumkbn2( N, x, -2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); @@ -241,6 +246,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; + var N; var v; x0 = new Float32Array([ @@ -256,8 +262,9 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + N = floor(x1.length / 2); - v = ssumkbn2( 4, x1, 2 ); + v = ssumkbn2( N, x1, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssumors/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/ssumors/src/addon.c index 0a5df0031a98..a5ada7b08c1e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssumors/src/addon.c +++ b/lib/node_modules/@stdlib/blas/ext/base/ssumors/src/addon.c @@ -39,7 +39,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 ); napi_value v; - napi_status status = napi_create_double( env, (double)stdlib_strided_ssumors( N, X, stride ), &v ); + napi_status status = napi_create_double( env, (double)stdlib_strided_ssumors( N, (float *)X, stride ), &v ); assert( status == napi_ok ); return v; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssumpw/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/ssumpw/src/addon.c index 60ee16c25d1c..b53060ca3dd9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssumpw/src/addon.c +++ b/lib/node_modules/@stdlib/blas/ext/base/ssumpw/src/addon.c @@ -39,7 +39,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 ); napi_value v; - napi_status status = napi_create_double( env, (double)stdlib_strided_ssumpw( N, X, stride ), &v ); + napi_status status = napi_create_double( env, (double)stdlib_strided_ssumpw( N, (float *)X, stride ), &v ); assert( status == napi_ok ); return v; diff --git a/lib/node_modules/@stdlib/buffer/alloc-unsafe/README.md b/lib/node_modules/@stdlib/buffer/alloc-unsafe/README.md index fd58aa5b5a1c..1ac2484196b2 100644 --- a/lib/node_modules/@stdlib/buffer/alloc-unsafe/README.md +++ b/lib/node_modules/@stdlib/buffer/alloc-unsafe/README.md @@ -18,7 +18,7 @@ limitations under the License. --> -# allocUnsafe +# alloc > Allocate a [buffer][@stdlib/buffer/ctor] having a specified number of bytes. diff --git a/lib/node_modules/@stdlib/constants/float32/half-pi/include/stdlib/constants/float32/half_pi.h b/lib/node_modules/@stdlib/constants/float32/half-pi/include/stdlib/constants/float32/half_pi.h deleted file mode 100644 index 8b7089769cee..000000000000 --- a/lib/node_modules/@stdlib/constants/float32/half-pi/include/stdlib/constants/float32/half_pi.h +++ /dev/null @@ -1,27 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#ifndef STDLIB_CONSTANTS_FLOAT32_HALF_PI_H -#define STDLIB_CONSTANTS_FLOAT32_HALF_PI_H - -/** -* Macro for one half times the mathematical constant π. -*/ -#define STDLIB_CONSTANT_FLOAT32_HALF_PI 1.5707963267948966f - -#endif // !STDLIB_CONSTANTS_FLOAT32_HALF_PI_H diff --git a/lib/node_modules/@stdlib/math/base/assert/is-composite/package.json b/lib/node_modules/@stdlib/math/base/assert/is-composite/package.json index 85d452b4aca1..eda5f90d078d 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-composite/package.json +++ b/lib/node_modules/@stdlib/math/base/assert/is-composite/package.json @@ -14,14 +14,11 @@ } ], "main": "./lib", - "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", - "include": "./include", "lib": "./lib", - "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/math/base/special/acscd/README.md b/lib/node_modules/@stdlib/math/base/special/acscd/README.md index 050bc5f3e842..2a8d438970ce 100644 --- a/lib/node_modules/@stdlib/math/base/special/acscd/README.md +++ b/lib/node_modules/@stdlib/math/base/special/acscd/README.md @@ -81,94 +81,6 @@ for ( i = 0; i < x.length; i++ ) { - - -* * * - -
- -## C APIs - - - -
- -
- - - - - -
- -### Usage - -```c -#include "stdlib/math/base/special/acscd.h" -``` - -#### stdlib_base_acscd( x ) - -Computes the [arccosecant][arccosecant] (in degrees) of a double-precision floating-point number. - -```c -double out = stdlib_base_acscd( 1.0 ); -// returns 90.0 - -out = stdlib_base_acscd( 2.0 ); -// returns ~30.0 -``` - -The function accepts the following arguments: - -- **x**: `[in] double` input value. - -```c -double stdlib_base_acscd( const double x ); -``` - -
- - - - - -
- -
- - - - - -
- -### Examples - -```c -#include "stdlib/math/base/special/acscd.h" -#include - -int main( void ) { - const double x[] = { 1.0, 1.45, 1.89, 2.33, 2.78, 3.22, 3.66, 4.11, 4.55, 5.0 }; - - double v; - int i; - for ( i = 0; i < 10; i++ ) { - v = stdlib_base_acscd( x[ i ] ); - printf( "acscd(%lf) = %lf\n", x[ i ], v ); - } -} -``` - -
- - - -
- - -
diff --git a/lib/node_modules/@stdlib/math/base/special/acscd/lib/native.js b/lib/node_modules/@stdlib/math/base/special/acscd/lib/native.js deleted file mode 100644 index b3fdfa75ecc2..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/acscd/lib/native.js +++ /dev/null @@ -1,65 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var addon = require( './../src/addon.node' ); - - -// MAIN // - -/** -* Computes the arccosecant (in degrees) of a double-precision floating-point number. -* -* @param {number} x - input value -* @returns {number} arccosecant (in degrees) -* -* @example -* var v = acscd( Infinity ); -* // returns 0.0 -* -* @example -* var v = acscd( 2 * Math.sqrt( 3 ) / 3 ); -* // returns ~60.0 -* -* @example -* var v = acscd( Math.sqrt( 2 ) ); -* // returns ~45.0 -* -* @example -* var v = acscd( 2 ); -* // returns ~30.0 -* -* @example -* var v = acscd( 1 ); -* // returns 90.0 -* -* @example -* var v = acscd( NaN ); -* // returns NaN -*/ -function acscd( x ) { - return addon( x ); -} - - -// EXPORTS // - -module.exports = acscd; diff --git a/lib/node_modules/@stdlib/math/base/special/acscd/package.json b/lib/node_modules/@stdlib/math/base/special/acscd/package.json index 3357c0c2344d..36aad8b405bd 100644 --- a/lib/node_modules/@stdlib/math/base/special/acscd/package.json +++ b/lib/node_modules/@stdlib/math/base/special/acscd/package.json @@ -14,14 +14,11 @@ } ], "main": "./lib", - "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", - "include": "./include", "lib": "./lib", - "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/math/base/special/acscd/src/main.c b/lib/node_modules/@stdlib/math/base/special/acscd/src/main.c deleted file mode 100644 index 7a7e326d65d1..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/acscd/src/main.c +++ /dev/null @@ -1,38 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/math/base/special/acscd.h" -#include "stdlib/math/base/special/acsc.h" -#include "stdlib/math/base/special/rad2deg.h" - -/** -* Computes the arccosecant (in degrees) of a double-precision floating-point number. -* -* @param x input value -* @returns arccosecant (in degrees) -* -* @example -* double v = stdlib_base_acscd( 1.0 ); -* // returns 90.0 -*/ -double stdlib_base_acscd( const double x ) { - double rad; - - rad = stdlib_base_acsc( x ); - return stdlib_base_rad2deg( rad ); -} diff --git a/lib/node_modules/@stdlib/math/base/special/acscd/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/acscd/test/test.native.js deleted file mode 100644 index 4837057ca88f..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/acscd/test/test.native.js +++ /dev/null @@ -1,128 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var resolve = require( 'path' ).resolve; -var tape = require( 'tape' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var abs = require( '@stdlib/math/base/special/abs' ); -var randu = require( '@stdlib/random/base/randu' ); -var EPS = require( '@stdlib/constants/float64/eps' ); -var tryRequire = require( '@stdlib/utils/try-require' ); - - -// VARIABLES // - -var acscd = tryRequire( resolve( __dirname, './../lib/native.js' ) ); -var opts = { - 'skip': ( acscd instanceof Error ) -}; - - -// FIXTURES // - -var negative = require( './fixtures/julia/negative.json' ); -var positive = require( './fixtures/julia/positive.json' ); - - -// TESTS // - -tape( 'main export is a function', opts, function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof acscd, 'function', 'main export is a function' ); - t.end(); -}); - -tape( 'the function computes the arccosecant in degrees (negative values)', opts, function test( t ) { - var expected; - var delta; - var tol; - var x; - var y; - var i; - - x = negative.x; - expected = negative.expected; - - for ( i = 0; i < x.length; i++ ) { - y = acscd( x[i] ); - if ( y === expected[ i ] ) { - t.equal( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } - } - t.end(); -}); - -tape( 'the function computes the arccosecant in degrees (positive values)', opts, function test( t ) { - var expected; - var delta; - var tol; - var x; - var y; - var i; - - x = positive.x; - expected = positive.expected; - - for ( i = 0; i < x.length; i++ ) { - y = acscd( x[i] ); - if ( y === expected[ i ] ) { - t.equal( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } - } - t.end(); -}); - -tape( 'the function returns `NaN` if provided `NaN`', opts, function test( t ) { - var v = acscd( NaN ); - t.equal( isnan( v ), true, 'returns NaN' ); - t.end(); -}); - -tape( 'the function returns `NaN` if provided a value greater than `-1`', opts, function test( t ) { - var v; - var i; - - for ( i = 0; i < 1e3; i++ ) { - v = -randu() - EPS; - t.equal( isnan( acscd( v ) ), true, 'returns NaN when provided '+v ); - } - t.end(); -}); - -tape( 'the function returns `NaN` if provided a value less than `+1`', opts, function test( t ) { - var v; - var i; - - for ( i = 0; i < 1e3; i++ ) { - v = (randu()) + EPS; - t.equal( isnan( acscd( v ) ), true, 'returns NaN when provided '+v ); - } - t.end(); -}); diff --git a/lib/node_modules/@stdlib/math/base/special/asinf/LICENSE b/lib/node_modules/@stdlib/math/base/special/asinf/LICENSE new file mode 100644 index 000000000000..a5bc4d9bf3fd --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/asinf/LICENSE @@ -0,0 +1,195 @@ + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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In no event and under no legal theory, + whether in tort (including negligence), contract, or otherwise, + unless required by applicable law (such as deliberate and grossly + negligent acts) or agreed to in writing, shall any Contributor be + liable to You for damages, including any direct, indirect, special, + incidental, or consequential damages of any character arising as a + result of this License or out of the use or inability to use the + Work (including but not limited to damages for loss of goodwill, + work stoppage, computer failure or malfunction, or any and all + other commercial damages or losses), even if such Contributor + has been advised of the possibility of such damages. + + 9. Accepting Warranty or Additional Liability. While redistributing + the Work or Derivative Works thereof, You may choose to offer, + and charge a fee for, acceptance of support, warranty, indemnity, + or other liability obligations and/or rights consistent with this + License. However, in accepting such obligations, You may act only + on Your own behalf and on Your sole responsibility, not on behalf + of any other Contributor, and only if You agree to indemnify, + defend, and hold each Contributor harmless for any liability + incurred by, or claims asserted against, such Contributor by reason + of your accepting any such warranty or additional liability. + + END OF TERMS AND CONDITIONS + +DEPENDENCIES & ATTRIBUTION + +The library links against the following external libraries or contains +implementations from the following external libraries, which have their own +licenses: + +* Cephes + +Copyright (c) 1984-2000 Stephen L. Moshier + +Some software in this archive may be from the book _Methods and Programs for +Mathematical Functions_ (Prentice-Hall or Simon & Schuster International, 1989) +or from the Cephes Mathematical Library, a commercial product. In either event, +it is copyrighted by the author. What you see here may be used freely but it +comes with no support or guarantee. + +Stephen L. Moshier +moshier@na-net.ornl.gov diff --git a/lib/node_modules/@stdlib/math/base/special/asinf/README.md b/lib/node_modules/@stdlib/math/base/special/asinf/README.md new file mode 100644 index 000000000000..60ad620152f2 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/asinf/README.md @@ -0,0 +1,175 @@ + + +# asinf + +> Compute the [arcsine][arcsine] of a single-precision floating-point number. + +
+ +## Usage + +```javascript +var asinf = require( '@stdlib/math/base/special/asinf' ); +``` + +#### asinf( x ) + +Computes the [arcsine][arcsine] of a single-precision floating-point number (in radians). + +```javascript +var v = asinf( 0.0 ); +// returns 0.0 + +v = asinf( -3.14/6.0 ); +// returns ~-0.551 +``` + +
+ + + +
+ +## Examples + + + +```javascript +var linspace = require( '@stdlib/array/base/linspace' ); +var asinf = require( '@stdlib/math/base/special/asinf' ); + +var x = linspace( -1.0, 1.0, 100 ); + +var i; +for ( i = 0; i < x.length; i++ ) { + console.log( asinf( x[ i ] ) ); +} +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/math/base/special/asinf.h" +``` + +#### stdlib_base_asinf( x ) + +Computes the [arcsine][arcsine] of a single-precision floating-point number (in radians). + +```c +float out = stdlib_base_asinf( 0.0f ); +// returns 0.0f + +out = stdlib_base_asinf( -3.14f/6.0f ); +// returns ~-0.551f +``` + +The function accepts the following arguments: + +- **x**: `[in] float` input value (in radians). + +```c +float stdlib_base_asinf( const float x ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/math/base/special/asinf.h" +#include + +int main( void ) { + const float x[] = { -1.0f, -0.78f, -0.56f, -0.33f, -0.11f, 0.11f, 0.33f, 0.56f, 0.78f, 1.0f }; + + float v; + int i; + for ( i = 0; i < 10; i++ ) { + v = stdlib_base_asinf( x[ i ] ); + printf( "asin(%f) = %f\n", x[ i ], v ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[arcsine]: https://en.wikipedia.org/wiki/Inverse_trigonometric_functions + +
+ + diff --git a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/base/special/asinf/benchmark/benchmark.js similarity index 68% rename from lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum/benchmark/benchmark.native.js rename to lib/node_modules/@stdlib/math/base/special/asinf/benchmark/benchmark.js index 280fe31407f2..9ac5217a683a 100644 --- a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/base/special/asinf/benchmark/benchmark.js @@ -20,39 +20,30 @@ // MODULES // -var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var tryRequire = require( '@stdlib/utils/try-require' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pkg = require( './../package.json' ).name; - - -// VARIABLES // - -var gammaLanczosSum = tryRequire( resolve( __dirname, './../lib/native.js' ) ); -var opts = { - 'skip': ( gammaLanczosSum instanceof Error ) -}; +var asinf = require( './../lib' ); // MAIN // -bench( pkg+'::native', opts, function benchmark( b ) { +bench( pkg, function benchmark( b ) { var x; var y; var i; b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu() * 100.0 ) - 50.0; - y = gammaLanczosSum( x ); - if ( isnan( y ) ) { + x = ( randu() * 2.0 ) - 1.0; + y = asinf( x ); + if ( isnanf( y ) ) { b.fail( 'should not return NaN' ); } } b.toc(); - if ( isnan( y ) ) { + if ( isnanf( y ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/math/base/special/acscd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/base/special/asinf/benchmark/benchmark.native.js similarity index 82% rename from lib/node_modules/@stdlib/math/base/special/acscd/benchmark/benchmark.native.js rename to lib/node_modules/@stdlib/math/base/special/asinf/benchmark/benchmark.native.js index dfa1a3acb7ac..8d48947490d0 100644 --- a/lib/node_modules/@stdlib/math/base/special/acscd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/base/special/asinf/benchmark/benchmark.native.js @@ -23,16 +23,16 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; // VARIABLES // -var acscd = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var asinf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); var opts = { - 'skip': ( acscd instanceof Error ) + 'skip': ( asinf instanceof Error ) }; @@ -45,14 +45,14 @@ bench( pkg+'::native', opts, function benchmark( b ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu() * 2.0 ) + 1.0; - y = acscd( x ); - if ( isnan( y ) ) { + x = ( randu() * 2.0 ) - 1.0; + y = asinf( x ); + if ( isnanf( y ) ) { b.fail( 'should not return NaN' ); } } b.toc(); - if ( isnan( y ) ) { + if ( isnanf( y ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/math/base/special/acscd/benchmark/c/native/Makefile b/lib/node_modules/@stdlib/math/base/special/asinf/benchmark/c/native/Makefile similarity index 100% rename from lib/node_modules/@stdlib/math/base/special/acscd/benchmark/c/native/Makefile rename to lib/node_modules/@stdlib/math/base/special/asinf/benchmark/c/native/Makefile diff --git a/lib/node_modules/@stdlib/math/base/special/acscd/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/math/base/special/asinf/benchmark/c/native/benchmark.c similarity index 91% rename from lib/node_modules/@stdlib/math/base/special/acscd/benchmark/c/native/benchmark.c rename to lib/node_modules/@stdlib/math/base/special/asinf/benchmark/c/native/benchmark.c index d9db1b25c953..44fbb4e1dc04 100644 --- a/lib/node_modules/@stdlib/math/base/special/acscd/benchmark/c/native/benchmark.c +++ b/lib/node_modules/@stdlib/math/base/special/asinf/benchmark/c/native/benchmark.c @@ -17,16 +17,16 @@ */ /** -* Benchmark `acscd`. +* Benchmark `asinf`. */ -#include "stdlib/math/base/special/acscd.h" +#include "stdlib/math/base/special/asinf.h" #include #include #include #include #include -#define NAME "acscd" +#define NAME "asinf" #define ITERATIONS 1000000 #define REPEATS 3 @@ -82,9 +82,9 @@ double tic() { * * @return random number */ -double rand_double() { +float rand_float() { int r = rand(); - return (double)r / ( (double)RAND_MAX + 1.0 ); + return (float)r / ( (float)RAND_MAX + 1.0f ); } /** @@ -94,15 +94,15 @@ double rand_double() { */ double benchmark() { double elapsed; - double x; - double y; double t; + float x; + float y; int i; t = tic(); for ( i = 0; i < ITERATIONS; i++ ) { - x = ( 2.0 * rand_double() ) + 1.0; - y = stdlib_base_acscd( x ); + x = ( 2.0f * rand_float() ) - 1.0f; + y = stdlib_base_asinf( x ); if ( y != y ) { printf( "should not return NaN\n" ); break; diff --git a/lib/node_modules/@stdlib/math/base/special/acscd/binding.gyp b/lib/node_modules/@stdlib/math/base/special/asinf/binding.gyp similarity index 100% rename from lib/node_modules/@stdlib/math/base/special/acscd/binding.gyp rename to lib/node_modules/@stdlib/math/base/special/asinf/binding.gyp diff --git a/lib/node_modules/@stdlib/math/base/special/asinf/docs/repl.txt b/lib/node_modules/@stdlib/math/base/special/asinf/docs/repl.txt new file mode 100644 index 000000000000..581c0e41ea72 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/asinf/docs/repl.txt @@ -0,0 +1,26 @@ + +{{alias}}( x ) + Computes the arcsine of a single-precision floating-point number. + + Parameters + ---------- + x: number + Input value. + + Returns + ------- + y: number + Arcsine (in radians). + + Examples + -------- + > var y = {{alias}}( 0.0 ) + 0.0 + > y = {{alias}}( -3.14/6.0 ) + ~-0.551 + > y = {{alias}}( NaN ) + NaN + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/lib/native.js b/lib/node_modules/@stdlib/math/base/special/asinf/docs/types/index.d.ts similarity index 59% rename from lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/lib/native.js rename to lib/node_modules/@stdlib/math/base/special/asinf/docs/types/index.d.ts index e21307d16ebd..24e8aefee272 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/lib/native.js +++ b/lib/node_modules/@stdlib/math/base/special/asinf/docs/types/index.d.ts @@ -1,4 +1,4 @@ -/** +/* * @license Apache-2.0 * * Copyright (c) 2024 The Stdlib Authors. @@ -16,32 +16,33 @@ * limitations under the License. */ -'use strict'; - -// MODULES // - -var addon = require( './../src/addon.node' ); - - -// MAIN // +// TypeScript Version: 4.1 /** -* Computes the hypotenuse using the alpha max plus beta min algorithm. +* Computes the arcsine of a single-precision floating-point number. +* +* @param x - input value +* @returns arcsine (in radians) * -* @private -* @param {number} x - number -* @param {number} y - number -* @returns {number} hypotenuse +* @example +* var v = asinf( 0.0 ); +* // returns ~0.0 +* +* @example +* var v = asinf( 3.14/4.0 ); +* // returns ~0.903 +* +* @example +* var v = asinf( -3.14/6.0 ); +* // returns ~-0.551 * * @example -* var h = ampbm( -5.0, 12.0 ); -* // returns ~13.5 +* var v = asinf( NaN ); +* // returns NaN */ -function ampbm( x, y ) { - return addon( x, y ); -} +declare function asinf( x: number ): number; // EXPORTS // -module.exports = ampbm; +export = asinf; diff --git a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/include/stdlib/math/base/special/nonfibonacci.h b/lib/node_modules/@stdlib/math/base/special/asinf/docs/types/test.ts similarity index 50% rename from lib/node_modules/@stdlib/math/base/special/nonfibonacci/include/stdlib/math/base/special/nonfibonacci.h rename to lib/node_modules/@stdlib/math/base/special/asinf/docs/types/test.ts index 2434bab878cd..a36aba524bea 100644 --- a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/include/stdlib/math/base/special/nonfibonacci.h +++ b/lib/node_modules/@stdlib/math/base/special/asinf/docs/types/test.ts @@ -1,4 +1,4 @@ -/** +/* * @license Apache-2.0 * * Copyright (c) 2024 The Stdlib Authors. @@ -16,26 +16,29 @@ * limitations under the License. */ -#ifndef STDLIB_MATH_BASE_SPECIAL_NONFIBONACCI_H -#define STDLIB_MATH_BASE_SPECIAL_NONFIBONACCI_H +import asinf = require( './index' ); -#include -/* -* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. -*/ -#ifdef __cplusplus -extern "C" -{ -#endif +// TESTS // -/** -* Computes the nth non-Fibonacci number. -*/ -double stdlib_base_nonfibonacci( const int32_t x ); +// The function returns a number... +{ + asinf( 8 ); // $ExpectType number +} -#ifdef __cplusplus +// The compiler throws an error if the function is provided a value other than a number... +{ + asinf( true ); // $ExpectError + asinf( false ); // $ExpectError + asinf( null ); // $ExpectError + asinf( undefined ); // $ExpectError + asinf( '5' ); // $ExpectError + asinf( [] ); // $ExpectError + asinf( {} ); // $ExpectError + asinf( ( x: number ): number => x ); // $ExpectError } -#endif -#endif // !STDLIB_MATH_BASE_SPECIAL_NONFIBONACCI_H +// The compiler throws an error if the function is provided insufficient arguments... +{ + asinf(); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/math/base/special/acscd/examples/c/Makefile b/lib/node_modules/@stdlib/math/base/special/asinf/examples/c/Makefile similarity index 100% rename from lib/node_modules/@stdlib/math/base/special/acscd/examples/c/Makefile rename to lib/node_modules/@stdlib/math/base/special/asinf/examples/c/Makefile diff --git a/lib/node_modules/@stdlib/math/base/special/acscd/examples/c/example.c b/lib/node_modules/@stdlib/math/base/special/asinf/examples/c/example.c similarity index 75% rename from lib/node_modules/@stdlib/math/base/special/acscd/examples/c/example.c rename to lib/node_modules/@stdlib/math/base/special/asinf/examples/c/example.c index 6456811b7cf0..f0bc9d53803d 100644 --- a/lib/node_modules/@stdlib/math/base/special/acscd/examples/c/example.c +++ b/lib/node_modules/@stdlib/math/base/special/asinf/examples/c/example.c @@ -16,16 +16,16 @@ * limitations under the License. */ -#include "stdlib/math/base/special/acscd.h" +#include "stdlib/math/base/special/asinf.h" #include int main( void ) { - const double x[] = { 0.0, 1.45, 1.89, 2.33, 2.78, 3.22, 3.66, 4.11, 4.55, 5.0 }; + const float x[] = { -1.0f, -0.78f, -0.56f, -0.33f, -0.11f, 0.11f, 0.33f, 0.56f, 0.78f, 1.0f }; - double v; + float v; int i; for ( i = 0; i < 10; i++ ) { - v = stdlib_base_acscd( x[ i ] ); - printf( "acscd(%lf) = %lf\n", x[ i ], v ); + v = stdlib_base_asinf( x[ i ] ); + printf( "asin(%f) = %f\n", x[ i ], v ); } } diff --git a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/examples/c/example.c b/lib/node_modules/@stdlib/math/base/special/asinf/examples/index.js similarity index 71% rename from lib/node_modules/@stdlib/math/base/special/nonfibonacci/examples/c/example.c rename to lib/node_modules/@stdlib/math/base/special/asinf/examples/index.js index 3bea3f3d3058..c63e9b21379d 100644 --- a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/examples/c/example.c +++ b/lib/node_modules/@stdlib/math/base/special/asinf/examples/index.js @@ -16,13 +16,14 @@ * limitations under the License. */ -#include "stdlib/math/base/special/nonfibonacci.h" -#include +'use strict'; -int main( void ) { - int i; - for ( i = 1; i < 12; i++ ) { - double result = stdlib_base_nonfibonacci( i ); - printf( "x: %i => result: %lf", i , result ); - } +var linspace = require( '@stdlib/array/base/linspace' ); +var asinf = require( './../lib' ); + +var x = linspace( -1.0, 1.0, 100 ); + +var i; +for ( i = 0; i < x.length; i++ ) { + console.log( 'asinf(%d) = %d', x[ i ], asinf( x[ i ] ) ); } diff --git a/lib/node_modules/@stdlib/math/base/special/acscd/include.gypi b/lib/node_modules/@stdlib/math/base/special/asinf/include.gypi similarity index 100% rename from lib/node_modules/@stdlib/math/base/special/acscd/include.gypi rename to lib/node_modules/@stdlib/math/base/special/asinf/include.gypi diff --git a/lib/node_modules/@stdlib/math/base/special/acscd/include/stdlib/math/base/special/acscd.h b/lib/node_modules/@stdlib/math/base/special/asinf/include/stdlib/math/base/special/asinf.h similarity index 76% rename from lib/node_modules/@stdlib/math/base/special/acscd/include/stdlib/math/base/special/acscd.h rename to lib/node_modules/@stdlib/math/base/special/asinf/include/stdlib/math/base/special/asinf.h index bb72c27311ea..61ce9c97453c 100644 --- a/lib/node_modules/@stdlib/math/base/special/acscd/include/stdlib/math/base/special/acscd.h +++ b/lib/node_modules/@stdlib/math/base/special/asinf/include/stdlib/math/base/special/asinf.h @@ -16,8 +16,8 @@ * limitations under the License. */ -#ifndef STDLIB_MATH_BASE_SPECIAL_ACSCD_H -#define STDLIB_MATH_BASE_SPECIAL_ACSCD_H +#ifndef STDLIB_MATH_BASE_SPECIAL_ASINF_H +#define STDLIB_MATH_BASE_SPECIAL_ASINF_H /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -27,12 +27,12 @@ extern "C" { #endif /** -* Computes the arccosecant (in degrees) of a double-precision floating-point number. +* Computes the arcsine of a single-precision floating-point number. */ -double stdlib_base_acscd( const double x ); +float stdlib_base_asinf( const float x ); #ifdef __cplusplus } #endif -#endif // !STDLIB_MATH_BASE_SPECIAL_ACSCD_H +#endif // !STDLIB_MATH_BASE_SPECIAL_ASINF_H diff --git a/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/lib/index.js b/lib/node_modules/@stdlib/math/base/special/asinf/lib/index.js similarity index 66% rename from lib/node_modules/@stdlib/string/base/last-grapheme-cluster/lib/index.js rename to lib/node_modules/@stdlib/math/base/special/asinf/lib/index.js index 9db71366e0e1..26037059a756 100644 --- a/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/lib/index.js +++ b/lib/node_modules/@stdlib/math/base/special/asinf/lib/index.js @@ -19,21 +19,24 @@ 'use strict'; /** -* Return the last `n` grapheme clusters (i.e., user-perceived characters) of a string. +* Compute the arcsine of a single-precision floating-point number. * -* @module @stdlib/string/base/last-grapheme-cluster +* @module @stdlib/math/base/special/asinf * * @example -* var last = require( '@stdlib/string/base/last-grapheme-cluster' ); +* var asinf = require( '@stdlib/math/base/special/asinf' ); * -* var out = last( 'Hello', 1 ); -* // returns 'o'; +* var v = asinf( 0.0 ); +* // returns 0.0 * -* out = last( 'JavaScript', 1 ); -* // returns 'Script'; +* v = asinf( 3.14/4.0 ); +* // returns ~0.903 * -* out = last( '🐮🐷🐸🐵', 2 ); -* // returns '🐸🐵'; +* v = asinf( -3.14/6.0 ); +* // returns ~-0.551 +* +* v = asinf( NaN ); +* // returns NaN */ // MODULES // diff --git a/lib/node_modules/@stdlib/math/base/special/asinf/lib/main.js b/lib/node_modules/@stdlib/math/base/special/asinf/lib/main.js new file mode 100644 index 000000000000..08cf40e4a0fa --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/asinf/lib/main.js @@ -0,0 +1,144 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2024 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +* +* +* ## Notice +* +* The original C code, long comment, copyright, license, and constants are from [Cephes]{@link http://www.netlib.org/cephes}. The implementation follows the original, but has been modified for JavaScript. +* +* ```text +* Copyright 1984, 1995, 2000 by Stephen L. Moshier +* +* Some software in this archive may be from the book _Methods and Programs for Mathematical Functions_ (Prentice-Hall or Simon & Schuster International, 1989) or from the Cephes Mathematical Library, a commercial product. In either event, it is copyrighted by the author. What you see here may be used freely but it comes with no support or guarantee. +* +* Stephen L. Moshier +* moshier@na-net.ornl.gov +* ``` +*/ + +'use strict'; + +// MODULES // + +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var sqrtf = require( '@stdlib/math/base/special/sqrtf' ); +var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); +var PI02F = require( '@stdlib/constants/float32/half-pi' ); +var polyp = require( './poly_p.js' ); + + +// MAIN // + +/** +* Computes the arcsine of a single-precision floating-point number. +* +* ## Method +* +* - A rational function of the form +* +* ```tex +* x + x^3 \frac{P(x^2)}{Q(x^2)} +* ``` +* +* is used for \\(\|x\|\\) in the interval \\(\[0, 0.5\]\\). If \\(\|x\| > 0.5\\), it is transformed by the identity +* +* ```tex +* \operatorname{asinf}(x) = \frac{\pi}{2} - 2 \operatorname{asinf}( \sqrt{ (1-x)/2 } ) +* ``` +* +* ## Notes +* +* - Relative error: +* +* | arithmetic | domain | # trials | peak | rms | +* |:-----------|:-------|:---------|:--------|:--------| +* | IEEE | -1, 1 | 10^5 | 1.4e-7 | 4.2e-8 | +* +* @param {number} x - input value +* @returns {number} arcsine (in radians) +* +* @example +* var v = asinf( 0.0 ); +* // returns ~0.0 +* +* @example +* var v = asinf( 3.14/4.0 ); +* // returns ~0.903 +* +* @example +* var v = asinf( -3.14/6.0 ); +* // returns ~-0.551 +* +* @example +* var v = asinf( NaN ); +* // returns NaN +*/ +function asinf( x ) { + var flag; + var sgn; + var a; + var z; + + if ( isnanf( x ) ) { + return NaN; + } + x = float64ToFloat32( x ); + if ( x > 0.0 ) { + sgn = 1; + a = x; + } + else { + sgn = -1; + a = -x; + } + if ( a > 1.0 ) { + return 0.0; + } + if ( a < 1.0e-4 ) { + z = float64ToFloat32( a ); + if ( sgn < 0 ) { + z = -z; + } + return z; + } + if ( a > 0.5 ) { + z = float64ToFloat32( 0.5 * float64ToFloat32( 1.0 - a ) ); + x = sqrtf( z ); + flag = 1; + } + else { + x = float64ToFloat32( a ); + z = float64ToFloat32( x * x ); + flag = 0; + } + // eslint-disable-next-line max-len + z = float64ToFloat32( float64ToFloat32( ( float64ToFloat32( polyp( z ) ) * float64ToFloat32( z * x ) ) ) + ( x ) ); + + if ( flag !== 0 ) { + z += z; + z = float64ToFloat32( PI02F - z ); + } + if ( sgn < 0 ) { + z = -z; + } + return z; +} + + +// EXPORTS // + +module.exports = asinf; diff --git a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/lib/native.js b/lib/node_modules/@stdlib/math/base/special/asinf/lib/native.js similarity index 67% rename from lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/lib/native.js rename to lib/node_modules/@stdlib/math/base/special/asinf/lib/native.js index 8a39704f6ab9..57ac21b143ea 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/lib/native.js +++ b/lib/node_modules/@stdlib/math/base/special/asinf/lib/native.js @@ -26,29 +26,33 @@ var addon = require( './../src/addon.node' ); // MAIN // /** -* Computes an integer binary logarithm (base two). +* Computes the arcsine of a single-precision floating-point number. * * @private -* @param {uinteger32} x - input value -* @returns {uinteger32} integer binary logarithm +* @param {number} x - input value +* @returns {number} arcsine (in radians) * * @example -* var out = log2Uint32( 4 ); -* // returns 2 +* var v = asinf( 0.0 ); +* // returns ~0.0 * * @example -* var out = log2Uint32( 8 ); -* // returns 3 +* var v = asinf( 3.14/4.0 ); +* // returns ~0.903 * * @example -* var out = log2Uint32( 9 ); -* // returns 3 +* var v = asinf( -3.14/6.0 ); +* // returns ~-0.551 +* +* @example +* var v = asinf( NaN ); +* // returns NaN */ -function log2Uint32( x ) { +function asinf( x ) { return addon( x ); } // EXPORTS // -module.exports = log2Uint32; +module.exports = asinf; diff --git a/lib/node_modules/@stdlib/math/base/special/asinf/lib/poly_p.js b/lib/node_modules/@stdlib/math/base/special/asinf/lib/poly_p.js new file mode 100644 index 000000000000..852b6a7134a7 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/asinf/lib/poly_p.js @@ -0,0 +1,52 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2024 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* This is a generated file. Do not edit directly. */ +'use strict'; + +// MODULES // + +var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); + + +// MAIN // + +/** +* Evaluates a polynomial. +* +* ## Notes +* +* - The implementation uses [Horner's rule][horners-method] for efficient computation. +* +* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method +* +* @private +* @param {number} x - value at which to evaluate the polynomial +* @returns {number} evaluated polynomial +*/ +function evalpoly( x ) { + if ( x === 0.0 ) { + return 0.16666752099990845; + } + return float64ToFloat32(0.16666752099990845 + float64ToFloat32(x * float64ToFloat32(0.07495300471782684 + float64ToFloat32(x * float64ToFloat32(0.04547002539038658 + float64ToFloat32(x * float64ToFloat32(0.024181311950087547 + float64ToFloat32(x * 0.04216320067644119)))))))); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = evalpoly; diff --git a/lib/node_modules/@stdlib/math/base/special/acscd/manifest.json b/lib/node_modules/@stdlib/math/base/special/asinf/manifest.json similarity index 73% rename from lib/node_modules/@stdlib/math/base/special/acscd/manifest.json rename to lib/node_modules/@stdlib/math/base/special/asinf/manifest.json index 139a4dc8b5aa..3c8dedd0c2a0 100644 --- a/lib/node_modules/@stdlib/math/base/special/acscd/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/asinf/manifest.json @@ -37,8 +37,9 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/napi/unary", - "@stdlib/math/base/special/rad2deg", - "@stdlib/math/base/special/acsc" + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/special/sqrtf", + "@stdlib/constants/float32/half-pi" ] }, { @@ -52,8 +53,9 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/special/rad2deg", - "@stdlib/math/base/special/acsc" + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/special/sqrtf", + "@stdlib/constants/float32/half-pi" ] }, { @@ -67,8 +69,9 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/special/rad2deg", - "@stdlib/math/base/special/acsc" + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/special/sqrtf", + "@stdlib/constants/float32/half-pi" ] } ] diff --git a/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/package.json b/lib/node_modules/@stdlib/math/base/special/asinf/package.json similarity index 72% rename from lib/node_modules/@stdlib/string/base/last-grapheme-cluster/package.json rename to lib/node_modules/@stdlib/math/base/special/asinf/package.json index 590dad302bb4..ab653cc347a8 100644 --- a/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/package.json +++ b/lib/node_modules/@stdlib/math/base/special/asinf/package.json @@ -1,7 +1,7 @@ { - "name": "@stdlib/string/base/last-grapheme-cluster", + "name": "@stdlib/math/base/special/asinf", "version": "0.0.0", - "description": "Return the last grapheme cluster (i.e., user-perceived character) of a string.", + "description": "Compute the arcsine of a single-precision floating-point number.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", @@ -14,11 +14,13 @@ } ], "main": "./lib", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", "lib": "./lib", + "scripts": "./scripts", "test": "./test" }, "types": "./docs/types", @@ -50,19 +52,19 @@ ], "keywords": [ "stdlib", - "stdstring", - "utilities", - "utility", - "utils", - "util", - "string", - "str", - "base", - "last", - "character", - "char", - "grapheme", - "cluster", - "unicode" + "stdmath", + "mathematics", + "math", + "math.asin", + "asinf", + "arcsine", + "sine", + "inverse", + "trig", + "trigonometry", + "radians", + "angle", + "polyfill", + "ponyfill" ] } diff --git a/lib/node_modules/@stdlib/math/base/special/asinf/scripts/evalpoly.js b/lib/node_modules/@stdlib/math/base/special/asinf/scripts/evalpoly.js new file mode 100644 index 000000000000..5aa348418876 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/asinf/scripts/evalpoly.js @@ -0,0 +1,128 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2024 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* +* This script compiles modules for evaluating polynomial functions. If any polynomial coefficients change, this script should be rerun to update the compiled files. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var readFileSync = require( '@stdlib/fs/read-file' ).sync; +var writeFileSync = require( '@stdlib/fs/write-file' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var compile = require( '@stdlib/math/base/tools/evalpoly-compile' ); +var compileC = require( '@stdlib/math/base/tools/evalpoly-compile-c' ); +var substringBefore = require( '@stdlib/string/substring-before' ); +var substringAfter = require( '@stdlib/string/substring-after' ); +var format = require( '@stdlib/string/format' ); + + +// VARIABLES // + +// Polynomial coefficients ordered in ascending degree... + +/* +* arcsin(x) = x + x^3 P(x^2)/Q(x^2) +* 0 <= x <= 0.625 +* Peak relative error = 1.2e-18 +*/ +var P = [ + 1.6666752422E-1, + 7.4953002686E-2, + 4.5470025998E-2, + 2.4181311049E-2, + 4.2163199048E-2 +]; + +// Header to add to output files: +var header = licenseHeader( 'Apache-2.0', 'js', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' +}); +header += '\n/* This is a generated file. Do not edit directly. */\n'; + + +// FUNCTIONS // + +/** +* Inserts a compiled function into file content. +* +* @private +* @param {string} text - source content +* @param {string} id - function identifier +* @param {string} str - function string +* @returns {string} updated content +*/ +function insert( text, id, str ) { + var before; + var after; + var begin; + var end; + + begin = '// BEGIN: '+id; + end = '// END: '+id; + + before = substringBefore( text, begin ); + after = substringAfter( text, end ); + + return format( '%s// BEGIN: %s\n\n%s\n%s%s', before, id, str, end, after ); +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var fpath; + var copts; + var opts; + var file; + var str; + + opts = { + 'dtype': 'float32', + 'encoding': 'utf8' + }; + + fpath = resolve( __dirname, '..', 'lib', 'poly_p.js' ); + str = header + compile( P ); + writeFileSync( fpath, str, opts ); + + copts = { + 'dtype': 'float', + 'name': 'poly_p' + }; + + fpath = resolve( __dirname, '..', 'src', 'main.c' ); + file = readFileSync( fpath, opts ); + + str = compileC( P, copts ); + file = insert( file, copts.name, str ); + + writeFileSync( fpath, file, opts ); +} + +main(); diff --git a/lib/node_modules/@stdlib/math/base/special/acscd/src/Makefile b/lib/node_modules/@stdlib/math/base/special/asinf/src/Makefile similarity index 100% rename from lib/node_modules/@stdlib/math/base/special/acscd/src/Makefile rename to lib/node_modules/@stdlib/math/base/special/asinf/src/Makefile diff --git a/lib/node_modules/@stdlib/math/base/special/acscd/src/addon.c b/lib/node_modules/@stdlib/math/base/special/asinf/src/addon.c similarity index 87% rename from lib/node_modules/@stdlib/math/base/special/acscd/src/addon.c rename to lib/node_modules/@stdlib/math/base/special/asinf/src/addon.c index 96575da9c66d..c93b670e488d 100644 --- a/lib/node_modules/@stdlib/math/base/special/acscd/src/addon.c +++ b/lib/node_modules/@stdlib/math/base/special/asinf/src/addon.c @@ -16,8 +16,8 @@ * limitations under the License. */ -#include "stdlib/math/base/special/acscd.h" +#include "stdlib/math/base/special/asinf.h" #include "stdlib/math/base/napi/unary.h" // cppcheck-suppress shadowFunction -STDLIB_MATH_BASE_NAPI_MODULE_D_D( stdlib_base_acscd ) +STDLIB_MATH_BASE_NAPI_MODULE_F_F( stdlib_base_asinf ) diff --git a/lib/node_modules/@stdlib/math/base/special/asinf/src/main.c b/lib/node_modules/@stdlib/math/base/special/asinf/src/main.c new file mode 100644 index 000000000000..7f626d8d6a15 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/asinf/src/main.c @@ -0,0 +1,137 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2022 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +* +* +* ## Notice +* +* The original C code, long comment, copyright, license, and constants are from [Cephes]{@link http://www.netlib.org/cephes}. The implementation follows the original, but has been modified according to project conventions. +* +* ```text +* Copyright 1984, 1995, 2000 by Stephen L. Moshier +* +* Some software in this archive may be from the book _Methods and Programs for Mathematical Functions_ (Prentice-Hall or Simon & Schuster International, 1989) or from the Cephes Mathematical Library, a commercial product. In either event, it is copyrighted by the author. What you see here may be used freely but it comes with no support or guarantee. +* +* Stephen L. Moshier +* moshier@na-net.ornl.gov +* ``` +*/ + +#include "stdlib/math/base/special/asinf.h" +#include "stdlib/math/base/assert/is_nanf.h" +#include "stdlib/math/base/special/sqrtf.h" +#include "stdlib/constants/float32/half_pi.h" +#include + +/* Begin auto-generated functions. The following functions are auto-generated. Do not edit directly. */ + +// BEGIN: poly_p + +/** +* Evaluates a polynomial. +* +* ## Notes +* +* - The implementation uses [Horner's rule][horners-method] for efficient computation. +* +* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method +* +* @param x value at which to evaluate the polynomial +* @return evaluated polynomial +*/ +static float poly_p( const float x ) { + return 0.16666752422 + (x * (0.074953002686f + (x * (0.045470025998f + (x * (0.024181311049f + (x * 0.042163199048f))))))); +} + +// END: poly_p + +/* End auto-generated functions. */ + +/** +* Computes the arcsine of a single-precision floating-point number. +* +* ## Method +* +* - A rational function of the form +* +* ```tex +* x + x^3 \frac{P(x^2)}{Q(x^2)} +* ``` +* +* is used for \\(\|x\|\\) in the interval \\(\[0, 0.5\]\\). If \\(\|x\| > 0.5\\), it is transformed by the identity +* +* ```tex +* \operatorname{asinf}(x) = \frac{\pi}{2} - 2 \operatorname{asinf}( \sqrt{ (1-x)/2 } ) +* ``` +* +* ## Notes +* +* - Relative error: +* +* | arithmetic | domain | # trials | peak | rms | +* |:-----------|:-------|:---------|:--------|:--------| +* | IEEE | -1, 1 | 10^5 | 1.4e-7 | 4.2e-8 | +* +* @param x input value +* @returns arcsine (in radians) +* +* @example +* float out = stdlib_base_asinf( 0.0 ); +* // returns ~0.0 +*/ +float stdlib_base_asinf( const float x ) { + int32_t flag; + int32_t sgn; + float xx; + float a; + float z; + + xx = x; + if ( stdlib_base_is_nanf( x ) ) { + return 0.0 / 0.0; // NaN + } + if ( xx > 0.0 ) { + sgn = 1; + a = xx; + } + else { + sgn = 0; + a = -xx; + } + if ( a > 1.0 ) { + return 0.0; + } + if ( a < 1.0e-4 ) { + z = a; + return ( sgn == 1 ) ? z : -z; + } + if ( a > 0.5 ) { + z = 0.5 * ( 1.0 - a ); + xx = stdlib_base_sqrtf( z ); + flag = 1; + } + else { + xx = a; + z = xx * xx; + flag = 0; + } + z = ( poly_p( z ) * z * xx ) + xx; + if ( flag != 0 ) { + z += z; + z = STDLIB_CONSTANT_FLOAT32_HALF_PI - z; + } + return ( sgn == 1 ) ? z : -z; +} diff --git a/lib/node_modules/@stdlib/math/base/special/asinf/test/fixtures/julia/REQUIRE b/lib/node_modules/@stdlib/math/base/special/asinf/test/fixtures/julia/REQUIRE new file mode 100644 index 000000000000..308c3be89c85 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/asinf/test/fixtures/julia/REQUIRE @@ -0,0 +1,2 @@ +julia 1.5 +JSON 0.21 diff --git a/lib/node_modules/@stdlib/math/base/special/asinf/test/fixtures/julia/data.json b/lib/node_modules/@stdlib/math/base/special/asinf/test/fixtures/julia/data.json new file mode 100644 index 000000000000..c7334fd10f7c --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/asinf/test/fixtures/julia/data.json @@ -0,0 +1 @@ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/asinf/test/fixtures/julia/runner.jl b/lib/node_modules/@stdlib/math/base/special/asinf/test/fixtures/julia/runner.jl new file mode 100644 index 000000000000..094bafe2fa7c --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/asinf/test/fixtures/julia/runner.jl @@ -0,0 +1,73 @@ +#!/usr/bin/env julia +# +# @license Apache-2.0 +# +# Copyright (c) 2024 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import JSON + +""" + gen( domain, name ) + +Generate fixture data and write to file. + +# Arguments + +* `domain`: domain +* `name::AbstractString`: output filename + +# Examples + +``` julia +julia> x = range( -1, stop = 1, length = 2001 ); +julia> gen( x, \"data.json\" ); +``` +""" +function gen( domain, name ) + x = collect( domain ); + y = asin.( x ); + + # Store data to be written to file as a collection: + data = Dict([ + ("x", x), + ("expected", y) + ]); + + # Based on the script directory, create an output filepath: + filepath = joinpath( dir, name ); + + # Write the data to the output filepath as JSON: + outfile = open( filepath, "w" ); + write( outfile, JSON.json(data) ); + close( outfile ); +end + +# Get the filename: +file = @__FILE__; + +# Extract the directory in which this file resides: +dir = dirname( file ); + +# Generate fixture data for decimal values: +x = range( -1.0, stop = 1.0, length = 2003 ); +gen( x, "data.json" ); + +# Generate fixture data for small negative values: +x = range( -1e-200, stop = -1e-208, length = 2003 ); +gen( x, "small_negative.json" ); + +# Generate fixture data for small negative values: +x = range( 1e-300, stop = 1e-308, length = 2003 ); +gen( x, "small_positive.json" ); diff --git a/lib/node_modules/@stdlib/math/base/special/asinf/test/fixtures/julia/small_negative.json b/lib/node_modules/@stdlib/math/base/special/asinf/test/fixtures/julia/small_negative.json new file mode 100644 index 000000000000..745a0ea5b42f --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/asinf/test/fixtures/julia/small_negative.json @@ -0,0 +1 @@ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/asinf/test/fixtures/julia/small_positive.json b/lib/node_modules/@stdlib/math/base/special/asinf/test/fixtures/julia/small_positive.json new file mode 100644 index 000000000000..9fdbc1926a68 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/asinf/test/fixtures/julia/small_positive.json @@ -0,0 +1 @@ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/asinf/test/test.js b/lib/node_modules/@stdlib/math/base/special/asinf/test/test.js new file mode 100644 index 000000000000..a6c97f897550 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/asinf/test/test.js @@ -0,0 +1,128 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2024 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var EPS = require( '@stdlib/constants/float32/eps' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); +var asinf = require( './../lib' ); + + +// FIXTURES // + +var data = require( './fixtures/julia/data.json' ); +var smallNegative = require( './fixtures/julia/small_negative.json' ); +var smallPositive = require( './fixtures/julia/small_positive.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof asinf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function computes the arcsine', function test( t ) { + var expected; + var delta; + var tol; + var x; + var y; + var i; + var e; + + x = data.x; + expected = data.expected; + + for ( i = 0; i < x.length; i++ ) { + y = asinf( ( ( x[ i ] ) ) ); + e = float64ToFloat32( expected[ i ] ); + if ( y === e ) { + t.equal( y, e, 'x: '+x[ i ]+'. E: '+e ); + } else { + delta = abs( y - e ); + tol = 3.3 * EPS * abs( e ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. y: '+y+'. E: '+e+'. tol: '+tol+'. Δ: '+delta+'.' ); + } + } + t.end(); +}); + +tape( 'the function computes the arcsine (small negative values)', function test( t ) { + var expected; + var delta; + var tol; + var x; + var y; + var i; + var e; + + x = smallNegative.x; + expected = smallNegative.expected; + + for ( i = 0; i < x.length; i++ ) { + y = asinf( ( x[ i ] ) ); + e = float64ToFloat32( expected[ i ] ); + if ( y === e ) { + t.equal( y, e, 'x: '+x[ i ]+'. E: '+e ); + } else { + delta = abs( y - e ); + tol = 3.3 * EPS * abs( e ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. y: '+y+'. E: '+e+'. tol: '+tol+'. Δ: '+delta+'.' ); + } + } + t.end(); +}); + +tape( 'the function computes the arcsine (small positive values)', function test( t ) { + var expected; + var delta; + var tol; + var x; + var y; + var i; + var e; + + x = smallPositive.x; + expected = smallPositive.expected; + + for ( i = 0; i < x.length; i++ ) { + y = asinf( x[ i ] ); + e = float64ToFloat32( expected[ i ] ); + if ( y === e ) { + t.equal( y, e, 'x: '+x[ i ]+'. E: '+e ); + } else { + delta = abs( y - e ); + tol = 3.3 * EPS * abs( e ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. y: '+y+'. E: '+e+'. tol: '+tol+'. Δ: '+delta+'.' ); + } + } + t.end(); +}); + +tape( 'the function returns `NaN` if provided `NaN`', function test( t ) { + var v = asinf( NaN ); + t.equal( isnanf( v ), true, 'returns NaN' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/special/asinf/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/asinf/test/test.native.js new file mode 100644 index 000000000000..5a1e9aac3d61 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/asinf/test/test.native.js @@ -0,0 +1,137 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2024 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var EPS = require( '@stdlib/constants/float32/eps' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var asinf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( asinf instanceof Error ) +}; + + +// FIXTURES // + +var data = require( './fixtures/julia/data.json' ); +var smallNegative = require( './fixtures/julia/small_negative.json' ); +var smallPositive = require( './fixtures/julia/small_positive.json' ); + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof asinf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function computes the arcsine', opts, function test( t ) { + var expected; + var delta; + var tol; + var x; + var y; + var i; + var e; + + x = data.x; + expected = data.expected; + + for ( i = 0; i < x.length; i++ ) { + y = asinf( ( ( x[ i ] ) ) ); + e = float64ToFloat32( expected[ i ] ); + if ( y === e ) { + t.equal( y, e, 'x: '+x[ i ]+'. E: '+e ); + } else { + delta = abs( y - e ); + tol = 3.3 * EPS * abs( e ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. y: '+y+'. E: '+e+'. tol: '+tol+'. Δ: '+delta+'.' ); + } + } + t.end(); +}); + +tape( 'the function computes the arcsine (small negative values)', opts, function test( t ) { + var expected; + var delta; + var tol; + var x; + var y; + var i; + var e; + + x = smallNegative.x; + expected = smallNegative.expected; + + for ( i = 0; i < x.length; i++ ) { + y = asinf( ( x[ i ] ) ); + e = float64ToFloat32( expected[ i ] ); + if ( y === e ) { + t.equal( y, e, 'x: '+x[ i ]+'. E: '+e ); + } else { + delta = abs( y - e ); + tol = EPS * abs( e ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. y: '+y+'. E: '+e+'. tol: '+tol+'. Δ: '+delta+'.' ); + } + } + t.end(); +}); + +tape( 'the function computes the arcsine (small positive values)', opts, function test( t ) { + var expected; + var delta; + var tol; + var x; + var y; + var i; + var e; + + x = smallPositive.x; + expected = smallPositive.expected; + + for ( i = 0; i < x.length; i++ ) { + y = asinf( x[ i ] ); + e = float64ToFloat32( expected[ i ] ); + if ( y === e ) { + t.equal( y, e, 'x: '+x[ i ]+'. E: '+e ); + } else { + delta = abs( y - e ); + tol = EPS * abs( e ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. y: '+y+'. E: '+e+'. tol: '+tol+'. Δ: '+delta+'.' ); + } + } + t.end(); +}); + +tape( 'the function returns `NaN` if provided `NaN`', opts, function test( t ) { + var v = asinf( NaN ); + t.equal( isnanf( v ), true, 'returns NaN' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/README.md b/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/README.md index 07289198dc11..19092489cb22 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/README.md +++ b/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/README.md @@ -133,83 +133,6 @@ for ( i = 0; i < 100; i++ ) { - - -* * * - -
- -## C APIs - - - -
- -
- - - - - -
- -### Usage - -```c -#include "stdlib/math/base/special/fast/alpha_max_plus_beta_min.h" -``` - -#### stdlib_base_fast_ampbm( x, y ) - -Computes the hypotenuse using the alpha max plus beta min algorithm. - -```c -double h = stdlib_base_fast_ampbm( -5.0, 12.0 ); -// returns ~13.5 -``` - -
- - - - - -
- -
- - - - - -
- -### Examples - -```c -#include "stdlib/math/base/special/fast/alpha_max_plus_beta_min.h" -#include - -int main( void ) { - const double x[] = { 3.0, 4.0, 5.0, 12.0 }; - - double y; - int i; - for ( i = 0; i < 4; i += 2 ) { - y = stdlib_base_fast_ampbm( x[ i ], x[ i + 1 ] ); - printf( "ampbm(%lf, %lf) = %lf\n", x[ i ], x[ i + 1 ], y ); - } -} -``` - -
- - - -
- - -
diff --git a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/benchmark/benchmark.native.js deleted file mode 100644 index 35e5026ffcb8..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/benchmark/benchmark.native.js +++ /dev/null @@ -1,62 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var resolve = require( 'path' ).resolve; -var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var tryRequire = require( '@stdlib/utils/try-require' ); -var pkg = require( './../package.json' ).name; - - -// VARIABLES // - -var ampbm = tryRequire( resolve( __dirname, './../lib/native.js' ) ); -var opts = { - 'skip': ( ampbm instanceof Error ) -}; - - -// MAIN // - -bench( pkg+'::native', opts, function benchmark( b ) { - var x; - var y; - var h; - var i; - - b.tic(); - for ( i = 0; i < b.iterations; i++ ) { - x = ( randu() * 100.0 ) - 50.0; - y = ( randu() * 100.0 ) - 50.0; - h = ampbm( x, y ); - if ( isnan( h ) ) { - b.fail( 'should not return NaN' ); - } - } - b.toc(); - if ( isnan( h ) ) { - b.fail( 'should not return NaN' ); - } - b.pass( 'benchmark finished' ); - b.end(); -}); diff --git a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/benchmark/c/native/Makefile b/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/benchmark/c/native/Makefile deleted file mode 100644 index f69e9da2b4d3..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/benchmark/c/native/Makefile +++ /dev/null @@ -1,146 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# VARIABLES # - -ifndef VERBOSE - QUIET := @ -else - QUIET := -endif - -# Determine the OS ([1][1], [2][2]). -# -# [1]: https://en.wikipedia.org/wiki/Uname#Examples -# [2]: http://stackoverflow.com/a/27776822/2225624 -OS ?= $(shell uname) -ifneq (, $(findstring MINGW,$(OS))) - OS := WINNT -else -ifneq (, $(findstring MSYS,$(OS))) - OS := WINNT -else -ifneq (, $(findstring CYGWIN,$(OS))) - OS := WINNT -else -ifneq (, $(findstring Windows_NT,$(OS))) - OS := WINNT -endif -endif -endif -endif - -# Define the program used for compiling C source files: -ifdef C_COMPILER - CC := $(C_COMPILER) -else - CC := gcc -endif - -# Define the command-line options when compiling C files: -CFLAGS ?= \ - -std=c99 \ - -O3 \ - -Wall \ - -pedantic - -# Determine whether to generate position independent code ([1][1], [2][2]). -# -# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options -# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option -ifeq ($(OS), WINNT) - fPIC ?= -else - fPIC ?= -fPIC -endif - -# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): -INCLUDE ?= - -# List of source files: -SOURCE_FILES ?= - -# List of libraries (e.g., `-lopenblas -lpthread`): -LIBRARIES ?= - -# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): -LIBPATH ?= - -# List of C targets: -c_targets := benchmark.out - - -# RULES # - -#/ -# Compiles source files. -# -# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) -# @param {string} [CFLAGS] - C compiler options -# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) -# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) -# @param {string} [SOURCE_FILES] - list of source files -# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) -# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) -# -# @example -# make -# -# @example -# make all -#/ -all: $(c_targets) - -.PHONY: all - -#/ -# Compiles C source files. -# -# @private -# @param {string} CC - C compiler (e.g., `gcc`) -# @param {string} CFLAGS - C compiler options -# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) -# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) -# @param {string} SOURCE_FILES - list of source files -# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) -# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) -#/ -$(c_targets): %.out: %.c - $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) - -#/ -# Runs compiled benchmarks. -# -# @example -# make run -#/ -run: $(c_targets) - $(QUIET) ./$< - -.PHONY: run - -#/ -# Removes generated files. -# -# @example -# make clean -#/ -clean: - $(QUIET) -rm -f *.o *.out - -.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/benchmark/c/native/benchmark.c deleted file mode 100644 index 972608084d44..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/benchmark/c/native/benchmark.c +++ /dev/null @@ -1,138 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/** -* Benchmark `alpha-max-plus-beta-min`. -*/ -#include "stdlib/math/base/special/fast/alpha_max_plus_beta_min.h" -#include -#include -#include -#include -#include - -#define NAME "alpha-max-plus-beta-min" -#define ITERATIONS 1000000 -#define REPEATS 3 - -/** -* Prints the TAP version. -*/ -void print_version() { - printf( "TAP version 13\n" ); -} - -/** -* Prints the TAP summary. -* -* @param total total number of tests -* @param passing total number of passing tests -*/ -void print_summary( int total, int passing ) { - printf( "#\n" ); - printf( "1..%d\n", total ); // TAP plan - printf( "# total %d\n", total ); - printf( "# pass %d\n", passing ); - printf( "#\n" ); - printf( "# ok\n" ); -} - -/** -* Prints benchmarks results. -* -* @param elapsed elapsed time in seconds -*/ -void print_results( double elapsed ) { - double rate = (double)ITERATIONS / elapsed; - printf( " ---\n" ); - printf( " iterations: %d\n", ITERATIONS ); - printf( " elapsed: %0.9f\n", elapsed ); - printf( " rate: %0.9f\n", rate ); - printf( " ...\n" ); -} - -/** -* Returns a clock time. -* -* @return clock time -*/ -double tic() { - struct timeval now; - gettimeofday( &now, NULL ); - return (double)now.tv_sec + (double)now.tv_usec/1.0e6; -} - -/** -* Generates a random number on the interval [0,1]. -* -* @return random number -*/ -double rand_double() { - int r = rand(); - return (double)r / ( (double)RAND_MAX + 1.0 ); -} - -/** -* Runs a benchmark. -* -* @return elapsed time in seconds -*/ -double benchmark() { - double elapsed; - double x; - double y; - double z; - double t; - int i; - - t = tic(); - for ( i = 0; i < ITERATIONS; i++ ) { - x = ( 100.0 * rand_double() ) - 50.0; - y = ( 100.0 * rand_double() ) - 50.0; - z = stdlib_base_fast_ampbm( x, y ); - if ( z != z ) { - printf( "should not return NaN\n" ); - break; - } - } - elapsed = tic() - t; - if ( z != z ) { - printf( "should not return NaN\n" ); - } - return elapsed; -} - -/** -* Main execution sequence. -*/ -int main( void ) { - double elapsed; - int i; - - // Use the current time to seed the random number generator: - srand( time( NULL ) ); - - print_version(); - for ( i = 0; i < REPEATS; i++ ) { - printf( "# c::native::%s\n", NAME ); - elapsed = benchmark(); - print_results( elapsed ); - printf( "ok %d benchmark finished\n", i+1 ); - } - print_summary( REPEATS, REPEATS ); -} diff --git a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/binding.gyp b/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/binding.gyp deleted file mode 100644 index ec3992233442..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/binding.gyp +++ /dev/null @@ -1,170 +0,0 @@ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# A `.gyp` file for building a Node.js native add-on. -# -# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md -# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md -{ - # List of files to include in this file: - 'includes': [ - './include.gypi', - ], - - # Define variables to be used throughout the configuration for all targets: - 'variables': { - # Target name should match the add-on export name: - 'addon_target_name%': 'addon', - - # Set variables based on the host OS: - 'conditions': [ - [ - 'OS=="win"', - { - # Define the object file suffix: - 'obj': 'obj', - }, - { - # Define the object file suffix: - 'obj': 'o', - } - ], # end condition (OS=="win") - ], # end conditions - }, # end variables - - # Define compile targets: - 'targets': [ - - # Target to generate an add-on: - { - # The target name should match the add-on export name: - 'target_name': '<(addon_target_name)', - - # Define dependencies: - 'dependencies': [], - - # Define directories which contain relevant include headers: - 'include_dirs': [ - # Local include directory: - '<@(include_dirs)', - ], - - # List of source files: - 'sources': [ - '<@(src_files)', - ], - - # Settings which should be applied when a target's object files are used as linker input: - 'link_settings': { - # Define libraries: - 'libraries': [ - '<@(libraries)', - ], - - # Define library directories: - 'library_dirs': [ - '<@(library_dirs)', - ], - }, - - # C/C++ compiler flags: - 'cflags': [ - # Enable commonly used warning options: - '-Wall', - - # Aggressive optimization: - '-O3', - ], - - # C specific compiler flags: - 'cflags_c': [ - # Specify the C standard to which a program is expected to conform: - '-std=c99', - ], - - # C++ specific compiler flags: - 'cflags_cpp': [ - # Specify the C++ standard to which a program is expected to conform: - '-std=c++11', - ], - - # Linker flags: - 'ldflags': [], - - # Apply conditions based on the host OS: - 'conditions': [ - [ - 'OS=="mac"', - { - # Linker flags: - 'ldflags': [ - '-undefined dynamic_lookup', - '-Wl,-no-pie', - '-Wl,-search_paths_first', - ], - }, - ], # end condition (OS=="mac") - [ - 'OS!="win"', - { - # C/C++ flags: - 'cflags': [ - # Generate platform-independent code: - '-fPIC', - ], - }, - ], # end condition (OS!="win") - ], # end conditions - }, # end target <(addon_target_name) - - # Target to copy a generated add-on to a standard location: - { - 'target_name': 'copy_addon', - - # Declare that the output of this target is not linked: - 'type': 'none', - - # Define dependencies: - 'dependencies': [ - # Require that the add-on be generated before building this target: - '<(addon_target_name)', - ], - - # Define a list of actions: - 'actions': [ - { - 'action_name': 'copy_addon', - 'message': 'Copying addon...', - - # Explicitly list the inputs in the command-line invocation below: - 'inputs': [], - - # Declare the expected outputs: - 'outputs': [ - '<(addon_output_dir)/<(addon_target_name).node', - ], - - # Define the command-line invocation: - 'action': [ - 'cp', - '<(PRODUCT_DIR)/<(addon_target_name).node', - '<(addon_output_dir)/<(addon_target_name).node', - ], - }, - ], # end actions - }, # end target copy_addon - ], # end targets -} diff --git a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/examples/c/Makefile b/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/examples/c/Makefile deleted file mode 100644 index 6aed70daf167..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/examples/c/Makefile +++ /dev/null @@ -1,146 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# VARIABLES # - -ifndef VERBOSE - QUIET := @ -else - QUIET := -endif - -# Determine the OS ([1][1], [2][2]). -# -# [1]: https://en.wikipedia.org/wiki/Uname#Examples -# [2]: http://stackoverflow.com/a/27776822/2225624 -OS ?= $(shell uname) -ifneq (, $(findstring MINGW,$(OS))) - OS := WINNT -else -ifneq (, $(findstring MSYS,$(OS))) - OS := WINNT -else -ifneq (, $(findstring CYGWIN,$(OS))) - OS := WINNT -else -ifneq (, $(findstring Windows_NT,$(OS))) - OS := WINNT -endif -endif -endif -endif - -# Define the program used for compiling C source files: -ifdef C_COMPILER - CC := $(C_COMPILER) -else - CC := gcc -endif - -# Define the command-line options when compiling C files: -CFLAGS ?= \ - -std=c99 \ - -O3 \ - -Wall \ - -pedantic - -# Determine whether to generate position independent code ([1][1], [2][2]). -# -# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options -# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option -ifeq ($(OS), WINNT) - fPIC ?= -else - fPIC ?= -fPIC -endif - -# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): -INCLUDE ?= - -# List of source files: -SOURCE_FILES ?= - -# List of libraries (e.g., `-lopenblas -lpthread`): -LIBRARIES ?= - -# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): -LIBPATH ?= - -# List of C targets: -c_targets := example.out - - -# RULES # - -#/ -# Compiles source files. -# -# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) -# @param {string} [CFLAGS] - C compiler options -# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) -# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) -# @param {string} [SOURCE_FILES] - list of source files -# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) -# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) -# -# @example -# make -# -# @example -# make all -#/ -all: $(c_targets) - -.PHONY: all - -#/ -# Compiles C source files. -# -# @private -# @param {string} CC - C compiler (e.g., `gcc`) -# @param {string} CFLAGS - C compiler options -# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) -# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) -# @param {string} SOURCE_FILES - list of source files -# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) -# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) -#/ -$(c_targets): %.out: %.c - $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) - -#/ -# Runs compiled examples. -# -# @example -# make run -#/ -run: $(c_targets) - $(QUIET) ./$< - -.PHONY: run - -#/ -# Removes generated files. -# -# @example -# make clean -#/ -clean: - $(QUIET) -rm -f *.o *.out - -.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/examples/c/example.c b/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/examples/c/example.c deleted file mode 100644 index af4dc21891e3..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/examples/c/example.c +++ /dev/null @@ -1,31 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/math/base/special/fast/alpha_max_plus_beta_min.h" -#include - -int main( void ) { - const double x[] = { 3.0, 4.0, 5.0, 12.0 }; - - double y; - int i; - for ( i = 0; i < 4; i += 2 ) { - y = stdlib_base_fast_ampbm( x[ i ], x[ i + 1 ] ); - printf( "ampbm(%lf, %lf) = %lf\n", x[ i ], x[ i + 1 ], y ); - } -} diff --git a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/include.gypi b/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/include.gypi deleted file mode 100644 index 575cb043c0bf..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/include.gypi +++ /dev/null @@ -1,53 +0,0 @@ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# A GYP include file for building a Node.js native add-on. -# -# Main documentation: -# -# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md -# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md -{ - # Define variables to be used throughout the configuration for all targets: - 'variables': { - # Source directory: - 'src_dir': './src', - - # Include directories: - 'include_dirs': [ - ' ay ) { - return (ALPHA * ax ) + ( BETA * ay ); - } - return (ALPHA * ay ) + ( BETA * ax ); -} diff --git a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/test/test.native.js deleted file mode 100644 index 51fdf53259fe..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/test/test.native.js +++ /dev/null @@ -1,71 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var resolve = require( 'path' ).resolve; -var tape = require( 'tape' ); -var randu = require( '@stdlib/random/base/randu' ).factory; -var abs = require( '@stdlib/math/base/special/abs' ); -var hypot = require( '@stdlib/math/base/special/hypot' ); -var tryRequire = require( '@stdlib/utils/try-require' ); - -var approx = tryRequire( resolve( __dirname, './../lib/native.js' ) ); -var opts = { - 'skip': ( approx instanceof Error ) -}; - - -// TESTS // - -tape( 'main export is a function', opts, function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof approx, 'function', 'main export is a function' ); - t.end(); -}); - -tape( 'the function computes the hypotenuse using the alpha max plus beta min algorithm', opts, function test( t ) { - var expected; - var rand; - var err; - var tol; - var h; - var x; - var y; - var i; - - rand = randu(); - t.ok( true, 'seed: '+rand.seed ); - - tol = 0.0396; - for ( i = 0; i < 500; i++ ) { - x = ( rand()*100.0 ) - 50.0; - y = ( rand()*100.0 ) - 50.0; - expected = hypot( x, y ); - h = approx( x, y ); - if ( h === expected ) { - t.ok( true, 'x: '+x+'. y: '+y+'. h: '+h+'. Expected: '+expected+'.' ); - } else { - err = abs( h - expected ) / abs( expected ); - t.strictEqual( err <= tol, true, 'within tolerance. x: '+x+'. y: '+y+'. h: '+h+'. Expected: '+expected+'. Error: '+err+'. Tol: '+tol+'.' ); - } - } - t.end(); -}); diff --git a/lib/node_modules/@stdlib/math/base/special/fast/atanh/package.json b/lib/node_modules/@stdlib/math/base/special/fast/atanh/package.json index dd3feaff98ce..04099cd42211 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/atanh/package.json +++ b/lib/node_modules/@stdlib/math/base/special/fast/atanh/package.json @@ -14,14 +14,11 @@ } ], "main": "./lib", - "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", - "include": "./include", "lib": "./lib", - "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/math/base/special/fast/max/package.json b/lib/node_modules/@stdlib/math/base/special/fast/max/package.json index 8203f2cc8be5..a43aa1f8304a 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/max/package.json +++ b/lib/node_modules/@stdlib/math/base/special/fast/max/package.json @@ -14,14 +14,11 @@ } ], "main": "./lib", - "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", - "include": "./include", "lib": "./lib", - "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/math/base/special/fast/min/package.json b/lib/node_modules/@stdlib/math/base/special/fast/min/package.json index fa827dcb1374..c030d1239165 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/min/package.json +++ b/lib/node_modules/@stdlib/math/base/special/fast/min/package.json @@ -14,14 +14,11 @@ } ], "main": "./lib", - "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", - "include": "./include", "lib": "./lib", - "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/math/base/special/fast/pow-int/package.json b/lib/node_modules/@stdlib/math/base/special/fast/pow-int/package.json index 98872a9bc33c..6235e387bd8b 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/pow-int/package.json +++ b/lib/node_modules/@stdlib/math/base/special/fast/pow-int/package.json @@ -14,14 +14,11 @@ } ], "main": "./lib", - "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", - "include": "./include", "lib": "./lib", - "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/README.md b/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/README.md index 20c5b974447e..76eaa5e2cc86 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/README.md +++ b/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/README.md @@ -88,97 +88,6 @@ for ( i = 1; i < 101; i++ ) { - - -* * * - -
- -## C APIs - - - -
- -
- - - - - -
- -### Usage - -```c -#include "stdlib/math/base/special/fast/uint32_log2.h" -``` - -#### stdlib_base_fast_uint32_log2( x ) - -Returns an **approximate** [binary logarithm][binary-logarithm] of an unsigned 32-bit integer `x`. - -```c -#include - -uint32_t out = stdlib_base_fast_uint32_log2( 4 ); -// returns 2 - -out = stdlib_base_fast_uint32_log2( 9 ); -// returns 3 -``` - -The function accepts the following arguments: - -- **x**: `[in] uint32_t` input value. - -```c -uint32_t stdlib_base_fast_uint32_log2( const uint32_t x ); -``` - -
- - - - - -
- -
- - - - - -
- -### Examples - -```c -#include "stdlib/math/base/special/fast/uint32_log2.h" -#include -#include - -int main( void ) { - const uint32_t x[] = { 5, 7, 10, 22, 98 }; - - uint32_t y; - int i; - for ( i = 0; i < 5; i++ ) { - y = stdlib_base_fast_uint32_log2( x[ i ] ); - printf( "uint32_log2(%u) = %u\n", x[ i ], y ); - } -} -``` - -
- - - -
- - -
diff --git a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/benchmark/benchmark.native.js deleted file mode 100644 index eeb82c9b56fa..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/benchmark/benchmark.native.js +++ /dev/null @@ -1,58 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var resolve = require( 'path' ).resolve; -var bench = require( '@stdlib/bench' ); -var minstd = require( '@stdlib/random/base/minstd-shuffle' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var tryRequire = require( '@stdlib/utils/try-require' ); -var pkg = require( './../package.json' ).name; - - -// VARIABLES // - -var log2Uint32 = tryRequire( resolve( __dirname, './../lib/native.js' ) ); -var opts = { - 'skip': ( log2Uint32 instanceof Error ) -}; - - -// MAIN // - -bench( pkg+'::native', opts, function benchmark( b ) { - var y; - var i; - - b.tic(); - for ( i = 0; i < b.iterations; i++ ) { - y = log2Uint32( minstd() >>> 0 ); - if ( isnan( y ) ) { - b.fail( 'should not return NaN' ); - } - } - b.toc(); - if ( isnan( y ) ) { - b.fail( 'should not return NaN' ); - } - b.pass( 'benchmark finished' ); - b.end(); -}); diff --git a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/benchmark/c/native/Makefile b/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/benchmark/c/native/Makefile deleted file mode 100644 index f69e9da2b4d3..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/benchmark/c/native/Makefile +++ /dev/null @@ -1,146 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# VARIABLES # - -ifndef VERBOSE - QUIET := @ -else - QUIET := -endif - -# Determine the OS ([1][1], [2][2]). -# -# [1]: https://en.wikipedia.org/wiki/Uname#Examples -# [2]: http://stackoverflow.com/a/27776822/2225624 -OS ?= $(shell uname) -ifneq (, $(findstring MINGW,$(OS))) - OS := WINNT -else -ifneq (, $(findstring MSYS,$(OS))) - OS := WINNT -else -ifneq (, $(findstring CYGWIN,$(OS))) - OS := WINNT -else -ifneq (, $(findstring Windows_NT,$(OS))) - OS := WINNT -endif -endif -endif -endif - -# Define the program used for compiling C source files: -ifdef C_COMPILER - CC := $(C_COMPILER) -else - CC := gcc -endif - -# Define the command-line options when compiling C files: -CFLAGS ?= \ - -std=c99 \ - -O3 \ - -Wall \ - -pedantic - -# Determine whether to generate position independent code ([1][1], [2][2]). -# -# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options -# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option -ifeq ($(OS), WINNT) - fPIC ?= -else - fPIC ?= -fPIC -endif - -# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): -INCLUDE ?= - -# List of source files: -SOURCE_FILES ?= - -# List of libraries (e.g., `-lopenblas -lpthread`): -LIBRARIES ?= - -# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): -LIBPATH ?= - -# List of C targets: -c_targets := benchmark.out - - -# RULES # - -#/ -# Compiles source files. -# -# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) -# @param {string} [CFLAGS] - C compiler options -# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) -# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) -# @param {string} [SOURCE_FILES] - list of source files -# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) -# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) -# -# @example -# make -# -# @example -# make all -#/ -all: $(c_targets) - -.PHONY: all - -#/ -# Compiles C source files. -# -# @private -# @param {string} CC - C compiler (e.g., `gcc`) -# @param {string} CFLAGS - C compiler options -# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) -# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) -# @param {string} SOURCE_FILES - list of source files -# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) -# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) -#/ -$(c_targets): %.out: %.c - $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) - -#/ -# Runs compiled benchmarks. -# -# @example -# make run -#/ -run: $(c_targets) - $(QUIET) ./$< - -.PHONY: run - -#/ -# Removes generated files. -# -# @example -# make clean -#/ -clean: - $(QUIET) -rm -f *.o *.out - -.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/benchmark/c/native/benchmark.c deleted file mode 100644 index fd96b3ad721a..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/benchmark/c/native/benchmark.c +++ /dev/null @@ -1,137 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/** -* Benchmark `uint32_log2`. -*/ -#include "stdlib/math/base/special/fast/uint32_log2.h" -#include -#include -#include -#include -#include -#include - -#define NAME "uint32_log2" -#define ITERATIONS 1000000 -#define REPEATS 3 - -/** -* Prints the TAP version. -*/ -void print_version() { - printf( "TAP version 13\n" ); -} - -/** -* Prints the TAP summary. -* -* @param total total number of tests -* @param passing total number of passing tests -*/ -void print_summary( int total, int passing ) { - printf( "#\n" ); - printf( "1..%d\n", total ); // TAP plan - printf( "# total %d\n", total ); - printf( "# pass %d\n", passing ); - printf( "#\n" ); - printf( "# ok\n" ); -} - -/** -* Prints benchmarks results. -* -* @param elapsed elapsed time in seconds -*/ -void print_results( double elapsed ) { - double rate = (double)ITERATIONS / elapsed; - printf( " ---\n" ); - printf( " iterations: %d\n", ITERATIONS ); - printf( " elapsed: %0.9f\n", elapsed ); - printf( " rate: %0.9f\n", rate ); - printf( " ...\n" ); -} - -/** -* Returns a clock time. -* -* @return clock time -*/ -double tic() { - struct timeval now; - gettimeofday( &now, NULL ); - return (double)now.tv_sec + (double)now.tv_usec/1.0e6; -} - -/** -* Generates a random number on the interval [0,1]. -* -* @return random number -*/ -double rand_double() { - int r = rand(); - return (double)r / ( (double)RAND_MAX + 1.0 ); -} - -/** -* Runs a benchmark. -* -* @return elapsed time in seconds -*/ -double benchmark() { - double elapsed; - uint32_t x; - uint32_t y; - double t; - int i; - - t = tic(); - for ( i = 0; i < ITERATIONS; i++ ) { - x = (uint32_t)rand(); - y = stdlib_base_fast_uint32_log2( x ); - if ( y > x ) { - printf( "unexpected result\n" ); - break; - } - } - elapsed = tic() - t; - if ( y > x ) { - printf( "unexpected result\n" ); - } - return elapsed; -} - -/** -* Main execution sequence. -*/ -int main( void ) { - double elapsed; - int i; - - // Use the current time to seed the random number generator: - srand( time( NULL ) ); - - print_version(); - for ( i = 0; i < REPEATS; i++ ) { - printf( "# c::native::%s\n", NAME ); - elapsed = benchmark(); - print_results( elapsed ); - printf( "ok %d benchmark finished\n", i+1 ); - } - print_summary( REPEATS, REPEATS ); -} diff --git a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/binding.gyp b/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/binding.gyp deleted file mode 100644 index ec3992233442..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/binding.gyp +++ /dev/null @@ -1,170 +0,0 @@ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# A `.gyp` file for building a Node.js native add-on. -# -# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md -# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md -{ - # List of files to include in this file: - 'includes': [ - './include.gypi', - ], - - # Define variables to be used throughout the configuration for all targets: - 'variables': { - # Target name should match the add-on export name: - 'addon_target_name%': 'addon', - - # Set variables based on the host OS: - 'conditions': [ - [ - 'OS=="win"', - { - # Define the object file suffix: - 'obj': 'obj', - }, - { - # Define the object file suffix: - 'obj': 'o', - } - ], # end condition (OS=="win") - ], # end conditions - }, # end variables - - # Define compile targets: - 'targets': [ - - # Target to generate an add-on: - { - # The target name should match the add-on export name: - 'target_name': '<(addon_target_name)', - - # Define dependencies: - 'dependencies': [], - - # Define directories which contain relevant include headers: - 'include_dirs': [ - # Local include directory: - '<@(include_dirs)', - ], - - # List of source files: - 'sources': [ - '<@(src_files)', - ], - - # Settings which should be applied when a target's object files are used as linker input: - 'link_settings': { - # Define libraries: - 'libraries': [ - '<@(libraries)', - ], - - # Define library directories: - 'library_dirs': [ - '<@(library_dirs)', - ], - }, - - # C/C++ compiler flags: - 'cflags': [ - # Enable commonly used warning options: - '-Wall', - - # Aggressive optimization: - '-O3', - ], - - # C specific compiler flags: - 'cflags_c': [ - # Specify the C standard to which a program is expected to conform: - '-std=c99', - ], - - # C++ specific compiler flags: - 'cflags_cpp': [ - # Specify the C++ standard to which a program is expected to conform: - '-std=c++11', - ], - - # Linker flags: - 'ldflags': [], - - # Apply conditions based on the host OS: - 'conditions': [ - [ - 'OS=="mac"', - { - # Linker flags: - 'ldflags': [ - '-undefined dynamic_lookup', - '-Wl,-no-pie', - '-Wl,-search_paths_first', - ], - }, - ], # end condition (OS=="mac") - [ - 'OS!="win"', - { - # C/C++ flags: - 'cflags': [ - # Generate platform-independent code: - '-fPIC', - ], - }, - ], # end condition (OS!="win") - ], # end conditions - }, # end target <(addon_target_name) - - # Target to copy a generated add-on to a standard location: - { - 'target_name': 'copy_addon', - - # Declare that the output of this target is not linked: - 'type': 'none', - - # Define dependencies: - 'dependencies': [ - # Require that the add-on be generated before building this target: - '<(addon_target_name)', - ], - - # Define a list of actions: - 'actions': [ - { - 'action_name': 'copy_addon', - 'message': 'Copying addon...', - - # Explicitly list the inputs in the command-line invocation below: - 'inputs': [], - - # Declare the expected outputs: - 'outputs': [ - '<(addon_output_dir)/<(addon_target_name).node', - ], - - # Define the command-line invocation: - 'action': [ - 'cp', - '<(PRODUCT_DIR)/<(addon_target_name).node', - '<(addon_output_dir)/<(addon_target_name).node', - ], - }, - ], # end actions - }, # end target copy_addon - ], # end targets -} diff --git a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/examples/c/Makefile b/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/examples/c/Makefile deleted file mode 100644 index 6aed70daf167..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/examples/c/Makefile +++ /dev/null @@ -1,146 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# VARIABLES # - -ifndef VERBOSE - QUIET := @ -else - QUIET := -endif - -# Determine the OS ([1][1], [2][2]). -# -# [1]: https://en.wikipedia.org/wiki/Uname#Examples -# [2]: http://stackoverflow.com/a/27776822/2225624 -OS ?= $(shell uname) -ifneq (, $(findstring MINGW,$(OS))) - OS := WINNT -else -ifneq (, $(findstring MSYS,$(OS))) - OS := WINNT -else -ifneq (, $(findstring CYGWIN,$(OS))) - OS := WINNT -else -ifneq (, $(findstring Windows_NT,$(OS))) - OS := WINNT -endif -endif -endif -endif - -# Define the program used for compiling C source files: -ifdef C_COMPILER - CC := $(C_COMPILER) -else - CC := gcc -endif - -# Define the command-line options when compiling C files: -CFLAGS ?= \ - -std=c99 \ - -O3 \ - -Wall \ - -pedantic - -# Determine whether to generate position independent code ([1][1], [2][2]). -# -# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options -# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option -ifeq ($(OS), WINNT) - fPIC ?= -else - fPIC ?= -fPIC -endif - -# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): -INCLUDE ?= - -# List of source files: -SOURCE_FILES ?= - -# List of libraries (e.g., `-lopenblas -lpthread`): -LIBRARIES ?= - -# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): -LIBPATH ?= - -# List of C targets: -c_targets := example.out - - -# RULES # - -#/ -# Compiles source files. -# -# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) -# @param {string} [CFLAGS] - C compiler options -# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) -# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) -# @param {string} [SOURCE_FILES] - list of source files -# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) -# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) -# -# @example -# make -# -# @example -# make all -#/ -all: $(c_targets) - -.PHONY: all - -#/ -# Compiles C source files. -# -# @private -# @param {string} CC - C compiler (e.g., `gcc`) -# @param {string} CFLAGS - C compiler options -# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) -# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) -# @param {string} SOURCE_FILES - list of source files -# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) -# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) -#/ -$(c_targets): %.out: %.c - $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) - -#/ -# Runs compiled examples. -# -# @example -# make run -#/ -run: $(c_targets) - $(QUIET) ./$< - -.PHONY: run - -#/ -# Removes generated files. -# -# @example -# make clean -#/ -clean: - $(QUIET) -rm -f *.o *.out - -.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/examples/c/example.c b/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/examples/c/example.c deleted file mode 100644 index 8dbbf2598b4d..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/examples/c/example.c +++ /dev/null @@ -1,32 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/math/base/special/fast/uint32_log2.h" -#include -#include - -int main( void ) { - const uint32_t x[] = { 5, 7, 10, 22, 98 }; - - uint32_t y; - int i; - for ( i = 0; i < 5; i++ ) { - y = stdlib_base_fast_uint32_log2( x[ i ] ); - printf( "uint32_log2(%u) = %u\n", x[ i ], y ); - } -} diff --git a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/include.gypi b/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/include.gypi deleted file mode 100644 index 575cb043c0bf..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/include.gypi +++ /dev/null @@ -1,53 +0,0 @@ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# A GYP include file for building a Node.js native add-on. -# -# Main documentation: -# -# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md -# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md -{ - # Define variables to be used throughout the configuration for all targets: - 'variables': { - # Source directory: - 'src_dir': './src', - - # Include directories: - 'include_dirs': [ - ' - -/* -* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. -*/ -#ifdef __cplusplus -extern "C" { -#endif - -/** -* Computes an integer binary logarithm (base two). -*/ -uint32_t stdlib_base_fast_uint32_log2( const uint32_t x ); - -#ifdef __cplusplus -} -#endif - -#endif // !STDLIB_MATH_BASE_SPECIAL_FAST_UINT32_LOG2_H diff --git a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/manifest.json b/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/manifest.json deleted file mode 100644 index 710288ade820..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/manifest.json +++ /dev/null @@ -1,68 +0,0 @@ -{ - "options": { - "task": "build" - }, - "fields": [ - { - "field": "src", - "resolve": true, - "relative": true - }, - { - "field": "include", - "resolve": true, - "relative": true - }, - { - "field": "libraries", - "resolve": false, - "relative": false - }, - { - "field": "libpath", - "resolve": true, - "relative": false - } - ], - "confs": [ - { - "task": "build", - "src": [ - "./src/main.c" - ], - "include": [ - "./include" - ], - "libraries": [], - "libpath": [], - "dependencies": [ - "@stdlib/napi/argv-uint32", - "@stdlib/napi/export" - ] - }, - { - "task": "benchmark", - "src": [ - "./src/main.c" - ], - "include": [ - "./include" - ], - "libraries": [], - "libpath": [], - "dependencies": [] - }, - { - "task": "examples", - "src": [ - "./src/main.c" - ], - "include": [ - "./include" - ], - "libraries": [], - "libpath": [], - "dependencies": [] - } - ] -} diff --git a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/package.json b/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/package.json index 5cbf6f00737b..804ad28205a9 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/package.json +++ b/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/package.json @@ -14,14 +14,11 @@ } ], "main": "./lib", - "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", - "include": "./include", "lib": "./lib", - "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/src/Makefile b/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/src/Makefile deleted file mode 100644 index bcf18aa46655..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/src/Makefile +++ /dev/null @@ -1,70 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# VARIABLES # - -ifndef VERBOSE - QUIET := @ -else - QUIET := -endif - -# Determine the OS ([1][1], [2][2]). -# -# [1]: https://en.wikipedia.org/wiki/Uname#Examples -# [2]: http://stackoverflow.com/a/27776822/2225624 -OS ?= $(shell uname) -ifneq (, $(findstring MINGW,$(OS))) - OS := WINNT -else -ifneq (, $(findstring MSYS,$(OS))) - OS := WINNT -else -ifneq (, $(findstring CYGWIN,$(OS))) - OS := WINNT -else -ifneq (, $(findstring Windows_NT,$(OS))) - OS := WINNT -endif -endif -endif -endif - - -# RULES # - -#/ -# Removes generated files for building an add-on. -# -# @example -# make clean-addon -#/ -clean-addon: - $(QUIET) -rm -f *.o *.node - -.PHONY: clean-addon - -#/ -# Removes generated files. -# -# @example -# make clean -#/ -clean: clean-addon - -.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/src/addon.c b/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/src/addon.c deleted file mode 100644 index 6f27f1455582..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/src/addon.c +++ /dev/null @@ -1,44 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/math/base/special/fast/uint32_log2.h" -#include "stdlib/napi/argv_uint32.h" -#include "stdlib/napi/export.h" -#include -#include - -/** -* Receives JavaScript callback invocation data. -* -* @private -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 1 ); - STDLIB_NAPI_ARGV_UINT32( env, value, argv, 0 ); - - napi_value v; - napi_status status = napi_create_uint32( env, stdlib_base_fast_uint32_log2( value ), &v ); - assert( status == napi_ok ); - - return v; -} - -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/src/main.c b/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/src/main.c deleted file mode 100644 index d280a62e3f2a..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/src/main.c +++ /dev/null @@ -1,94 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/math/base/special/fast/uint32_log2.h" -#include - -static const uint32_t B4 = 0xFFFF0000u; -static const uint32_t B3 = 0xFF00u; -static const uint32_t B2 = 0xF0u; -static const uint32_t B1 = 0xCu; -static const uint32_t B0 = 0x2u; -static const uint32_t S4 = 16u; -static const uint32_t S3 = 8u; -static const uint32_t S2 = 4u; -static const uint32_t S1 = 2u; -static const uint32_t S0 = 1u; - -/** -* Computes an integer binary logarithm (base two). -* -* ## Method -* -* 1. Note that the largest unsigned 32-bit integer is `4294967295`, which is `2^{32}-1`. Hence, the integer binary logarithm cannot exceed `31` (i.e., `16 + 8 + 4 + 2 + 1`), which corresponds to the bit sequence -* -* ```binarystring -* 00000000000000000000000000011111 -* ``` -* -* 2. Initialize a return variable with the value zero. -* -* 3. If at least one of the first sixteen most significant bits of the input 32-bit integer `x` is turned on, we know that the power to which the number `2` must be raised to obtain `x` is at least `16` (i.e., `x > 65536`). Hence, activate the corresponding bit of the return variable. Mutate `x` by shifting sixteen bits to the right, discarding the bits shifted off. -* -* 4. Carry out the following steps with `B` in `[ 8, 4, 2, 1 ]`: -* -* - If at least one of the next `B` most significant bits of the current `x` is turned on, we know that the power to which the number `2` must be raised to obtain `x` has to be increased by `B`. -* - Activate the bit of the return variable that corresponds to `B`. -* - Mutate `x` by shifting `B` bits to the right, discarding the bits shifted off. -* -* 5. The final value of the return variable is the integer binary logarithm of `x`. -* -* @param x number -* @return integer binary logarithm -* -* @example -* uint32_t out = stdlib_base_fast_uint32_log2( 8 ); -* // returns 3 -*/ -uint32_t stdlib_base_fast_uint32_log2( const uint32_t x ) { - uint32_t out; - uint32_t xc; - - xc = x; - out = 0; - // `xc >= 65536`: - if ( xc & B4 ) { - xc >>= S4; - out |= S4; - } - // `xc >= 256`: - if ( xc & B3 ) { - xc >>= S3; - out |= S3; - } - // `xc >= 16`: - if ( xc & B2 ) { - xc >>= S2; - out |= S2; - } - // `xc >= 4`: - if ( xc & B1 ) { - xc >>= S1; - out |= S1; - } - // `xc >= 2`: - if ( xc & B0 ) { - out |= S0; - } - return out; -} diff --git a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/test/test.native.js deleted file mode 100644 index 06275f6daf3e..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/fast/uint32-log2/test/test.native.js +++ /dev/null @@ -1,74 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var resolve = require( 'path' ).resolve; -var tape = require( 'tape' ); -var minstd = require( '@stdlib/random/base/minstd-shuffle' ); -var log2 = require( '@stdlib/math/base/special/log2' ); -var floor = require( '@stdlib/math/base/special/floor' ); -var pow = require( '@stdlib/math/base/special/pow' ); -var tryRequire = require( '@stdlib/utils/try-require' ); - - -// VARIABLES // - -var log2Uint32 = tryRequire( resolve( __dirname, './../lib/native.js' ) ); -var opts = { - 'skip': ( log2Uint32 instanceof Error ) -}; - - -// TESTS // - -tape( 'main export is a function', opts, function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof log2Uint32, 'function', 'main export is a function' ); - t.end(); -}); - -tape( 'the function returns an approximate binary logarithm (base two) for integer arguments', opts, function test( t ) { - var x; - var y; - var v; - var i; - - for ( i = 0; i < 5000; i++ ) { - x = minstd() >>> 0; - y = log2( x ); - v = log2Uint32( x ); - t.strictEqual( v, floor( y ), 'returns an approximate binary logarithm' ); - } - t.end(); -}); - -tape( 'the function returns the exact binary logarithm (base two) for integer powers of 2', opts, function test( t ) { - var x; - var y; - var i; - - for ( i = 0; i < 32; i++ ) { - x = pow( 2, i ); - y = log2Uint32( x ); - t.strictEqual( y, i, 'returns binary logarithm' ); - } - t.end(); -}); diff --git a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/README.md b/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/README.md index eab2628500ae..9e7fbeb68578 100644 --- a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/README.md +++ b/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/README.md @@ -116,95 +116,6 @@ for ( i = 0; i < x.length; i++ ) { - - -* * * - -
- -## C APIs - - - -
- -
- - - - - -
- -### Usage - -```c -#include "stdlib/math/base/special/gamma_lanczos_sum_expg_scaled.h" -``` - -#### gamma_lanczos_sum_expg_scaled( x ) - -Calculates the Lanczos sum for the approximation of the [gamma function][gamma-function] (scaled by `exp(-g)`, where `g = 10.900511`). - -```c -double out = gamma_lanczos_sum_expg_scaled( 4.0 ); -// returns ~0.018 - -out = gamma_lanczos_sum_expg_scaled( -1.5 ); -// returns ~25.337 -``` - -The function accepts the following arguments: - -- **x**: `[in] double` input value. - -```c -double gamma_lanczos_sum_expg_scaled( const double x ); -``` - -
- - - - - -
- -
- - - - - -
- -### Examples - -```c -#include "stdlib/math/base/special/gamma_lanczos_sum_expg_scaled.h" -#include -#include - -int main( void ) { - const double x[] = { 4.0, -1.5, -0.5, 0.5 }; - - double y; - int i; - for ( i = 0; i < 4; i++ ) { - y = stdlib_base_gamma_lanczos_sum_expg_scaled( x[ i ] ); - printf( "gamma_lanczos_sum_expg_scaled(%lf) = %lf\n", x[ i ], y ); - } -} -``` - -
- - - -
- - -
diff --git a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/benchmark/benchmark.native.js deleted file mode 100644 index f6df4972efe2..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/benchmark/benchmark.native.js +++ /dev/null @@ -1,60 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var resolve = require( 'path' ).resolve; -var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var tryRequire = require( '@stdlib/utils/try-require' ); -var pkg = require( './../package.json' ).name; - - -// VARIABLES // - -var gammaLanczosSumExpGScaled = tryRequire( resolve( __dirname, './../lib/native.js' ) ); -var opts = { - 'skip': ( gammaLanczosSumExpGScaled instanceof Error ) -}; - - -// MAIN // - -bench( pkg+'::native', opts, function benchmark( b ) { - var x; - var y; - var i; - - b.tic(); - for ( i = 0; i < b.iterations; i++ ) { - x = ( randu() * 100.0 ) - 50.0; - y = gammaLanczosSumExpGScaled( x ); - if ( isnan( y ) ) { - b.fail( 'should not return NaN' ); - } - } - b.toc(); - if ( isnan( y ) ) { - b.fail( 'should not return NaN' ); - } - b.pass( 'benchmark finished' ); - b.end(); -}); diff --git a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/benchmark/c/native/Makefile b/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/benchmark/c/native/Makefile deleted file mode 100644 index f69e9da2b4d3..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/benchmark/c/native/Makefile +++ /dev/null @@ -1,146 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# VARIABLES # - -ifndef VERBOSE - QUIET := @ -else - QUIET := -endif - -# Determine the OS ([1][1], [2][2]). -# -# [1]: https://en.wikipedia.org/wiki/Uname#Examples -# [2]: http://stackoverflow.com/a/27776822/2225624 -OS ?= $(shell uname) -ifneq (, $(findstring MINGW,$(OS))) - OS := WINNT -else -ifneq (, $(findstring MSYS,$(OS))) - OS := WINNT -else -ifneq (, $(findstring CYGWIN,$(OS))) - OS := WINNT -else -ifneq (, $(findstring Windows_NT,$(OS))) - OS := WINNT -endif -endif -endif -endif - -# Define the program used for compiling C source files: -ifdef C_COMPILER - CC := $(C_COMPILER) -else - CC := gcc -endif - -# Define the command-line options when compiling C files: -CFLAGS ?= \ - -std=c99 \ - -O3 \ - -Wall \ - -pedantic - -# Determine whether to generate position independent code ([1][1], [2][2]). -# -# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options -# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option -ifeq ($(OS), WINNT) - fPIC ?= -else - fPIC ?= -fPIC -endif - -# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): -INCLUDE ?= - -# List of source files: -SOURCE_FILES ?= - -# List of libraries (e.g., `-lopenblas -lpthread`): -LIBRARIES ?= - -# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): -LIBPATH ?= - -# List of C targets: -c_targets := benchmark.out - - -# RULES # - -#/ -# Compiles source files. -# -# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) -# @param {string} [CFLAGS] - C compiler options -# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) -# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) -# @param {string} [SOURCE_FILES] - list of source files -# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) -# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) -# -# @example -# make -# -# @example -# make all -#/ -all: $(c_targets) - -.PHONY: all - -#/ -# Compiles C source files. -# -# @private -# @param {string} CC - C compiler (e.g., `gcc`) -# @param {string} CFLAGS - C compiler options -# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) -# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) -# @param {string} SOURCE_FILES - list of source files -# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) -# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) -#/ -$(c_targets): %.out: %.c - $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) - -#/ -# Runs compiled benchmarks. -# -# @example -# make run -#/ -run: $(c_targets) - $(QUIET) ./$< - -.PHONY: run - -#/ -# Removes generated files. -# -# @example -# make clean -#/ -clean: - $(QUIET) -rm -f *.o *.out - -.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/benchmark/c/native/benchmark.c deleted file mode 100644 index a7f39b832073..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/benchmark/c/native/benchmark.c +++ /dev/null @@ -1,136 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/** -* Benchmark `gamma_lanczos_sum_expg_scaled`. -*/ -#include "stdlib/math/base/special/gamma_lanczos_sum_expg_scaled.h" -#include -#include -#include -#include -#include - -#define NAME "gamma_lanczos_sum_expg_scaled" -#define ITERATIONS 1000000 -#define REPEATS 3 - -/** -* Prints the TAP version. -*/ -void print_version() { - printf( "TAP version 13\n" ); -} - -/** -* Prints the TAP summary. -* -* @param total total number of tests -* @param passing total number of passing tests -*/ -void print_summary( int total, int passing ) { - printf( "#\n" ); - printf( "1..%d\n", total ); // TAP plan - printf( "# total %d\n", total ); - printf( "# pass %d\n", passing ); - printf( "#\n" ); - printf( "# ok\n" ); -} - -/** -* Prints benchmarks results. -* -* @param elapsed elapsed time in seconds -*/ -void print_results( double elapsed ) { - double rate = (double)ITERATIONS / elapsed; - printf( " ---\n" ); - printf( " iterations: %d\n", ITERATIONS ); - printf( " elapsed: %0.9f\n", elapsed ); - printf( " rate: %0.9f\n", rate ); - printf( " ...\n" ); -} - -/** -* Returns a clock time. -* -* @return clock time -*/ -double tic() { - struct timeval now; - gettimeofday( &now, NULL ); - return (double)now.tv_sec + (double)now.tv_usec / 1.0e6; -} - -/** -* Generates a random number on the interval [0,1]. -* -* @return random number -*/ -double rand_double() { - int r = rand(); - return (double)r / ( (double)RAND_MAX + 1.0 ); -} - -/** -* Runs a benchmark. -* -* @return elapsed time in seconds -*/ -double benchmark() { - double elapsed; - double x; - double y; - double t; - int i; - - t = tic(); - for ( i = 0; i < ITERATIONS; i++ ) { - x = ( 100.0 * rand_double() ) - 50.0; - y = stdlib_base_gamma_lanczos_sum_expg_scaled( x ); - if ( y != y ) { - printf( "should not return NaN\n" ); - break; - } - } - elapsed = tic() - t; - if ( y != y ) { - printf( "should not return NaN\n" ); - } - return elapsed; -} - -/** -* Main execution sequence. -*/ -int main( void ) { - double elapsed; - int i; - - // Use the current time to seed the random number generator: - srand( time( NULL ) ); - - print_version(); - for ( i = 0; i < REPEATS; i++ ) { - printf( "# c::native::%s\n", NAME ); - elapsed = benchmark(); - print_results( elapsed ); - printf( "ok %d benchmark finished\n", i+1 ); - } - print_summary( REPEATS, REPEATS ); -} diff --git a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/binding.gyp b/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/binding.gyp deleted file mode 100644 index ec3992233442..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/binding.gyp +++ /dev/null @@ -1,170 +0,0 @@ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# A `.gyp` file for building a Node.js native add-on. -# -# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md -# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md -{ - # List of files to include in this file: - 'includes': [ - './include.gypi', - ], - - # Define variables to be used throughout the configuration for all targets: - 'variables': { - # Target name should match the add-on export name: - 'addon_target_name%': 'addon', - - # Set variables based on the host OS: - 'conditions': [ - [ - 'OS=="win"', - { - # Define the object file suffix: - 'obj': 'obj', - }, - { - # Define the object file suffix: - 'obj': 'o', - } - ], # end condition (OS=="win") - ], # end conditions - }, # end variables - - # Define compile targets: - 'targets': [ - - # Target to generate an add-on: - { - # The target name should match the add-on export name: - 'target_name': '<(addon_target_name)', - - # Define dependencies: - 'dependencies': [], - - # Define directories which contain relevant include headers: - 'include_dirs': [ - # Local include directory: - '<@(include_dirs)', - ], - - # List of source files: - 'sources': [ - '<@(src_files)', - ], - - # Settings which should be applied when a target's object files are used as linker input: - 'link_settings': { - # Define libraries: - 'libraries': [ - '<@(libraries)', - ], - - # Define library directories: - 'library_dirs': [ - '<@(library_dirs)', - ], - }, - - # C/C++ compiler flags: - 'cflags': [ - # Enable commonly used warning options: - '-Wall', - - # Aggressive optimization: - '-O3', - ], - - # C specific compiler flags: - 'cflags_c': [ - # Specify the C standard to which a program is expected to conform: - '-std=c99', - ], - - # C++ specific compiler flags: - 'cflags_cpp': [ - # Specify the C++ standard to which a program is expected to conform: - '-std=c++11', - ], - - # Linker flags: - 'ldflags': [], - - # Apply conditions based on the host OS: - 'conditions': [ - [ - 'OS=="mac"', - { - # Linker flags: - 'ldflags': [ - '-undefined dynamic_lookup', - '-Wl,-no-pie', - '-Wl,-search_paths_first', - ], - }, - ], # end condition (OS=="mac") - [ - 'OS!="win"', - { - # C/C++ flags: - 'cflags': [ - # Generate platform-independent code: - '-fPIC', - ], - }, - ], # end condition (OS!="win") - ], # end conditions - }, # end target <(addon_target_name) - - # Target to copy a generated add-on to a standard location: - { - 'target_name': 'copy_addon', - - # Declare that the output of this target is not linked: - 'type': 'none', - - # Define dependencies: - 'dependencies': [ - # Require that the add-on be generated before building this target: - '<(addon_target_name)', - ], - - # Define a list of actions: - 'actions': [ - { - 'action_name': 'copy_addon', - 'message': 'Copying addon...', - - # Explicitly list the inputs in the command-line invocation below: - 'inputs': [], - - # Declare the expected outputs: - 'outputs': [ - '<(addon_output_dir)/<(addon_target_name).node', - ], - - # Define the command-line invocation: - 'action': [ - 'cp', - '<(PRODUCT_DIR)/<(addon_target_name).node', - '<(addon_output_dir)/<(addon_target_name).node', - ], - }, - ], # end actions - }, # end target copy_addon - ], # end targets -} diff --git a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/examples/c/Makefile b/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/examples/c/Makefile deleted file mode 100644 index 6aed70daf167..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/examples/c/Makefile +++ /dev/null @@ -1,146 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# VARIABLES # - -ifndef VERBOSE - QUIET := @ -else - QUIET := -endif - -# Determine the OS ([1][1], [2][2]). -# -# [1]: https://en.wikipedia.org/wiki/Uname#Examples -# [2]: http://stackoverflow.com/a/27776822/2225624 -OS ?= $(shell uname) -ifneq (, $(findstring MINGW,$(OS))) - OS := WINNT -else -ifneq (, $(findstring MSYS,$(OS))) - OS := WINNT -else -ifneq (, $(findstring CYGWIN,$(OS))) - OS := WINNT -else -ifneq (, $(findstring Windows_NT,$(OS))) - OS := WINNT -endif -endif -endif -endif - -# Define the program used for compiling C source files: -ifdef C_COMPILER - CC := $(C_COMPILER) -else - CC := gcc -endif - -# Define the command-line options when compiling C files: -CFLAGS ?= \ - -std=c99 \ - -O3 \ - -Wall \ - -pedantic - -# Determine whether to generate position independent code ([1][1], [2][2]). -# -# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options -# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option -ifeq ($(OS), WINNT) - fPIC ?= -else - fPIC ?= -fPIC -endif - -# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): -INCLUDE ?= - -# List of source files: -SOURCE_FILES ?= - -# List of libraries (e.g., `-lopenblas -lpthread`): -LIBRARIES ?= - -# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): -LIBPATH ?= - -# List of C targets: -c_targets := example.out - - -# RULES # - -#/ -# Compiles source files. -# -# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) -# @param {string} [CFLAGS] - C compiler options -# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) -# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) -# @param {string} [SOURCE_FILES] - list of source files -# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) -# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) -# -# @example -# make -# -# @example -# make all -#/ -all: $(c_targets) - -.PHONY: all - -#/ -# Compiles C source files. -# -# @private -# @param {string} CC - C compiler (e.g., `gcc`) -# @param {string} CFLAGS - C compiler options -# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) -# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) -# @param {string} SOURCE_FILES - list of source files -# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) -# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) -#/ -$(c_targets): %.out: %.c - $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) - -#/ -# Runs compiled examples. -# -# @example -# make run -#/ -run: $(c_targets) - $(QUIET) ./$< - -.PHONY: run - -#/ -# Removes generated files. -# -# @example -# make clean -#/ -clean: - $(QUIET) -rm -f *.o *.out - -.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/examples/c/example.c b/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/examples/c/example.c deleted file mode 100644 index dea764aecd42..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/examples/c/example.c +++ /dev/null @@ -1,31 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/math/base/special/gamma_lanczos_sum_expg_scaled.h" -#include - -int main( void ) { - const double x[] = { 4.0, -1.5, -0.5, 0.5 }; - - double y; - int i; - for ( i = 0; i < 4; i++ ) { - y = stdlib_base_gamma_lanczos_sum_expg_scaled( x[ i ] ); - printf( "gamma_lanczos_sum_expg_scaled(%lf) = %lf\n", x[ i ], y ); - } -} diff --git a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/include.gypi b/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/include.gypi deleted file mode 100644 index 575cb043c0bf..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled/include.gypi +++ /dev/null @@ -1,53 +0,0 @@ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# A GYP include file for building a Node.js native add-on. -# -# Main documentation: -# -# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md -# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md -{ - # Define variables to be used throughout the configuration for all targets: - 'variables': { - # Source directory: - 'src_dir': './src', - - # Include directories: - 'include_dirs': [ - ' - - -* * * - -
- -## C APIs - - - -
- -
- - - - - -
- -### Usage - -```c -#include "stdlib/math/base/special/gamma_lanczos_sum.h" -``` - -#### gamma_lanczos_sum( x ) - -Calculates the Lanczos sum for the approximation of the [gamma function][gamma-function]. - -```c -double out = gamma_lanczos_sum( 4.0 ); -// returns ~950.366 - -out = gamma_lanczos_sum( -1.5 ); -// returns ~1373366.245 -``` - -The function accepts the following arguments: - -- **x**: `[in] double` input value. - -```c -double gamma_lanczos_sum( const double x ); -``` - -
- - - - - -
- -
- - - - - -
- -### Examples - -```c -#include "stdlib/math/base/special/gamma_lanczos_sum.h" -#include -#include - -int main( void ) { - const double x[] = { 4.0, -1.5, -0.5, 0.5 }; - - double y; - int i; - for ( i = 0; i < 4; i++ ) { - y = stdlib_base_gamm_lanczos_sum( x[ i ] ); - printf( "gamm_lanczos_sum(%lf) = %lf\n", x[ i ], y ); - } -} -``` - -
- - - -
- - -
diff --git a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum/benchmark/c/native/Makefile b/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum/benchmark/c/native/Makefile deleted file mode 100644 index f69e9da2b4d3..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum/benchmark/c/native/Makefile +++ /dev/null @@ -1,146 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# VARIABLES # - -ifndef VERBOSE - QUIET := @ -else - QUIET := -endif - -# Determine the OS ([1][1], [2][2]). -# -# [1]: https://en.wikipedia.org/wiki/Uname#Examples -# [2]: http://stackoverflow.com/a/27776822/2225624 -OS ?= $(shell uname) -ifneq (, $(findstring MINGW,$(OS))) - OS := WINNT -else -ifneq (, $(findstring MSYS,$(OS))) - OS := WINNT -else -ifneq (, $(findstring CYGWIN,$(OS))) - OS := WINNT -else -ifneq (, $(findstring Windows_NT,$(OS))) - OS := WINNT -endif -endif -endif -endif - -# Define the program used for compiling C source files: -ifdef C_COMPILER - CC := $(C_COMPILER) -else - CC := gcc -endif - -# Define the command-line options when compiling C files: -CFLAGS ?= \ - -std=c99 \ - -O3 \ - -Wall \ - -pedantic - -# Determine whether to generate position independent code ([1][1], [2][2]). -# -# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options -# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option -ifeq ($(OS), WINNT) - fPIC ?= -else - fPIC ?= -fPIC -endif - -# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): -INCLUDE ?= - -# List of source files: -SOURCE_FILES ?= - -# List of libraries (e.g., `-lopenblas -lpthread`): -LIBRARIES ?= - -# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): -LIBPATH ?= - -# List of C targets: -c_targets := benchmark.out - - -# RULES # - -#/ -# Compiles source files. -# -# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) -# @param {string} [CFLAGS] - C compiler options -# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) -# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) -# @param {string} [SOURCE_FILES] - list of source files -# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) -# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) -# -# @example -# make -# -# @example -# make all -#/ -all: $(c_targets) - -.PHONY: all - -#/ -# Compiles C source files. -# -# @private -# @param {string} CC - C compiler (e.g., `gcc`) -# @param {string} CFLAGS - C compiler options -# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) -# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) -# @param {string} SOURCE_FILES - list of source files -# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) -# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) -#/ -$(c_targets): %.out: %.c - $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) - -#/ -# Runs compiled benchmarks. -# -# @example -# make run -#/ -run: $(c_targets) - $(QUIET) ./$< - -.PHONY: run - -#/ -# Removes generated files. -# -# @example -# make clean -#/ -clean: - $(QUIET) -rm -f *.o *.out - -.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum/benchmark/c/native/benchmark.c deleted file mode 100644 index 61738e498d7c..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum/benchmark/c/native/benchmark.c +++ /dev/null @@ -1,136 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/** -* Benchmark `gamma_lanczos_sum`. -*/ -#include "stdlib/math/base/special/gamma_lanczos_sum.h" -#include -#include -#include -#include -#include - -#define NAME "gamma_lanczos_sum" -#define ITERATIONS 1000000 -#define REPEATS 3 - -/** -* Prints the TAP version. -*/ -void print_version() { - printf( "TAP version 13\n" ); -} - -/** -* Prints the TAP summary. -* -* @param total total number of tests -* @param passing total number of passing tests -*/ -void print_summary( int total, int passing ) { - printf( "#\n" ); - printf( "1..%d\n", total ); // TAP plan - printf( "# total %d\n", total ); - printf( "# pass %d\n", passing ); - printf( "#\n" ); - printf( "# ok\n" ); -} - -/** -* Prints benchmarks results. -* -* @param elapsed elapsed time in seconds -*/ -void print_results( double elapsed ) { - double rate = (double)ITERATIONS / elapsed; - printf( " ---\n" ); - printf( " iterations: %d\n", ITERATIONS ); - printf( " elapsed: %0.9f\n", elapsed ); - printf( " rate: %0.9f\n", rate ); - printf( " ...\n" ); -} - -/** -* Returns a clock time. -* -* @return clock time -*/ -double tic() { - struct timeval now; - gettimeofday( &now, NULL ); - return (double)now.tv_sec + (double)now.tv_usec / 1.0e6; -} - -/** -* Generates a random number on the interval [0,1]. -* -* @return random number -*/ -double rand_double() { - int r = rand(); - return (double)r / ( (double)RAND_MAX + 1.0 ); -} - -/** -* Runs a benchmark. -* -* @return elapsed time in seconds -*/ -double benchmark() { - double elapsed; - double x; - double y; - double t; - int i; - - t = tic(); - for ( i = 0; i < ITERATIONS; i++ ) { - x = ( 100.0 * rand_double() ) - 50.0; - y = stdlib_base_gamma_lanczos_sum( x ); - if ( y != y ) { - printf( "should not return NaN\n" ); - break; - } - } - elapsed = tic() - t; - if ( y != y ) { - printf( "should not return NaN\n" ); - } - return elapsed; -} - -/** -* Main execution sequence. -*/ -int main( void ) { - double elapsed; - int i; - - // Use the current time to seed the random number generator: - srand( time( NULL ) ); - - print_version(); - for ( i = 0; i < REPEATS; i++ ) { - printf( "# c::native::%s\n", NAME ); - elapsed = benchmark(); - print_results( elapsed ); - printf( "ok %d benchmark finished\n", i+1 ); - } - print_summary( REPEATS, REPEATS ); -} diff --git a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum/binding.gyp b/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum/binding.gyp deleted file mode 100644 index ec3992233442..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum/binding.gyp +++ /dev/null @@ -1,170 +0,0 @@ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# A `.gyp` file for building a Node.js native add-on. -# -# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md -# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md -{ - # List of files to include in this file: - 'includes': [ - './include.gypi', - ], - - # Define variables to be used throughout the configuration for all targets: - 'variables': { - # Target name should match the add-on export name: - 'addon_target_name%': 'addon', - - # Set variables based on the host OS: - 'conditions': [ - [ - 'OS=="win"', - { - # Define the object file suffix: - 'obj': 'obj', - }, - { - # Define the object file suffix: - 'obj': 'o', - } - ], # end condition (OS=="win") - ], # end conditions - }, # end variables - - # Define compile targets: - 'targets': [ - - # Target to generate an add-on: - { - # The target name should match the add-on export name: - 'target_name': '<(addon_target_name)', - - # Define dependencies: - 'dependencies': [], - - # Define directories which contain relevant include headers: - 'include_dirs': [ - # Local include directory: - '<@(include_dirs)', - ], - - # List of source files: - 'sources': [ - '<@(src_files)', - ], - - # Settings which should be applied when a target's object files are used as linker input: - 'link_settings': { - # Define libraries: - 'libraries': [ - '<@(libraries)', - ], - - # Define library directories: - 'library_dirs': [ - '<@(library_dirs)', - ], - }, - - # C/C++ compiler flags: - 'cflags': [ - # Enable commonly used warning options: - '-Wall', - - # Aggressive optimization: - '-O3', - ], - - # C specific compiler flags: - 'cflags_c': [ - # Specify the C standard to which a program is expected to conform: - '-std=c99', - ], - - # C++ specific compiler flags: - 'cflags_cpp': [ - # Specify the C++ standard to which a program is expected to conform: - '-std=c++11', - ], - - # Linker flags: - 'ldflags': [], - - # Apply conditions based on the host OS: - 'conditions': [ - [ - 'OS=="mac"', - { - # Linker flags: - 'ldflags': [ - '-undefined dynamic_lookup', - '-Wl,-no-pie', - '-Wl,-search_paths_first', - ], - }, - ], # end condition (OS=="mac") - [ - 'OS!="win"', - { - # C/C++ flags: - 'cflags': [ - # Generate platform-independent code: - '-fPIC', - ], - }, - ], # end condition (OS!="win") - ], # end conditions - }, # end target <(addon_target_name) - - # Target to copy a generated add-on to a standard location: - { - 'target_name': 'copy_addon', - - # Declare that the output of this target is not linked: - 'type': 'none', - - # Define dependencies: - 'dependencies': [ - # Require that the add-on be generated before building this target: - '<(addon_target_name)', - ], - - # Define a list of actions: - 'actions': [ - { - 'action_name': 'copy_addon', - 'message': 'Copying addon...', - - # Explicitly list the inputs in the command-line invocation below: - 'inputs': [], - - # Declare the expected outputs: - 'outputs': [ - '<(addon_output_dir)/<(addon_target_name).node', - ], - - # Define the command-line invocation: - 'action': [ - 'cp', - '<(PRODUCT_DIR)/<(addon_target_name).node', - '<(addon_output_dir)/<(addon_target_name).node', - ], - }, - ], # end actions - }, # end target copy_addon - ], # end targets -} diff --git a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum/examples/c/Makefile b/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum/examples/c/Makefile deleted file mode 100644 index 6aed70daf167..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum/examples/c/Makefile +++ /dev/null @@ -1,146 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# VARIABLES # - -ifndef VERBOSE - QUIET := @ -else - QUIET := -endif - -# Determine the OS ([1][1], [2][2]). -# -# [1]: https://en.wikipedia.org/wiki/Uname#Examples -# [2]: http://stackoverflow.com/a/27776822/2225624 -OS ?= $(shell uname) -ifneq (, $(findstring MINGW,$(OS))) - OS := WINNT -else -ifneq (, $(findstring MSYS,$(OS))) - OS := WINNT -else -ifneq (, $(findstring CYGWIN,$(OS))) - OS := WINNT -else -ifneq (, $(findstring Windows_NT,$(OS))) - OS := WINNT -endif -endif -endif -endif - -# Define the program used for compiling C source files: -ifdef C_COMPILER - CC := $(C_COMPILER) -else - CC := gcc -endif - -# Define the command-line options when compiling C files: -CFLAGS ?= \ - -std=c99 \ - -O3 \ - -Wall \ - -pedantic - -# Determine whether to generate position independent code ([1][1], [2][2]). -# -# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options -# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option -ifeq ($(OS), WINNT) - fPIC ?= -else - fPIC ?= -fPIC -endif - -# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): -INCLUDE ?= - -# List of source files: -SOURCE_FILES ?= - -# List of libraries (e.g., `-lopenblas -lpthread`): -LIBRARIES ?= - -# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): -LIBPATH ?= - -# List of C targets: -c_targets := example.out - - -# RULES # - -#/ -# Compiles source files. -# -# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) -# @param {string} [CFLAGS] - C compiler options -# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) -# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) -# @param {string} [SOURCE_FILES] - list of source files -# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) -# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) -# -# @example -# make -# -# @example -# make all -#/ -all: $(c_targets) - -.PHONY: all - -#/ -# Compiles C source files. -# -# @private -# @param {string} CC - C compiler (e.g., `gcc`) -# @param {string} CFLAGS - C compiler options -# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) -# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) -# @param {string} SOURCE_FILES - list of source files -# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) -# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) -#/ -$(c_targets): %.out: %.c - $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) - -#/ -# Runs compiled examples. -# -# @example -# make run -#/ -run: $(c_targets) - $(QUIET) ./$< - -.PHONY: run - -#/ -# Removes generated files. -# -# @example -# make clean -#/ -clean: - $(QUIET) -rm -f *.o *.out - -.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum/examples/c/example.c b/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum/examples/c/example.c deleted file mode 100644 index 5e7c0f71e965..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum/examples/c/example.c +++ /dev/null @@ -1,31 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/math/base/special/gamma_lanczos_sum.h" -#include - -int main( void ) { - const double x[] = { 4.0, -1.5, -0.5, 0.5 }; - - double y; - int i; - for ( i = 0; i < 4; i++ ) { - y = stdlib_base_gamma_lanczos_sum( x[ i ] ); - printf( "gamma_lanczos_sum(%lf) = %lf\n", x[ i ], y ); - } -} diff --git a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum/include.gypi b/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum/include.gypi deleted file mode 100644 index 575cb043c0bf..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/gamma-lanczos-sum/include.gypi +++ /dev/null @@ -1,53 +0,0 @@ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# A GYP include file for building a Node.js native add-on. -# -# Main documentation: -# -# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md -# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md -{ - # Define variables to be used throughout the configuration for all targets: - 'variables': { - # Source directory: - 'src_dir': './src', - - # Include directories: - 'include_dirs': [ - ' - - -* * * - -
- -## C APIs - - - -
- -
- - - - - -
- -### Usage - -```c -#include "stdlib/math/base/special/nonfibonacci.h" -``` - -#### stdlib_base_nonfibonacci( x ) - -Computes the nth non-Fibonacci number. - -```c -double out = stdlib_base_nonfibonacci( 1 ); -// returns 4 - -out = stdlib_base_nonfibonacci( 2 ); -// returns 6 -``` - -The function accepts the following arguments: - -- **x**: `[in] int32_t` input value. - -```c -double stdlib_base_nonfibonacci( const int32_t x ); -``` - -
- - - - - -
- -
- - - - - -
- -### Examples - -```c -#include "stdlib/math/base/special/nonfibonacci.h" -#include -#include -int main( void ) { - int i; - for ( i = 1; i < 12; i++ ) { - double result = stdlib_base_nonfibonacci( i ); - printf( "x: %i => result: %lf", i , result ); - } -} -``` - -
- - - -
- - - * * * diff --git a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/base/special/nonfibonacci/benchmark/benchmark.native.js deleted file mode 100644 index 7fc665652b4f..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/benchmark/benchmark.native.js +++ /dev/null @@ -1,61 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2018 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var resolve = require( 'path' ).resolve; -var floor = require( '@stdlib/math/base/special/floor' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var pkg = require( '@stdlib/math/base/special/nonfibonacci/package.json' ).name; -var randu = require( '@stdlib/random/base/randu' ); -var tryRequire = require( '@stdlib/utils/try-require' ); -var bench = require( '@stdlib/bench' ); - - -// VARIABLES // - -var nonfibonacci = tryRequire( resolve( __dirname, './../lib/native.js' ) ); -var opts = { - 'skip': ( nonfibonacci instanceof Error ) -}; - - -// MAIN // - -bench( pkg+'::native', opts, function benchmark( b ) { - var x; - var y; - var i; - - b.tic(); - for ( i = 0; i < b.iterations; i++ ) { - x = floor( (randu()*100.0) + 1.0 ); - y = nonfibonacci( x ); - if ( isnan( y ) ) { - b.fail( 'should not return NaN' ); - } - } - b.toc(); - if ( isnan( y ) ) { - b.fail( 'should not return NaN' ); - } - b.pass( 'benchmark finished' ); - b.end(); -}); diff --git a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/benchmark/c/Makefile b/lib/node_modules/@stdlib/math/base/special/nonfibonacci/benchmark/c/Makefile new file mode 100644 index 000000000000..e4542b1e66e9 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/nonfibonacci/benchmark/c/Makefile @@ -0,0 +1,107 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2018 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +endif + +# Determine the OS: +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate [position independent code][1]: +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of C targets: +c_targets := benchmark.out + + +# TARGETS # + +# Default target. +# +# This target is the default target. + +all: $(c_targets) + +.PHONY: all + + +# Compile C source. +# +# This target compiles C source files. + +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) -o $@ $< -lm + + +# Run a benchmark. +# +# This target runs a benchmark. + +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + + +# Perform clean-up. +# +# This target removes generated files. + +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/math/base/special/nonfibonacci/benchmark/c/benchmark.c similarity index 86% rename from lib/node_modules/@stdlib/math/base/special/nonfibonacci/benchmark/c/native/benchmark.c rename to lib/node_modules/@stdlib/math/base/special/nonfibonacci/benchmark/c/benchmark.c index 93b1cf3595c8..c85bf33f1f14 100644 --- a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/benchmark/c/native/benchmark.c +++ b/lib/node_modules/@stdlib/math/base/special/nonfibonacci/benchmark/c/benchmark.c @@ -19,7 +19,6 @@ /** * Benchmark `nonfibonacci`. */ -#include "stdlib/math/base/special/nonfibonacci.h" #include #include #include @@ -86,6 +85,32 @@ double rand_double() { int r = rand(); return (double)r / ( (double)RAND_MAX + 1.0 ); } + +/** +* Computes the nth non-Fibonacci number. +* +* @param n Fibonacci number +* @return function result +*/ +double nonfibonacci( int n ) { + double sqrt5; + double lphi; + double phi; + double dn; + double a; + double b; + + phi = 1.618033988749895; + lphi = log( phi ); + + sqrt5 = sqrt( 5.0 ); + dn = (double)n + 1; + + a = log( dn*sqrt5 ) / lphi; + b = (sqrt5 * ( dn+a )) - 5.0 + (3.0/dn); + return floor( n + (log( b )/lphi) - 2.0 ); +} + /** * Runs a benchmark. * @@ -101,7 +126,7 @@ double benchmark() { t = tic(); for ( i = 0; i < ITERATIONS; i++ ) { x = (int)floor( (100.0*rand_double()) + 1.0 ); - y = stdlib_base_nonfibonacci( x ); + y = nonfibonacci( x ); if ( y < 0 ) { printf( "should return a nonnegative integer\n" ); break; diff --git a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/benchmark/c/native/Makefile b/lib/node_modules/@stdlib/math/base/special/nonfibonacci/benchmark/c/native/Makefile deleted file mode 100644 index 0ebf4545e1a9..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/benchmark/c/native/Makefile +++ /dev/null @@ -1,146 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# VARIABLES # - -ifndef VERBOSE - QUIET := @ -else - QUIET := -endif - -# Determine the OS ([1][1], [2][2]). -# -# [1]: https://en.wikipedia.org/wiki/Uname#Examples -# [2]: http://stackoverflow.com/a/27776822/2225624 -OS ?= $(shell uname) -ifneq (, $(findstring MINGW,$(OS))) - OS := WINNT -else -ifneq (, $(findstring MSYS,$(OS))) - OS := WINNT -else -ifneq (, $(findstring CYGWIN,$(OS))) - OS := WINNT -else -ifneq (, $(findstring Windows_NT,$(OS))) - OS := WINNT -endif -endif -endif -endif - -# Define the program used for compiling C source files: -ifdef C_COMPILER - CC := $(C_COMPILER) -else - CC := gcc -endif - -# Define the command-line options when compiling C files: -CFLAGS ?= \ - -std=c99 \ - -O3 \ - -Wall \ - -pedantic - -# Determine whether to generate position independent code ([1][1], [2][2]). -# -# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options -# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option -ifeq ($(OS), WINNT) - fPIC ?= -else - fPIC ?= -fPIC -endif - -# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): -INCLUDE ?= - -# List of source files: -SOURCE_FILES ?= - -# List of libraries (e.g., `-lopenblas -lpthread`): -LIBRARIES ?= - -# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): -LIBPATH ?= - -# List of C targets: -c_targets := benchmark.out - - -# RULES # - -#/ -# Compiles source files. -# -# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) -# @param {string} [CFLAGS] - C compiler options -# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) -# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) -# @param {string} [SOURCE_FILES] - list of source files -# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) -# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) -# -# @example -# make -# -# @example -# make all -#/ -all: $(c_targets) - -.PHONY: all - -#/ -# Compiles C source files. -# -# @private -# @param {string} CC - C compiler (e.g., `gcc`) -# @param {string} CFLAGS - C compiler options -# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) -# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) -# @param {string} SOURCE_FILES - list of source files -# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) -# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) -#/ -$(c_targets): %.out: %.c - $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) - -#/ -# Runs compiled benchmarks. -# -# @example -# make run -#/ -run: $(c_targets) - $(QUIET) ./$< - -.PHONY: run - -#/ -# Removes generated files. -# -# @example -# make clean -#/ -clean: - $(QUIET) -rm -f *.o *.out - -.PHONY: clean \ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/binding.gyp b/lib/node_modules/@stdlib/math/base/special/nonfibonacci/binding.gyp deleted file mode 100644 index ec3992233442..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/binding.gyp +++ /dev/null @@ -1,170 +0,0 @@ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# A `.gyp` file for building a Node.js native add-on. -# -# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md -# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md -{ - # List of files to include in this file: - 'includes': [ - './include.gypi', - ], - - # Define variables to be used throughout the configuration for all targets: - 'variables': { - # Target name should match the add-on export name: - 'addon_target_name%': 'addon', - - # Set variables based on the host OS: - 'conditions': [ - [ - 'OS=="win"', - { - # Define the object file suffix: - 'obj': 'obj', - }, - { - # Define the object file suffix: - 'obj': 'o', - } - ], # end condition (OS=="win") - ], # end conditions - }, # end variables - - # Define compile targets: - 'targets': [ - - # Target to generate an add-on: - { - # The target name should match the add-on export name: - 'target_name': '<(addon_target_name)', - - # Define dependencies: - 'dependencies': [], - - # Define directories which contain relevant include headers: - 'include_dirs': [ - # Local include directory: - '<@(include_dirs)', - ], - - # List of source files: - 'sources': [ - '<@(src_files)', - ], - - # Settings which should be applied when a target's object files are used as linker input: - 'link_settings': { - # Define libraries: - 'libraries': [ - '<@(libraries)', - ], - - # Define library directories: - 'library_dirs': [ - '<@(library_dirs)', - ], - }, - - # C/C++ compiler flags: - 'cflags': [ - # Enable commonly used warning options: - '-Wall', - - # Aggressive optimization: - '-O3', - ], - - # C specific compiler flags: - 'cflags_c': [ - # Specify the C standard to which a program is expected to conform: - '-std=c99', - ], - - # C++ specific compiler flags: - 'cflags_cpp': [ - # Specify the C++ standard to which a program is expected to conform: - '-std=c++11', - ], - - # Linker flags: - 'ldflags': [], - - # Apply conditions based on the host OS: - 'conditions': [ - [ - 'OS=="mac"', - { - # Linker flags: - 'ldflags': [ - '-undefined dynamic_lookup', - '-Wl,-no-pie', - '-Wl,-search_paths_first', - ], - }, - ], # end condition (OS=="mac") - [ - 'OS!="win"', - { - # C/C++ flags: - 'cflags': [ - # Generate platform-independent code: - '-fPIC', - ], - }, - ], # end condition (OS!="win") - ], # end conditions - }, # end target <(addon_target_name) - - # Target to copy a generated add-on to a standard location: - { - 'target_name': 'copy_addon', - - # Declare that the output of this target is not linked: - 'type': 'none', - - # Define dependencies: - 'dependencies': [ - # Require that the add-on be generated before building this target: - '<(addon_target_name)', - ], - - # Define a list of actions: - 'actions': [ - { - 'action_name': 'copy_addon', - 'message': 'Copying addon...', - - # Explicitly list the inputs in the command-line invocation below: - 'inputs': [], - - # Declare the expected outputs: - 'outputs': [ - '<(addon_output_dir)/<(addon_target_name).node', - ], - - # Define the command-line invocation: - 'action': [ - 'cp', - '<(PRODUCT_DIR)/<(addon_target_name).node', - '<(addon_output_dir)/<(addon_target_name).node', - ], - }, - ], # end actions - }, # end target copy_addon - ], # end targets -} diff --git a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/examples/c/Makefile b/lib/node_modules/@stdlib/math/base/special/nonfibonacci/examples/c/Makefile deleted file mode 100644 index 6aed70daf167..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/examples/c/Makefile +++ /dev/null @@ -1,146 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# VARIABLES # - -ifndef VERBOSE - QUIET := @ -else - QUIET := -endif - -# Determine the OS ([1][1], [2][2]). -# -# [1]: https://en.wikipedia.org/wiki/Uname#Examples -# [2]: http://stackoverflow.com/a/27776822/2225624 -OS ?= $(shell uname) -ifneq (, $(findstring MINGW,$(OS))) - OS := WINNT -else -ifneq (, $(findstring MSYS,$(OS))) - OS := WINNT -else -ifneq (, $(findstring CYGWIN,$(OS))) - OS := WINNT -else -ifneq (, $(findstring Windows_NT,$(OS))) - OS := WINNT -endif -endif -endif -endif - -# Define the program used for compiling C source files: -ifdef C_COMPILER - CC := $(C_COMPILER) -else - CC := gcc -endif - -# Define the command-line options when compiling C files: -CFLAGS ?= \ - -std=c99 \ - -O3 \ - -Wall \ - -pedantic - -# Determine whether to generate position independent code ([1][1], [2][2]). -# -# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options -# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option -ifeq ($(OS), WINNT) - fPIC ?= -else - fPIC ?= -fPIC -endif - -# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): -INCLUDE ?= - -# List of source files: -SOURCE_FILES ?= - -# List of libraries (e.g., `-lopenblas -lpthread`): -LIBRARIES ?= - -# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): -LIBPATH ?= - -# List of C targets: -c_targets := example.out - - -# RULES # - -#/ -# Compiles source files. -# -# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) -# @param {string} [CFLAGS] - C compiler options -# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) -# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) -# @param {string} [SOURCE_FILES] - list of source files -# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) -# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) -# -# @example -# make -# -# @example -# make all -#/ -all: $(c_targets) - -.PHONY: all - -#/ -# Compiles C source files. -# -# @private -# @param {string} CC - C compiler (e.g., `gcc`) -# @param {string} CFLAGS - C compiler options -# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) -# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) -# @param {string} SOURCE_FILES - list of source files -# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) -# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) -#/ -$(c_targets): %.out: %.c - $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) - -#/ -# Runs compiled examples. -# -# @example -# make run -#/ -run: $(c_targets) - $(QUIET) ./$< - -.PHONY: run - -#/ -# Removes generated files. -# -# @example -# make clean -#/ -clean: - $(QUIET) -rm -f *.o *.out - -.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/include.gypi b/lib/node_modules/@stdlib/math/base/special/nonfibonacci/include.gypi deleted file mode 100644 index c6495fc1da3f..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/include.gypi +++ /dev/null @@ -1,53 +0,0 @@ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# A GYP include file for building a Node.js native add-on. -# -# Main documentation: -# -# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md -# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md -{ - # Define variables to be used throughout the configuration for all targets: - 'variables': { - # Source directory: - 'src_dir': './src', - - # Include directories: - 'include_dirs': [ - '. -* - Farhi, Bakir. 2011. "An explicit formula generating the non-Fibonacci numbers." _arXiv_ abs/1105.1127 \[Math.NT\] (May): 1–5. . -* -* @param {NonNegativeInteger} n - the non-Fibonacci number to compute -* @returns {NonNegativeInteger} non-Fibonacci number -* -* @example -* var v = nonfibonacci( 1 ); -* // returns 4 -* -* @example -* var v = nonfibonacci( 2 ); -* // returns 6 -* -* @example -* var v = nonfibonacci( 3 ); -* // returns 7 -* -* @example -* var v = nonfibonacci( NaN ); -* // returns NaN -* -* @example -* var v = nonfibonacci( 3.14 ); -* // returns NaN -* -* @example -* var v = nonfibonacci( -1 ); -* // returns NaN -*/ -function nonfibonacci( n ) { - if ( isInteger( n ) === false ) { - return NaN; - } - return addon( n ); -} - - -// EXPORTS // - -module.exports = nonfibonacci; diff --git a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/manifest.json b/lib/node_modules/@stdlib/math/base/special/nonfibonacci/manifest.json deleted file mode 100644 index 322b087d791e..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/manifest.json +++ /dev/null @@ -1,89 +0,0 @@ -{ - "options": { - "task": "build" - }, - "fields": [ - { - "field": "src", - "resolve": true, - "relative": true - }, - { - "field": "include", - "resolve": true, - "relative": true - }, - { - "field": "libraries", - "resolve": false, - "relative": false - }, - { - "field": "libpath", - "resolve": true, - "relative": false - } - ], - "confs": [ - { - "task": "build", - "src": [ - "./src/main.c" - ], - "include": [ - "./include" - ], - "libraries": [], - "libpath": [], - "dependencies": [ - "@stdlib/constants/float64/nan", - "@stdlib/constants/float64/phi", - "@stdlib/constants/float64/pinf", - "@stdlib/math/base/assert/is-integer", - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/floor", - "@stdlib/math/base/special/ln" - ] - }, - { - "task": "benchmark", - "src": [ - "./src/main.c" - ], - "include": [ - "./include" - ], - "libraries": [], - "libpath": [], - "dependencies": [ - "@stdlib/constants/float64/nan", - "@stdlib/constants/float64/phi", - "@stdlib/constants/float64/pinf", - "@stdlib/math/base/assert/is-integer", - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/floor", - "@stdlib/math/base/special/ln" - ] - }, - { - "task": "examples", - "src": [ - "./src/main.c" - ], - "include": [ - "./include" - ], - "libraries": [], - "libpath": [], - "dependencies": [ - "@stdlib/constants/float64/nan", - "@stdlib/constants/float64/phi", - "@stdlib/constants/float64/pinf", - "@stdlib/math/base/assert/is-integer", - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/floor", - "@stdlib/math/base/special/ln" - ] - } - ] -} \ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/package.json b/lib/node_modules/@stdlib/math/base/special/nonfibonacci/package.json index 1d007b653059..35cf48b491f5 100644 --- a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/package.json +++ b/lib/node_modules/@stdlib/math/base/special/nonfibonacci/package.json @@ -14,14 +14,11 @@ } ], "main": "./lib", - "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", - "include": "./include", "lib": "./lib", - "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/src/Makefile b/lib/node_modules/@stdlib/math/base/special/nonfibonacci/src/Makefile deleted file mode 100644 index 81bb164286c3..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/src/Makefile +++ /dev/null @@ -1,70 +0,0 @@ -#/ -# @license Apache-2.0 -# -# Copyright (c) 2024 The Stdlib Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -#/ - -# VARIABLES # - -ifndef VERBOSE - QUIET := @ -else - QUIET := -endif - -# Determine the OS ([1][1], [2][2]). -# -# [1]: https://en.wikipedia.org/wiki/Uname#Examples -# [2]: http://stackoverflow.com/a/27776822/2225624 -OS ?= $(shell uname) -ifneq (, $(findstring MINGW,$(OS))) - OS := WINNT -else -ifneq (, $(findstring MSYS,$(OS))) - OS := WINNT -else -ifneq (, $(findstring CYGWIN,$(OS))) - OS := WINNT -else -ifneq (, $(findstring Windows_NT,$(OS))) - OS := WINNT -endif -endif -endif -endif - - -# RULES # - -#/ -# Removes generated files for building an add-on. -# -# @example -# make clean-addon -#/ -clean-addon: - $(QUIET) -rm -f *.o *.node - -.PHONY: clean-addon - -#/ -# Removes generated files. -# -# @example -# make clean -#/ -clean: clean-addon - -.PHONY: clean \ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/src/addon.c b/lib/node_modules/@stdlib/math/base/special/nonfibonacci/src/addon.c deleted file mode 100644 index eb018398169f..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/src/addon.c +++ /dev/null @@ -1,22 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/math/base/special/nonfibonacci.h" -#include "stdlib/math/base/napi/unary.h" - -STDLIB_MATH_BASE_NAPI_MODULE_I_D( stdlib_base_nonfibonacci ) diff --git a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/src/main.c b/lib/node_modules/@stdlib/math/base/special/nonfibonacci/src/main.c deleted file mode 100644 index 7ae39072d1c7..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/src/main.c +++ /dev/null @@ -1,81 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include - -#include "stdlib/constants/float64/nan.h" -#include "stdlib/constants/float64/phi.h" -#include "stdlib/constants/float64/pinf.h" -#include "stdlib/math/base/assert/is_integer.h" -#include "stdlib/math/base/assert/is_nan.h" -#include "stdlib/math/base/special/floor.h" -#include "stdlib/math/base/special/ln.h" - -#define SQRT5 2.23606797749979 -#define LN_PHI 0.48121182506 - -/** -* Computes the nth non-Fibonacci number. -* -* @param x input value -* @return output value -* -* @example -* double y = stdlib_base_nonfibonacci( 2 ); -* // returns 6.0 -* -* @example -* double y = stdlib_base_nonfibonacci( 1 ); -* // returns 4.0 -* -* @example -* double y = stdlib_base_nonfibonacci( 3 ); -* // returns 7.0 -* -* @example -* double y = stdlib_base_nonfibonacci( NaN ); -* // returns NaN -* -* @example -* double y = stdlib_base_nonfibonacci( 3.14 ); -* // returns NaN -* -* @example -* double y = stdlib_base_nonfibonacci( -1 ); -* // returns NaN -*/ -double stdlib_base_nonfibonacci( const int32_t n ) { - double a; - double b; - int32_t mut_n = n; - - if ( - stdlib_base_is_nan( n ) || - !stdlib_base_is_integer( n ) || - n < 1.0 || - n == STDLIB_CONSTANT_FLOAT64_PINF - ) { - return STDLIB_CONSTANT_FLOAT64_NAN; - } - - mut_n += 1; - a = stdlib_base_ln( mut_n * SQRT5 ) / LN_PHI; - b = stdlib_base_ln( (SQRT5 * (mut_n + a)) - 5.0 + (3.0 / mut_n) ) / LN_PHI; - - return stdlib_base_floor( mut_n + b - 2.0 ); -} diff --git a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/nonfibonacci/test/test.native.js deleted file mode 100644 index 7a685dc47f99..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/nonfibonacci/test/test.native.js +++ /dev/null @@ -1,93 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var resolve = require( 'path' ).resolve; -var tape = require( 'tape' ); -var PINF = require( '@stdlib/constants/float64/pinf' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var tryRequire = require( '@stdlib/utils/try-require' ); - - -// VARIABLES // - -var nonfibonacci = tryRequire( resolve( __dirname, './../lib/native.js' ) ); -var opts = { - 'skip': ( nonfibonacci instanceof Error ) -}; - - -// FIXTURES // - -// Expected values are from https://oeis.org/A001690: -var expected = require( './fixtures/expected.json' ); - - -// TESTS // - -tape( 'main export is a function', opts, function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof nonfibonacci, 'function', 'main export is a function' ); - t.end(); -}); - -tape( 'if provided `NaN`, the function returns `NaN`', opts, function test( t ) { - var n = nonfibonacci( NaN ); - t.strictEqual( isnan( n ), true, 'returns NaN when provided a NaN' ); - t.end(); -}); - -tape( 'if provided `+infinity`, the function returns `NaN`', opts, function test( t ) { - var n = nonfibonacci( PINF ); - t.strictEqual( isnan( n ), true, 'returns NaN' ); - t.end(); -}); - -tape( 'if provided a number less than 1, the function returns `NaN`', opts, function test( t ) { - var n; - var i; - - t.strictEqual( isnan( nonfibonacci( -3.14 ) ), true, 'returns NaN' ); - - for ( i = 0; i > -100; i-- ) { - n = nonfibonacci( i ); - t.strictEqual( isnan( n ), true, 'returns NaN when provided ' + i ); - } - t.end(); -}); - -tape( 'if provided a non-integer, the function returns `NaN`', opts, function test( t ) { - var n = nonfibonacci( 3.14 ); - - t.strictEqual( isnan( n ), true, 'returns NaN' ); - t.end(); -}); - -tape( 'the function returns the nth non-Fibonacci number', opts, function test( t ) { - var v; - var i; - - for ( i = 1; i < expected.length; i++ ) { - v = nonfibonacci( i ); - t.strictEqual( v, expected[ i-1 ], 'returns the '+i+'th non-Fibonacci number' ); - } - t.end(); -}); diff --git a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile-c/README.md b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile-c/README.md index 38064341f80f..04ce49e4a80c 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile-c/README.md +++ b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile-c/README.md @@ -123,14 +123,29 @@ static float polyval123( const float x ) { ```javascript -var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float64Array = require( '@stdlib/array/float64' ); var compile = require( '@stdlib/math/base/tools/evalpoly-compile-c' ); -// Create an array of random coefficients: -var coef = discreteUniform( 10, -100, 100 ); +var coef; +var sign; +var str; +var i; + +// Create an array of random coefficients... +coef = new Float64Array( 10 ); +for ( i = 0; i < coef.length; i++ ) { + if ( randu() < 0.5 ) { + sign = -1.0; + } else { + sign = 1.0; + } + coef[ i ] = sign * round( randu()*100.0 ); +} // Compile a function for evaluating a polynomial: -var str = compile( coef ); +str = compile( coef ); console.log( str ); ``` diff --git a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile-c/docs/types/index.d.ts b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile-c/docs/types/index.d.ts index 511529158217..f31e964b9d41 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile-c/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile-c/docs/types/index.d.ts @@ -18,10 +18,6 @@ // TypeScript Version: 4.1 -/// - -import { Collection } from '@stdlib/types/array'; - /** * Interface describing function options. */ @@ -29,7 +25,7 @@ interface Options { /** * Input value floating-point data type (e.g., `double` or `float`). Default: `'double'`. */ - dtype?: 'double' | 'float'; + dtype?: string; /** * Function name. Default: `'evalpoly'`. @@ -48,7 +44,7 @@ interface Options { * var str = compile( [ 3.0, 2.0, 1.0 ] ); * // returns */ -declare function compile( c: Collection, options?: Options ): string; +declare function compile( c: Array, options?: Options ): string; // EXPORTS // diff --git a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile-c/docs/types/test.ts b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile-c/docs/types/test.ts index bf039a869971..6f8b55411de3 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile-c/docs/types/test.ts +++ b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile-c/docs/types/test.ts @@ -55,7 +55,7 @@ import compile = require( './index' ); compile( [ 3.0, 2.0, 1.0 ], ( x: number ): number => x ); // $ExpectError } -// The compiler throws an error if the function is provided an invalid `dtype` option... +// The compiler throws an error if the function is provided a `dtype` option which is not a string... { compile( [ 3.0, 2.0, 1.0 ], { 'dtype': true } ); // $ExpectError compile( [ 3.0, 2.0, 1.0 ], { 'dtype': false } ); // $ExpectError diff --git a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile-c/examples/index.js b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile-c/examples/index.js index 81b27f15dc1e..968b94ff51aa 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile-c/examples/index.js +++ b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile-c/examples/index.js @@ -19,7 +19,9 @@ 'use strict'; var resolve = require( 'path' ).resolve; -var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var compile = tryRequire( resolve( __dirname, '..', 'lib' ) ); @@ -30,10 +32,23 @@ if ( compile instanceof Error ) { } function main() { - // Create an array of random coefficients: - var coef = discreteUniform( 10, -100, 100 ); + var coef; + var sign; + var str; + var i; + + // Create an array of random coefficients... + coef = new Float64Array( 10 ); + for ( i = 0; i < coef.length; i++ ) { + if ( randu() < 0.5 ) { + sign = -1.0; + } else { + sign = 1.0; + } + coef[ i ] = sign * round( randu()*100.0 ); + } // Compile a function for evaluating a polynomial: - var str = compile( coef ); + str = compile( coef ); console.log( str ); } diff --git a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/README.md b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/README.md index 3241616b5486..c9e1081bbd21 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/README.md +++ b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/README.md @@ -36,20 +36,16 @@ limitations under the License. var compile = require( '@stdlib/math/base/tools/evalpoly-compile' ); ``` -#### compile( c\[, options] ) +#### compile( c ) -Compiles a module string containing an exported function which evaluates a [polynomial][@stdlib/math/base/tools/evalpoly] having coefficients `c`. +Compiles a module `string` containing an exported function which evaluates a [polynomial][@stdlib/math/base/tools/evalpoly] having coefficients `c`. ```javascript var str = compile( [ 3.0, 2.0, 1.0 ] ); // returns ``` -The function supports the following `options`: - -- **dtype**: input argument floating-point data type (e.g., `float64` or `float32`). Default: `'float64'`. - -In the example above, the output string would correspond to the following module: +In the example above, the output `string` would correspond to the following module: @@ -75,7 +71,7 @@ function evalpoly( x ) { if ( x === 0.0 ) { return 3.0; } - return 3.0 + (x * (2.0 + (x * 1.0))); + return 3.0 + (x * (2.0 + (x * 1.0))); // eslint-disable-line max-len } @@ -86,55 +82,6 @@ module.exports = evalpoly; The coefficients should be ordered in **ascending** degree, thus matching summation notation. -By default, the function assumes double-precision floating-point arithmetic. To emulate single-precision floating-point arithmetic, set the `dtype` option to `'float32'`. - -```javascript -var str = compile( [ 3.0, 2.0, 1.0 ], { - 'dtype': 'float32' -}); -// returns -``` - -In the previous example, the output string would correspond to the following module: - - - -```javascript -'use strict'; - -// MODULES // - -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); - - -// MAIN // - -/** -* Evaluates a polynomial. -* -* ## Notes -* -* - The implementation uses [Horner's rule][horners-method] for efficient computation. -* -* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method -* -* @private -* @param {number} x - value at which to evaluate the polynomial -* @returns {number} evaluated polynomial -*/ -function evalpoly( x ) { - if ( x === 0.0 ) { - return 3.0; - } - return float64ToFloat32(3.0 + float64ToFloat32(x * float64ToFloat32(2.0 + float64ToFloat32(x * 1.0)))); // eslint-disable-line max-len -} - - -// EXPORTS // - -module.exports = evalpoly; -``` -
@@ -156,14 +103,29 @@ module.exports = evalpoly; ```javascript -var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float64Array = require( '@stdlib/array/float64' ); var compile = require( '@stdlib/math/base/tools/evalpoly-compile' ); -// Create an array of random coefficients: -var coef = discreteUniform( 10, -100, 100 ); +var coef; +var sign; +var str; +var i; + +// Create an array of random coefficients... +coef = new Float64Array( 10 ); +for ( i = 0; i < coef.length; i++ ) { + if ( randu() < 0.5 ) { + sign = -1.0; + } else { + sign = 1.0; + } + coef[ i ] = sign * round( randu()*100.0 ); +} // Compile a module for evaluating a polynomial: -var str = compile( coef ); +str = compile( coef ); console.log( str ); ``` diff --git a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/docs/types/index.d.ts b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/docs/types/index.d.ts index 13765988138d..68b278d2590b 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/docs/types/index.d.ts @@ -18,32 +18,17 @@ // TypeScript Version: 4.1 -/// - -import { Collection } from '@stdlib/types/array'; - -/** -* Interface describing function options. -*/ -interface Options { - /** - * Input value floating-point data type (e.g., `float64` or `float32`). Default: `'float64'`. - */ - dtype?: 'float64' | 'float32'; -} - /** * Compiles a module string which exports a function for evaluating a polynomial. * * @param c - polynomial coefficients sorted in ascending degree -* @param options - function options * @returns module string exporting a function for evaluating a polynomial * * @example * var str = compile( [ 3.0, 2.0, 1.0 ] ); * // returns */ -declare function compile( c: Collection, options?: Options ): string; +declare function compile( c: Array ): string; // EXPORTS // diff --git a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/docs/types/test.ts b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/docs/types/test.ts index 93d3b80cb951..74506548e3dd 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/docs/types/test.ts +++ b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/docs/types/test.ts @@ -24,7 +24,6 @@ import compile = require( './index' ); // The function returns a string... { compile( [ 3.0, 2.0, 1.0 ] ); // $ExpectType string - compile( [ 3.0, 2.0, 1.0 ], { 'dtype': 'float32' } ); // $ExpectType string } // The compiler throws an error if the function is provided a first argument which is not an array of numbers... @@ -35,31 +34,6 @@ import compile = require( './index' ); compile( 123 ); // $ExpectError compile( {} ); // $ExpectError compile( ( x: number ): number => x ); // $ExpectError - - compile( true, {} ); // $ExpectError - compile( false, {} ); // $ExpectError - compile( 'abc', {} ); // $ExpectError - compile( 123, {} ); // $ExpectError - compile( {}, {} ); // $ExpectError - compile( ( x: number ): number => x, {} ); // $ExpectError -} - -// The compiler throws an error if the function is provided a second argument which is not an object... -{ - compile( [ 3.0, 2.0, 1.0 ], true ); // $ExpectError - compile( [ 3.0, 2.0, 1.0 ], false ); // $ExpectError - compile( [ 3.0, 2.0, 1.0 ], 'abc' ); // $ExpectError - compile( [ 3.0, 2.0, 1.0 ], 123 ); // $ExpectError - compile( [ 3.0, 2.0, 1.0 ], ( x: number ): number => x ); // $ExpectError -} - -// The compiler throws an error if the function is provided an invalid `dtype` option... -{ - compile( [ 3.0, 2.0, 1.0 ], { 'dtype': true } ); // $ExpectError - compile( [ 3.0, 2.0, 1.0 ], { 'dtype': false } ); // $ExpectError - compile( [ 3.0, 2.0, 1.0 ], { 'dtype': [] } ); // $ExpectError - compile( [ 3.0, 2.0, 1.0 ], { 'dtype': 123 } ); // $ExpectError - compile( [ 3.0, 2.0, 1.0 ], { 'dtype': ( x: number ): number => x } ); // $ExpectError } // The compiler throws an error if the function is provided an insufficient number of arguments... diff --git a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/examples/index.js b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/examples/index.js index 74c2c078cd22..472c4c458dcd 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/examples/index.js +++ b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/examples/index.js @@ -19,7 +19,9 @@ 'use strict'; var resolve = require( 'path' ).resolve; -var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var compile = tryRequire( resolve( __dirname, '..', 'lib' ) ); @@ -30,10 +32,23 @@ if ( compile instanceof Error ) { } function main() { - // Create an array of random coefficients: - var coef = discreteUniform( 10, -100, 100 ); + var coef; + var sign; + var str; + var i; + + // Create an array of random coefficients... + coef = new Float64Array( 10 ); + for ( i = 0; i < coef.length; i++ ) { + if ( randu() < 0.5 ) { + sign = -1.0; + } else { + sign = 1.0; + } + coef[ i ] = sign * round( randu()*100.0 ); + } // Compile a module for evaluating a polynomial: - var str = compile( coef ); + str = compile( coef ); console.log( str ); } diff --git a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/lib/main.js b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/lib/main.js index 5e4fe4829874..e610cd9b5ace 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/lib/main.js +++ b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/lib/main.js @@ -24,7 +24,6 @@ var join = require( 'path' ).join; var readFile = require( '@stdlib/fs/read-file' ).sync; var replace = require( '@stdlib/string/replace' ); var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; -var Float32Array = require( '@stdlib/array/float32' ); // VARIABLES // @@ -36,15 +35,9 @@ var dir = join( __dirname, 'templates' ); // Templates: var SINGLE_COEFFICIENT_TEMPLATE = readFile( join( dir, 'single_coefficient.js.txt' ), opts ); // eslint-disable-line id-length - var EVALPOLY_TEMPLATE = readFile( join( dir, 'evalpoly.js.txt' ), opts ); -var EVALPOLY_FLOAT32_TEMPLATE = readFile( join( dir, 'evalpoly.float32.js.txt' ), opts ); - var EMPTY_TEMPLATE = readFile( join( dir, 'empty.js.txt' ), opts ); - var LOOP_TEMPLATE = readFile( join( dir, 'loop.js.txt' ), opts ); -var LOOP_FLOAT32_TEMPLATE = readFile( join( dir, 'loop.float32.js.txt' ), opts ); - var MAX_CHARS = 68; // max-len (80) - chars already in line ('tab': 4, 'return ': 7, ';': 1) @@ -54,39 +47,25 @@ var MAX_CHARS = 68; // max-len (80) - chars already in line ('tab': 4, 'return ' * Compiles a module string which exports a function for evaluating a polynomial. * * @param {NumericArray} c - polynomial coefficients sorted in ascending degree -* @param {Options} [options] - function options -* @param {string} [options.dtype='float64'] - input value floating-point data type * @returns {string} module string exporting a function for evaluating a polynomial * * @example * var str = compile( [ 3.0, 2.0, 1.0 ] ); * // returns */ -function compile( c, options ) { +function compile( c ) { var horner; - var opts; - var tmpl; var str; var n; var m; var i; - opts = { - 'dtype': 'float64' - }; - if ( arguments.length > 1 ) { - opts.dtype = options.dtype || opts.dtype; - } n = c.length; // If no coefficients, the function always returns 0... if ( n === 0 ) { return EMPTY_TEMPLATE; } - if ( opts.dtype === 'float32' ) { - // Ensure that coefficients have been converted to single-precision: - c = new Float32Array( c ); - } // If only one coefficient, the function always returns that coefficient... if ( n === 1 ) { str = c[ 0 ].toString(); @@ -109,34 +88,17 @@ function compile( c, options ) { str += ',\n'; } } - if ( opts.dtype === 'float32' ) { - tmpl = LOOP_FLOAT32_TEMPLATE; - } else { - tmpl = LOOP_TEMPLATE; - } - return replace( tmpl, '{{coefficients}}', str ); + return replace( LOOP_TEMPLATE, '{{coefficients}}', str ); } // If more than one coefficient, apply Horner's method... - if ( opts.dtype === 'float32' ) { - horner = 'float64ToFloat32('; - } else { - horner = ''; - } - horner += c[ 0 ].toString(); + horner = c[ 0 ].toString(); if ( isInteger( c[ 0 ] ) ) { horner += '.0'; } for ( i = 1; i < n; i++ ) { - if ( opts.dtype === 'float32' ) { - horner += ' + float64ToFloat32(x * '; - if ( i < m ) { - horner += 'float64ToFloat32('; - } - } else { - horner += ' + (x * '; - if ( i < m ) { - horner += '('; - } + horner += ' + (x * '; + if ( i < m ) { + horner += '('; } horner += c[ i ].toString(); if ( isInteger( c[ i ] ) ) { @@ -147,19 +109,11 @@ function compile( c, options ) { for ( i = 0; i < (2*(n-1))-1; i++ ) { horner += ')'; } - if ( opts.dtype === 'float32' ) { - horner += ')'; - } str = c[ 0 ].toString(); if ( isInteger( c[ 0 ] ) ) { str += '.0'; } - if ( opts.dtype === 'float32' ) { - tmpl = EVALPOLY_FLOAT32_TEMPLATE; - } else { - tmpl = EVALPOLY_TEMPLATE; - } - str = replace( tmpl, '{{coefficient}}', str ); + str = replace( EVALPOLY_TEMPLATE, '{{coefficient}}', str ); str = replace( str, '{{horner}}', horner ); return replace( str, '{{eslint}}', ( horner.length > MAX_CHARS ) ? ' // eslint-disable-line max-len' : '' ); } diff --git a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/lib/templates/evalpoly.float32.js.txt b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/lib/templates/evalpoly.float32.js.txt deleted file mode 100644 index c3964fd593f2..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/lib/templates/evalpoly.float32.js.txt +++ /dev/null @@ -1,33 +0,0 @@ -'use strict'; - -// MODULES // - -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); - - -// MAIN // - -/** -* Evaluates a polynomial. -* -* ## Notes -* -* - The implementation uses [Horner's rule][horners-method] for efficient computation. -* -* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method -* -* @private -* @param {number} x - value at which to evaluate the polynomial -* @returns {number} evaluated polynomial -*/ -function evalpoly( x ) { - if ( x === 0.0 ) { - return {{coefficient}}; - } - return {{horner}};{{eslint}} -} - - -// EXPORTS // - -module.exports = evalpoly; diff --git a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/lib/templates/loop.float32.js.txt b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/lib/templates/loop.float32.js.txt deleted file mode 100644 index 848985d058f0..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/lib/templates/loop.float32.js.txt +++ /dev/null @@ -1,51 +0,0 @@ -'use strict'; - -// MODULES // - -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); - - -// VARIABLES // - -var C = [ -{{coefficients}} -]; -var END = C.length - 1; - - -// MAIN // - -/** -* Evaluates a polynomial. -* -* ## Notes -* -* - The implementation uses [Horner's rule][horners-method] for efficient computation. -* -* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method -* -* @private -* @param {number} x - value at which to evaluate the polynomial -* @returns {number} evaluated polynomial -*/ -function evalpoly( x ) { - var p; - var i; - - if ( x === 0.0 ) { - return C[ 0 ]; - } - i = END; - p = float64ToFloat32( float64ToFloat32( C[ i ] * x ) + C[ i-1 ] ); - i -= 2; - while ( i >= 0 ) { - p = float64ToFloat32( float64ToFloat32( p * x ) + C[ i ] ); - i -= 1; - } - return p; -} - - -// EXPORTS // - -module.exports = evalpoly; diff --git a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/evalpoly1.float32.js.txt b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/evalpoly1.float32.js.txt deleted file mode 100644 index 09a91437d477..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/evalpoly1.float32.js.txt +++ /dev/null @@ -1,33 +0,0 @@ -'use strict'; - -// MODULES // - -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); - - -// MAIN // - -/** -* Evaluates a polynomial. -* -* ## Notes -* -* - The implementation uses [Horner's rule][horners-method] for efficient computation. -* -* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method -* -* @private -* @param {number} x - value at which to evaluate the polynomial -* @returns {number} evaluated polynomial -*/ -function evalpoly( x ) { - if ( x === 0.0 ) { - return 1.0; - } - return float64ToFloat32(1.0 + float64ToFloat32(x * float64ToFloat32(2.5 + float64ToFloat32(x * float64ToFloat32(3.140000104904175 + float64ToFloat32(x * -1.0)))))); // eslint-disable-line max-len -} - - -// EXPORTS // - -module.exports = evalpoly; diff --git a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/evalpoly2.float32.js.txt b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/evalpoly2.float32.js.txt deleted file mode 100644 index 1e6b3d2283ea..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/evalpoly2.float32.js.txt +++ /dev/null @@ -1,33 +0,0 @@ -'use strict'; - -// MODULES // - -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); - - -// MAIN // - -/** -* Evaluates a polynomial. -* -* ## Notes -* -* - The implementation uses [Horner's rule][horners-method] for efficient computation. -* -* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method -* -* @private -* @param {number} x - value at which to evaluate the polynomial -* @returns {number} evaluated polynomial -*/ -function evalpoly( x ) { - if ( x === 0.0 ) { - return -3.140000104904175; - } - return float64ToFloat32(-3.140000104904175 + float64ToFloat32(x * 0.0)); -} - - -// EXPORTS // - -module.exports = evalpoly; diff --git a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/evalpoly3.float32.js.txt b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/evalpoly3.float32.js.txt deleted file mode 100644 index 55b11849031e..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/evalpoly3.float32.js.txt +++ /dev/null @@ -1,33 +0,0 @@ -'use strict'; - -// MODULES // - -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); - - -// MAIN // - -/** -* Evaluates a polynomial. -* -* ## Notes -* -* - The implementation uses [Horner's rule][horners-method] for efficient computation. -* -* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method -* -* @private -* @param {number} x - value at which to evaluate the polynomial -* @returns {number} evaluated polynomial -*/ -function evalpoly( x ) { - if ( x === 0.0 ) { - return 1.0; - } - return float64ToFloat32(1.0 + float64ToFloat32(x * float64ToFloat32(2.5 + float64ToFloat32(x * float64ToFloat32(3.140000104904175 + float64ToFloat32(x * float64ToFloat32(-1.0 + float64ToFloat32(x * float64ToFloat32(5.0 + float64ToFloat32(x * float64ToFloat32(2.0 + float64ToFloat32(x * float64ToFloat32(3.5 + float64ToFloat32(x * float64ToFloat32(8.0 + float64ToFloat32(x * float64ToFloat32(4.199999809265137 + float64ToFloat32(x * 1.0)))))))))))))))))); // eslint-disable-line max-len -} - - -// EXPORTS // - -module.exports = evalpoly; diff --git a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/loop1.float32.js.txt b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/loop1.float32.js.txt deleted file mode 100644 index aca23c389d8e..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/loop1.float32.js.txt +++ /dev/null @@ -1,551 +0,0 @@ -'use strict'; - -// MODULES // - -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); - - -// VARIABLES // - -var C = [ - 0.0, - 1.0, - 2.0, - 3.0, - 4.0, - 5.0, - 6.0, - 7.0, - 8.0, - 9.0, - 10.0, - 11.0, - 12.0, - 13.0, - 14.0, - 15.0, - 16.0, - 17.0, - 18.0, - 19.0, - 20.0, - 21.0, - 22.0, - 23.0, - 24.0, - 25.0, - 26.0, - 27.0, - 28.0, - 29.0, - 30.0, - 31.0, - 32.0, - 33.0, - 34.0, - 35.0, - 36.0, - 37.0, - 38.0, - 39.0, - 40.0, - 41.0, - 42.0, - 43.0, - 44.0, - 45.0, - 46.0, - 47.0, - 48.0, - 49.0, - 50.0, - 51.0, - 52.0, - 53.0, - 54.0, - 55.0, - 56.0, - 57.0, - 58.0, - 59.0, - 60.0, - 61.0, - 62.0, - 63.0, - 64.0, - 65.0, - 66.0, - 67.0, - 68.0, - 69.0, - 70.0, - 71.0, - 72.0, - 73.0, - 74.0, - 75.0, - 76.0, - 77.0, - 78.0, - 79.0, - 80.0, - 81.0, - 82.0, - 83.0, - 84.0, - 85.0, - 86.0, - 87.0, - 88.0, - 89.0, - 90.0, - 91.0, - 92.0, - 93.0, - 94.0, - 95.0, - 96.0, - 97.0, - 98.0, - 99.0, - 100.0, - 101.0, - 102.0, - 103.0, - 104.0, - 105.0, - 106.0, - 107.0, - 108.0, - 109.0, - 110.0, - 111.0, - 112.0, - 113.0, - 114.0, - 115.0, - 116.0, - 117.0, - 118.0, - 119.0, - 120.0, - 121.0, - 122.0, - 123.0, - 124.0, - 125.0, - 126.0, - 127.0, - 128.0, - 129.0, - 130.0, - 131.0, - 132.0, - 133.0, - 134.0, - 135.0, - 136.0, - 137.0, - 138.0, - 139.0, - 140.0, - 141.0, - 142.0, - 143.0, - 144.0, - 145.0, - 146.0, - 147.0, - 148.0, - 149.0, - 150.0, - 151.0, - 152.0, - 153.0, - 154.0, - 155.0, - 156.0, - 157.0, - 158.0, - 159.0, - 160.0, - 161.0, - 162.0, - 163.0, - 164.0, - 165.0, - 166.0, - 167.0, - 168.0, - 169.0, - 170.0, - 171.0, - 172.0, - 173.0, - 174.0, - 175.0, - 176.0, - 177.0, - 178.0, - 179.0, - 180.0, - 181.0, - 182.0, - 183.0, - 184.0, - 185.0, - 186.0, - 187.0, - 188.0, - 189.0, - 190.0, - 191.0, - 192.0, - 193.0, - 194.0, - 195.0, - 196.0, - 197.0, - 198.0, - 199.0, - 200.0, - 201.0, - 202.0, - 203.0, - 204.0, - 205.0, - 206.0, - 207.0, - 208.0, - 209.0, - 210.0, - 211.0, - 212.0, - 213.0, - 214.0, - 215.0, - 216.0, - 217.0, - 218.0, - 219.0, - 220.0, - 221.0, - 222.0, - 223.0, - 224.0, - 225.0, - 226.0, - 227.0, - 228.0, - 229.0, - 230.0, - 231.0, - 232.0, - 233.0, - 234.0, - 235.0, - 236.0, - 237.0, - 238.0, - 239.0, - 240.0, - 241.0, - 242.0, - 243.0, - 244.0, - 245.0, - 246.0, - 247.0, - 248.0, - 249.0, - 250.0, - 251.0, - 252.0, - 253.0, - 254.0, - 255.0, - 256.0, - 257.0, - 258.0, - 259.0, - 260.0, - 261.0, - 262.0, - 263.0, - 264.0, - 265.0, - 266.0, - 267.0, - 268.0, - 269.0, - 270.0, - 271.0, - 272.0, - 273.0, - 274.0, - 275.0, - 276.0, - 277.0, - 278.0, - 279.0, - 280.0, - 281.0, - 282.0, - 283.0, - 284.0, - 285.0, - 286.0, - 287.0, - 288.0, - 289.0, - 290.0, - 291.0, - 292.0, - 293.0, - 294.0, - 295.0, - 296.0, - 297.0, - 298.0, - 299.0, - 300.0, - 301.0, - 302.0, - 303.0, - 304.0, - 305.0, - 306.0, - 307.0, - 308.0, - 309.0, - 310.0, - 311.0, - 312.0, - 313.0, - 314.0, - 315.0, - 316.0, - 317.0, - 318.0, - 319.0, - 320.0, - 321.0, - 322.0, - 323.0, - 324.0, - 325.0, - 326.0, - 327.0, - 328.0, - 329.0, - 330.0, - 331.0, - 332.0, - 333.0, - 334.0, - 335.0, - 336.0, - 337.0, - 338.0, - 339.0, - 340.0, - 341.0, - 342.0, - 343.0, - 344.0, - 345.0, - 346.0, - 347.0, - 348.0, - 349.0, - 350.0, - 351.0, - 352.0, - 353.0, - 354.0, - 355.0, - 356.0, - 357.0, - 358.0, - 359.0, - 360.0, - 361.0, - 362.0, - 363.0, - 364.0, - 365.0, - 366.0, - 367.0, - 368.0, - 369.0, - 370.0, - 371.0, - 372.0, - 373.0, - 374.0, - 375.0, - 376.0, - 377.0, - 378.0, - 379.0, - 380.0, - 381.0, - 382.0, - 383.0, - 384.0, - 385.0, - 386.0, - 387.0, - 388.0, - 389.0, - 390.0, - 391.0, - 392.0, - 393.0, - 394.0, - 395.0, - 396.0, - 397.0, - 398.0, - 399.0, - 400.0, - 401.0, - 402.0, - 403.0, - 404.0, - 405.0, - 406.0, - 407.0, - 408.0, - 409.0, - 410.0, - 411.0, - 412.0, - 413.0, - 414.0, - 415.0, - 416.0, - 417.0, - 418.0, - 419.0, - 420.0, - 421.0, - 422.0, - 423.0, - 424.0, - 425.0, - 426.0, - 427.0, - 428.0, - 429.0, - 430.0, - 431.0, - 432.0, - 433.0, - 434.0, - 435.0, - 436.0, - 437.0, - 438.0, - 439.0, - 440.0, - 441.0, - 442.0, - 443.0, - 444.0, - 445.0, - 446.0, - 447.0, - 448.0, - 449.0, - 450.0, - 451.0, - 452.0, - 453.0, - 454.0, - 455.0, - 456.0, - 457.0, - 458.0, - 459.0, - 460.0, - 461.0, - 462.0, - 463.0, - 464.0, - 465.0, - 466.0, - 467.0, - 468.0, - 469.0, - 470.0, - 471.0, - 472.0, - 473.0, - 474.0, - 475.0, - 476.0, - 477.0, - 478.0, - 479.0, - 480.0, - 481.0, - 482.0, - 483.0, - 484.0, - 485.0, - 486.0, - 487.0, - 488.0, - 489.0, - 490.0, - 491.0, - 492.0, - 493.0, - 494.0, - 495.0, - 496.0, - 497.0, - 498.0, - 499.0, - 500.0 -]; -var END = C.length - 1; - - -// MAIN // - -/** -* Evaluates a polynomial. -* -* ## Notes -* -* - The implementation uses [Horner's rule][horners-method] for efficient computation. -* -* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method -* -* @private -* @param {number} x - value at which to evaluate the polynomial -* @returns {number} evaluated polynomial -*/ -function evalpoly( x ) { - var p; - var i; - - if ( x === 0.0 ) { - return C[ 0 ]; - } - i = END; - p = float64ToFloat32( float64ToFloat32( C[ i ] * x ) + C[ i-1 ] ); - i -= 2; - while ( i >= 0 ) { - p = float64ToFloat32( float64ToFloat32( p * x ) + C[ i ] ); - i -= 1; - } - return p; -} - - -// EXPORTS // - -module.exports = evalpoly; diff --git a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/loop1.js.txt b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/loop1.js.txt index c3d4535ca01b..716b461417fd 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/loop1.js.txt +++ b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/loop1.js.txt @@ -519,6 +519,7 @@ var END = C.length - 1; * * [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method * +* * @private * @param {number} x - value at which to evaluate the polynomial * @returns {number} evaluated polynomial diff --git a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/loop2.float32.js.txt b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/loop2.float32.js.txt deleted file mode 100644 index e4d0f5875b2f..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/loop2.float32.js.txt +++ /dev/null @@ -1,551 +0,0 @@ -'use strict'; - -// MODULES // - -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); - - -// VARIABLES // - -var C = [ - 0.5, - 1.5, - 2.5, - 3.5, - 4.5, - 5.5, - 6.5, - 7.5, - 8.5, - 9.5, - 10.5, - 11.5, - 12.5, - 13.5, - 14.5, - 15.5, - 16.5, - 17.5, - 18.5, - 19.5, - 20.5, - 21.5, - 22.5, - 23.5, - 24.5, - 25.5, - 26.5, - 27.5, - 28.5, - 29.5, - 30.5, - 31.5, - 32.5, - 33.5, - 34.5, - 35.5, - 36.5, - 37.5, - 38.5, - 39.5, - 40.5, - 41.5, - 42.5, - 43.5, - 44.5, - 45.5, - 46.5, - 47.5, - 48.5, - 49.5, - 50.5, - 51.5, - 52.5, - 53.5, - 54.5, - 55.5, - 56.5, - 57.5, - 58.5, - 59.5, - 60.5, - 61.5, - 62.5, - 63.5, - 64.5, - 65.5, - 66.5, - 67.5, - 68.5, - 69.5, - 70.5, - 71.5, - 72.5, - 73.5, - 74.5, - 75.5, - 76.5, - 77.5, - 78.5, - 79.5, - 80.5, - 81.5, - 82.5, - 83.5, - 84.5, - 85.5, - 86.5, - 87.5, - 88.5, - 89.5, - 90.5, - 91.5, - 92.5, - 93.5, - 94.5, - 95.5, - 96.5, - 97.5, - 98.5, - 99.5, - 100.5, - 101.5, - 102.5, - 103.5, - 104.5, - 105.5, - 106.5, - 107.5, - 108.5, - 109.5, - 110.5, - 111.5, - 112.5, - 113.5, - 114.5, - 115.5, - 116.5, - 117.5, - 118.5, - 119.5, - 120.5, - 121.5, - 122.5, - 123.5, - 124.5, - 125.5, - 126.5, - 127.5, - 128.5, - 129.5, - 130.5, - 131.5, - 132.5, - 133.5, - 134.5, - 135.5, - 136.5, - 137.5, - 138.5, - 139.5, - 140.5, - 141.5, - 142.5, - 143.5, - 144.5, - 145.5, - 146.5, - 147.5, - 148.5, - 149.5, - 150.5, - 151.5, - 152.5, - 153.5, - 154.5, - 155.5, - 156.5, - 157.5, - 158.5, - 159.5, - 160.5, - 161.5, - 162.5, - 163.5, - 164.5, - 165.5, - 166.5, - 167.5, - 168.5, - 169.5, - 170.5, - 171.5, - 172.5, - 173.5, - 174.5, - 175.5, - 176.5, - 177.5, - 178.5, - 179.5, - 180.5, - 181.5, - 182.5, - 183.5, - 184.5, - 185.5, - 186.5, - 187.5, - 188.5, - 189.5, - 190.5, - 191.5, - 192.5, - 193.5, - 194.5, - 195.5, - 196.5, - 197.5, - 198.5, - 199.5, - 200.5, - 201.5, - 202.5, - 203.5, - 204.5, - 205.5, - 206.5, - 207.5, - 208.5, - 209.5, - 210.5, - 211.5, - 212.5, - 213.5, - 214.5, - 215.5, - 216.5, - 217.5, - 218.5, - 219.5, - 220.5, - 221.5, - 222.5, - 223.5, - 224.5, - 225.5, - 226.5, - 227.5, - 228.5, - 229.5, - 230.5, - 231.5, - 232.5, - 233.5, - 234.5, - 235.5, - 236.5, - 237.5, - 238.5, - 239.5, - 240.5, - 241.5, - 242.5, - 243.5, - 244.5, - 245.5, - 246.5, - 247.5, - 248.5, - 249.5, - 250.5, - 251.5, - 252.5, - 253.5, - 254.5, - 255.5, - 256.5, - 257.5, - 258.5, - 259.5, - 260.5, - 261.5, - 262.5, - 263.5, - 264.5, - 265.5, - 266.5, - 267.5, - 268.5, - 269.5, - 270.5, - 271.5, - 272.5, - 273.5, - 274.5, - 275.5, - 276.5, - 277.5, - 278.5, - 279.5, - 280.5, - 281.5, - 282.5, - 283.5, - 284.5, - 285.5, - 286.5, - 287.5, - 288.5, - 289.5, - 290.5, - 291.5, - 292.5, - 293.5, - 294.5, - 295.5, - 296.5, - 297.5, - 298.5, - 299.5, - 300.5, - 301.5, - 302.5, - 303.5, - 304.5, - 305.5, - 306.5, - 307.5, - 308.5, - 309.5, - 310.5, - 311.5, - 312.5, - 313.5, - 314.5, - 315.5, - 316.5, - 317.5, - 318.5, - 319.5, - 320.5, - 321.5, - 322.5, - 323.5, - 324.5, - 325.5, - 326.5, - 327.5, - 328.5, - 329.5, - 330.5, - 331.5, - 332.5, - 333.5, - 334.5, - 335.5, - 336.5, - 337.5, - 338.5, - 339.5, - 340.5, - 341.5, - 342.5, - 343.5, - 344.5, - 345.5, - 346.5, - 347.5, - 348.5, - 349.5, - 350.5, - 351.5, - 352.5, - 353.5, - 354.5, - 355.5, - 356.5, - 357.5, - 358.5, - 359.5, - 360.5, - 361.5, - 362.5, - 363.5, - 364.5, - 365.5, - 366.5, - 367.5, - 368.5, - 369.5, - 370.5, - 371.5, - 372.5, - 373.5, - 374.5, - 375.5, - 376.5, - 377.5, - 378.5, - 379.5, - 380.5, - 381.5, - 382.5, - 383.5, - 384.5, - 385.5, - 386.5, - 387.5, - 388.5, - 389.5, - 390.5, - 391.5, - 392.5, - 393.5, - 394.5, - 395.5, - 396.5, - 397.5, - 398.5, - 399.5, - 400.5, - 401.5, - 402.5, - 403.5, - 404.5, - 405.5, - 406.5, - 407.5, - 408.5, - 409.5, - 410.5, - 411.5, - 412.5, - 413.5, - 414.5, - 415.5, - 416.5, - 417.5, - 418.5, - 419.5, - 420.5, - 421.5, - 422.5, - 423.5, - 424.5, - 425.5, - 426.5, - 427.5, - 428.5, - 429.5, - 430.5, - 431.5, - 432.5, - 433.5, - 434.5, - 435.5, - 436.5, - 437.5, - 438.5, - 439.5, - 440.5, - 441.5, - 442.5, - 443.5, - 444.5, - 445.5, - 446.5, - 447.5, - 448.5, - 449.5, - 450.5, - 451.5, - 452.5, - 453.5, - 454.5, - 455.5, - 456.5, - 457.5, - 458.5, - 459.5, - 460.5, - 461.5, - 462.5, - 463.5, - 464.5, - 465.5, - 466.5, - 467.5, - 468.5, - 469.5, - 470.5, - 471.5, - 472.5, - 473.5, - 474.5, - 475.5, - 476.5, - 477.5, - 478.5, - 479.5, - 480.5, - 481.5, - 482.5, - 483.5, - 484.5, - 485.5, - 486.5, - 487.5, - 488.5, - 489.5, - 490.5, - 491.5, - 492.5, - 493.5, - 494.5, - 495.5, - 496.5, - 497.5, - 498.5, - 499.5, - 500.5 -]; -var END = C.length - 1; - - -// MAIN // - -/** -* Evaluates a polynomial. -* -* ## Notes -* -* - The implementation uses [Horner's rule][horners-method] for efficient computation. -* -* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method -* -* @private -* @param {number} x - value at which to evaluate the polynomial -* @returns {number} evaluated polynomial -*/ -function evalpoly( x ) { - var p; - var i; - - if ( x === 0.0 ) { - return C[ 0 ]; - } - i = END; - p = float64ToFloat32( float64ToFloat32( C[ i ] * x ) + C[ i-1 ] ); - i -= 2; - while ( i >= 0 ) { - p = float64ToFloat32( float64ToFloat32( p * x ) + C[ i ] ); - i -= 1; - } - return p; -} - - -// EXPORTS // - -module.exports = evalpoly; diff --git a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/loop2.js.txt b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/loop2.js.txt index 6b80d33bb911..353ce527d5f5 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/loop2.js.txt +++ b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/loop2.js.txt @@ -519,6 +519,7 @@ var END = C.length - 1; * * [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method * +* * @private * @param {number} x - value at which to evaluate the polynomial * @returns {number} evaluated polynomial diff --git a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/single_coefficient.float32.js.txt b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/single_coefficient.float32.js.txt deleted file mode 100644 index bc649465a14f..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/fixtures/single_coefficient.float32.js.txt +++ /dev/null @@ -1,19 +0,0 @@ -'use strict'; - -// MAIN // - -/** -* Evaluates a polynomial. -* -* @private -* @param {number} x - value at which to evaluate the polynomial -* @returns {number} evaluated polynomial -*/ -function evalpoly() { - return 3.140000104904175; -} - - -// EXPORTS // - -module.exports = evalpoly; diff --git a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/test.js b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/test.js index 8077c407bc43..4b38d50d6186 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/test.js +++ b/lib/node_modules/@stdlib/math/base/tools/evalpoly-compile/test/test.js @@ -26,7 +26,6 @@ var tape = require( 'tape' ); var IS_BROWSER = require( '@stdlib/assert/is-browser' ); var readFile = require( '@stdlib/fs/read-file' ).sync; var Float64Array = require( '@stdlib/array/float64' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -64,52 +63,6 @@ tape( 'the function returns a string', opts, function test( t ) { t.end(); }); -tape( 'the function returns a string (dtype=float64)', opts, function test( t ) { - var options; - var str; - - options = { - 'dtype': 'float64' - }; - - str = compile( [], options ); - t.equal( typeof str, 'string', 'returns a string' ); - - str = compile( [ 1.0 ], options ); - t.equal( typeof str, 'string', 'returns a string' ); - - str = compile( [ 1.0, 2.0, 3.0 ], options ); - t.equal( typeof str, 'string', 'returns a string' ); - - str = compile( new Float64Array( 501 ) ); - t.equal( typeof str, 'string', 'returns a string' ); - - t.end(); -}); - -tape( 'the function returns a string (dtype=float32)', opts, function test( t ) { - var options; - var str; - - options = { - 'dtype': 'float32' - }; - - str = compile( [], options ); - t.equal( typeof str, 'string', 'returns a string' ); - - str = compile( [ 1.0 ], options ); - t.equal( typeof str, 'string', 'returns a string' ); - - str = compile( [ 1.0, 2.0, 3.0 ], options ); - t.equal( typeof str, 'string', 'returns a string' ); - - str = compile( new Float64Array( 501 ) ); - t.equal( typeof str, 'string', 'returns a string' ); - - t.end(); -}); - tape( 'if provided an empty coefficient array, the function returns a module string containing an exported function which always returns `0`', opts, function test( t ) { var expected; var actual; @@ -128,46 +81,6 @@ tape( 'if provided an empty coefficient array, the function returns a module str t.end(); }); -tape( 'if provided an empty coefficient array, the function returns a module string containing an exported function which always returns `0` (dtype=float64)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'empty.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( [], { - 'dtype': 'float64' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'if provided an empty coefficient array, the function returns a module string containing an exported function which always returns `0` (dtype=float32)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'empty.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( [], { - 'dtype': 'float32' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - tape( 'if provided only 1 coefficient, the function returns a module string containing an exported function which always returns that coefficient', opts, function test( t ) { var expected; var actual; @@ -186,46 +99,6 @@ tape( 'if provided only 1 coefficient, the function returns a module string cont t.end(); }); -tape( 'if provided only 1 coefficient, the function returns a module string containing an exported function which always returns that coefficient (dtype=float64)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'single_coefficient.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( [ 3.14 ], { - 'dtype': 'float64' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'if provided only 1 coefficient, the function returns a module string containing an exported function which always returns that coefficient (dtype=float32)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'single_coefficient.float32.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( new Float32Array( [ 3.14 ] ), { - 'dtype': 'float32' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - tape( 'if provided only 1 coefficient, the function returns a module string containing an exported function which always returns that coefficient (integer value)', opts, function test( t ) { var expected; var actual; @@ -244,46 +117,6 @@ tape( 'if provided only 1 coefficient, the function returns a module string cont t.end(); }); -tape( 'if provided only 1 coefficient, the function returns a module string containing an exported function which always returns that coefficient (integer value; dtype=float64)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'single_coefficient_integer.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( [ -3.0 ], { - 'dtype': 'float64' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'if provided only 1 coefficient, the function returns a module string containing an exported function which always returns that coefficient (integer value; dtype=float32)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'single_coefficient_integer.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( new Float32Array( [ -3.0 ] ), { - 'dtype': 'float32' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - tape( 'the function returns a module string containing an exported function which evaluates a polynomial', opts, function test( t ) { var expected; var actual; @@ -302,46 +135,6 @@ tape( 'the function returns a module string containing an exported function whic t.end(); }); -tape( 'the function returns a module string containing an exported function which evaluates a polynomial (dtype=float64)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'evalpoly1.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( [ 1.0, 2.5, 3.14, -1.0 ], { - 'dtype': 'float64' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function returns a module string containing an exported function which evaluates a polynomial (dtype=float32)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'evalpoly1.float32.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( new Float32Array( [ 1.0, 2.5, 3.14, -1.0 ] ), { - 'dtype': 'float32' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - tape( 'the function returns a module string containing an exported function which evaluates a polynomial', opts, function test( t ) { var expected; var actual; @@ -360,46 +153,6 @@ tape( 'the function returns a module string containing an exported function whic t.end(); }); -tape( 'the function returns a module string containing an exported function which evaluates a polynomial (dtype=float64)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'evalpoly2.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( [ -3.14, 0.0 ], { - 'dtype': 'float64' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function returns a module string containing an exported function which evaluates a polynomial (dtype=float32)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'evalpoly2.float32.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( new Float32Array( [ -3.14, 0.0 ] ), { - 'dtype': 'float32' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - tape( 'the function returns a module string containing an exported function which evaluates a polynomial', opts, function test( t ) { var expected; var actual; @@ -418,46 +171,6 @@ tape( 'the function returns a module string containing an exported function whic t.end(); }); -tape( 'the function returns a module string containing an exported function which evaluates a polynomial (dtype=float64)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'evalpoly3.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( [ 1.0, 2.5, 3.14, -1.0, 5.0, 2.0, 3.5, 8.0, 4.2, 1.0 ], { - 'dtype': 'float64' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function returns a module string containing an exported function which evaluates a polynomial (dtype=float32)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'evalpoly3.float32.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( new Float32Array( [ 1.0, 2.5, 3.14, -1.0, 5.0, 2.0, 3.5, 8.0, 4.2, 1.0 ] ), { // eslint-disable-line max-len - 'dtype': 'float32' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - tape( 'the function returns a module string containing an exported function which evaluates a polynomial (large number of coefficients; integers)', opts, function test( t ) { var expected; var actual; @@ -472,9 +185,9 @@ tape( 'the function returns a module string containing an exported function whic }; expected = readFile( fpath, fopts ); - c = []; - for ( i = 0; i < 501; i++ ) { - c.push( i ); + c = new Array( 501 ); + for ( i = 0; i < c.length; i++ ) { + c[ i ] = i; } actual = compile( c ); t.equal( actual, expected, 'returns expected value' ); @@ -482,58 +195,6 @@ tape( 'the function returns a module string containing an exported function whic t.end(); }); -tape( 'the function returns a module string containing an exported function which evaluates a polynomial (large number of coefficients; integers; dtype=float64)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - var c; - var i; - - fpath = join( __dirname, 'fixtures', 'loop1.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - c = []; - for ( i = 0; i < 501; i++ ) { - c.push( i ); - } - actual = compile( c, { - 'dtype': 'float64' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function returns a module string containing an exported function which evaluates a polynomial (large number of coefficients; integers; dtype=float32)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - var c; - var i; - - fpath = join( __dirname, 'fixtures', 'loop1.float32.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - c = []; - for ( i = 0; i < 501; i++ ) { - c.push( i ); - } - actual = compile( new Float32Array( c ), { - 'dtype': 'float32' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - tape( 'the function returns a module string containing an exported function which evaluates a polynomial (large number of coefficients; decimals)', opts, function test( t ) { var expected; var actual; @@ -548,64 +209,12 @@ tape( 'the function returns a module string containing an exported function whic }; expected = readFile( fpath, fopts ); - c = []; - for ( i = 0; i < 501; i++ ) { - c.push( i + 0.1 ); + c = new Array( 501 ); + for ( i = 0; i < c.length; i++ ) { + c[ i ] = i + 0.1; } actual = compile( c ); t.equal( actual, expected, 'returns expected value' ); t.end(); }); - -tape( 'the function returns a module string containing an exported function which evaluates a polynomial (large number of coefficients; decimals; dtype=float64)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - var c; - var i; - - fpath = join( __dirname, 'fixtures', 'loop2.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - c = []; - for ( i = 0; i < 501; i++ ) { - c.push( i + 0.1 ); - } - actual = compile( c, { - 'dtype': 'float64' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function returns a module string containing an exported function which evaluates a polynomial (large number of coefficients; decimals; dtype=float32)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - var c; - var i; - - fpath = join( __dirname, 'fixtures', 'loop2.float32.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - c = []; - for ( i = 0; i < 501; i++ ) { - c.push( i + 0.5 ); - } - actual = compile( new Float32Array( c ), { - 'dtype': 'float32' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/docs/types/index.d.ts b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/docs/types/index.d.ts index 22e0e869d522..c4233395cd5f 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/docs/types/index.d.ts @@ -18,10 +18,6 @@ // TypeScript Version: 4.1 -/// - -import { Collection } from '@stdlib/types/array'; - /** * Interface describing function options. */ @@ -29,7 +25,7 @@ interface Options { /** * Input value floating-point data type (e.g., `double` or `float`). Default: `'double'`. */ - dtype?: 'double' | 'float'; + dtype?: string; /** * Function name. Default: `'evalpoly'`. @@ -52,7 +48,7 @@ interface Options { * var str = compile( P, Q ); * // returns */ -declare function compile( P: Collection, Q: Collection, options?: Options ): string; +declare function compile( P: Array, Q: Array, options?: Options ): string; // EXPORTS // diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/lib/main.js b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/lib/main.js index 9cdd4486212a..cec10b4fe8c8 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/lib/main.js +++ b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/lib/main.js @@ -25,8 +25,6 @@ var readFile = require( '@stdlib/fs/read-file' ).sync; var replace = require( '@stdlib/string/replace' ); var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; var uppercase = require( '@stdlib/string/base/uppercase' ); -var PINF = require( '@stdlib/constants/float64/pinf' ); -var NINF = require( '@stdlib/constants/float64/ninf' ); // VARIABLES // @@ -53,14 +51,7 @@ var NAN_TEMPLATE = readFile( join( dir, 'nan.c.txt' ), opts ); * @returns {string} serialized value */ function value2string( x ) { - var str; - if ( x === PINF ) { - return '1.0{{dtype_suffix}} / 0.0{{dtype_suffix}}'; - } - if ( x === NINF ) { - return '-1.0{{dtype_suffix}} / 0.0{{dtype_suffix}}'; - } - str = x.toString(); + var str = x.toString(); if ( isInteger( x ) ) { str += '.0'; } @@ -233,7 +224,7 @@ function compile( P, Q, options ) { if ( n > 500 ) { str = replace( LOOP_TEMPLATE, '{{P}}', array2list( P ) ); str = replace( str, '{{Q}}', array2list( Q ) ); - str = replace( str, '{{ratio}}', value2string( P[0] / Q[0] ) ); + str = replace( str, '{{ratio}}', value2string( P[0]/Q[0] ) ); str = replace( str, '{{num_coefficients}}', n.toString() ); str = replace( str, '{{dtype}}', opts.dtype ); str = replace( str, '{{dtype_suffix}}', opts.suffix ); @@ -245,7 +236,7 @@ function compile( P, Q, options ) { str = replace( str, '{{Q_ASCENDING}}', hornerAscending( Q ) ); str = replace( str, '{{P_DESCENDING}}', hornerDescending( P ) ); str = replace( str, '{{Q_DESCENDING}}', hornerDescending( Q ) ); - str = replace( str, '{{ratio}}', value2string( P[0] / Q[0] ) ); + str = replace( str, '{{ratio}}', value2string( P[0]/Q[0] ) ); str = replace( str, '{{dtype}}', opts.dtype ); str = replace( str, '{{dtype_suffix}}', opts.suffix ); return replace( str, '{{fname}}', opts.name ); diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/fixtures/coefficient_ratio_negative_infinity.c.txt b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/fixtures/coefficient_ratio_negative_infinity.c.txt deleted file mode 100644 index 0860b66d4dd2..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/fixtures/coefficient_ratio_negative_infinity.c.txt +++ /dev/null @@ -1,9 +0,0 @@ -/** -* Evaluates a rational function. -* -* @param x value at which to evaluate the rational function -* @return evaluated rational function -*/ -static double evalrational() { - return -1.0 / 0.0; -} diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/fixtures/coefficient_ratio_negative_infinity_custom.c.txt b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/fixtures/coefficient_ratio_negative_infinity_custom.c.txt deleted file mode 100644 index 631da1511719..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/fixtures/coefficient_ratio_negative_infinity_custom.c.txt +++ /dev/null @@ -1,9 +0,0 @@ -/** -* Evaluates a rational function. -* -* @param x value at which to evaluate the rational function -* @return evaluated rational function -*/ -static float rational123() { - return -1.0f / 0.0f; -} diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/fixtures/coefficient_ratio_positive_infinity.c.txt b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/fixtures/coefficient_ratio_positive_infinity.c.txt deleted file mode 100644 index aad954eb346b..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/fixtures/coefficient_ratio_positive_infinity.c.txt +++ /dev/null @@ -1,9 +0,0 @@ -/** -* Evaluates a rational function. -* -* @param x value at which to evaluate the rational function -* @return evaluated rational function -*/ -static double evalrational() { - return 1.0 / 0.0; -} diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/fixtures/coefficient_ratio_positive_infinity_custom.c.txt b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/fixtures/coefficient_ratio_positive_infinity_custom.c.txt deleted file mode 100644 index 6549a147b46f..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/fixtures/coefficient_ratio_positive_infinity_custom.c.txt +++ /dev/null @@ -1,9 +0,0 @@ -/** -* Evaluates a rational function. -* -* @param x value at which to evaluate the rational function -* @return evaluated rational function -*/ -static float rational123() { - return 1.0f / 0.0f; -} diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/fixtures/evalrational4.c.txt b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/fixtures/evalrational4.c.txt deleted file mode 100644 index df0d513506f4..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/fixtures/evalrational4.c.txt +++ /dev/null @@ -1,36 +0,0 @@ -/** -* Evaluates a rational function (i.e., the ratio of two polynomials described by the coefficients stored in \\(P\\) and \\(Q\\)). -* -* ## Notes -* -* - Coefficients should be sorted in ascending degree. -* - The implementation uses [Horner's rule][horners-method] for efficient computation. -* -* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method -* -* @param x value at which to evaluate the rational function -* @return evaluated rational function -*/ -static double evalrational( const double x ) { - double ax; - double ix; - double s1; - double s2; - if ( x == 0.0 ) { - return -1.0 / 0.0; - } - if ( x < 0.0 ) { - ax = -x; - } else { - ax = x; - } - if ( ax <= 1.0 ) { - s1 = -1.0 + (x * (2.5 + (x * (3.14 + (x * -1.0))))); - s2 = 0.0 + (x * (-3.5 + (x * (2.2 + (x * 1.25))))); - } else { - ix = 1.0 / x; - s1 = -1.0 + (ix * (3.14 + (ix * (2.5 + (ix * -1.0))))); - s2 = 1.25 + (ix * (2.2 + (ix * (-3.5 + (ix * 0.0))))); - } - return s1 / s2; -} diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/fixtures/loop3.c.txt b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/fixtures/loop3.c.txt deleted file mode 100644 index fd2086693f0b..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/fixtures/loop3.c.txt +++ /dev/null @@ -1,1057 +0,0 @@ -static const double EVALRATIONAL_COEFFICIENTS_P = { - 1.0, - 1.0, - 2.0, - 3.0, - 4.0, - 5.0, - 6.0, - 7.0, - 8.0, - 9.0, - 10.0, - 11.0, - 12.0, - 13.0, - 14.0, - 15.0, - 16.0, - 17.0, - 18.0, - 19.0, - 20.0, - 21.0, - 22.0, - 23.0, - 24.0, - 25.0, - 26.0, - 27.0, - 28.0, - 29.0, - 30.0, - 31.0, - 32.0, - 33.0, - 34.0, - 35.0, - 36.0, - 37.0, - 38.0, - 39.0, - 40.0, - 41.0, - 42.0, - 43.0, - 44.0, - 45.0, - 46.0, - 47.0, - 48.0, - 49.0, - 50.0, - 51.0, - 52.0, - 53.0, - 54.0, - 55.0, - 56.0, - 57.0, - 58.0, - 59.0, - 60.0, - 61.0, - 62.0, - 63.0, - 64.0, - 65.0, - 66.0, - 67.0, - 68.0, - 69.0, - 70.0, - 71.0, - 72.0, - 73.0, - 74.0, - 75.0, - 76.0, - 77.0, - 78.0, - 79.0, - 80.0, - 81.0, - 82.0, - 83.0, - 84.0, - 85.0, - 86.0, - 87.0, - 88.0, - 89.0, - 90.0, - 91.0, - 92.0, - 93.0, - 94.0, - 95.0, - 96.0, - 97.0, - 98.0, - 99.0, - 100.0, - 101.0, - 102.0, - 103.0, - 104.0, - 105.0, - 106.0, - 107.0, - 108.0, - 109.0, - 110.0, - 111.0, - 112.0, - 113.0, - 114.0, - 115.0, - 116.0, - 117.0, - 118.0, - 119.0, - 120.0, - 121.0, - 122.0, - 123.0, - 124.0, - 125.0, - 126.0, - 127.0, - 128.0, - 129.0, - 130.0, - 131.0, - 132.0, - 133.0, - 134.0, - 135.0, - 136.0, - 137.0, - 138.0, - 139.0, - 140.0, - 141.0, - 142.0, - 143.0, - 144.0, - 145.0, - 146.0, - 147.0, - 148.0, - 149.0, - 150.0, - 151.0, - 152.0, - 153.0, - 154.0, - 155.0, - 156.0, - 157.0, - 158.0, - 159.0, - 160.0, - 161.0, - 162.0, - 163.0, - 164.0, - 165.0, - 166.0, - 167.0, - 168.0, - 169.0, - 170.0, - 171.0, - 172.0, - 173.0, - 174.0, - 175.0, - 176.0, - 177.0, - 178.0, - 179.0, - 180.0, - 181.0, - 182.0, - 183.0, - 184.0, - 185.0, - 186.0, - 187.0, - 188.0, - 189.0, - 190.0, - 191.0, - 192.0, - 193.0, - 194.0, - 195.0, - 196.0, - 197.0, - 198.0, - 199.0, - 200.0, - 201.0, - 202.0, - 203.0, - 204.0, - 205.0, - 206.0, - 207.0, - 208.0, - 209.0, - 210.0, - 211.0, - 212.0, - 213.0, - 214.0, - 215.0, - 216.0, - 217.0, - 218.0, - 219.0, - 220.0, - 221.0, - 222.0, - 223.0, - 224.0, - 225.0, - 226.0, - 227.0, - 228.0, - 229.0, - 230.0, - 231.0, - 232.0, - 233.0, - 234.0, - 235.0, - 236.0, - 237.0, - 238.0, - 239.0, - 240.0, - 241.0, - 242.0, - 243.0, - 244.0, - 245.0, - 246.0, - 247.0, - 248.0, - 249.0, - 250.0, - 251.0, - 252.0, - 253.0, - 254.0, - 255.0, - 256.0, - 257.0, - 258.0, - 259.0, - 260.0, - 261.0, - 262.0, - 263.0, - 264.0, - 265.0, - 266.0, - 267.0, - 268.0, - 269.0, - 270.0, - 271.0, - 272.0, - 273.0, - 274.0, - 275.0, - 276.0, - 277.0, - 278.0, - 279.0, - 280.0, - 281.0, - 282.0, - 283.0, - 284.0, - 285.0, - 286.0, - 287.0, - 288.0, - 289.0, - 290.0, - 291.0, - 292.0, - 293.0, - 294.0, - 295.0, - 296.0, - 297.0, - 298.0, - 299.0, - 300.0, - 301.0, - 302.0, - 303.0, - 304.0, - 305.0, - 306.0, - 307.0, - 308.0, - 309.0, - 310.0, - 311.0, - 312.0, - 313.0, - 314.0, - 315.0, - 316.0, - 317.0, - 318.0, - 319.0, - 320.0, - 321.0, - 322.0, - 323.0, - 324.0, - 325.0, - 326.0, - 327.0, - 328.0, - 329.0, - 330.0, - 331.0, - 332.0, - 333.0, - 334.0, - 335.0, - 336.0, - 337.0, - 338.0, - 339.0, - 340.0, - 341.0, - 342.0, - 343.0, - 344.0, - 345.0, - 346.0, - 347.0, - 348.0, - 349.0, - 350.0, - 351.0, - 352.0, - 353.0, - 354.0, - 355.0, - 356.0, - 357.0, - 358.0, - 359.0, - 360.0, - 361.0, - 362.0, - 363.0, - 364.0, - 365.0, - 366.0, - 367.0, - 368.0, - 369.0, - 370.0, - 371.0, - 372.0, - 373.0, - 374.0, - 375.0, - 376.0, - 377.0, - 378.0, - 379.0, - 380.0, - 381.0, - 382.0, - 383.0, - 384.0, - 385.0, - 386.0, - 387.0, - 388.0, - 389.0, - 390.0, - 391.0, - 392.0, - 393.0, - 394.0, - 395.0, - 396.0, - 397.0, - 398.0, - 399.0, - 400.0, - 401.0, - 402.0, - 403.0, - 404.0, - 405.0, - 406.0, - 407.0, - 408.0, - 409.0, - 410.0, - 411.0, - 412.0, - 413.0, - 414.0, - 415.0, - 416.0, - 417.0, - 418.0, - 419.0, - 420.0, - 421.0, - 422.0, - 423.0, - 424.0, - 425.0, - 426.0, - 427.0, - 428.0, - 429.0, - 430.0, - 431.0, - 432.0, - 433.0, - 434.0, - 435.0, - 436.0, - 437.0, - 438.0, - 439.0, - 440.0, - 441.0, - 442.0, - 443.0, - 444.0, - 445.0, - 446.0, - 447.0, - 448.0, - 449.0, - 450.0, - 451.0, - 452.0, - 453.0, - 454.0, - 455.0, - 456.0, - 457.0, - 458.0, - 459.0, - 460.0, - 461.0, - 462.0, - 463.0, - 464.0, - 465.0, - 466.0, - 467.0, - 468.0, - 469.0, - 470.0, - 471.0, - 472.0, - 473.0, - 474.0, - 475.0, - 476.0, - 477.0, - 478.0, - 479.0, - 480.0, - 481.0, - 482.0, - 483.0, - 484.0, - 485.0, - 486.0, - 487.0, - 488.0, - 489.0, - 490.0, - 491.0, - 492.0, - 493.0, - 494.0, - 495.0, - 496.0, - 497.0, - 498.0, - 499.0, - 500.0 -}; -static const double EVALRATIONAL_COEFFICIENTS_Q = { - 0.0, - 2.0, - 3.0, - 4.0, - 5.0, - 6.0, - 7.0, - 8.0, - 9.0, - 10.0, - 11.0, - 12.0, - 13.0, - 14.0, - 15.0, - 16.0, - 17.0, - 18.0, - 19.0, - 20.0, - 21.0, - 22.0, - 23.0, - 24.0, - 25.0, - 26.0, - 27.0, - 28.0, - 29.0, - 30.0, - 31.0, - 32.0, - 33.0, - 34.0, - 35.0, - 36.0, - 37.0, - 38.0, - 39.0, - 40.0, - 41.0, - 42.0, - 43.0, - 44.0, - 45.0, - 46.0, - 47.0, - 48.0, - 49.0, - 50.0, - 51.0, - 52.0, - 53.0, - 54.0, - 55.0, - 56.0, - 57.0, - 58.0, - 59.0, - 60.0, - 61.0, - 62.0, - 63.0, - 64.0, - 65.0, - 66.0, - 67.0, - 68.0, - 69.0, - 70.0, - 71.0, - 72.0, - 73.0, - 74.0, - 75.0, - 76.0, - 77.0, - 78.0, - 79.0, - 80.0, - 81.0, - 82.0, - 83.0, - 84.0, - 85.0, - 86.0, - 87.0, - 88.0, - 89.0, - 90.0, - 91.0, - 92.0, - 93.0, - 94.0, - 95.0, - 96.0, - 97.0, - 98.0, - 99.0, - 100.0, - 101.0, - 102.0, - 103.0, - 104.0, - 105.0, - 106.0, - 107.0, - 108.0, - 109.0, - 110.0, - 111.0, - 112.0, - 113.0, - 114.0, - 115.0, - 116.0, - 117.0, - 118.0, - 119.0, - 120.0, - 121.0, - 122.0, - 123.0, - 124.0, - 125.0, - 126.0, - 127.0, - 128.0, - 129.0, - 130.0, - 131.0, - 132.0, - 133.0, - 134.0, - 135.0, - 136.0, - 137.0, - 138.0, - 139.0, - 140.0, - 141.0, - 142.0, - 143.0, - 144.0, - 145.0, - 146.0, - 147.0, - 148.0, - 149.0, - 150.0, - 151.0, - 152.0, - 153.0, - 154.0, - 155.0, - 156.0, - 157.0, - 158.0, - 159.0, - 160.0, - 161.0, - 162.0, - 163.0, - 164.0, - 165.0, - 166.0, - 167.0, - 168.0, - 169.0, - 170.0, - 171.0, - 172.0, - 173.0, - 174.0, - 175.0, - 176.0, - 177.0, - 178.0, - 179.0, - 180.0, - 181.0, - 182.0, - 183.0, - 184.0, - 185.0, - 186.0, - 187.0, - 188.0, - 189.0, - 190.0, - 191.0, - 192.0, - 193.0, - 194.0, - 195.0, - 196.0, - 197.0, - 198.0, - 199.0, - 200.0, - 201.0, - 202.0, - 203.0, - 204.0, - 205.0, - 206.0, - 207.0, - 208.0, - 209.0, - 210.0, - 211.0, - 212.0, - 213.0, - 214.0, - 215.0, - 216.0, - 217.0, - 218.0, - 219.0, - 220.0, - 221.0, - 222.0, - 223.0, - 224.0, - 225.0, - 226.0, - 227.0, - 228.0, - 229.0, - 230.0, - 231.0, - 232.0, - 233.0, - 234.0, - 235.0, - 236.0, - 237.0, - 238.0, - 239.0, - 240.0, - 241.0, - 242.0, - 243.0, - 244.0, - 245.0, - 246.0, - 247.0, - 248.0, - 249.0, - 250.0, - 251.0, - 252.0, - 253.0, - 254.0, - 255.0, - 256.0, - 257.0, - 258.0, - 259.0, - 260.0, - 261.0, - 262.0, - 263.0, - 264.0, - 265.0, - 266.0, - 267.0, - 268.0, - 269.0, - 270.0, - 271.0, - 272.0, - 273.0, - 274.0, - 275.0, - 276.0, - 277.0, - 278.0, - 279.0, - 280.0, - 281.0, - 282.0, - 283.0, - 284.0, - 285.0, - 286.0, - 287.0, - 288.0, - 289.0, - 290.0, - 291.0, - 292.0, - 293.0, - 294.0, - 295.0, - 296.0, - 297.0, - 298.0, - 299.0, - 300.0, - 301.0, - 302.0, - 303.0, - 304.0, - 305.0, - 306.0, - 307.0, - 308.0, - 309.0, - 310.0, - 311.0, - 312.0, - 313.0, - 314.0, - 315.0, - 316.0, - 317.0, - 318.0, - 319.0, - 320.0, - 321.0, - 322.0, - 323.0, - 324.0, - 325.0, - 326.0, - 327.0, - 328.0, - 329.0, - 330.0, - 331.0, - 332.0, - 333.0, - 334.0, - 335.0, - 336.0, - 337.0, - 338.0, - 339.0, - 340.0, - 341.0, - 342.0, - 343.0, - 344.0, - 345.0, - 346.0, - 347.0, - 348.0, - 349.0, - 350.0, - 351.0, - 352.0, - 353.0, - 354.0, - 355.0, - 356.0, - 357.0, - 358.0, - 359.0, - 360.0, - 361.0, - 362.0, - 363.0, - 364.0, - 365.0, - 366.0, - 367.0, - 368.0, - 369.0, - 370.0, - 371.0, - 372.0, - 373.0, - 374.0, - 375.0, - 376.0, - 377.0, - 378.0, - 379.0, - 380.0, - 381.0, - 382.0, - 383.0, - 384.0, - 385.0, - 386.0, - 387.0, - 388.0, - 389.0, - 390.0, - 391.0, - 392.0, - 393.0, - 394.0, - 395.0, - 396.0, - 397.0, - 398.0, - 399.0, - 400.0, - 401.0, - 402.0, - 403.0, - 404.0, - 405.0, - 406.0, - 407.0, - 408.0, - 409.0, - 410.0, - 411.0, - 412.0, - 413.0, - 414.0, - 415.0, - 416.0, - 417.0, - 418.0, - 419.0, - 420.0, - 421.0, - 422.0, - 423.0, - 424.0, - 425.0, - 426.0, - 427.0, - 428.0, - 429.0, - 430.0, - 431.0, - 432.0, - 433.0, - 434.0, - 435.0, - 436.0, - 437.0, - 438.0, - 439.0, - 440.0, - 441.0, - 442.0, - 443.0, - 444.0, - 445.0, - 446.0, - 447.0, - 448.0, - 449.0, - 450.0, - 451.0, - 452.0, - 453.0, - 454.0, - 455.0, - 456.0, - 457.0, - 458.0, - 459.0, - 460.0, - 461.0, - 462.0, - 463.0, - 464.0, - 465.0, - 466.0, - 467.0, - 468.0, - 469.0, - 470.0, - 471.0, - 472.0, - 473.0, - 474.0, - 475.0, - 476.0, - 477.0, - 478.0, - 479.0, - 480.0, - 481.0, - 482.0, - 483.0, - 484.0, - 485.0, - 486.0, - 487.0, - 488.0, - 489.0, - 490.0, - 491.0, - 492.0, - 493.0, - 494.0, - 495.0, - 496.0, - 497.0, - 498.0, - 499.0, - 500.0, - 501.0 -}; - -/** -* Evaluates a rational function (i.e., the ratio of two polynomials described by the coefficients stored in \\(P\\) and \\(Q\\)). -* -* ## Notes -* -* - Coefficients should be sorted in ascending degree. -* - The implementation uses [Horner's rule][horners-method] for efficient computation. -* -* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method -* -* @param x value at which to evaluate the rational function -* @return evaluated rational function -*/ -static double evalrational( const double x ) { - double s1; - double s2; - double ax; - double ix; - int i; - - if ( x == 0.0 ) { - return 1.0 / 0.0; - } - if ( x < 0.0 ) { - ax = -x; - } else { - ax = x; - } - if ( ax <= 1.0 ) { - s1 = EVALRATIONAL_COEFFICIENTS_P[ 501 ]; - s2 = EVALRATIONAL_COEFFICIENTS_Q[ 501 ]; - for ( i = 501-1; i >= 0; i-- ) { - s1 *= x; - s2 *= x; - s1 += EVALRATIONAL_COEFFICIENTS_P[ i ]; - s2 += EVALRATIONAL_COEFFICIENTS_Q[ i ]; - } - } else { - ix = 1.0 / x; // use inverse to avoid overflow - s1 = EVALRATIONAL_COEFFICIENTS_P[ 0 ]; - s2 = EVALRATIONAL_COEFFICIENTS_Q[ 0 ]; - for ( i = 1; i <= 501; i++ ) { - s1 *= ix; - s2 *= ix; - s1 += EVALRATIONAL_COEFFICIENTS_P[ i ]; - s2 += EVALRATIONAL_COEFFICIENTS_Q[ i ]; - } - } - return s1 / s2; -} diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/test.js b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/test.js index 97edbf2a33fa..bb9dc850be20 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/test.js +++ b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile-c/test/test.js @@ -272,88 +272,6 @@ tape( 'if provided coefficient arrays each containing 1 coefficient, the functio t.end(); }); -tape( 'if provided coefficient arrays each containing 1 coefficient, the function returns a function string which always returns the ratio of those two coefficients (positive infinity)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'coefficient_ratio_positive_infinity.c.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( [ 1.0 ], [ 0.0 ] ); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'if provided coefficient arrays each containing 1 coefficient, the function returns a function string which always returns the ratio of those two coefficients (positive infinity; custom)', opts, function test( t ) { - var expected; - var options; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'coefficient_ratio_positive_infinity_custom.c.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - options = { - 'dtype': 'float', - 'name': 'rational123' - }; - actual = compile( [ 1.0 ], [ 0.0 ], options ); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'if provided coefficient arrays each containing 1 coefficient, the function returns a function string which always returns the ratio of those two coefficients (negative infinity)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'coefficient_ratio_negative_infinity.c.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( [ -1.0 ], [ 0.0 ] ); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'if provided coefficient arrays each containing 1 coefficient, the function returns a function string which always returns the ratio of those two coefficients (negative infinity; custom)', opts, function test( t ) { - var expected; - var options; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'coefficient_ratio_negative_infinity_custom.c.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - options = { - 'dtype': 'float', - 'name': 'rational123' - }; - actual = compile( [ -1.0 ], [ 0.0 ], options ); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - tape( 'the function returns a function string which evaluates a rational function', opts, function test( t ) { var expected; var actual; @@ -412,24 +330,6 @@ tape( 'the function returns a function string which evaluates a rational functio t.end(); }); -tape( 'the function returns a function string which evaluates a rational function', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'evalrational4.c.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( [ -1.0, 2.5, 3.14, -1.0 ], [ 0.0, -3.5, 2.2, 1.25 ] ); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - tape( 'the function returns a function string which evaluates a rational function (custom)', opts, function test( t ) { var expected; var options; @@ -539,32 +439,3 @@ tape( 'the function returns a function string which evaluates a rational functio t.end(); }); - -tape( 'the function returns a function string which evaluates a rational function (large number of coefficients; integers and infinity)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - var P; - var Q; - var i; - - fpath = join( __dirname, 'fixtures', 'loop3.c.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - P = new Float64Array( 501 ); - Q = new Float64Array( 501 ); - for ( i = 0; i < P.length; i++ ) { - P[ i ] = i; - Q[ i ] = i + 1; - } - P[ 0 ] = 1.0; - Q[ 0 ] = 0.0; - actual = compile( P, Q ); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/README.md b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/README.md index a2d54b9c7eb5..8955f946738d 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/README.md +++ b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/README.md @@ -36,9 +36,9 @@ limitations under the License. var compile = require( '@stdlib/math/base/tools/evalrational-compile' ); ``` -#### compile( P, Q\[, options] ) +#### compile( P, Q ) -Compiles a module string containing an exported function which evaluates a [rational function][@stdlib/math/base/tools/evalrational] having coefficients `P` and `Q`. +Compiles a module `string` containing an exported function which evaluates a [rational function][@stdlib/math/base/tools/evalrational] having coefficients `P` and `Q`. ```javascript var P = [ 3.0, 2.0, 1.0 ]; @@ -48,11 +48,7 @@ var str = compile( P, Q ); // returns ``` -The function supports the following `options`: - -- **dtype**: input argument floating-point data type (e.g., `float64` or `float32`). Default: `'float64'`. - -In the example above, the output string would correspond to the following module: +In the example above, the output `string` would correspond to the following module: @@ -88,12 +84,12 @@ function evalrational( x ) { ax = x; } if ( ax <= 1.0 ) { - s1 = 3.0 + (x * (2.0 + (x * 1.0))); - s2 = -1.0 + (x * (-2.0 + (x * -3.0))); + s1 = 3.0 + (x * (2.0 + (x * 1.0))); // eslint-disable-line max-len + s2 = -1.0 + (x * (-2.0 + (x * -3.0))); // eslint-disable-line max-len } else { x = 1.0 / x; - s1 = 1.0 + (x * (2.0 + (x * 3.0))); - s2 = -3.0 + (x * (-2.0 + (x * -1.0))); + s1 = 1.0 + (x * (2.0 + (x * 3.0))); // eslint-disable-line max-len + s2 = -3.0 + (x * (-2.0 + (x * -1.0))); // eslint-disable-line max-len } return s1 / s2; } @@ -106,75 +102,6 @@ module.exports = evalrational; The coefficients should be ordered in **ascending** degree, thus matching summation notation. -By default, the function assumes double-precision floating-point arithmetic. To emulate single-precision floating-point arithmetic, set the `dtype` option to `'float32'`. - -```javascript -var P = [ 3.0, 2.0, 1.0 ]; -var Q = [ -1.0, -2.0, -3.0 ]; - -var str = compile( P, Q, { - 'dtype': 'float32' -}); -// returns -``` - -In the previous example, the output string would correspond to the following module: - - - -```javascript -'use strict'; - -// MODULES // - -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); - - -// MAIN // - -/** -* Evaluates a rational function (i.e., the ratio of two polynomials described by the coefficients stored in \\(P\\) and \\(Q\\)). -* -* ## Notes -* -* - Coefficients should be sorted in ascending degree. -* - The implementation uses [Horner's rule][horners-method] for efficient computation. -* -* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method -* -* @private -* @param {number} x - value at which to evaluate the rational function -* @returns {number} evaluated rational function -*/ -function evalrational( x ) { - var ax; - var s1; - var s2; - if ( x === 0.0 ) { - return -3.0; - } - if ( x < 0.0 ) { - ax = -x; - } else { - ax = x; - } - if ( ax <= 1.0 ) { - s1 = float64ToFloat32(3.0 + float64ToFloat32(x * float64ToFloat32(2.0 + float64ToFloat32(x * 1.0)))); // eslint-disable-line max-len - s2 = float64ToFloat32(-1.0 + float64ToFloat32(x * float64ToFloat32(-2.0 + float64ToFloat32(x * -3.0)))); // eslint-disable-line max-len - } else { - x = float64ToFloat32( 1.0 / x ); - s1 = float64ToFloat32(1.0 + float64ToFloat32(x * float64ToFloat32(2.0 + float64ToFloat32(x * 3.0)))); // eslint-disable-line max-len - s2 = float64ToFloat32(-3.0 + float64ToFloat32(x * float64ToFloat32(-2.0 + float64ToFloat32(x * -1.0)))); // eslint-disable-line max-len - } - return float64ToFloat32( s1 / s2 ); -} - - -// EXPORTS // - -module.exports = evalrational; -``` -
@@ -196,15 +123,32 @@ module.exports = evalrational; ```javascript -var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float64Array = require( '@stdlib/array/float64' ); var compile = require( '@stdlib/math/base/tools/evalrational-compile' ); -// Create arrays of random coefficients: -var P = discreteUniform( 10, -100, 100 ); -var Q = discreteUniform( 10, -100, 100 ); +var sign; +var str; +var P; +var Q; +var i; + +// Create two arrays of random coefficients... +P = new Float64Array( 10 ); +Q = new Float64Array( 10 ); +for ( i = 0; i < P.length; i++ ) { + if ( randu() < 0.5 ) { + sign = -1.0; + } else { + sign = 1.0; + } + P[ i ] = sign * round( randu()*100.0 ); + Q[ i ] = sign * round( randu()*100.0 ); +} // Compile a module for evaluating a rational function: -var str = compile( P, Q ); +str = compile( P, Q ); console.log( str ); ``` diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/docs/types/index.d.ts b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/docs/types/index.d.ts index 749ca7163040..f224d81c394b 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/docs/types/index.d.ts @@ -18,26 +18,11 @@ // TypeScript Version: 4.1 -/// - -import { Collection } from '@stdlib/types/array'; - -/** -* Interface describing function options. -*/ -interface Options { - /** - * Input value floating-point data type (e.g., `float64` or `float32`). Default: `'float64'`. - */ - dtype?: 'float64' | 'float32'; -} - /** * Compiles a module string which exports a function for evaluating a rational function. * * @param P - numerator polynomial coefficients sorted in ascending degree * @param Q - denominator polynomial coefficients sorted in ascending degree -* @param options - function options * @returns module string exporting a function for evaluating a rational function * * @example @@ -47,7 +32,7 @@ interface Options { * var str = compile( P, Q ); * // returns */ -declare function compile( P: Collection, Q: Collection, options?: Options ): string; +declare function compile( P: Array, Q: Array ): string; // EXPORTS // diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/docs/types/test.ts b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/docs/types/test.ts index 7a58924b43f2..82cb278faaf2 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/docs/types/test.ts +++ b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/docs/types/test.ts @@ -24,75 +24,33 @@ import compile = require( './index' ); // The function returns a string... { compile( [ -6.0, -5.0 ], [ 3.0, 0.5 ] ); // $ExpectType string - compile( [ 3.0, 2.0, 1.0 ], { 'dtype': 'float32' } ); // $ExpectType string } // The compiler throws an error if the function is provided a first argument which is not an array of numbers... { const Q = [ 3.0, 0.5 ]; - compile( true, Q ); // $ExpectError compile( false, Q ); // $ExpectError compile( 'abc', Q ); // $ExpectError compile( 123, Q ); // $ExpectError compile( {}, Q ); // $ExpectError compile( ( x: number ): number => x, Q ); // $ExpectError - - compile( true, Q, {} ); // $ExpectError - compile( false, Q, {} ); // $ExpectError - compile( 'abc', Q, {} ); // $ExpectError - compile( 123, Q, {} ); // $ExpectError - compile( {}, Q, {} ); // $ExpectError - compile( ( x: number ): number => x, Q, {} ); // $ExpectError } // The compiler throws an error if the function is provided a second argument which is not an array of numbers... { const P = [ -6.0, -5.0 ]; - compile( P, true ); // $ExpectError compile( P, false ); // $ExpectError compile( P, 'abc' ); // $ExpectError compile( P, 123 ); // $ExpectError compile( P, {} ); // $ExpectError compile( P, ( x: number ): number => x ); // $ExpectError - - compile( P, true, {} ); // $ExpectError - compile( P, false, {} ); // $ExpectError - compile( P, 'abc', {} ); // $ExpectError - compile( P, 123, {} ); // $ExpectError - compile( P, {}, {} ); // $ExpectError - compile( P, ( x: number ): number => x, {} ); // $ExpectError -} - -// The compiler throws an error if the function is provided a third argument which is not an object... -{ - const P = [ -6.0, -5.0 ]; - const Q = [ 3.0, 0.5 ]; - - compile( P, Q, true ); // $ExpectError - compile( P, Q, false ); // $ExpectError - compile( P, Q, 'abc' ); // $ExpectError - compile( P, Q, 123 ); // $ExpectError - compile( P, Q, ( x: number ): number => x ); // $ExpectError -} - -// The compiler throws an error if the function is provided an invalid `dtype` option... -{ - const P = [ -6.0, -5.0 ]; - const Q = [ 3.0, 0.5 ]; - - compile( P, Q, { 'dtype': true } ); // $ExpectError - compile( P, Q, { 'dtype': false } ); // $ExpectError - compile( P, Q, { 'dtype': [] } ); // $ExpectError - compile( P, Q, { 'dtype': 123 } ); // $ExpectError - compile( P, Q, { 'dtype': ( x: number ): number => x } ); // $ExpectError } // The compiler throws an error if the function is provided an insufficient number of arguments... { const P = [ -6.0, -5.0 ]; - compile(); // $ExpectError compile( P ); // $ExpectError } diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/examples/index.js b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/examples/index.js index 1bde208e6090..36161935327c 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/examples/index.js +++ b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/examples/index.js @@ -19,7 +19,9 @@ 'use strict'; var resolve = require( 'path' ).resolve; -var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var compile = tryRequire( resolve( __dirname, '..', 'lib' ) ); @@ -30,11 +32,26 @@ if ( compile instanceof Error ) { } function main() { - // Create arrays of random coefficients: - var P = discreteUniform( 10, -100, 100 ); - var Q = discreteUniform( 10, -100, 100 ); + var sign; + var str; + var P; + var Q; + var i; + + // Create two arrays of random coefficients... + P = new Float64Array( 10 ); + Q = new Float64Array( 10 ); + for ( i = 0; i < P.length; i++ ) { + if ( randu() < 0.5 ) { + sign = -1.0; + } else { + sign = 1.0; + } + P[ i ] = sign * round( randu()*100.0 ); + Q[ i ] = sign * round( randu()*100.0 ); + } // Compile a module for evaluating a rational function: - var str = compile( P, Q ); + str = compile( P, Q ); console.log( str ); } diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/lib/main.js b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/lib/main.js index b774195b0020..81289ac12074 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/lib/main.js +++ b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/lib/main.js @@ -24,8 +24,6 @@ var join = require( 'path' ).join; var readFile = require( '@stdlib/fs/read-file' ).sync; var replace = require( '@stdlib/string/replace' ); var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; -var Float32Array = require( '@stdlib/array/float32' ); -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); // VARIABLES // @@ -37,15 +35,9 @@ var dir = join( __dirname, 'templates' ); // Templates: var COEFFICIENT_RATIO_TEMPLATE = readFile( join( dir, 'coefficient_ratio.js.txt' ), opts ); // eslint-disable-line id-length - var EVALRATIONAL_TEMPLATE = readFile( join( dir, 'evalrational.js.txt' ), opts ); -var EVALRATIONAL_FLOAT32_TEMPLATE = readFile( join( dir, 'evalrational.float32.js.txt' ), opts ); // eslint-disable-line id-length - var LOOP_TEMPLATE = readFile( join( dir, 'loop.js.txt' ), opts ); -var LOOP_FLOAT32_TEMPLATE = readFile( join( dir, 'loop.float32.js.txt' ), opts ); - var NAN_TEMPLATE = readFile( join( dir, 'nan.js.txt' ), opts ); - var MAX_CHARS = 66; // max-len (80) - chars already in line ('2x tab': 8, 's1 = ': 5, ';': 1) @@ -99,10 +91,9 @@ function array2list( x ) { * * @private * @param {NumericArray} x - coefficients sorted in ascending degree -* @param {string} dtype - input value floating-point data type * @returns {string} output string */ -function hornerAscending( x, dtype ) { +function hornerAscending( x ) { var str; var n; var m; @@ -110,26 +101,14 @@ function hornerAscending( x, dtype ) { n = x.length; m = n - 1; - if ( dtype === 'float32' ) { - str = 'float64ToFloat32('; - } else { - str = ''; - } - str += x[ 0 ].toString(); + str = x[ 0 ].toString(); if ( isInteger( x[ 0 ] ) ) { str += '.0'; } for ( i = 1; i < n; i++ ) { - if ( dtype === 'float32' ) { - str += ' + float64ToFloat32(x * '; - if ( i < m ) { - str += 'float64ToFloat32('; - } - } else { - str += ' + (x * '; - if ( i < m ) { - str += '('; - } + str += ' + (x * '; + if ( i < m ) { + str += '('; } str += x[ i ].toString(); if ( isInteger( x[ i ] ) ) { @@ -140,9 +119,6 @@ function hornerAscending( x, dtype ) { for ( i = 0; i < (2*m)-1; i++ ) { str += ')'; } - if ( dtype === 'float32' ) { - str += ')'; - } return str; } @@ -151,35 +127,22 @@ function hornerAscending( x, dtype ) { * * @private * @param {NumericArray} x - coefficients sorted in descending degree -* @param {string} dtype - input value floating-point data type * @returns {string} output string */ -function hornerDescending( x, dtype ) { +function hornerDescending( x ) { var str; var m; var i; m = x.length - 1; - if ( dtype === 'float32' ) { - str = 'float64ToFloat32('; - } else { - str = ''; - } - str += x[ m ].toString(); + str = x[ m ].toString(); if ( isInteger( x[ m ] ) ) { str += '.0'; } for ( i = m-1; i >= 0; i-- ) { - if ( dtype === 'float32' ) { - str += ' + float64ToFloat32(x * '; - if ( i > 0 ) { - str += 'float64ToFloat32('; - } - } else { - str += ' + (x * '; - if ( i > 0 ) { - str += '('; - } + str += ' + (x * '; + if ( i > 0 ) { + str += '('; } str += x[ i ].toString(); if ( isInteger( x[ i ] ) ) { @@ -190,9 +153,6 @@ function hornerDescending( x, dtype ) { for ( i = 0; i < (2*m)-1; i++ ) { str += ')'; } - if ( dtype === 'float32' ) { - str += ')'; - } return str; } @@ -223,8 +183,6 @@ function replaceString( src, target, str ) { * * @param {NumericArray} P - numerator polynomial coefficients sorted in ascending degree * @param {NumericArray} Q - denominator polynomial coefficients sorted in ascending degree -* @param {Options} [options] - function options -* @param {string} [options.dtype='float64'] - input value floating-point data type * @returns {string} module string exporting a function for evaluating a rational function * * @example @@ -234,19 +192,10 @@ function replaceString( src, target, str ) { * var str = compile( P, Q ); * // returns */ -function compile( P, Q, options ) { - var opts; - var tmpl; +function compile( P, Q ) { var str; var n; - var r; - opts = { - 'dtype': 'float64' - }; - if ( arguments.length > 2 ) { - opts.dtype = options.dtype || opts.dtype; - } n = P.length; // If no coefficients, the function always returns NaN... @@ -257,38 +206,22 @@ function compile( P, Q, options ) { if ( n !== Q.length ) { return NAN_TEMPLATE; } - r = P[0] / Q[0]; - if ( opts.dtype === 'float32' ) { - P = new Float32Array( P ); - Q = new Float32Array( Q ); - r = float64ToFloat32( r ); - } // If P and Q only have one coefficient, the function always returns the ratio of those coefficients... if ( n === 1 ) { - return replace( COEFFICIENT_RATIO_TEMPLATE, '{{ratio}}', value2string( r ) ); + return replace( COEFFICIENT_RATIO_TEMPLATE, '{{ratio}}', value2string( P[0] / Q[0] ) ); } // Avoid exceeding the maximum stack size on V8 by using a simple loop :(. Note that the choice of `500` was empirically determined... if ( n > 500 ) { - if ( opts.dtype === 'float32' ) { - tmpl = LOOP_FLOAT32_TEMPLATE; - } else { - tmpl = LOOP_TEMPLATE; - } - str = replace( tmpl, '{{P}}', array2list( P ) ); + str = replace( LOOP_TEMPLATE, '{{P}}', array2list( P ) ); str = replace( str, '{{Q}}', array2list( Q ) ); - return replace( str, '{{ratio}}', value2string( r ) ); + return replace( str, '{{ratio}}', value2string( P[0]/Q[0] ) ); } // If more than one coefficient, apply Horner's method... - if ( opts.dtype === 'float32' ) { - tmpl = EVALRATIONAL_FLOAT32_TEMPLATE; - } else { - tmpl = EVALRATIONAL_TEMPLATE; - } - str = replaceString( tmpl, 'P_ASCENDING', hornerAscending( P, opts.dtype ) ); - str = replaceString( str, 'Q_ASCENDING', hornerAscending( Q, opts.dtype ) ); - str = replaceString( str, 'P_DESCENDING', hornerDescending( P, opts.dtype ) ); - str = replaceString( str, 'Q_DESCENDING', hornerDescending( Q, opts.dtype ) ); - return replace( str, '{{ratio}}', value2string( r ) ); + str = replaceString( EVALRATIONAL_TEMPLATE, 'P_ASCENDING', hornerAscending( P ) ); + str = replaceString( str, 'Q_ASCENDING', hornerAscending( Q ) ); + str = replaceString( str, 'P_DESCENDING', hornerDescending( P ) ); + str = replaceString( str, 'Q_DESCENDING', hornerDescending( Q ) ); + return replace( str, '{{ratio}}', value2string( P[0]/Q[0] ) ); } diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/lib/templates/evalrational.float32.js.txt b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/lib/templates/evalrational.float32.js.txt deleted file mode 100644 index 9cc338633e8f..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/lib/templates/evalrational.float32.js.txt +++ /dev/null @@ -1,50 +0,0 @@ -'use strict'; - -// MODULES // - -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); - - -// MAIN // - -/** -* Evaluates a rational function (i.e., the ratio of two polynomials described by the coefficients stored in \\(P\\) and \\(Q\\)). -* -* ## Notes -* -* - Coefficients should be sorted in ascending degree. -* - The implementation uses [Horner's rule][horners-method] for efficient computation. -* -* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method -* -* @private -* @param {number} x - value at which to evaluate the rational function -* @returns {number} evaluated rational function -*/ -function evalrational( x ) { - var ax; - var s1; - var s2; - if ( x === 0.0 ) { - return {{ratio}}; - } - if ( x < 0.0 ) { - ax = -x; - } else { - ax = x; - } - if ( ax <= 1.0 ) { - s1 = {{P_ASCENDING}};{{P_ASCENDING_ESLINT}} - s2 = {{Q_ASCENDING}};{{Q_ASCENDING_ESLINT}} - } else { - x = float64ToFloat32( 1.0 / x ); - s1 = {{P_DESCENDING}};{{P_DESCENDING_ESLINT}} - s2 = {{Q_DESCENDING}};{{Q_DESCENDING_ESLINT}} - } - return float64ToFloat32( s1 / s2 ); -} - - -// EXPORTS // - -module.exports = evalrational; diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/lib/templates/loop.float32.js.txt b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/lib/templates/loop.float32.js.txt deleted file mode 100644 index 8d41096d7129..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/lib/templates/loop.float32.js.txt +++ /dev/null @@ -1,70 +0,0 @@ -'use strict'; - -// MODULES // - -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); -var abs = require( '@stdlib/math/base/special/abs' ); - - -// VARIABLES // - -var P = [ -{{P}} -]; -var Q = [ -{{Q}} -]; -var END = P.length - 1; - - -// MAIN // - -/** -* Evaluates a rational function (i.e., the ratio of two polynomials described by the coefficients stored in \\(P\\) and \\(Q\\)). -* -* ## Notes -* -* - Coefficients should be sorted in ascending degree. -* - The implementation uses [Horner's rule][horners-method] for efficient computation. -* -* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method -* -* @private -* @param {number} x - value at which to evaluate the rational function -* @returns {number} evaluated rational function -*/ -function evalrational( x ) { - var s1; - var s2; - var i; - - if ( x === 0.0 ) { - return {{ratio}}; - } - if ( abs( x ) <= 1.0 ) { - s1 = P[ END ]; - s2 = Q[ END ]; - for ( i = END-1; i >= 0; i-- ) { - s1 = float64ToFloat32( s1 * x ); - s2 = float64ToFloat32( s2 * x ); - s1 = float64ToFloat32( s1 + P[ i ] ); - s2 = float64ToFloat32( s2 + Q[ i ] ); - } - } else { - x = float64ToFloat32( 1.0 / x ); // use inverse to avoid overflow - s1 = P[ 0 ]; - s2 = Q[ 0 ]; - for ( i = 1; i <= END; i++ ) { - s1 = float64ToFloat32( s1 * x ); - s2 = float64ToFloat32( s2 * x ); - s1 = float64ToFloat32( s1 + P[ i ] ); - s2 = float64ToFloat32( s2 + Q[ i ] ); - } - } - return float64ToFloat32( s1 / s2 ); -} - - -// EXPORTS // - -module.exports = evalrational; diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/coefficient_ratio.float32.js.txt b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/coefficient_ratio.float32.js.txt deleted file mode 100644 index 9c5441284ee2..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/coefficient_ratio.float32.js.txt +++ /dev/null @@ -1,19 +0,0 @@ -'use strict'; - -// MAIN // - -/** -* Evaluates a rational function. -* -* @private -* @param {number} x - value at which to evaluate the rational function -* @returns {number} evaluated rational function -*/ -function evalrational() { - return -6.28000020980835; -} - - -// EXPORTS // - -module.exports = evalrational; diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/coefficient_ratio_integer.js.txt b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/coefficient_ratio_integer.js.txt index bc02f6d8caa7..0dd61b1ff67f 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/coefficient_ratio_integer.js.txt +++ b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/coefficient_ratio_integer.js.txt @@ -10,7 +10,7 @@ * @returns {number} evaluated rational function */ function evalrational() { - return -1.5; + return -2.0; } diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/evalrational1.float32.js.txt b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/evalrational1.float32.js.txt deleted file mode 100644 index 49b2b1280f0d..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/evalrational1.float32.js.txt +++ /dev/null @@ -1,50 +0,0 @@ -'use strict'; - -// MODULES // - -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); - - -// MAIN // - -/** -* Evaluates a rational function (i.e., the ratio of two polynomials described by the coefficients stored in \\(P\\) and \\(Q\\)). -* -* ## Notes -* -* - Coefficients should be sorted in ascending degree. -* - The implementation uses [Horner's rule][horners-method] for efficient computation. -* -* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method -* -* @private -* @param {number} x - value at which to evaluate the rational function -* @returns {number} evaluated rational function -*/ -function evalrational( x ) { - var ax; - var s1; - var s2; - if ( x === 0.0 ) { - return 0.25; - } - if ( x < 0.0 ) { - ax = -x; - } else { - ax = x; - } - if ( ax <= 1.0 ) { - s1 = float64ToFloat32(1.0 + float64ToFloat32(x * float64ToFloat32(2.5 + float64ToFloat32(x * float64ToFloat32(3.140000104904175 + float64ToFloat32(x * -1.0)))))); // eslint-disable-line max-len - s2 = float64ToFloat32(4.0 + float64ToFloat32(x * float64ToFloat32(-3.5 + float64ToFloat32(x * float64ToFloat32(2.200000047683716 + float64ToFloat32(x * 1.25)))))); // eslint-disable-line max-len - } else { - x = float64ToFloat32( 1.0 / x ); - s1 = float64ToFloat32(-1.0 + float64ToFloat32(x * float64ToFloat32(3.140000104904175 + float64ToFloat32(x * float64ToFloat32(2.5 + float64ToFloat32(x * 1.0)))))); // eslint-disable-line max-len - s2 = float64ToFloat32(1.25 + float64ToFloat32(x * float64ToFloat32(2.200000047683716 + float64ToFloat32(x * float64ToFloat32(-3.5 + float64ToFloat32(x * 4.0)))))); // eslint-disable-line max-len - } - return float64ToFloat32( s1 / s2 ); -} - - -// EXPORTS // - -module.exports = evalrational; diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/evalrational2.float32.js.txt b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/evalrational2.float32.js.txt deleted file mode 100644 index 10ccc1b43dc3..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/evalrational2.float32.js.txt +++ /dev/null @@ -1,50 +0,0 @@ -'use strict'; - -// MODULES // - -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); - - -// MAIN // - -/** -* Evaluates a rational function (i.e., the ratio of two polynomials described by the coefficients stored in \\(P\\) and \\(Q\\)). -* -* ## Notes -* -* - Coefficients should be sorted in ascending degree. -* - The implementation uses [Horner's rule][horners-method] for efficient computation. -* -* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method -* -* @private -* @param {number} x - value at which to evaluate the rational function -* @returns {number} evaluated rational function -*/ -function evalrational( x ) { - var ax; - var s1; - var s2; - if ( x === 0.0 ) { - return -0.5233333706855774; - } - if ( x < 0.0 ) { - ax = -x; - } else { - ax = x; - } - if ( ax <= 1.0 ) { - s1 = float64ToFloat32(-3.140000104904175 + float64ToFloat32(x * 0.0)); - s2 = float64ToFloat32(6.0 + float64ToFloat32(x * 0.0)); - } else { - x = float64ToFloat32( 1.0 / x ); - s1 = float64ToFloat32(0.0 + float64ToFloat32(x * -3.140000104904175)); - s2 = float64ToFloat32(0.0 + float64ToFloat32(x * 6.0)); - } - return float64ToFloat32( s1 / s2 ); -} - - -// EXPORTS // - -module.exports = evalrational; diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/evalrational3.float32.js.txt b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/evalrational3.float32.js.txt deleted file mode 100644 index 07ef4f2b32c1..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/evalrational3.float32.js.txt +++ /dev/null @@ -1,50 +0,0 @@ -'use strict'; - -// MODULES // - -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); - - -// MAIN // - -/** -* Evaluates a rational function (i.e., the ratio of two polynomials described by the coefficients stored in \\(P\\) and \\(Q\\)). -* -* ## Notes -* -* - Coefficients should be sorted in ascending degree. -* - The implementation uses [Horner's rule][horners-method] for efficient computation. -* -* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method -* -* @private -* @param {number} x - value at which to evaluate the rational function -* @returns {number} evaluated rational function -*/ -function evalrational( x ) { - var ax; - var s1; - var s2; - if ( x === 0.0 ) { - return -0.5233333706855774; - } - if ( x < 0.0 ) { - ax = -x; - } else { - ax = x; - } - if ( ax <= 1.0 ) { - s1 = float64ToFloat32(-3.140000104904175 + float64ToFloat32(x * float64ToFloat32(0.0 + float64ToFloat32(x * float64ToFloat32(4.0 + float64ToFloat32(x * float64ToFloat32(2.0 + float64ToFloat32(x * float64ToFloat32(3.0 + float64ToFloat32(x * float64ToFloat32(9.0 + float64ToFloat32(x * 5.400000095367432)))))))))))); // eslint-disable-line max-len - s2 = float64ToFloat32(6.0 + float64ToFloat32(x * float64ToFloat32(0.0 + float64ToFloat32(x * float64ToFloat32(2.0 + float64ToFloat32(x * float64ToFloat32(1.0 + float64ToFloat32(x * float64ToFloat32(2.0 + float64ToFloat32(x * float64ToFloat32(4.800000190734863 + float64ToFloat32(x * 2.200000047683716)))))))))))); // eslint-disable-line max-len - } else { - x = float64ToFloat32( 1.0 / x ); - s1 = float64ToFloat32(5.400000095367432 + float64ToFloat32(x * float64ToFloat32(9.0 + float64ToFloat32(x * float64ToFloat32(3.0 + float64ToFloat32(x * float64ToFloat32(2.0 + float64ToFloat32(x * float64ToFloat32(4.0 + float64ToFloat32(x * float64ToFloat32(0.0 + float64ToFloat32(x * -3.140000104904175)))))))))))); // eslint-disable-line max-len - s2 = float64ToFloat32(2.200000047683716 + float64ToFloat32(x * float64ToFloat32(4.800000190734863 + float64ToFloat32(x * float64ToFloat32(2.0 + float64ToFloat32(x * float64ToFloat32(1.0 + float64ToFloat32(x * float64ToFloat32(2.0 + float64ToFloat32(x * float64ToFloat32(0.0 + float64ToFloat32(x * 6.0)))))))))))); // eslint-disable-line max-len - } - return float64ToFloat32( s1 / s2 ); -} - - -// EXPORTS // - -module.exports = evalrational; diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/loop1.float32.js.txt b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/loop1.float32.js.txt deleted file mode 100644 index d062bdb4fbba..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/loop1.float32.js.txt +++ /dev/null @@ -1,1070 +0,0 @@ -'use strict'; - -// MODULES // - -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); -var abs = require( '@stdlib/math/base/special/abs' ); - - -// VARIABLES // - -var P = [ - 0.0, - 1.0, - 2.0, - 3.0, - 4.0, - 5.0, - 6.0, - 7.0, - 8.0, - 9.0, - 10.0, - 11.0, - 12.0, - 13.0, - 14.0, - 15.0, - 16.0, - 17.0, - 18.0, - 19.0, - 20.0, - 21.0, - 22.0, - 23.0, - 24.0, - 25.0, - 26.0, - 27.0, - 28.0, - 29.0, - 30.0, - 31.0, - 32.0, - 33.0, - 34.0, - 35.0, - 36.0, - 37.0, - 38.0, - 39.0, - 40.0, - 41.0, - 42.0, - 43.0, - 44.0, - 45.0, - 46.0, - 47.0, - 48.0, - 49.0, - 50.0, - 51.0, - 52.0, - 53.0, - 54.0, - 55.0, - 56.0, - 57.0, - 58.0, - 59.0, - 60.0, - 61.0, - 62.0, - 63.0, - 64.0, - 65.0, - 66.0, - 67.0, - 68.0, - 69.0, - 70.0, - 71.0, - 72.0, - 73.0, - 74.0, - 75.0, - 76.0, - 77.0, - 78.0, - 79.0, - 80.0, - 81.0, - 82.0, - 83.0, - 84.0, - 85.0, - 86.0, - 87.0, - 88.0, - 89.0, - 90.0, - 91.0, - 92.0, - 93.0, - 94.0, - 95.0, - 96.0, - 97.0, - 98.0, - 99.0, - 100.0, - 101.0, - 102.0, - 103.0, - 104.0, - 105.0, - 106.0, - 107.0, - 108.0, - 109.0, - 110.0, - 111.0, - 112.0, - 113.0, - 114.0, - 115.0, - 116.0, - 117.0, - 118.0, - 119.0, - 120.0, - 121.0, - 122.0, - 123.0, - 124.0, - 125.0, - 126.0, - 127.0, - 128.0, - 129.0, - 130.0, - 131.0, - 132.0, - 133.0, - 134.0, - 135.0, - 136.0, - 137.0, - 138.0, - 139.0, - 140.0, - 141.0, - 142.0, - 143.0, - 144.0, - 145.0, - 146.0, - 147.0, - 148.0, - 149.0, - 150.0, - 151.0, - 152.0, - 153.0, - 154.0, - 155.0, - 156.0, - 157.0, - 158.0, - 159.0, - 160.0, - 161.0, - 162.0, - 163.0, - 164.0, - 165.0, - 166.0, - 167.0, - 168.0, - 169.0, - 170.0, - 171.0, - 172.0, - 173.0, - 174.0, - 175.0, - 176.0, - 177.0, - 178.0, - 179.0, - 180.0, - 181.0, - 182.0, - 183.0, - 184.0, - 185.0, - 186.0, - 187.0, - 188.0, - 189.0, - 190.0, - 191.0, - 192.0, - 193.0, - 194.0, - 195.0, - 196.0, - 197.0, - 198.0, - 199.0, - 200.0, - 201.0, - 202.0, - 203.0, - 204.0, - 205.0, - 206.0, - 207.0, - 208.0, - 209.0, - 210.0, - 211.0, - 212.0, - 213.0, - 214.0, - 215.0, - 216.0, - 217.0, - 218.0, - 219.0, - 220.0, - 221.0, - 222.0, - 223.0, - 224.0, - 225.0, - 226.0, - 227.0, - 228.0, - 229.0, - 230.0, - 231.0, - 232.0, - 233.0, - 234.0, - 235.0, - 236.0, - 237.0, - 238.0, - 239.0, - 240.0, - 241.0, - 242.0, - 243.0, - 244.0, - 245.0, - 246.0, - 247.0, - 248.0, - 249.0, - 250.0, - 251.0, - 252.0, - 253.0, - 254.0, - 255.0, - 256.0, - 257.0, - 258.0, - 259.0, - 260.0, - 261.0, - 262.0, - 263.0, - 264.0, - 265.0, - 266.0, - 267.0, - 268.0, - 269.0, - 270.0, - 271.0, - 272.0, - 273.0, - 274.0, - 275.0, - 276.0, - 277.0, - 278.0, - 279.0, - 280.0, - 281.0, - 282.0, - 283.0, - 284.0, - 285.0, - 286.0, - 287.0, - 288.0, - 289.0, - 290.0, - 291.0, - 292.0, - 293.0, - 294.0, - 295.0, - 296.0, - 297.0, - 298.0, - 299.0, - 300.0, - 301.0, - 302.0, - 303.0, - 304.0, - 305.0, - 306.0, - 307.0, - 308.0, - 309.0, - 310.0, - 311.0, - 312.0, - 313.0, - 314.0, - 315.0, - 316.0, - 317.0, - 318.0, - 319.0, - 320.0, - 321.0, - 322.0, - 323.0, - 324.0, - 325.0, - 326.0, - 327.0, - 328.0, - 329.0, - 330.0, - 331.0, - 332.0, - 333.0, - 334.0, - 335.0, - 336.0, - 337.0, - 338.0, - 339.0, - 340.0, - 341.0, - 342.0, - 343.0, - 344.0, - 345.0, - 346.0, - 347.0, - 348.0, - 349.0, - 350.0, - 351.0, - 352.0, - 353.0, - 354.0, - 355.0, - 356.0, - 357.0, - 358.0, - 359.0, - 360.0, - 361.0, - 362.0, - 363.0, - 364.0, - 365.0, - 366.0, - 367.0, - 368.0, - 369.0, - 370.0, - 371.0, - 372.0, - 373.0, - 374.0, - 375.0, - 376.0, - 377.0, - 378.0, - 379.0, - 380.0, - 381.0, - 382.0, - 383.0, - 384.0, - 385.0, - 386.0, - 387.0, - 388.0, - 389.0, - 390.0, - 391.0, - 392.0, - 393.0, - 394.0, - 395.0, - 396.0, - 397.0, - 398.0, - 399.0, - 400.0, - 401.0, - 402.0, - 403.0, - 404.0, - 405.0, - 406.0, - 407.0, - 408.0, - 409.0, - 410.0, - 411.0, - 412.0, - 413.0, - 414.0, - 415.0, - 416.0, - 417.0, - 418.0, - 419.0, - 420.0, - 421.0, - 422.0, - 423.0, - 424.0, - 425.0, - 426.0, - 427.0, - 428.0, - 429.0, - 430.0, - 431.0, - 432.0, - 433.0, - 434.0, - 435.0, - 436.0, - 437.0, - 438.0, - 439.0, - 440.0, - 441.0, - 442.0, - 443.0, - 444.0, - 445.0, - 446.0, - 447.0, - 448.0, - 449.0, - 450.0, - 451.0, - 452.0, - 453.0, - 454.0, - 455.0, - 456.0, - 457.0, - 458.0, - 459.0, - 460.0, - 461.0, - 462.0, - 463.0, - 464.0, - 465.0, - 466.0, - 467.0, - 468.0, - 469.0, - 470.0, - 471.0, - 472.0, - 473.0, - 474.0, - 475.0, - 476.0, - 477.0, - 478.0, - 479.0, - 480.0, - 481.0, - 482.0, - 483.0, - 484.0, - 485.0, - 486.0, - 487.0, - 488.0, - 489.0, - 490.0, - 491.0, - 492.0, - 493.0, - 494.0, - 495.0, - 496.0, - 497.0, - 498.0, - 499.0, - 500.0 -]; -var Q = [ - 1.0, - 2.0, - 3.0, - 4.0, - 5.0, - 6.0, - 7.0, - 8.0, - 9.0, - 10.0, - 11.0, - 12.0, - 13.0, - 14.0, - 15.0, - 16.0, - 17.0, - 18.0, - 19.0, - 20.0, - 21.0, - 22.0, - 23.0, - 24.0, - 25.0, - 26.0, - 27.0, - 28.0, - 29.0, - 30.0, - 31.0, - 32.0, - 33.0, - 34.0, - 35.0, - 36.0, - 37.0, - 38.0, - 39.0, - 40.0, - 41.0, - 42.0, - 43.0, - 44.0, - 45.0, - 46.0, - 47.0, - 48.0, - 49.0, - 50.0, - 51.0, - 52.0, - 53.0, - 54.0, - 55.0, - 56.0, - 57.0, - 58.0, - 59.0, - 60.0, - 61.0, - 62.0, - 63.0, - 64.0, - 65.0, - 66.0, - 67.0, - 68.0, - 69.0, - 70.0, - 71.0, - 72.0, - 73.0, - 74.0, - 75.0, - 76.0, - 77.0, - 78.0, - 79.0, - 80.0, - 81.0, - 82.0, - 83.0, - 84.0, - 85.0, - 86.0, - 87.0, - 88.0, - 89.0, - 90.0, - 91.0, - 92.0, - 93.0, - 94.0, - 95.0, - 96.0, - 97.0, - 98.0, - 99.0, - 100.0, - 101.0, - 102.0, - 103.0, - 104.0, - 105.0, - 106.0, - 107.0, - 108.0, - 109.0, - 110.0, - 111.0, - 112.0, - 113.0, - 114.0, - 115.0, - 116.0, - 117.0, - 118.0, - 119.0, - 120.0, - 121.0, - 122.0, - 123.0, - 124.0, - 125.0, - 126.0, - 127.0, - 128.0, - 129.0, - 130.0, - 131.0, - 132.0, - 133.0, - 134.0, - 135.0, - 136.0, - 137.0, - 138.0, - 139.0, - 140.0, - 141.0, - 142.0, - 143.0, - 144.0, - 145.0, - 146.0, - 147.0, - 148.0, - 149.0, - 150.0, - 151.0, - 152.0, - 153.0, - 154.0, - 155.0, - 156.0, - 157.0, - 158.0, - 159.0, - 160.0, - 161.0, - 162.0, - 163.0, - 164.0, - 165.0, - 166.0, - 167.0, - 168.0, - 169.0, - 170.0, - 171.0, - 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284.0, - 285.0, - 286.0, - 287.0, - 288.0, - 289.0, - 290.0, - 291.0, - 292.0, - 293.0, - 294.0, - 295.0, - 296.0, - 297.0, - 298.0, - 299.0, - 300.0, - 301.0, - 302.0, - 303.0, - 304.0, - 305.0, - 306.0, - 307.0, - 308.0, - 309.0, - 310.0, - 311.0, - 312.0, - 313.0, - 314.0, - 315.0, - 316.0, - 317.0, - 318.0, - 319.0, - 320.0, - 321.0, - 322.0, - 323.0, - 324.0, - 325.0, - 326.0, - 327.0, - 328.0, - 329.0, - 330.0, - 331.0, - 332.0, - 333.0, - 334.0, - 335.0, - 336.0, - 337.0, - 338.0, - 339.0, - 340.0, - 341.0, - 342.0, - 343.0, - 344.0, - 345.0, - 346.0, - 347.0, - 348.0, - 349.0, - 350.0, - 351.0, - 352.0, - 353.0, - 354.0, - 355.0, - 356.0, - 357.0, - 358.0, - 359.0, - 360.0, - 361.0, - 362.0, - 363.0, - 364.0, - 365.0, - 366.0, - 367.0, - 368.0, - 369.0, - 370.0, - 371.0, - 372.0, - 373.0, - 374.0, - 375.0, - 376.0, - 377.0, - 378.0, - 379.0, - 380.0, - 381.0, - 382.0, - 383.0, - 384.0, - 385.0, - 386.0, - 387.0, - 388.0, - 389.0, - 390.0, - 391.0, - 392.0, - 393.0, - 394.0, - 395.0, - 396.0, - 397.0, - 398.0, - 399.0, - 400.0, - 401.0, - 402.0, - 403.0, - 404.0, - 405.0, - 406.0, - 407.0, - 408.0, - 409.0, - 410.0, - 411.0, - 412.0, - 413.0, - 414.0, - 415.0, - 416.0, - 417.0, - 418.0, - 419.0, - 420.0, - 421.0, - 422.0, - 423.0, - 424.0, - 425.0, - 426.0, - 427.0, - 428.0, - 429.0, - 430.0, - 431.0, - 432.0, - 433.0, - 434.0, - 435.0, - 436.0, - 437.0, - 438.0, - 439.0, - 440.0, - 441.0, - 442.0, - 443.0, - 444.0, - 445.0, - 446.0, - 447.0, - 448.0, - 449.0, - 450.0, - 451.0, - 452.0, - 453.0, - 454.0, - 455.0, - 456.0, - 457.0, - 458.0, - 459.0, - 460.0, - 461.0, - 462.0, - 463.0, - 464.0, - 465.0, - 466.0, - 467.0, - 468.0, - 469.0, - 470.0, - 471.0, - 472.0, - 473.0, - 474.0, - 475.0, - 476.0, - 477.0, - 478.0, - 479.0, - 480.0, - 481.0, - 482.0, - 483.0, - 484.0, - 485.0, - 486.0, - 487.0, - 488.0, - 489.0, - 490.0, - 491.0, - 492.0, - 493.0, - 494.0, - 495.0, - 496.0, - 497.0, - 498.0, - 499.0, - 500.0, - 501.0 -]; -var END = P.length - 1; - - -// MAIN // - -/** -* Evaluates a rational function (i.e., the ratio of two polynomials described by the coefficients stored in \\(P\\) and \\(Q\\)). -* -* ## Notes -* -* - Coefficients should be sorted in ascending degree. -* - The implementation uses [Horner's rule][horners-method] for efficient computation. -* -* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method -* -* @private -* @param {number} x - value at which to evaluate the rational function -* @returns {number} evaluated rational function -*/ -function evalrational( x ) { - var s1; - var s2; - var i; - - if ( x === 0.0 ) { - return 0.0; - } - if ( abs( x ) <= 1.0 ) { - s1 = P[ END ]; - s2 = Q[ END ]; - for ( i = END-1; i >= 0; i-- ) { - s1 = float64ToFloat32( s1 * x ); - s2 = float64ToFloat32( s2 * x ); - s1 = float64ToFloat32( s1 + P[ i ] ); - s2 = float64ToFloat32( s2 + Q[ i ] ); - } - } else { - x = float64ToFloat32( 1.0 / x ); // use inverse to avoid overflow - s1 = P[ 0 ]; - s2 = Q[ 0 ]; - for ( i = 1; i <= END; i++ ) { - s1 = float64ToFloat32( s1 * x ); - s2 = float64ToFloat32( s2 * x ); - s1 = float64ToFloat32( s1 + P[ i ] ); - s2 = float64ToFloat32( s2 + Q[ i ] ); - } - } - return float64ToFloat32( s1 / s2 ); -} - - -// EXPORTS // - -module.exports = evalrational; diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/loop2.float32.js.txt b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/loop2.float32.js.txt deleted file mode 100644 index 8fb272c41e51..000000000000 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/fixtures/loop2.float32.js.txt +++ /dev/null @@ -1,1070 +0,0 @@ -'use strict'; - -// MODULES // - -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); -var abs = require( '@stdlib/math/base/special/abs' ); - - -// VARIABLES // - -var P = [ - 0.5, - 1.5, - 2.5, - 3.5, - 4.5, - 5.5, - 6.5, - 7.5, - 8.5, - 9.5, - 10.5, - 11.5, - 12.5, - 13.5, - 14.5, - 15.5, - 16.5, - 17.5, - 18.5, - 19.5, - 20.5, - 21.5, - 22.5, - 23.5, - 24.5, - 25.5, - 26.5, - 27.5, - 28.5, - 29.5, - 30.5, - 31.5, - 32.5, - 33.5, - 34.5, - 35.5, - 36.5, - 37.5, - 38.5, - 39.5, - 40.5, - 41.5, - 42.5, - 43.5, - 44.5, - 45.5, - 46.5, - 47.5, - 48.5, - 49.5, - 50.5, - 51.5, - 52.5, - 53.5, - 54.5, - 55.5, - 56.5, - 57.5, - 58.5, - 59.5, - 60.5, - 61.5, - 62.5, - 63.5, - 64.5, - 65.5, - 66.5, - 67.5, - 68.5, - 69.5, - 70.5, - 71.5, - 72.5, - 73.5, - 74.5, - 75.5, - 76.5, - 77.5, - 78.5, - 79.5, - 80.5, - 81.5, - 82.5, - 83.5, - 84.5, - 85.5, - 86.5, - 87.5, - 88.5, - 89.5, - 90.5, - 91.5, - 92.5, - 93.5, - 94.5, - 95.5, - 96.5, - 97.5, - 98.5, - 99.5, - 100.5, - 101.5, - 102.5, - 103.5, - 104.5, - 105.5, - 106.5, - 107.5, - 108.5, - 109.5, - 110.5, - 111.5, - 112.5, - 113.5, - 114.5, - 115.5, - 116.5, - 117.5, - 118.5, - 119.5, - 120.5, - 121.5, - 122.5, - 123.5, - 124.5, - 125.5, - 126.5, - 127.5, - 128.5, - 129.5, - 130.5, - 131.5, - 132.5, - 133.5, - 134.5, - 135.5, - 136.5, - 137.5, - 138.5, - 139.5, - 140.5, - 141.5, - 142.5, - 143.5, - 144.5, - 145.5, - 146.5, - 147.5, - 148.5, - 149.5, - 150.5, - 151.5, - 152.5, - 153.5, - 154.5, - 155.5, - 156.5, - 157.5, - 158.5, - 159.5, - 160.5, - 161.5, - 162.5, - 163.5, - 164.5, - 165.5, - 166.5, - 167.5, - 168.5, - 169.5, - 170.5, - 171.5, - 172.5, - 173.5, - 174.5, - 175.5, - 176.5, - 177.5, - 178.5, - 179.5, - 180.5, - 181.5, - 182.5, - 183.5, - 184.5, - 185.5, - 186.5, - 187.5, - 188.5, - 189.5, - 190.5, - 191.5, - 192.5, - 193.5, - 194.5, - 195.5, - 196.5, - 197.5, - 198.5, - 199.5, - 200.5, - 201.5, - 202.5, - 203.5, - 204.5, - 205.5, - 206.5, - 207.5, - 208.5, - 209.5, - 210.5, - 211.5, - 212.5, - 213.5, - 214.5, - 215.5, - 216.5, - 217.5, - 218.5, - 219.5, - 220.5, - 221.5, - 222.5, - 223.5, - 224.5, - 225.5, - 226.5, - 227.5, - 228.5, - 229.5, - 230.5, - 231.5, - 232.5, - 233.5, - 234.5, - 235.5, - 236.5, - 237.5, - 238.5, - 239.5, - 240.5, - 241.5, - 242.5, - 243.5, - 244.5, - 245.5, - 246.5, - 247.5, - 248.5, - 249.5, - 250.5, - 251.5, - 252.5, - 253.5, - 254.5, - 255.5, - 256.5, - 257.5, - 258.5, - 259.5, - 260.5, - 261.5, - 262.5, - 263.5, - 264.5, - 265.5, - 266.5, - 267.5, - 268.5, - 269.5, - 270.5, - 271.5, - 272.5, - 273.5, - 274.5, - 275.5, - 276.5, - 277.5, - 278.5, - 279.5, - 280.5, - 281.5, - 282.5, - 283.5, - 284.5, - 285.5, - 286.5, - 287.5, - 288.5, - 289.5, - 290.5, - 291.5, - 292.5, - 293.5, - 294.5, - 295.5, - 296.5, - 297.5, - 298.5, - 299.5, - 300.5, - 301.5, - 302.5, - 303.5, - 304.5, - 305.5, - 306.5, - 307.5, - 308.5, - 309.5, - 310.5, - 311.5, - 312.5, - 313.5, - 314.5, - 315.5, - 316.5, - 317.5, - 318.5, - 319.5, - 320.5, - 321.5, - 322.5, - 323.5, - 324.5, - 325.5, - 326.5, - 327.5, - 328.5, - 329.5, - 330.5, - 331.5, - 332.5, - 333.5, - 334.5, - 335.5, - 336.5, - 337.5, - 338.5, - 339.5, - 340.5, - 341.5, - 342.5, - 343.5, - 344.5, - 345.5, - 346.5, - 347.5, - 348.5, - 349.5, - 350.5, - 351.5, - 352.5, - 353.5, - 354.5, - 355.5, - 356.5, - 357.5, - 358.5, - 359.5, - 360.5, - 361.5, - 362.5, - 363.5, - 364.5, - 365.5, - 366.5, - 367.5, - 368.5, - 369.5, - 370.5, - 371.5, - 372.5, - 373.5, - 374.5, - 375.5, - 376.5, - 377.5, - 378.5, - 379.5, - 380.5, - 381.5, - 382.5, - 383.5, - 384.5, - 385.5, - 386.5, - 387.5, - 388.5, - 389.5, - 390.5, - 391.5, - 392.5, - 393.5, - 394.5, - 395.5, - 396.5, - 397.5, - 398.5, - 399.5, - 400.5, - 401.5, - 402.5, - 403.5, - 404.5, - 405.5, - 406.5, - 407.5, - 408.5, - 409.5, - 410.5, - 411.5, - 412.5, - 413.5, - 414.5, - 415.5, - 416.5, - 417.5, - 418.5, - 419.5, - 420.5, - 421.5, - 422.5, - 423.5, - 424.5, - 425.5, - 426.5, - 427.5, - 428.5, - 429.5, - 430.5, - 431.5, - 432.5, - 433.5, - 434.5, - 435.5, - 436.5, - 437.5, - 438.5, - 439.5, - 440.5, - 441.5, - 442.5, - 443.5, - 444.5, - 445.5, - 446.5, - 447.5, - 448.5, - 449.5, - 450.5, - 451.5, - 452.5, - 453.5, - 454.5, - 455.5, - 456.5, - 457.5, - 458.5, - 459.5, - 460.5, - 461.5, - 462.5, - 463.5, - 464.5, - 465.5, - 466.5, - 467.5, - 468.5, - 469.5, - 470.5, - 471.5, - 472.5, - 473.5, - 474.5, - 475.5, - 476.5, - 477.5, - 478.5, - 479.5, - 480.5, - 481.5, - 482.5, - 483.5, - 484.5, - 485.5, - 486.5, - 487.5, - 488.5, - 489.5, - 490.5, - 491.5, - 492.5, - 493.5, - 494.5, - 495.5, - 496.5, - 497.5, - 498.5, - 499.5, - 500.5 -]; -var Q = [ - 1.5, - 2.5, - 3.5, - 4.5, - 5.5, - 6.5, - 7.5, - 8.5, - 9.5, - 10.5, - 11.5, - 12.5, - 13.5, - 14.5, - 15.5, - 16.5, - 17.5, - 18.5, - 19.5, - 20.5, - 21.5, - 22.5, - 23.5, - 24.5, - 25.5, - 26.5, - 27.5, - 28.5, - 29.5, - 30.5, - 31.5, - 32.5, - 33.5, - 34.5, - 35.5, - 36.5, - 37.5, - 38.5, - 39.5, - 40.5, - 41.5, - 42.5, - 43.5, - 44.5, - 45.5, - 46.5, - 47.5, - 48.5, - 49.5, - 50.5, - 51.5, - 52.5, - 53.5, - 54.5, - 55.5, - 56.5, - 57.5, - 58.5, - 59.5, - 60.5, - 61.5, - 62.5, - 63.5, - 64.5, - 65.5, - 66.5, - 67.5, - 68.5, - 69.5, - 70.5, - 71.5, - 72.5, - 73.5, - 74.5, - 75.5, - 76.5, - 77.5, - 78.5, - 79.5, - 80.5, - 81.5, - 82.5, - 83.5, - 84.5, - 85.5, - 86.5, - 87.5, - 88.5, - 89.5, - 90.5, - 91.5, - 92.5, - 93.5, - 94.5, - 95.5, - 96.5, - 97.5, - 98.5, - 99.5, - 100.5, - 101.5, - 102.5, - 103.5, - 104.5, - 105.5, - 106.5, - 107.5, - 108.5, - 109.5, - 110.5, - 111.5, - 112.5, - 113.5, - 114.5, - 115.5, - 116.5, - 117.5, - 118.5, - 119.5, - 120.5, - 121.5, - 122.5, - 123.5, - 124.5, - 125.5, - 126.5, - 127.5, - 128.5, - 129.5, - 130.5, - 131.5, - 132.5, - 133.5, - 134.5, - 135.5, - 136.5, - 137.5, - 138.5, - 139.5, - 140.5, - 141.5, - 142.5, - 143.5, - 144.5, - 145.5, - 146.5, - 147.5, - 148.5, - 149.5, - 150.5, - 151.5, - 152.5, - 153.5, - 154.5, - 155.5, - 156.5, - 157.5, - 158.5, - 159.5, - 160.5, - 161.5, - 162.5, - 163.5, - 164.5, - 165.5, - 166.5, - 167.5, - 168.5, - 169.5, - 170.5, - 171.5, - 172.5, - 173.5, - 174.5, - 175.5, - 176.5, - 177.5, - 178.5, - 179.5, - 180.5, - 181.5, - 182.5, - 183.5, - 184.5, - 185.5, - 186.5, - 187.5, - 188.5, - 189.5, - 190.5, - 191.5, - 192.5, - 193.5, - 194.5, - 195.5, - 196.5, - 197.5, - 198.5, - 199.5, - 200.5, - 201.5, - 202.5, - 203.5, - 204.5, - 205.5, - 206.5, - 207.5, - 208.5, - 209.5, - 210.5, - 211.5, - 212.5, - 213.5, - 214.5, - 215.5, - 216.5, - 217.5, - 218.5, - 219.5, - 220.5, - 221.5, - 222.5, - 223.5, - 224.5, - 225.5, - 226.5, - 227.5, - 228.5, - 229.5, - 230.5, - 231.5, - 232.5, - 233.5, - 234.5, - 235.5, - 236.5, - 237.5, - 238.5, - 239.5, - 240.5, - 241.5, - 242.5, - 243.5, - 244.5, - 245.5, - 246.5, - 247.5, - 248.5, - 249.5, - 250.5, - 251.5, - 252.5, - 253.5, - 254.5, - 255.5, - 256.5, - 257.5, - 258.5, - 259.5, - 260.5, - 261.5, - 262.5, - 263.5, - 264.5, - 265.5, - 266.5, - 267.5, - 268.5, - 269.5, - 270.5, - 271.5, - 272.5, - 273.5, - 274.5, - 275.5, - 276.5, - 277.5, - 278.5, - 279.5, - 280.5, - 281.5, - 282.5, - 283.5, - 284.5, - 285.5, - 286.5, - 287.5, - 288.5, - 289.5, - 290.5, - 291.5, - 292.5, - 293.5, - 294.5, - 295.5, - 296.5, - 297.5, - 298.5, - 299.5, - 300.5, - 301.5, - 302.5, - 303.5, - 304.5, - 305.5, - 306.5, - 307.5, - 308.5, - 309.5, - 310.5, - 311.5, - 312.5, - 313.5, - 314.5, - 315.5, - 316.5, - 317.5, - 318.5, - 319.5, - 320.5, - 321.5, - 322.5, - 323.5, - 324.5, - 325.5, - 326.5, - 327.5, - 328.5, - 329.5, - 330.5, - 331.5, - 332.5, - 333.5, - 334.5, - 335.5, - 336.5, - 337.5, - 338.5, - 339.5, - 340.5, - 341.5, - 342.5, - 343.5, - 344.5, - 345.5, - 346.5, - 347.5, - 348.5, - 349.5, - 350.5, - 351.5, - 352.5, - 353.5, - 354.5, - 355.5, - 356.5, - 357.5, - 358.5, - 359.5, - 360.5, - 361.5, - 362.5, - 363.5, - 364.5, - 365.5, - 366.5, - 367.5, - 368.5, - 369.5, - 370.5, - 371.5, - 372.5, - 373.5, - 374.5, - 375.5, - 376.5, - 377.5, - 378.5, - 379.5, - 380.5, - 381.5, - 382.5, - 383.5, - 384.5, - 385.5, - 386.5, - 387.5, - 388.5, - 389.5, - 390.5, - 391.5, - 392.5, - 393.5, - 394.5, - 395.5, - 396.5, - 397.5, - 398.5, - 399.5, - 400.5, - 401.5, - 402.5, - 403.5, - 404.5, - 405.5, - 406.5, - 407.5, - 408.5, - 409.5, - 410.5, - 411.5, - 412.5, - 413.5, - 414.5, - 415.5, - 416.5, - 417.5, - 418.5, - 419.5, - 420.5, - 421.5, - 422.5, - 423.5, - 424.5, - 425.5, - 426.5, - 427.5, - 428.5, - 429.5, - 430.5, - 431.5, - 432.5, - 433.5, - 434.5, - 435.5, - 436.5, - 437.5, - 438.5, - 439.5, - 440.5, - 441.5, - 442.5, - 443.5, - 444.5, - 445.5, - 446.5, - 447.5, - 448.5, - 449.5, - 450.5, - 451.5, - 452.5, - 453.5, - 454.5, - 455.5, - 456.5, - 457.5, - 458.5, - 459.5, - 460.5, - 461.5, - 462.5, - 463.5, - 464.5, - 465.5, - 466.5, - 467.5, - 468.5, - 469.5, - 470.5, - 471.5, - 472.5, - 473.5, - 474.5, - 475.5, - 476.5, - 477.5, - 478.5, - 479.5, - 480.5, - 481.5, - 482.5, - 483.5, - 484.5, - 485.5, - 486.5, - 487.5, - 488.5, - 489.5, - 490.5, - 491.5, - 492.5, - 493.5, - 494.5, - 495.5, - 496.5, - 497.5, - 498.5, - 499.5, - 500.5, - 501.5 -]; -var END = P.length - 1; - - -// MAIN // - -/** -* Evaluates a rational function (i.e., the ratio of two polynomials described by the coefficients stored in \\(P\\) and \\(Q\\)). -* -* ## Notes -* -* - Coefficients should be sorted in ascending degree. -* - The implementation uses [Horner's rule][horners-method] for efficient computation. -* -* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method -* -* @private -* @param {number} x - value at which to evaluate the rational function -* @returns {number} evaluated rational function -*/ -function evalrational( x ) { - var s1; - var s2; - var i; - - if ( x === 0.0 ) { - return 0.3333333432674408; - } - if ( abs( x ) <= 1.0 ) { - s1 = P[ END ]; - s2 = Q[ END ]; - for ( i = END-1; i >= 0; i-- ) { - s1 = float64ToFloat32( s1 * x ); - s2 = float64ToFloat32( s2 * x ); - s1 = float64ToFloat32( s1 + P[ i ] ); - s2 = float64ToFloat32( s2 + Q[ i ] ); - } - } else { - x = float64ToFloat32( 1.0 / x ); // use inverse to avoid overflow - s1 = P[ 0 ]; - s2 = Q[ 0 ]; - for ( i = 1; i <= END; i++ ) { - s1 = float64ToFloat32( s1 * x ); - s2 = float64ToFloat32( s2 * x ); - s1 = float64ToFloat32( s1 + P[ i ] ); - s2 = float64ToFloat32( s2 + Q[ i ] ); - } - } - return float64ToFloat32( s1 / s2 ); -} - - -// EXPORTS // - -module.exports = evalrational; diff --git a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/test.js b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/test.js index 4d24707c667d..b1cc50871b64 100644 --- a/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/test.js +++ b/lib/node_modules/@stdlib/math/base/tools/evalrational-compile/test/test.js @@ -16,8 +16,6 @@ * limitations under the License. */ -/* eslint-disable max-len */ - 'use strict'; // MODULES // @@ -28,7 +26,6 @@ var tape = require( 'tape' ); var IS_BROWSER = require( '@stdlib/assert/is-browser' ); var readFile = require( '@stdlib/fs/read-file' ).sync; var Float64Array = require( '@stdlib/array/float64' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -66,52 +63,6 @@ tape( 'the function returns a string', opts, function test( t ) { t.end(); }); -tape( 'the function returns a string (dtype=float64)', opts, function test( t ) { - var options; - var str; - - options = { - 'dtype': 'float64' - }; - - str = compile( [], [], options ); - t.equal( typeof str, 'string', 'returns a string' ); - - str = compile( [ 1.0 ], [ 2.0 ], options ); - t.equal( typeof str, 'string', 'returns a string' ); - - str = compile( [ 1.0, 2.0, 3.0 ], [ 3.0, 2.0, 1.0 ], options ); - t.equal( typeof str, 'string', 'returns a string' ); - - str = compile( new Float64Array( 501 ), new Float64Array( 501 ), options ); - t.equal( typeof str, 'string', 'returns a string' ); - - t.end(); -}); - -tape( 'the function returns a string (dtype=float32)', opts, function test( t ) { - var options; - var str; - - options = { - 'dtype': 'float32' - }; - - str = compile( [], [], options ); - t.equal( typeof str, 'string', 'returns a string' ); - - str = compile( [ 1.0 ], [ 2.0 ], options ); - t.equal( typeof str, 'string', 'returns a string' ); - - str = compile( [ 1.0, 2.0, 3.0 ], [ 3.0, 2.0, 1.0 ], options ); - t.equal( typeof str, 'string', 'returns a string' ); - - str = compile( new Float32Array( 501 ), new Float32Array( 501 ), options ); - t.equal( typeof str, 'string', 'returns a string' ); - - t.end(); -}); - tape( 'if provided empty coefficient arrays, the function returns a module string containing an exported function which always returns `NaN`', opts, function test( t ) { var expected; var actual; @@ -130,46 +81,6 @@ tape( 'if provided empty coefficient arrays, the function returns a module strin t.end(); }); -tape( 'if provided empty coefficient arrays, the function returns a module string containing an exported function which always returns `NaN` (dtype=float64)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'nan.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( [], [], { - 'dtype': 'float64' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'if provided empty coefficient arrays, the function returns a module string containing an exported function which always returns `NaN` (dtype=float32)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'nan.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( [], [], { - 'dtype': 'float32' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - tape( 'if provided coefficient arrays having different lengths, the function returns a module string containing an exported function which always returns `NaN`', opts, function test( t ) { var expected; var actual; @@ -188,46 +99,6 @@ tape( 'if provided coefficient arrays having different lengths, the function ret t.end(); }); -tape( 'if provided coefficient arrays having different lengths, the function returns a module string containing an exported function which always returns `NaN` (dtype=float64)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'nan.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( [ 1.0, 2.0 ], [ 1.0, 2.0, 3.0 ], { - 'dtype': 'float64' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'if provided coefficient arrays having different lengths, the function returns a module string containing an exported function which always returns `NaN` (dtype=float32)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'nan.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( [ 1.0, 2.0 ], [ 1.0, 2.0, 3.0 ], { - 'dtype': 'float32' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - tape( 'if provided coefficient arrays each containing 1 coefficient, the function returns a module string containing an exported function which always returns the ratio of those two coefficients', opts, function test( t ) { var expected; var actual; @@ -246,46 +117,6 @@ tape( 'if provided coefficient arrays each containing 1 coefficient, the functio t.end(); }); -tape( 'if provided coefficient arrays each containing 1 coefficient, the function returns a module string containing an exported function which always returns the ratio of those two coefficients (dtype=float64)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'coefficient_ratio.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( [ 3.14 ], [ -0.5 ], { - 'dtype': 'float64' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'if provided coefficient arrays each containing 1 coefficient, the function returns a module string containing an exported function which always returns the ratio of those two coefficients (dtype=float32)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'coefficient_ratio.float32.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( new Float32Array( [ 3.14 ] ), new Float32Array( [ -0.5 ] ), { - 'dtype': 'float32' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - tape( 'if provided coefficient arrays each containing 1 coefficient, the function returns a module string containing an exported function which always returns the ratio of those two coefficients (integer values)', opts, function test( t ) { var expected; var actual; @@ -298,47 +129,7 @@ tape( 'if provided coefficient arrays each containing 1 coefficient, the functio }; expected = readFile( fpath, fopts ); - actual = compile( [ -3.0 ], [ 2.0 ] ); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'if provided coefficient arrays each containing 1 coefficient, the function returns a module string containing an exported function which always returns the ratio of those two coefficients (integer values; dtype=float64)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'coefficient_ratio_integer.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( [ -3.0 ], [ 2.0 ], { - 'dtype': 'float64' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'if provided coefficient arrays each containing 1 coefficient, the function returns a module string containing an exported function which always returns the ratio of those two coefficients (integer values; dtype=float32)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'coefficient_ratio_integer.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( new Float32Array( [ -3.0 ] ), new Float32Array( [ 2.0 ] ), { - 'dtype': 'float32' - }); + actual = compile( [ -3.0 ], [ 1.5 ] ); t.equal( actual, expected, 'returns expected value' ); t.end(); @@ -362,46 +153,6 @@ tape( 'the function returns a module string containing an exported function whic t.end(); }); -tape( 'the function returns a module string containing an exported function which evaluates a rational function (dtype=float64)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'evalrational1.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( [ 1.0, 2.5, 3.14, -1.0 ], [ 4.0, -3.5, 2.2, 1.25 ], { - 'dtype': 'float64' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function returns a module string containing an exported function which evaluates a rational function (dtype=float32)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'evalrational1.float32.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( new Float32Array( [ 1.0, 2.5, 3.14, -1.0 ] ), new Float32Array( [ 4.0, -3.5, 2.2, 1.25 ] ), { - 'dtype': 'float32' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - tape( 'the function returns a module string containing an exported function which evaluates a rational function', opts, function test( t ) { var expected; var actual; @@ -420,46 +171,6 @@ tape( 'the function returns a module string containing an exported function whic t.end(); }); -tape( 'the function returns a module string containing an exported function which evaluates a rational function (dtype=float64)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'evalrational2.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( [ -3.14, 0.0 ], [ 6.0, 0.0 ], { - 'dtype': 'float64' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function returns a module string containing an exported function which evaluates a rational function (dtype=float32)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - - fpath = join( __dirname, 'fixtures', 'evalrational2.float32.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - actual = compile( new Float32Array( [ -3.14, 0.0 ] ), new Float32Array( [ 6.0, 0.0 ] ), { - 'dtype': 'float32' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - tape( 'the function returns a module string containing an exported function which evaluates a rational function', opts, function test( t ) { var expected; var actual; @@ -482,54 +193,6 @@ tape( 'the function returns a module string containing an exported function whic t.end(); }); -tape( 'the function returns a module string containing an exported function which evaluates a rational function (dtype=float64)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - var P; - var Q; - - fpath = join( __dirname, 'fixtures', 'evalrational3.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - P = [ -3.14, 0.0, 4.0, 2.0, 3.0, 9.0, 5.4 ]; - Q = [ 6.0, 0.0, 2.0, 1.0, 2.0, 4.8, 2.2 ]; - actual = compile( P, Q, { - 'dtype': 'float64' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function returns a module string containing an exported function which evaluates a rational function (dtype=float32)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - var P; - var Q; - - fpath = join( __dirname, 'fixtures', 'evalrational3.float32.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - P = new Float32Array( [ -3.14, 0.0, 4.0, 2.0, 3.0, 9.0, 5.4 ] ); - Q = new Float32Array( [ 6.0, 0.0, 2.0, 1.0, 2.0, 4.8, 2.2 ] ); - actual = compile( P, Q, { - 'dtype': 'float32' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - tape( 'the function returns a module string containing an exported function which evaluates a rational function (large number of coefficients; integers)', opts, function test( t ) { var expected; var actual; @@ -545,11 +208,11 @@ tape( 'the function returns a module string containing an exported function whic }; expected = readFile( fpath, fopts ); - P = []; - Q = []; - for ( i = 0; i < 501; i++ ) { - P.push( i ); - Q.push( i+1 ); + P = new Array( 501 ); + Q = new Array( 501 ); + for ( i = 0; i < P.length; i++ ) { + P[ i ] = i; + Q[ i ] = i + 1; } actual = compile( P, Q ); t.equal( actual, expected, 'returns expected value' ); @@ -557,64 +220,6 @@ tape( 'the function returns a module string containing an exported function whic t.end(); }); -tape( 'the function returns a module string containing an exported function which evaluates a rational function (large number of coefficients; integers; dtype=float64)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - var P; - var Q; - var i; - - fpath = join( __dirname, 'fixtures', 'loop1.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - P = []; - Q = []; - for ( i = 0; i < 501; i++ ) { - P.push( i ); - Q.push( i+1 ); - } - actual = compile( P, Q, { - 'dtype': 'float64' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function returns a module string containing an exported function which evaluates a rational function (large number of coefficients; integers; dtype=float32)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - var P; - var Q; - var i; - - fpath = join( __dirname, 'fixtures', 'loop1.float32.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - P = []; - Q = []; - for ( i = 0; i < 501; i++ ) { - P.push( i ); - Q.push( i+1 ); - } - actual = compile( new Float32Array( P ), new Float32Array( Q ), { - 'dtype': 'float32' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - tape( 'the function returns a module string containing an exported function which evaluates a rational function (large number of coefficients; decimals)', opts, function test( t ) { var expected; var actual; @@ -630,72 +235,14 @@ tape( 'the function returns a module string containing an exported function whic }; expected = readFile( fpath, fopts ); - P = []; - Q = []; - for ( i = 0; i < 501; i++ ) { - P.push( i+0.1 ); - Q.push( i+1.1 ); + P = new Array( 501 ); + Q = new Array( 501 ); + for ( i = 0; i < P.length; i++ ) { + P[ i ] = i + 0.1; + Q[ i ] = i + 1.1; } actual = compile( P, Q ); t.equal( actual, expected, 'returns expected value' ); t.end(); }); - -tape( 'the function returns a module string containing an exported function which evaluates a rational function (large number of coefficients; decimals; dtype=float64)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - var P; - var Q; - var i; - - fpath = join( __dirname, 'fixtures', 'loop2.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - P = []; - Q = []; - for ( i = 0; i < 501; i++ ) { - P.push( i+0.1 ); - Q.push( i+1.1 ); - } - actual = compile( P, Q, { - 'dtype': 'float64' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function returns a module string containing an exported function which evaluates a rational function (large number of coefficients; decimals; dtype=float32)', opts, function test( t ) { - var expected; - var actual; - var fpath; - var fopts; - var P; - var Q; - var i; - - fpath = join( __dirname, 'fixtures', 'loop2.float32.js.txt' ); - fopts = { - 'encoding': 'utf8' - }; - expected = readFile( fpath, fopts ); - - P = []; - Q = []; - for ( i = 0; i < 501; i++ ) { - P.push( i+0.5 ); - Q.push( i+1.5 ); - } - actual = compile( new Float32Array( P ), new Float32Array( Q ), { - 'dtype': 'float32' - }); - t.equal( actual, expected, 'returns expected value' ); - - t.end(); -}); diff --git a/lib/node_modules/@stdlib/random/array/poisson/README.md b/lib/node_modules/@stdlib/random/array/poisson/README.md index 3ca9c6fae5e9..ea3a4c50ba1e 100644 --- a/lib/node_modules/@stdlib/random/array/poisson/README.md +++ b/lib/node_modules/@stdlib/random/array/poisson/README.md @@ -357,7 +357,6 @@ logEach( '%f', x4 ); ## See Also - [`@stdlib/random/base/poisson`][@stdlib/random/base/poisson]: Poisson distributed random numbers. -- [`@stdlib/random/strided/poisson`][@stdlib/random/strided/poisson]: fill a strided array with pseudorandom numbers drawn from a Poisson distribution.
@@ -375,12 +374,6 @@ logEach( '%f', x4 ); [@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64 - - -[@stdlib/random/strided/poisson]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/random/strided/poisson - - -
diff --git a/lib/node_modules/@stdlib/random/base/minstd-shuffle/README.md b/lib/node_modules/@stdlib/random/base/minstd-shuffle/README.md index 74c4c4d235db..c4de9d72df58 100644 --- a/lib/node_modules/@stdlib/random/base/minstd-shuffle/README.md +++ b/lib/node_modules/@stdlib/random/base/minstd-shuffle/README.md @@ -83,7 +83,7 @@ var rand = minstd.factory({ }); var r = rand(); -// returns 1421600654 +// returns 20739838 ``` To return a generator having a specific initial state, set the generator `state` option. diff --git a/lib/node_modules/@stdlib/random/base/mt19937/README.md b/lib/node_modules/@stdlib/random/base/mt19937/README.md index e9506e1f5e0a..9e047118d8df 100644 --- a/lib/node_modules/@stdlib/random/base/mt19937/README.md +++ b/lib/node_modules/@stdlib/random/base/mt19937/README.md @@ -60,9 +60,9 @@ The function accepts the following `options`: - **seed**: pseudorandom number generator seed. - **state**: a [`Uint32Array`][@stdlib/array/uint32] containing pseudorandom number generator state. If provided, the function ignores the `seed` option. -- **copy**: boolean indicating whether to copy a provided pseudorandom number generator state. Setting this option to `false` allows sharing state between two or more pseudorandom number generators. Setting this option to `true` ensures that a returned generator has exclusive control over its internal state. Default: `true`. +- **copy**: `boolean` indicating whether to copy a provided pseudorandom number generator state. Setting this option to `false` allows sharing state between two or more pseudorandom number generators. Setting this option to `true` ensures that a returned generator has exclusive control over its internal state. Default: `true`. -By default, a random integer is used to seed the returned generator. To seed the generator, provide either a nonzero integer on the interval `[1, 4294967295]` +By default, a random integer is used to seed the returned generator. To seed the generator, provide either an `integer` on the interval `[0, 4294967295]` ```javascript var rand = mt19937.factory({ @@ -73,7 +73,7 @@ var r = rand(); // returns 822569775 ``` -or, for arbitrary length seeds, an array-like object containing unsigned 32-bit integers +or, for arbitrary length seeds, an array-like `object` containing unsigned 32-bit integers ```javascript var Uint32Array = require( '@stdlib/array/uint32' ); diff --git a/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv b/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv index f2f6b489ba4f..d35089169195 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv +++ b/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv @@ -1510,12 +1510,12 @@ base.strided.dabs,"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar base.strided.dabs.ndarray,"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n" base.strided.dabs2,"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs2( N, x1, -2, y1, 1 )\ny0\n" base.strided.dabs2.ndarray,"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n" -base.strided.dapx,"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapx( 3, 5.0, x1, 2 )\nx0\n" -base.strided.dapx.ndarray,"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n" +base.strided.dapx,"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nvar alpha = 5.0;\nbase.strided.dapx( x.length, alpha, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.dapx( N, alpha, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nalpha = 5.0;\nstride = 2;\nbase.strided.dapx( N, alpha, x1, stride )\nx0\n" +base.strided.dapx.ndarray,"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nvar alpha = 5.0;\nbase.strided.dapx.ndarray( x.length, alpha, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.dapx.ndarray( N, alpha, x, stride, 1 )\n" base.strided.dapxsum,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dapxsum( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dapxsum( N, 5.0, x1, stride )\n" base.strided.dapxsum.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dapxsum.ndarray( N, 5.0, x, 2, 1 )\n" -base.strided.dapxsumkbn,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn( 3, 5.0, x1, 2)\n" -base.strided.dapxsumkbn.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n" +base.strided.dapxsumkbn,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dapxsumkbn( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dapxsumkbn( N, 5.0, x1, stride )\n" +base.strided.dapxsumkbn.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n" base.strided.dapxsumkbn2,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dapxsumkbn2( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dapxsumkbn2( N, 5.0, x1, stride )\n" base.strided.dapxsumkbn2.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n" base.strided.dapxsumors,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dapxsumors( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dapxsumors( N, 5.0, x1, stride )\n" @@ -1726,8 +1726,8 @@ base.strided.drev,"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, base.strided.drev.ndarray,"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.drev.ndarray( 3, x, 2, 1 )\n" base.strided.drsqrt,"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.drsqrt( N, x1, -2, y1, 1 )\ny0\n" base.strided.drsqrt.ndarray,"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n" -base.strided.dsapxsum,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsum( 3, 5.0, x1, 2 )\n" -base.strided.dsapxsum.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n" +base.strided.dsapxsum,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsapxsum( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsapxsum( N, 5.0, x1, stride )\n" +base.strided.dsapxsum.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsapxsum.ndarray( N, 5.0, x, 2, 1 )\n" base.strided.dsapxsumpw,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsapxsumpw( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsapxsumpw( N, 5.0, x1, stride )\n" base.strided.dsapxsumpw.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n" base.strided.dscal,"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dscal( 3, 5.0, x1, 2 )\nx0\n" @@ -1804,8 +1804,8 @@ base.strided.dstdevwd,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.str base.strided.dstdevwd.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n" base.strided.dstdevyc,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevyc( N, 1, x1, stride )\n" base.strided.dstdevyc.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n" -base.strided.dsum,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsum( 3, x1, 2 )\n" -base.strided.dsum.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsum.ndarray( 3, x, 2, 1 )\n" +base.strided.dsum,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsum( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsum( N, x1, stride )\n" +base.strided.dsum.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsum.ndarray( N, x, 2, 1 )\n" base.strided.dsumkbn,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsumkbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsumkbn( N, x1, stride )\n" base.strided.dsumkbn.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsumkbn.ndarray( N, x, 2, 1 )\n" base.strided.dsumkbn2,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsumkbn2( N, x1, stride )\n" @@ -2032,18 +2032,18 @@ base.strided.sabs,"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar base.strided.sabs.ndarray,"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n" base.strided.sabs2,"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs2( N, x1, -2, y1, 1 )\ny0\n" base.strided.sabs2.ndarray,"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n" -base.strided.sapx,"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapx( 3, 5.0, x1, 2 )\nx0\n" -base.strided.sapx.ndarray,"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n" -base.strided.sapxsum,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsum( 3, 5.0, x1, 2 )\n" -base.strided.sapxsum.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n" -base.strided.sapxsumkbn,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n" -base.strided.sapxsumkbn.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n" +base.strided.sapx,"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nvar alpha = 5.0;\nbase.strided.sapx( x.length, alpha, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.sapx( N, alpha, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nalpha = 5.0;\nstride = 2;\nbase.strided.sapx( N, alpha, x1, stride )\nx0\n" +base.strided.sapx.ndarray,"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nvar alpha = 5.0;\nbase.strided.sapx.ndarray( x.length, alpha, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.sapx.ndarray( N, alpha, x, stride, 1 )\n" +base.strided.sapxsum,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sapxsum( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sapxsum( N, 5.0, x1, stride )\n" +base.strided.sapxsum.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sapxsum.ndarray( N, 5.0, x, 2, 1 )\n" +base.strided.sapxsumkbn,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sapxsumkbn( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sapxsumkbn( N, 5.0, x1, stride )\n" +base.strided.sapxsumkbn.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n" base.strided.sapxsumkbn2,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sapxsumkbn2( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sapxsumkbn2( N, 5.0, x1, stride )\n" base.strided.sapxsumkbn2.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n" base.strided.sapxsumors,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sapxsumors( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sapxsumors( N, 5.0, x1, stride )\n" base.strided.sapxsumors.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n" -base.strided.sapxsumpw,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.sapxsumpw( 3, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sapxsumpw( 3, 5.0, x1, stride )\n" -base.strided.sapxsumpw.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n" +base.strided.sapxsumpw,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sapxsumpw( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sapxsumpw( N, 5.0, x1, stride )\n" +base.strided.sapxsumpw.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n" base.strided.sasum,"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum( x.length, x, 1 )\ns = base.strided.sasum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.sasum( 3, x1, 2 )\n" base.strided.sasum.ndarray,"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n" base.strided.sasumpw,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sasumpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sasumpw( N, x1, stride )\n" @@ -2064,24 +2064,24 @@ base.strided.scumin,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = ne base.strided.scumin.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n" base.strided.scuminabs,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scuminabs( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scuminabs( N, x1, 2, y1, 1 )\ny0\n" base.strided.scuminabs.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n" -base.strided.scusum,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n" -base.strided.scusum.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n" -base.strided.scusumkbn,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumkbn( N, 0.0, x1, 2, y1, 1 )\ny0\n" -base.strided.scusumkbn.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n" -base.strided.scusumkbn2,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumkbn2( N, 0.0, x1, 2, y1, 1 )\ny0\n" -base.strided.scusumkbn2.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n" -base.strided.scusumors,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n" -base.strided.scusumors.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n" -base.strided.scusumpw,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n" -base.strided.scusumpw.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n" +base.strided.scusum,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scusum( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusum( N, 0.0, x1, 2, y1, 1 )\ny0\n" +base.strided.scusum.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n" +base.strided.scusumkbn,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scusumkbn( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumkbn( N, 0.0, x1, 2, y1, 1 )\ny0\n" +base.strided.scusumkbn.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n" +base.strided.scusumkbn2,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scusumkbn2( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumkbn2( N, 0.0, x1, 2, y1, 1 )\ny0\n" +base.strided.scusumkbn2.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n" +base.strided.scusumors,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scusumors( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumors( N, 0.0, x1, 2, y1, 1 )\ny0\n" +base.strided.scusumors.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n" +base.strided.scusumpw,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scusumpw( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumpw( N, 0.0, x1, 2, y1, 1 )\ny0\n" +base.strided.scusumpw.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n" base.strided.sdeg2rad,"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sdeg2rad( N, x1, -2, y1, 1 )\ny0\n" base.strided.sdeg2rad.ndarray,"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n" base.strided.sdot,"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdot( 3, x1, -2, y1, 1 )\n" base.strided.sdot.ndarray,"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n" -base.strided.sdsapxsum,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsum( 3, 5.0, x1, 2 )\n" -base.strided.sdsapxsum.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n" -base.strided.sdsapxsumpw,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n" -base.strided.sdsapxsumpw.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n" +base.strided.sdsapxsum,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsapxsum( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsapxsum( N, 5.0, x1, stride )\n" +base.strided.sdsapxsum.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsapxsum.ndarray( N, 5.0, x, 2, 1 )\n" +base.strided.sdsapxsumpw,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsapxsumpw( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsapxsumpw( N, 5.0, x1, stride )\n" +base.strided.sdsapxsumpw.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n" base.strided.sdsdot,"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n" base.strided.sdsdot.ndarray,"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n" base.strided.sdsmean,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsmean( N, x1, stride )\n" @@ -2278,8 +2278,8 @@ base.strided.ssum,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided base.strided.ssum.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssum.ndarray( N, x, 2, 1 )\n" base.strided.ssumkbn,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn( 3, x1, 2 )\n" base.strided.ssumkbn.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n" -base.strided.ssumkbn2,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn2( 3, x1, 2 )\n" -base.strided.ssumkbn2.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n" +base.strided.ssumkbn2,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.ssumkbn2( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.ssumkbn2( N, x1, stride )\n" +base.strided.ssumkbn2.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssumkbn2.ndarray( N, x, 2, 1 )\n" base.strided.ssumors,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumors( 3, x1, 2 )\n" base.strided.ssumors.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumors.ndarray( 3, x, 2, 1 )\n" base.strided.ssumpw,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumpw( 3, x1, 2 )\n" diff --git a/lib/node_modules/@stdlib/repl/code-blocks/data/data.json b/lib/node_modules/@stdlib/repl/code-blocks/data/data.json index 3e9c33d3ce3d..f914d0970a4c 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/data/data.json +++ b/lib/node_modules/@stdlib/repl/code-blocks/data/data.json @@ -1 +1 @@ -{"abs":"var y = abs( -1.0 )\nvar x = new Float64Array( [ -1.0, -2.0 ] );\ny = abs( x )\nx = [ -1.0, -2.0 ];\ny = abs( x )\nx = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\ny = abs( x )\ny.get( 0, 1 )\n","abs.assign":"var x = new Float64Array( [ -1.0, -2.0 ] );\nvar y = new Float64Array( x.length );\nvar out = abs.assign( x, y )\nvar bool = ( out === y )\nx = [ -1.0, -2.0 ];\ny = [ 0.0, 0.0 ];\nout = abs.assign( x, y )\nbool = ( out === y )\nx = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\ny = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\nout = abs.assign( x, y )\nout.get( 0, 1 )\nbool = ( out === y )\n","acartesianPower":"var x = [ 1, 2 ];\nvar out = acartesianPower( x, 2 )\n","acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = acartesianProduct( x1, x2 )\n","acartesianSquare":"var out = acartesianSquare( [ 1, 2 ] )\n","acronym":"var out = acronym( 'the quick brown fox' )\nout = acronym( 'Hard-boiled eggs' )\n","aempty":"var arr = aempty( 2 )\narr = aempty( 2, 'float32' )\n","aemptyLike":"var x = new Float64Array( 2 );\nvar arr = aemptyLike( x )\narr = aemptyLike( x, 'float32' )\n","AFINN_96":"var list = AFINN_96()\n","AFINN_111":"var list = AFINN_111()\n","afull":"var arr = afull( 2, 1.0 )\narr = afull( 2, 1.0, 'float32' )\n","afullLike":"var x = new Float64Array( 2 );\nvar y = afullLike( x, 1.0 )\ny = afullLike( x, 1.0, 'float32' )\n","alias2pkg":"var v = alias2pkg( 'base.sin' )\n","alias2related":"var v = alias2related( 'base.sin' )\n","alias2standalone":"var v = alias2standalone( 'base.sin' )\n","aliases":"var o = aliases()\no = aliases( '@stdlib/math/base/special' )\n","allocUnsafe":"var buf = allocUnsafe( 100 )\n","amskfilter":"var x = [ 1, 2, 3, 4 ];\nvar y = amskfilter( x, [ 0, 1, 0, 1 ] )\n","amskreject":"var x = [ 1, 2, 3, 4 ];\nvar y = amskreject( x, [ 0, 1, 0, 1 ] )\n","anans":"var arr = anans( 2 )\narr = anans( 2, 'float32' )\n","anansLike":"var x = new Float64Array( 2 );\nvar y = anansLike( x )\ny = anansLike( x, 'float32' )\n","anova1":"var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\nvar f = [\n 'control', 'treatA', 'treatB', 'treatC', 'control',\n 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ];\nvar out = anova1( x, f )\n","ANSCOMBES_QUARTET":"var d = ANSCOMBES_QUARTET()\n","any":"var arr = [ 0, 0, 0, 0, 1 ];\nvar bool = any( arr )\n","anyBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4, -1 ];\nvar bool = anyBy( arr, negative )\n","anyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\n","anyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","anyByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, 2, 3, 4 ];\nvar bool = anyByRight( arr, negative )\n","anyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\n","anyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","aones":"var arr = aones( 2 )\narr = aones( 2, 'float32' )\n","aonesLike":"var x = new Float64Array( 2 );\nvar y = aonesLike( x )\ny = aonesLike( x, 'float32' )\n","aoneTo":"var arr = aoneTo( 2 )\narr = aoneTo( 2, 'float32' )\n","aoneToLike":"var arr = aoneToLike( [ 0, 0 ] )\narr = aoneToLike( [ 0, 0 ], 'float32' )\n","APERY":"APERY\n","append":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = append( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = append( arr, [ 3.0, 4.0 ] )\narr = { 'length': 0 };\narr = append( arr, [ 1.0, 2.0 ] )\n","ARCH":"ARCH\n","argumentFunction":"var argn = argumentFunction( 1 );\nvar v = argn( 3.14, -3.14, 0.0 )\nv = argn( -1.0, -0.0, 1.0 )\nv = argn( 'beep', 'boop', 'bop' )\nv = argn( 'beep' )\n","ARGV":"var execPath = ARGV[ 0 ]\n","array":"var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","array2buffer":"var buf = array2buffer( [ 1, 2, 3, 4 ] )\n","array2fancy":"var y = array2fancy( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.factory":"var f = array2fancy.factory();\nvar y = f( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.idx":"var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n","array2iterator":"var it = array2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","array2iteratorRight":"var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","ArrayBuffer":"var buf = new ArrayBuffer( 5 )\n","ArrayBuffer.length":"ArrayBuffer.length\n","ArrayBuffer.isView":"var arr = new Float64Array( 10 );\nArrayBuffer.isView( arr )\n","ArrayBuffer.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nbuf.byteLength\n","ArrayBuffer.prototype.slice":"var b1 = new ArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","arraybuffer2buffer":"var ab = new ArrayBuffer( 10 )\nvar buf = arraybuffer2buffer( ab )\nvar len = buf.length\nbuf = arraybuffer2buffer( ab, 2, 6 )\nlen = buf.length\n","arrayCtors":"var ctor = arrayCtors( 'float64' )\nctor = arrayCtors( 'float' )\n","arrayDataType":"var arr = new Float64Array( 10 );\nvar dt = arrayDataType( arr )\ndt = arrayDataType( 'beep' )\n","arrayDataTypes":"var out = arrayDataTypes()\nout = arrayDataTypes( 'floating_point' )\nout = arrayDataTypes( 'floating_point_and_generic' )\n","ArrayIndex":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n","ArrayIndex.free":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n// ...\nArrayIndex.free( idx.id )\n","ArrayIndex.get":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.get( idx.id )\n","ArrayIndex.prototype.data":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.data\n","ArrayIndex.prototype.dtype":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.dtype\n","ArrayIndex.prototype.id":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.id\n","ArrayIndex.prototype.isCached":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.isCached\n","ArrayIndex.prototype.type":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.type\n","ArrayIndex.prototype.toString":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toString()\n","ArrayIndex.prototype.toJSON":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toJSON()\n","arrayMinDataType":"var dt = arrayMinDataType( 3.141592653589793 )\ndt = arrayMinDataType( 3 )\ndt = arrayMinDataType( -3 )\ndt = arrayMinDataType( '-3' )\n","arrayMostlySafeCasts":"var out = arrayMostlySafeCasts( 'float32' )\n","arrayNextDataType":"var out = arrayNextDataType( 'float32' )\n","arrayPromotionRules":"var out = arrayPromotionRules( 'float32', 'int32' )\n","arraySafeCasts":"var out = arraySafeCasts( 'float32' )\n","arraySameKindCasts":"var out = arraySameKindCasts( 'float32' )\n","arrayShape":"var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n","arrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = arrayStream( [ 1, 2, 3 ] );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","arrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = arrayStream.factory( opts );\n","arrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = arrayStream.objectMode( [ 1, 2, 3 ] );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","arrayview2iterator":"var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","arrayview2iteratorRight":"var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","aslice":"var out = aslice( [ 1, 2, 3, 4 ] )\nout = aslice( [ 1, 2, 3, 4 ], 1 )\nout = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n","AsyncIteratorSymbol":"var s = AsyncIteratorSymbol\n","atake":"var x = [ 1, 2, 3, 4 ];\nvar y = atake( x, [ 1, 3 ] )\n","azeros":"var arr = azeros( 2 )\narr = azeros( 2, 'float32' )\n","azerosLike":"var x = new Float64Array( 2 );\nvar y = azerosLike( x )\ny = azerosLike( x, 'float32' )\n","azeroTo":"var arr = azeroTo( 2 )\narr = azeroTo( 2, 'float32' )\n","azeroToLike":"var arr = azeroToLike( [ 0, 0 ] )\narr = azeroToLike( [ 0, 0 ], 'float32' )\n","bartlettTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = bartlettTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = bartlettTest( arr, { 'groups': groups } )\n","base.abs":"var y = base.abs( -1.0 )\ny = base.abs( 2.0 )\ny = base.abs( 0.0 )\ny = base.abs( -0.0 )\ny = base.abs( NaN )\n","base.abs2":"var y = base.abs2( -1.0 )\ny = base.abs2( 2.0 )\ny = base.abs2( 0.0 )\ny = base.abs2( -0.0 )\ny = base.abs2( NaN )\n","base.abs2f":"var y = base.abs2f( -1.0 )\ny = base.abs2f( 2.0 )\ny = base.abs2f( 0.0 )\ny = base.abs2f( -0.0 )\ny = base.abs2f( NaN )\n","base.absdiff":"var d = base.absdiff( 2.0, 5.0 )\nd = base.absdiff( -1.0, 3.14 )\nd = base.absdiff( 10.1, -2.05 )\nd = base.absdiff( -0.0, 0.0 )\nd = base.absdiff( NaN, 5.0 )\nd = base.absdiff( PINF, NINF )\nd = base.absdiff( PINF, PINF )\n","base.absf":"var y = base.absf( -1.0 )\ny = base.absf( 2.0 )\ny = base.absf( 0.0 )\ny = base.absf( -0.0 )\ny = base.absf( NaN )\n","base.acos":"var y = base.acos( 1.0 )\ny = base.acos( 0.707 )\ny = base.acos( NaN )\n","base.acosh":"var y = base.acosh( 1.0 )\ny = base.acosh( 2.0 )\ny = base.acosh( NaN )\n","base.acot":"var y = base.acot( 2.0 )\ny = base.acot( 0.0 )\ny = base.acot( 0.5 )\ny = base.acot( 1.0 )\ny = base.acot( NaN )\n","base.acoth":"var y = base.acoth( 2.0 )\ny = base.acoth( 0.0 )\ny = base.acoth( 0.5 )\ny = base.acoth( 1.0 )\ny = base.acoth( NaN )\n","base.acovercos":"var y = base.acovercos( -1.5 )\ny = base.acovercos( -0.0 )\n","base.acoversin":"var y = base.acoversin( 1.5 )\ny = base.acoversin( 0.0 )\n","base.acsc":"var y = base.acsc( 1.0 )\ny = base.acsc( PI )\ny = base.acsc( -PI )\ny = base.acsc( NaN )\n","base.acsch":"var y = base.acsch( 0.0 )\ny = base.acsch( -1.0 )\ny = base.acsch( NaN )\n","base.add":"var v = base.add( -1.0, 5.0 )\nv = base.add( 2.0, 5.0 )\nv = base.add( 0.0, 5.0 )\nv = base.add( -0.0, 0.0 )\nv = base.add( NaN, NaN )\n","base.add3":"var v = base.add3( -1.0, 5.0, 2.0 )\nv = base.add3( 2.0, 5.0, 2.0 )\nv = base.add3( 0.0, 5.0, 2.0 )\nv = base.add3( -0.0, 0.0, -0.0 )\nv = base.add3( NaN, NaN, NaN )\n","base.add4":"var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\nv = base.add4( 2.0, 5.0, 2.0, -3.0 )\nv = base.add4( 0.0, 5.0, 2.0, -3.0 )\nv = base.add4( -0.0, 0.0, -0.0, -0.0 )\nv = base.add4( NaN, NaN, NaN, NaN )\n","base.add5":"var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\nv = base.add5( NaN, NaN, NaN, NaN, NaN )\n","base.addf":"var v = base.addf( -1.0, 5.0 )\nv = base.addf( 2.0, 5.0 )\nv = base.addf( 0.0, 5.0 )\nv = base.addf( -0.0, 0.0 )\nv = base.addf( NaN, NaN )\n","base.ahavercos":"var y = base.ahavercos( 0.5 )\ny = base.ahavercos( 0.0 )\n","base.ahaversin":"var y = base.ahaversin( 0.5 )\ny = base.ahaversin( 0.0 )\n","base.asec":"var y = base.asec( 1.0 )\ny = base.asec( 2.0 )\ny = base.asec( NaN )\n","base.asech":"var y = base.asech( 1.0 )\ny = base.asech( 0.5 )\ny = base.asech( NaN )\n","base.asin":"var y = base.asin( 0.0 )\ny = base.asin( -PI/6.0 )\ny = base.asin( NaN )\n","base.asinh":"var y = base.asinh( 0.0 )\ny = base.asinh( 2.0 )\ny = base.asinh( -2.0 )\ny = base.asinh( NaN )\ny = base.asinh( NINF )\ny = base.asinh( PINF )\n","base.atan":"var y = base.atan( 0.0 )\ny = base.atan( -PI/2.0 )\ny = base.atan( PI/2.0 )\ny = base.atan( NaN )\n","base.atan2":"var v = base.atan2( 2.0, 2.0 )\nv = base.atan2( 6.0, 2.0 )\nv = base.atan2( -1.0, -1.0 )\nv = base.atan2( 3.0, 0.0 )\nv = base.atan2( -2.0, 0.0 )\nv = base.atan2( 0.0, 0.0 )\nv = base.atan2( 3.0, NaN )\nv = base.atan2( NaN, 2.0 )\n","base.atanh":"var y = base.atanh( 0.0 )\ny = base.atanh( 0.9 )\ny = base.atanh( 1.0 )\ny = base.atanh( -1.0 )\ny = base.atanh( NaN )\n","base.avercos":"var y = base.avercos( -1.5 )\ny = base.avercos( -0.0 )\n","base.aversin":"var y = base.aversin( 1.5 )\ny = base.aversin( 0.0 )\n","base.bernoulli":"var y = base.bernoulli( 0 )\ny = base.bernoulli( 1 )\ny = base.bernoulli( 2 )\ny = base.bernoulli( 3 )\ny = base.bernoulli( 4 )\ny = base.bernoulli( 5 )\ny = base.bernoulli( 20 )\ny = base.bernoulli( 260 )\ny = base.bernoulli( 262 )\ny = base.bernoulli( NaN )\n","base.besselj0":"var y = base.besselj0( 0.0 )\ny = base.besselj0( 1.0 )\ny = base.besselj0( PINF )\ny = base.besselj0( NINF )\ny = base.besselj0( NaN )\n","base.besselj1":"var y = base.besselj1( 0.0 )\ny = base.besselj1( 1.0 )\ny = base.besselj1( PINF )\ny = base.besselj1( NINF )\ny = base.besselj1( NaN )\n","base.bessely0":"var y = base.bessely0( 0.0 )\ny = base.bessely0( 1.0 )\ny = base.bessely0( -1.0 )\ny = base.bessely0( PINF )\ny = base.bessely0( NINF )\ny = base.bessely0( NaN )\n","base.bessely1":"var y = base.bessely1( 0.0 )\ny = base.bessely1( 1.0 )\ny = base.bessely1( -1.0 )\ny = base.bessely1( PINF )\ny = base.bessely1( NINF )\ny = base.bessely1( NaN )\n","base.beta":"var v = base.beta( 0.0, 0.5 )\nv = base.beta( 1.0, 1.0 )\nv = base.beta( -1.0, 2.0 )\nv = base.beta( 5.0, 0.2 )\nv = base.beta( 4.0, 1.0 )\nv = base.beta( NaN, 2.0 )\n","base.betainc":"var y = base.betainc( 0.5, 2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, 2.0, false )\ny = base.betainc( 0.2, 1.0, 2.0 )\ny = base.betainc( 0.2, 1.0, 2.0, true, true )\ny = base.betainc( NaN, 1.0, 1.0 )\ny = base.betainc( 0.8, NaN, 1.0 )\ny = base.betainc( 0.8, 1.0, NaN )\ny = base.betainc( 1.5, 1.0, 1.0 )\ny = base.betainc( -0.5, 1.0, 1.0 )\ny = base.betainc( 0.5, -2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, -2.0 )\n","base.betaincinv":"var y = base.betaincinv( 0.2, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0, true )\ny = base.betaincinv( 0.4, 1.0, 6.0 )\ny = base.betaincinv( 0.8, 1.0, 6.0 )\ny = base.betaincinv( NaN, 1.0, 1.0 )\ny = base.betaincinv( 0.5, NaN, 1.0 )\ny = base.betaincinv( 0.5, 1.0, NaN )\ny = base.betaincinv( 1.2, 1.0, 1.0 )\ny = base.betaincinv( -0.5, 1.0, 1.0 )\ny = base.betaincinv( 0.5, -2.0, 2.0 )\ny = base.betaincinv( 0.5, 0.0, 2.0 )\ny = base.betaincinv( 0.5, 2.0, -2.0 )\ny = base.betaincinv( 0.5, 2.0, 0.0 )\n","base.betaln":"var v = base.betaln( 0.0, 0.0 )\nv = base.betaln( 1.0, 1.0 )\nv = base.betaln( -1.0, 2.0 )\nv = base.betaln( 5.0, 0.2 )\nv = base.betaln( 4.0, 1.0 )\nv = base.betaln( NaN, 2.0 )\n","base.binet":"var y = base.binet( 0.0 )\ny = base.binet( 1.0 )\ny = base.binet( 2.0 )\ny = base.binet( 3.0 )\ny = base.binet( 4.0 )\ny = base.binet( 5.0 )\ny = base.binet( NaN )\n","base.binomcoef":"var v = base.binomcoef( 8, 2 )\nv = base.binomcoef( 0, 0 )\nv = base.binomcoef( -4, 2 )\nv = base.binomcoef( 5, 3 )\nv = base.binomcoef( NaN, 3 )\nv = base.binomcoef( 5, NaN )\nv = base.binomcoef( NaN, NaN )\n","base.binomcoefln":"var v = base.binomcoefln( 8, 2 )\nv = base.binomcoefln( 0, 0 )\nv = base.binomcoefln( -4, 2 )\nv = base.binomcoefln( 88, 3 )\nv = base.binomcoefln( NaN, 3 )\nv = base.binomcoefln( 5, NaN )\nv = base.binomcoefln( NaN, NaN )\n","base.boxcox":"var v = base.boxcox( 1.0, 2.5 )\nv = base.boxcox( 4.0, 2.5 )\nv = base.boxcox( 10.0, 2.5 )\nv = base.boxcox( 2.0, 0.0 )\nv = base.boxcox( -1.0, 2.5 )\nv = base.boxcox( 0.0, -1.0 )\n","base.boxcox1p":"var v = base.boxcox1p( 1.0, 2.5 )\nv = base.boxcox1p( 4.0, 2.5 )\nv = base.boxcox1p( 10.0, 2.5 )\nv = base.boxcox1p( 2.0, 0.0 )\nv = base.boxcox1p( -1.0, 2.5 )\nv = base.boxcox1p( 0.0, -1.0 )\nv = base.boxcox1p( -1.0, -1.0 )\n","base.boxcox1pinv":"var v = base.boxcox1pinv( 1.0, 2.5 )\nv = base.boxcox1pinv( 4.0, 2.5 )\nv = base.boxcox1pinv( 10.0, 2.5 )\nv = base.boxcox1pinv( 2.0, 0.0 )\nv = base.boxcox1pinv( -1.0, 2.5 )\nv = base.boxcox1pinv( 0.0, -1.0 )\nv = base.boxcox1pinv( 1.0, NaN )\nv = base.boxcox1pinv( NaN, 3.1 )\n","base.boxcoxinv":"var v = base.boxcoxinv( 1.0, 2.5 )\nv = base.boxcoxinv( 4.0, 2.5 )\nv = base.boxcoxinv( 10.0, 2.5 )\nv = base.boxcoxinv( 2.0, 0.0 )\nv = base.boxcoxinv( -1.0, 2.5 )\nv = base.boxcoxinv( 0.0, -1.0 )\nv = base.boxcoxinv( 1.0, NaN )\nv = base.boxcoxinv( NaN, 3.1 )\n","base.cabs":"var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n","base.cabs2":"var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n","base.cabs2f":"var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n","base.cabsf":"var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n","base.cadd":"var z = new Complex128( 5.0, 3.0 )\nvar out = base.cadd( z, z )\nvar re = real( out )\nvar im = imag( out )\n","base.caddf":"var z = new Complex64( 5.0, 3.0 )\nvar out = base.caddf( z, z )\nvar re = realf( out )\nvar im = imagf( out )\n","base.cbrt":"var y = base.cbrt( 64.0 )\ny = base.cbrt( 27.0 )\ny = base.cbrt( 0.0 )\ny = base.cbrt( -0.0 )\ny = base.cbrt( -9.0 )\ny = base.cbrt( NaN )\n","base.cbrtf":"var y = base.cbrtf( 64.0 )\ny = base.cbrtf( 27.0 )\ny = base.cbrtf( 0.0 )\ny = base.cbrtf( -0.0 )\ny = base.cbrtf( -9.0 )\ny = base.cbrtf( NaN )\n","base.cceil":"var v = base.cceil( new Complex128( -1.5, 2.5 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.cceilf":"var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.cceiln":"var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\nvar re = real( out )\nvar im = imag( out )\n","base.ccis":"var y = base.ccis( new Complex128( 0.0, 0.0 ) )\nvar re = real( y )\nvar im = imag( y )\ny = base.ccis( new Complex128( 1.0, 0.0 ) )\nre = real( y )\nim = imag( y )\n","base.cdiv":"var z1 = new Complex128( -13.0, -1.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar y = base.cdiv( z1, z2 )\nvar re = real( y )\nvar im = imag( y )\n","base.ceil":"var y = base.ceil( 3.14 )\ny = base.ceil( -4.2 )\ny = base.ceil( -4.6 )\ny = base.ceil( 9.5 )\ny = base.ceil( -0.0 )\n","base.ceil2":"var y = base.ceil2( 3.14 )\ny = base.ceil2( -4.2 )\ny = base.ceil2( -4.6 )\ny = base.ceil2( 9.5 )\ny = base.ceil2( 13.0 )\ny = base.ceil2( -13.0 )\ny = base.ceil2( -0.0 )\n","base.ceil10":"var y = base.ceil10( 3.14 )\ny = base.ceil10( -4.2 )\ny = base.ceil10( -4.6 )\ny = base.ceil10( 9.5 )\ny = base.ceil10( 13.0 )\ny = base.ceil10( -13.0 )\ny = base.ceil10( -0.0 )\n","base.ceilb":"var y = base.ceilb( 3.14159, -4, 10 )\ny = base.ceilb( 3.14159, 0, 2 )\ny = base.ceilb( 5.0, 1, 2 )\n","base.ceilf":"var y = base.ceilf( 3.14 )\ny = base.ceilf( -4.2 )\ny = base.ceilf( -4.6 )\ny = base.ceilf( 9.5 )\ny = base.ceilf( -0.0 )\n","base.ceiln":"var y = base.ceiln( 3.14159, -2 )\ny = base.ceiln( 3.14159, 0 )\ny = base.ceiln( 12368.0, 3 )\n","base.ceilsd":"var y = base.ceilsd( 3.14159, 5 )\ny = base.ceilsd( 3.14159, 1 )\ny = base.ceilsd( 12368.0, 2 )\ny = base.ceilsd( 0.0313, 2, 2 )\n","base.cexp":"var y = base.cexp( new Complex128( 0.0, 0.0 ) )\nvar re = real( y )\nvar im = imag( y )\ny = base.cexp( new Complex128( 0.0, 1.0 ) )\nre = real( y )\nim = imag( y )\n","base.cflipsign":"var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\nvar re = real( v )\nvar im = imag( v )\n","base.cflipsignf":"var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\nvar re = real( v )\nvar im = imag( v )\n","base.cfloor":"var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.cfloorn":"var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\nvar re = real( v )\nvar im = imag( v )\n","base.cidentity":"var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\nvar re = real( v )\nvar img = imag( v )\n","base.cidentityf":"var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\nvar re = real( v )\nvar img = imag( v )\n","base.cinv":"var v = base.cinv( new Complex128( 2.0, 4.0 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.clamp":"var y = base.clamp( 3.14, 0.0, 5.0 )\ny = base.clamp( -3.14, 0.0, 5.0 )\ny = base.clamp( 3.14, 0.0, 3.0 )\ny = base.clamp( -0.0, 0.0, 5.0 )\ny = base.clamp( 0.0, -3.14, -0.0 )\ny = base.clamp( NaN, 0.0, 5.0 )\n","base.clampf":"var y = base.clampf( 3.14, 0.0, 5.0 )\ny = base.clampf( -3.14, 0.0, 5.0 )\ny = base.clampf( 3.14, 0.0, 3.0 )\ny = base.clampf( -0.0, 0.0, 5.0 )\ny = base.clampf( 0.0, -3.14, -0.0 )\ny = base.clampf( NaN, 0.0, 5.0 )\n","base.cmul":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.cmul( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.cmulf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.cmulf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.cneg":"var z = new Complex128( -4.2, 5.5 )\nvar v = base.cneg( z )\nvar re = real( v )\nvar im = imag( v )\n","base.cnegf":"var z = new Complex64( -4.0, 5.0 )\nvar v = base.cnegf( z )\nvar re = realf( v )\nvar im = imagf( v )\n","base.continuedFraction":"function closure() {\nvar i = 0;\nreturn function() {\n i += 1;\n return [ i, i ];\n};\n };\nvar gen = closure();\nvar out = base.continuedFraction( gen )\nfunction* generator() {\n var i = 0;\n while ( true ) {\n i += 1;\n yield [ i, i ];\n }\n };\ngen = generator();\nout = base.continuedFraction( gen )\nout = base.continuedFraction( generator(), { 'keep': true } )\nout = base.continuedFraction( generator(), { 'maxIter': 10 } )\nout = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n","base.copysign":"var z = base.copysign( -3.14, 10.0 )\nz = base.copysign( 3.14, -1.0 )\nz = base.copysign( 1.0, -0.0 )\nz = base.copysign( -3.14, -0.0 )\nz = base.copysign( -0.0, 1.0 )\n","base.copysignf":"var z = base.copysignf( -3.0, 10.0 )\nz = base.copysignf( 3.0, -1.0 )\nz = base.copysignf( 1.0, -0.0 )\nz = base.copysignf( -3.0, -0.0 )\nz = base.copysignf( -0.0, 1.0 )\n","base.cos":"var y = base.cos( 0.0 )\ny = base.cos( PI/4.0 )\ny = base.cos( -PI/6.0 )\ny = base.cos( NaN )\n","base.cosh":"var y = base.cosh( 0.0 )\ny = base.cosh( 2.0 )\ny = base.cosh( -2.0 )\ny = base.cosh( NaN )\n","base.cosm1":"var y = base.cosm1( 0.0 )\ny = base.cosm1( PI/4.0 )\ny = base.cosm1( -PI/6.0 )\ny = base.cosm1( NaN )\n","base.cospi":"var y = base.cospi( 0.0 )\ny = base.cospi( 0.5 )\ny = base.cospi( 0.1 )\ny = base.cospi( NaN )\n","base.cot":"var y = base.cot( 0.0 )\ny = base.cot( -PI/4.0 )\ny = base.cot( PI/4.0 )\ny = base.cot( NaN )\n","base.coth":"var y = base.coth( 0.0 )\ny = base.coth( -0.0 )\ny = base.coth( 2.0 )\ny = base.coth( -2.0 )\ny = base.coth( +Infinity )\ny = base.coth( -Infinity )\ny = base.coth( NaN )\n","base.covercos":"var y = base.covercos( 3.14 )\ny = base.covercos( -4.2 )\ny = base.covercos( -4.6 )\ny = base.covercos( 9.5 )\ny = base.covercos( -0.0 )\n","base.coversin":"var y = base.coversin( 3.14 )\ny = base.coversin( -4.2 )\ny = base.coversin( -4.6 )\ny = base.coversin( 9.5 )\ny = base.coversin( -0.0 )\n","base.cphase":"var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n","base.cpolar":"var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n","base.cpolar.assign":"var out = new Float64Array( 2 );\nvar v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\nvar bool = ( v === out )\n","base.cround":"var v = base.cround( new Complex128( 5.5, 3.3 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.croundn":"var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\nvar re = real( v )\nvar im = imag( v )\n","base.csch":"var y = base.csch( +0.0 )\nvar y = base.csch( -0.0 )\nvar y = base.csch( +Infinity )\nvar y = base.csch( -Infinity )\ny = base.csch( 2.0 )\ny = base.csch( -2.0 )\ny = base.csch( NaN )\n","base.csignum":"var v = base.csignum( new Complex128( -4.2, 5.5 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.csub":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.csub( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.csubf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.csubf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.deg2rad":"var r = base.deg2rad( 90.0 )\nr = base.deg2rad( -45.0 )\nr = base.deg2rad( NaN )\n","base.deg2radf":"var r = base.deg2radf( 90.0 )\nr = base.deg2radf( -45.0 )\nr = base.deg2radf( NaN )\n","base.digamma":"var y = base.digamma( -2.5 )\ny = base.digamma( 1.0 )\ny = base.digamma( 10.0 )\ny = base.digamma( NaN )\ny = base.digamma( -1.0 )\n","base.diracDelta":"var y = base.diracDelta( 3.14 )\ny = base.diracDelta( 0.0 )\n","base.div":"var v = base.div( -1.0, 5.0 )\nv = base.div( 2.0, 5.0 )\nv = base.div( 0.0, 5.0 )\nv = base.div( -0.0, 5.0 )\nv = base.div( NaN, NaN )\n","base.divf":"var v = base.divf( -1.0, 5.0 )\nv = base.divf( 2.0, 5.0 )\nv = base.divf( 0.0, 5.0 )\nv = base.divf( -0.0, 5.0 )\nv = base.divf( NaN, NaN )\n","base.dists.arcsine.Arcsine":"var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\narcsine.a\narcsine.b\narcsine.entropy\narcsine.kurtosis\narcsine.mean\narcsine.median\narcsine.mode\narcsine.skewness\narcsine.stdev\narcsine.variance\narcsine.cdf( 0.8 )\narcsine.logcdf( 0.8 )\narcsine.logpdf( 0.4 )\narcsine.pdf( 0.8 )\narcsine.quantile( 0.8 )\n","base.dists.arcsine.cdf":"var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n","base.dists.arcsine.cdf.factory":"var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.arcsine.entropy":"var v = base.dists.arcsine.entropy( 0.0, 1.0 )\nv = base.dists.arcsine.entropy( 4.0, 12.0 )\nv = base.dists.arcsine.entropy( 2.0, 8.0 )\n","base.dists.arcsine.kurtosis":"var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\nv = base.dists.arcsine.kurtosis( 4.0, 12.0 )\nv = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n","base.dists.arcsine.logcdf":"var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.arcsine.logcdf.factory":"var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.arcsine.logpdf":"var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.logpdf.factory":"var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 7.0 )\ny = mylogPDF( 5.0 )\n","base.dists.arcsine.mean":"var v = base.dists.arcsine.mean( 0.0, 1.0 )\nv = base.dists.arcsine.mean( 4.0, 12.0 )\nv = base.dists.arcsine.mean( 2.0, 8.0 )\n","base.dists.arcsine.median":"var v = base.dists.arcsine.median( 0.0, 1.0 )\nv = base.dists.arcsine.median( 4.0, 12.0 )\nv = base.dists.arcsine.median( 2.0, 8.0 )\n","base.dists.arcsine.mode":"var v = base.dists.arcsine.mode( 0.0, 1.0 )\nv = base.dists.arcsine.mode( 4.0, 12.0 )\nv = base.dists.arcsine.mode( 2.0, 8.0 )\n","base.dists.arcsine.pdf":"var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.pdf.factory":"var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.arcsine.quantile":"var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\ny = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n","base.dists.arcsine.quantile.factory":"var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.arcsine.skewness":"var v = base.dists.arcsine.skewness( 0.0, 1.0 )\nv = base.dists.arcsine.skewness( 4.0, 12.0 )\nv = base.dists.arcsine.skewness( 2.0, 8.0 )\n","base.dists.arcsine.stdev":"var v = base.dists.arcsine.stdev( 0.0, 1.0 )\nv = base.dists.arcsine.stdev( 4.0, 12.0 )\nv = base.dists.arcsine.stdev( 2.0, 8.0 )\n","base.dists.arcsine.variance":"var v = base.dists.arcsine.variance( 0.0, 1.0 )\nv = base.dists.arcsine.variance( 4.0, 12.0 )\nv = base.dists.arcsine.variance( 2.0, 8.0 )\n","base.dists.bernoulli.Bernoulli":"var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\nbernoulli.p\nbernoulli.entropy\nbernoulli.kurtosis\nbernoulli.mean\nbernoulli.median\nbernoulli.skewness\nbernoulli.stdev\nbernoulli.variance\nbernoulli.cdf( 0.5 )\nbernoulli.mgf( 3.0 )\nbernoulli.pmf( 0.0 )\nbernoulli.quantile( 0.7 )\n","base.dists.bernoulli.cdf":"var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\ny = base.dists.bernoulli.cdf( 0.8, 0.1 )\ny = base.dists.bernoulli.cdf( -1.0, 0.4 )\ny = base.dists.bernoulli.cdf( 1.5, 0.4 )\ny = base.dists.bernoulli.cdf( NaN, 0.5 )\ny = base.dists.bernoulli.cdf( 0.0, NaN )\ny = base.dists.bernoulli.cdf( 2.0, 1.4 )\n","base.dists.bernoulli.cdf.factory":"var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 0.7 )\n","base.dists.bernoulli.entropy":"var v = base.dists.bernoulli.entropy( 0.1 )\nv = base.dists.bernoulli.entropy( 0.5 )\n","base.dists.bernoulli.kurtosis":"var v = base.dists.bernoulli.kurtosis( 0.1 )\nv = base.dists.bernoulli.kurtosis( 0.5 )\n","base.dists.bernoulli.mean":"var v = base.dists.bernoulli.mean( 0.1 )\nv = base.dists.bernoulli.mean( 0.5 )\n","base.dists.bernoulli.median":"var v = base.dists.bernoulli.median( 0.1 )\nv = base.dists.bernoulli.median( 0.8 )\n","base.dists.bernoulli.mgf":"var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\ny = base.dists.bernoulli.mgf( 0.4, 0.5 )\ny = base.dists.bernoulli.mgf( NaN, 0.0 )\ny = base.dists.bernoulli.mgf( 0.0, NaN )\ny = base.dists.bernoulli.mgf( -2.0, -1.0 )\ny = base.dists.bernoulli.mgf( 0.2, 2.0 )\n","base.dists.bernoulli.mgf.factory":"var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.bernoulli.mode":"var v = base.dists.bernoulli.mode( 0.1 )\nv = base.dists.bernoulli.mode( 0.8 )\n","base.dists.bernoulli.pmf":"var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\ny = base.dists.bernoulli.pmf( 0.0, 0.7 )\ny = base.dists.bernoulli.pmf( -1.0, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, NaN )\ny = base.dists.bernoulli.pmf( NaN, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, 1.5 )\n","base.dists.bernoulli.pmf.factory":"var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\nvar y = mypmf( 1.0 )\ny = mypmf( 0.0 )\n","base.dists.bernoulli.quantile":"var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\ny = base.dists.bernoulli.quantile( 0.5, 0.4 )\ny = base.dists.bernoulli.quantile( 0.9, 0.1 )\ny = base.dists.bernoulli.quantile( -0.2, 0.1 )\ny = base.dists.bernoulli.quantile( NaN, 0.8 )\ny = base.dists.bernoulli.quantile( 0.4, NaN )\ny = base.dists.bernoulli.quantile( 0.5, -1.0 )\ny = base.dists.bernoulli.quantile( 0.5, 1.5 )\n","base.dists.bernoulli.quantile.factory":"var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.bernoulli.skewness":"var v = base.dists.bernoulli.skewness( 0.1 )\nv = base.dists.bernoulli.skewness( 0.5 )\n","base.dists.bernoulli.stdev":"var v = base.dists.bernoulli.stdev( 0.1 )\nv = base.dists.bernoulli.stdev( 0.5 )\n","base.dists.bernoulli.variance":"var v = base.dists.bernoulli.variance( 0.1 )\nv = base.dists.bernoulli.variance( 0.5 )\n","base.dists.beta.Beta":"var beta = base.dists.beta.Beta( 1.0, 1.0 );\nbeta.alpha\nbeta.beta\nbeta.entropy\nbeta.kurtosis\nbeta.mean\nbeta.median\nbeta.mode\nbeta.skewness\nbeta.stdev\nbeta.variance\nbeta.cdf( 0.8 )\nbeta.logcdf( 0.8 )\nbeta.logpdf( 1.0 )\nbeta.mgf( 3.14 )\nbeta.pdf( 1.0 )\nbeta.quantile( 0.8 )\n","base.dists.beta.cdf":"var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.cdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.cdf( 0.0, 1.0, NaN )\n","base.dists.beta.cdf.factory":"var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.beta.entropy":"var v = base.dists.beta.entropy( 1.0, 1.0 )\nv = base.dists.beta.entropy( 4.0, 12.0 )\nv = base.dists.beta.entropy( 8.0, 2.0 )\nv = base.dists.beta.entropy( 1.0, -0.1 )\nv = base.dists.beta.entropy( -0.1, 1.0 )\nv = base.dists.beta.entropy( 2.0, NaN )\nv = base.dists.beta.entropy( NaN, 2.0 )\n","base.dists.beta.kurtosis":"var v = base.dists.beta.kurtosis( 1.0, 1.0 )\nv = base.dists.beta.kurtosis( 4.0, 12.0 )\nv = base.dists.beta.kurtosis( 8.0, 2.0 )\nv = base.dists.beta.kurtosis( 1.0, -0.1 )\nv = base.dists.beta.kurtosis( -0.1, 1.0 )\nv = base.dists.beta.kurtosis( 2.0, NaN )\nv = base.dists.beta.kurtosis( NaN, 2.0 )\n","base.dists.beta.logcdf":"var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n","base.dists.beta.logcdf.factory":"var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.beta.logpdf":"var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n","base.dists.beta.logpdf.factory":"var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.beta.mean":"var v = base.dists.beta.mean( 1.0, 1.0 )\nv = base.dists.beta.mean( 4.0, 12.0 )\nv = base.dists.beta.mean( 8.0, 2.0 )\n","base.dists.beta.median":"var v = base.dists.beta.median( 1.0, 1.0 )\nv = base.dists.beta.median( 4.0, 12.0 )\nv = base.dists.beta.median( 8.0, 2.0 )\nv = base.dists.beta.median( 1.0, -0.1 )\nv = base.dists.beta.median( -0.1, 1.0 )\nv = base.dists.beta.median( 2.0, NaN )\nv = base.dists.beta.median( NaN, 2.0 )\n","base.dists.beta.mgf":"var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\ny = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\ny = base.dists.beta.mgf( NaN, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.0, NaN, 1.0 )\ny = base.dists.beta.mgf( 0.0, 1.0, NaN )\ny = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n","base.dists.beta.mgf.factory":"var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.3 )\n","base.dists.beta.mode":"var v = base.dists.beta.mode( 4.0, 12.0 )\nv = base.dists.beta.mode( 8.0, 2.0 )\nv = base.dists.beta.mode( 1.0, 1.0 )\n","base.dists.beta.pdf":"var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.pdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.pdf( 0.5, 1.0, NaN )\n","base.dists.beta.pdf.factory":"var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.beta.quantile":"var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.beta.quantile( NaN, 1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, NaN, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, NaN )\ny = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n","base.dists.beta.quantile.factory":"var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\ny = myquantile( 0.8 )\ny = myquantile( 0.4 )\n","base.dists.beta.skewness":"var v = base.dists.beta.skewness( 1.0, 1.0 )\nv = base.dists.beta.skewness( 4.0, 12.0 )\nv = base.dists.beta.skewness( 8.0, 2.0 )\nv = base.dists.beta.skewness( 1.0, -0.1 )\nv = base.dists.beta.skewness( -0.1, 1.0 )\nv = base.dists.beta.skewness( 2.0, NaN )\nv = base.dists.beta.skewness( NaN, 2.0 )\n","base.dists.beta.stdev":"var v = base.dists.beta.stdev( 1.0, 1.0 )\nv = base.dists.beta.stdev( 4.0, 12.0 )\nv = base.dists.beta.stdev( 8.0, 2.0 )\nv = base.dists.beta.stdev( 1.0, -0.1 )\nv = base.dists.beta.stdev( -0.1, 1.0 )\nv = base.dists.beta.stdev( 2.0, NaN )\nv = base.dists.beta.stdev( NaN, 2.0 )\n","base.dists.beta.variance":"var v = base.dists.beta.variance( 1.0, 1.0 )\nv = base.dists.beta.variance( 4.0, 12.0 )\nv = base.dists.beta.variance( 8.0, 2.0 )\nv = base.dists.beta.variance( 1.0, -0.1 )\nv = base.dists.beta.variance( -0.1, 1.0 )\nv = base.dists.beta.variance( 2.0, NaN )\nv = base.dists.beta.variance( NaN, 2.0 )\n","base.dists.betaprime.BetaPrime":"var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\nbetaprime.alpha\nbetaprime.beta\nbetaprime.kurtosis\nbetaprime.mean\nbetaprime.mode\nbetaprime.skewness\nbetaprime.stdev\nbetaprime.variance\nbetaprime.cdf( 0.8 )\nbetaprime.logcdf( 0.8 )\nbetaprime.logpdf( 1.0 )\nbetaprime.pdf( 1.0 )\nbetaprime.quantile( 0.8 )\n","base.dists.betaprime.cdf":"var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.cdf.factory":"var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.betaprime.kurtosis":"var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 4.0, 12.0 )\nv = base.dists.betaprime.kurtosis( 8.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 1.0, 2.8 )\nv = base.dists.betaprime.kurtosis( 1.0, -0.1 )\nv = base.dists.betaprime.kurtosis( -0.1, 5.0 )\nv = base.dists.betaprime.kurtosis( 2.0, NaN )\nv = base.dists.betaprime.kurtosis( NaN, 6.0 )\n","base.dists.betaprime.logcdf":"var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.logcdf.factory":"var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.betaprime.logpdf":"var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.logpdf.factory":"var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.betaprime.mean":"var v = base.dists.betaprime.mean( 1.0, 2.0 )\nv = base.dists.betaprime.mean( 4.0, 12.0 )\nv = base.dists.betaprime.mean( 8.0, 2.0 )\n","base.dists.betaprime.mode":"var v = base.dists.betaprime.mode( 1.0, 2.0 )\nv = base.dists.betaprime.mode( 4.0, 12.0 )\nv = base.dists.betaprime.mode( 8.0, 2.0 )\n","base.dists.betaprime.pdf":"var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.pdf.factory":"var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.betaprime.quantile":"var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\ny = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n","base.dists.betaprime.quantile.factory":"var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\ny = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.betaprime.skewness":"var v = base.dists.betaprime.skewness( 2.0, 4.0 )\nv = base.dists.betaprime.skewness( 4.0, 12.0 )\nv = base.dists.betaprime.skewness( 8.0, 4.0 )\nv = base.dists.betaprime.skewness( 1.0, 2.8 )\nv = base.dists.betaprime.skewness( 1.0, -0.1 )\nv = base.dists.betaprime.skewness( -0.1, 4.0 )\nv = base.dists.betaprime.skewness( 2.0, NaN )\nv = base.dists.betaprime.skewness( NaN, 4.0 )\n","base.dists.betaprime.stdev":"var v = base.dists.betaprime.stdev( 1.0, 2.5 )\nv = base.dists.betaprime.stdev( 4.0, 12.0 )\nv = base.dists.betaprime.stdev( 8.0, 2.5 )\nv = base.dists.betaprime.stdev( 8.0, 1.0 )\nv = base.dists.betaprime.stdev( 1.0, -0.1 )\nv = base.dists.betaprime.stdev( -0.1, 3.0 )\nv = base.dists.betaprime.stdev( 2.0, NaN )\nv = base.dists.betaprime.stdev( NaN, 3.0 )\n","base.dists.betaprime.variance":"var v = base.dists.betaprime.variance( 1.0, 2.5 )\nv = base.dists.betaprime.variance( 4.0, 12.0 )\nv = base.dists.betaprime.variance( 8.0, 2.5 )\nv = base.dists.betaprime.variance( 8.0, 1.0 )\nv = base.dists.betaprime.variance( 1.0, -0.1 )\nv = base.dists.betaprime.variance( -0.1, 3.0 )\nv = base.dists.betaprime.variance( 2.0, NaN )\nv = base.dists.betaprime.variance( NaN, 3.0 )\n","base.dists.binomial.Binomial":"var binomial = base.dists.binomial.Binomial( 8, 0.5 );\nbinomial.n\nbinomial.p\nbinomial.kurtosis\nbinomial.mean\nbinomial.median\nbinomial.mode\nbinomial.skewness\nbinomial.stdev\nbinomial.variance\nbinomial.cdf( 2.9 )\nbinomial.logpmf( 3.0 )\nbinomial.mgf( 0.2 )\nbinomial.pmf( 3.0 )\nbinomial.quantile( 0.8 )\n","base.dists.binomial.cdf":"var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 21.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 5.0, 10, 0.4 )\ny = base.dists.binomial.cdf( 0.0, 10, 0.4 )\ny = base.dists.binomial.cdf( NaN, 20, 0.5 )\ny = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.cdf( 0.0, 20, NaN )\ny = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n","base.dists.binomial.cdf.factory":"var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.binomial.entropy":"var v = base.dists.binomial.entropy( 100, 0.1 )\nv = base.dists.binomial.entropy( 20, 0.5 )\nv = base.dists.binomial.entropy( 10.3, 0.5 )\nv = base.dists.binomial.entropy( 20, 1.1 )\nv = base.dists.binomial.entropy( 20, NaN )\n","base.dists.binomial.kurtosis":"var v = base.dists.binomial.kurtosis( 100, 0.1 )\nv = base.dists.binomial.kurtosis( 20, 0.5 )\nv = base.dists.binomial.kurtosis( 10.3, 0.5 )\nv = base.dists.binomial.kurtosis( 20, 1.1 )\nv = base.dists.binomial.kurtosis( 20, NaN )\n","base.dists.binomial.logpmf":"var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( NaN, 20, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, 20, NaN )\ny = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n","base.dists.binomial.logpmf.factory":"var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 5.0 )\n","base.dists.binomial.mean":"var v = base.dists.binomial.mean( 100, 0.1 )\nv = base.dists.binomial.mean( 20, 0.5 )\nv = base.dists.binomial.mean( 10.3, 0.5 )\nv = base.dists.binomial.mean( 20, 1.1 )\nv = base.dists.binomial.mean( 20, NaN )\n","base.dists.binomial.median":"var v = base.dists.binomial.median( 100, 0.1 )\nv = base.dists.binomial.median( 20, 0.5 )\nv = base.dists.binomial.median( 10.3, 0.5 )\nv = base.dists.binomial.median( 20, 1.1 )\nv = base.dists.binomial.median( 20, NaN )\n","base.dists.binomial.mgf":"var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\ny = base.dists.binomial.mgf( 5.0, 20, 0.2 )\ny = base.dists.binomial.mgf( 0.9, 10, 0.4 )\ny = base.dists.binomial.mgf( 0.0, 10, 0.4 )\ny = base.dists.binomial.mgf( NaN, 20, 0.5 )\ny = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.mgf( 0.0, 20, NaN )\ny = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.mgf( 2.0, 20, -1.0 )\ny = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n","base.dists.binomial.mgf.factory":"var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\nvar y = myMGF( 0.3 )\n","base.dists.binomial.mode":"var v = base.dists.binomial.mode( 100, 0.1 )\nv = base.dists.binomial.mode( 20, 0.5 )\nv = base.dists.binomial.mode( 10.3, 0.5 )\nv = base.dists.binomial.mode( 20, 1.1 )\nv = base.dists.binomial.mode( 20, NaN )\n","base.dists.binomial.pmf":"var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.pmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.pmf( NaN, 20, 0.5 )\ny = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.pmf( 0.0, 20, NaN )\ny = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n","base.dists.binomial.pmf.factory":"var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 5.0 )\n","base.dists.binomial.quantile":"var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.8, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.5, 10, 0.4 )\ny = base.dists.binomial.quantile( 0.0, 10, 0.4 )\ny = base.dists.binomial.quantile( 1.0, 10, 0.4 )\ny = base.dists.binomial.quantile( NaN, 20, 0.5 )\ny = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\ny = base.dists.binomial.quantile( 0.2, 20, NaN )\ny = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\ny = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.binomial.quantile( 0.5, 20, -1.0 )\ny = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n","base.dists.binomial.quantile.factory":"var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\nvar y = myquantile( 0.1 )\ny = myquantile( 0.9 )\n","base.dists.binomial.skewness":"var v = base.dists.binomial.skewness( 100, 0.1 )\nv = base.dists.binomial.skewness( 20, 0.5 )\nv = base.dists.binomial.skewness( 10.3, 0.5 )\nv = base.dists.binomial.skewness( 20, 1.1 )\nv = base.dists.binomial.skewness( 20, NaN )\n","base.dists.binomial.stdev":"var v = base.dists.binomial.stdev( 100, 0.1 )\nv = base.dists.binomial.stdev( 20, 0.5 )\nv = base.dists.binomial.stdev( 10.3, 0.5 )\nv = base.dists.binomial.stdev( 20, 1.1 )\nv = base.dists.binomial.stdev( 20, NaN )\n","base.dists.binomial.variance":"var v = base.dists.binomial.variance( 100, 0.1 )\nv = base.dists.binomial.variance( 20, 0.5 )\nv = base.dists.binomial.variance( 10.3, 0.5 )\nv = base.dists.binomial.variance( 20, 1.1 )\nv = base.dists.binomial.variance( 20, NaN )\n","base.dists.cauchy.Cauchy":"var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\ncauchy.x0\ncauchy.gamma\ncauchy.entropy\ncauchy.median\ncauchy.mode\ncauchy.cdf( 0.8 )\ncauchy.logcdf( 1.0 )\ncauchy.logpdf( 1.0 )\ncauchy.pdf( 1.0 )\ncauchy.quantile( 0.8 )\n","base.dists.cauchy.cdf":"var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.cdf.factory":"var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\nvar y = myCDF( 1.0 )\n","base.dists.cauchy.entropy":"var v = base.dists.cauchy.entropy( 10.0, 7.0 )\nv = base.dists.cauchy.entropy( 22.0, 0.5 )\nv = base.dists.cauchy.entropy( 10.3, -0.5 )\n","base.dists.cauchy.logcdf":"var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.logcdf.factory":"var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\nvar y = mylogCDF( 1.0 )\n","base.dists.cauchy.logpdf":"var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.logpdf.factory":"var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.cauchy.median":"var v = base.dists.cauchy.median( 10.0, 5.0 )\nv = base.dists.cauchy.median( 7.0, 0.5 )\nv = base.dists.cauchy.median( 10.3, -0.5 )\n","base.dists.cauchy.mode":"var v = base.dists.cauchy.mode( 10.0, 5.0 )\nv = base.dists.cauchy.mode( 7.0, 0.5 )\nv = base.dists.cauchy.mode( 10.3, -0.5 )\n","base.dists.cauchy.pdf":"var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.pdf.factory":"var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.cauchy.quantile":"var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\ny = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\ny = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\ny = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\ny = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cauchy.quantile.factory":"var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.chi.cdf":"var y = base.dists.chi.cdf( 2.0, 3.0 )\ny = base.dists.chi.cdf( 1.0, 0.5 )\ny = base.dists.chi.cdf( -1.0, 4.0 )\ny = base.dists.chi.cdf( NaN, 1.0 )\ny = base.dists.chi.cdf( 0.0, NaN )\ny = base.dists.chi.cdf( 2.0, -1.0 )\ny = base.dists.chi.cdf( 2.0, 0.0 )\ny = base.dists.chi.cdf( -2.0, 0.0 )\ny = base.dists.chi.cdf( 0.0, 0.0 )\n","base.dists.chi.cdf.factory":"var mycdf = base.dists.chi.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chi.Chi":"var chi = base.dists.chi.Chi( 6.0 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);\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chi.skewness":"var v = base.dists.chi.skewness( 11.0 )\nv = base.dists.chi.skewness( 1.5 )\n","base.dists.chi.stdev":"var v = base.dists.chi.stdev( 11.0 )\nv = base.dists.chi.stdev( 1.5 )\n","base.dists.chi.variance":"var v = base.dists.chi.variance( 11.0 )\nv = base.dists.chi.variance( 1.5 )\n","base.dists.chisquare.cdf":"var y = base.dists.chisquare.cdf( 2.0, 3.0 )\ny = base.dists.chisquare.cdf( 1.0, 0.5 )\ny = base.dists.chisquare.cdf( -1.0, 4.0 )\ny = base.dists.chisquare.cdf( NaN, 1.0 )\ny = base.dists.chisquare.cdf( 0.0, NaN )\ny = base.dists.chisquare.cdf( 2.0, -1.0 )\ny = base.dists.chisquare.cdf( 2.0, 0.0 )\ny = base.dists.chisquare.cdf( -2.0, 0.0 )\ny = base.dists.chisquare.cdf( 0.0, 0.0 )\n","base.dists.chisquare.cdf.factory":"var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chisquare.ChiSquare":"var chisquare = base.dists.chisquare.ChiSquare( 6.0 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base.dists.chisquare.logpdf.factory( 6.0 );\nvar y = myLogPDF( 3.0 )\n","base.dists.chisquare.mean":"var v = base.dists.chisquare.mean( 11.0 )\nv = base.dists.chisquare.mean( 4.5 )\n","base.dists.chisquare.median":"var k = base.dists.chisquare.median( 9.0 )\nk = base.dists.chisquare.median( 2.0 )\n","base.dists.chisquare.mgf":"var y = base.dists.chisquare.mgf( 0.4, 2 )\ny = base.dists.chisquare.mgf( -1.0, 5.0 )\ny = base.dists.chisquare.mgf( 0.0, 10.0 )\n","base.dists.chisquare.mgf.factory":"var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\nvar y = mymgf( 0.2 )\ny = mymgf( 0.4 )\n","base.dists.chisquare.mode":"var v = base.dists.chisquare.mode( 11.0 )\nv = base.dists.chisquare.mode( 1.5 )\n","base.dists.chisquare.pdf":"var y = base.dists.chisquare.pdf( 0.3, 4.0 )\ny = base.dists.chisquare.pdf( 0.7, 0.7 )\ny = base.dists.chisquare.pdf( -1.0, 0.5 )\ny = base.dists.chisquare.pdf( 0.0, NaN )\ny = base.dists.chisquare.pdf( NaN, 2.0 )\ny = base.dists.chisquare.pdf( 2.0, -1.0 )\ny = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.pdf.factory":"var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chisquare.quantile":"var y = base.dists.chisquare.quantile( 0.8, 1.0 )\ny = base.dists.chisquare.quantile( 0.5, 4.0 )\ny = base.dists.chisquare.quantile( 0.8, 0.1 )\ny = base.dists.chisquare.quantile( -0.2, 0.5 )\ny = base.dists.chisquare.quantile( 1.1, 0.5 )\ny = base.dists.chisquare.quantile( NaN, 1.0 )\ny = base.dists.chisquare.quantile( 0.0, NaN )\ny = base.dists.chisquare.quantile( 0.5, -1.0 )\ny = base.dists.chisquare.quantile( 0.3, 0.0 )\ny = base.dists.chisquare.quantile( 0.9, 0.0 )\n","base.dists.chisquare.quantile.factory":"var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chisquare.skewness":"var v = base.dists.chisquare.skewness( 11.0 )\nv = base.dists.chisquare.skewness( 1.5 )\n","base.dists.chisquare.stdev":"var v = base.dists.chisquare.stdev( 11.0 )\nv = base.dists.chisquare.stdev( 1.5 )\n","base.dists.chisquare.variance":"var v = base.dists.chisquare.variance( 11.0 )\nv = base.dists.chisquare.variance( 1.5 )\n","base.dists.cosine.cdf":"var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.cdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.cdf.factory":"var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\nvar y = mycdf( 1.9 )\n","base.dists.cosine.Cosine":"var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\ncosine.mu\ncosine.s\ncosine.kurtosis\ncosine.mean\ncosine.median\ncosine.mode\ncosine.skewness\ncosine.stdev\ncosine.variance\ncosine.cdf( 0.5 )\ncosine.logcdf( 0.5 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2.0, 4.0 )\ny = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.logpdf.factory":"var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\n","base.dists.cosine.mean":"var y = base.dists.cosine.mean( 0.0, 1.0 )\ny = base.dists.cosine.mean( 4.0, 2.0 )\ny = base.dists.cosine.mean( NaN, 1.0 )\ny = base.dists.cosine.mean( 0.0, NaN )\ny = base.dists.cosine.mean( 0.0, 0.0 )\n","base.dists.cosine.median":"var y = base.dists.cosine.median( 0.0, 1.0 )\ny = base.dists.cosine.median( 4.0, 2.0 )\ny = base.dists.cosine.median( NaN, 1.0 )\ny = base.dists.cosine.median( 0.0, NaN )\ny = base.dists.cosine.median( 0.0, 0.0 )\n","base.dists.cosine.mgf":"var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.mgf( 0.5, 0.0, NaN )\ny = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\ny = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n","base.dists.cosine.mgf.factory":"var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\nvar y = mymgf( 1.9 )\n","base.dists.cosine.mode":"var y = base.dists.cosine.mode( 0.0, 1.0 )\ny = base.dists.cosine.mode( 4.0, 2.0 )\ny = base.dists.cosine.mode( NaN, 1.0 )\ny = base.dists.cosine.mode( 0.0, NaN )\ny = base.dists.cosine.mode( 0.0, 0.0 )\n","base.dists.cosine.pdf":"var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\ny = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.pdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.pdf.factory":"var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\nvar y = myPDF( 2.0 )\n","base.dists.cosine.quantile":"var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cosine.quantile( 0.0, 0.0, NaN )\ny = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cosine.quantile.factory":"var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.3 )\n","base.dists.cosine.skewness":"var y = base.dists.cosine.skewness( 0.0, 1.0 )\ny = base.dists.cosine.skewness( 4.0, 2.0 )\ny = base.dists.cosine.skewness( NaN, 1.0 )\ny = base.dists.cosine.skewness( 0.0, NaN )\ny = base.dists.cosine.skewness( 0.0, 0.0 )\n","base.dists.cosine.stdev":"var y = base.dists.cosine.stdev( 0.0, 1.0 )\ny = base.dists.cosine.stdev( 4.0, 2.0 )\ny = base.dists.cosine.stdev( NaN, 1.0 )\ny = base.dists.cosine.stdev( 0.0, NaN )\ny = base.dists.cosine.stdev( 0.0, 0.0 )\n","base.dists.cosine.variance":"var y = base.dists.cosine.variance( 0.0, 1.0 )\ny = base.dists.cosine.variance( 4.0, 2.0 )\ny = base.dists.cosine.variance( NaN, 1.0 )\ny = base.dists.cosine.variance( 0.0, NaN )\ny = base.dists.cosine.variance( 0.0, 0.0 )\n","base.dists.degenerate.cdf":"var y = base.dists.degenerate.cdf( 2.0, 3.0 )\ny = base.dists.degenerate.cdf( 4.0, 3.0 )\ny = base.dists.degenerate.cdf( 3.0, 3.0 )\ny = base.dists.degenerate.cdf( NaN, 0.0 )\ny = base.dists.degenerate.cdf( 0.0, NaN )\n","base.dists.degenerate.cdf.factory":"var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 6.0 )\n","base.dists.degenerate.Degenerate":"var degenerate = base.dists.degenerate.Degenerate( 2.0 );\ndegenerate.mu\ndegenerate.entropy\ndegenerate.mean\ndegenerate.mode\ndegenerate.median\ndegenerate.stdev\ndegenerate.variance\ndegenerate.cdf( 0.5 )\ndegenerate.logcdf( 2.5 )\ndegenerate.logpdf( 0.5 )\ndegenerate.logpmf( 2.5 )\ndegenerate.mgf( 0.2 )\ndegenerate.pdf( 2.0 )\ndegenerate.pmf( 2.0 )\ndegenerate.quantile( 0.7 )\n","base.dists.degenerate.entropy":"var v = base.dists.degenerate.entropy( 20.0 )\nv = base.dists.degenerate.entropy( -10.0 )\n","base.dists.degenerate.logcdf":"var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\ny = base.dists.degenerate.logcdf( 4.0, 3.0 )\ny = base.dists.degenerate.logcdf( 3.0, 3.0 )\ny = base.dists.degenerate.logcdf( NaN, 0.0 )\ny = base.dists.degenerate.logcdf( 0.0, NaN )\n","base.dists.degenerate.logcdf.factory":"var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 6.0 )\n","base.dists.degenerate.logpdf":"var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\ny = base.dists.degenerate.logpdf( 3.0, 3.0 )\ny = base.dists.degenerate.logpdf( NaN, 0.0 )\ny = base.dists.degenerate.logpdf( 0.0, NaN )\n","base.dists.degenerate.logpdf.factory":"var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.degenerate.logpmf":"var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\ny = base.dists.degenerate.logpmf( 3.0, 3.0 )\ny = base.dists.degenerate.logpmf( NaN, 0.0 )\ny = base.dists.degenerate.logpmf( 0.0, NaN )\n","base.dists.degenerate.logpmf.factory":"var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\nvar y = mylogPMF( 10.0 )\n","base.dists.degenerate.mean":"var v = base.dists.degenerate.mean( 20.0 )\nv = base.dists.degenerate.mean( -10.0 )\n","base.dists.degenerate.median":"var v = base.dists.degenerate.median( 20.0 )\nv = base.dists.degenerate.median( -10.0 )\n","base.dists.degenerate.mgf":"var y = base.dists.degenerate.mgf( 1.0, 1.0 )\ny = base.dists.degenerate.mgf( 2.0, 3.0 )\ny = base.dists.degenerate.mgf( NaN, 0.0 )\ny = base.dists.degenerate.mgf( 0.0, NaN )\n","base.dists.degenerate.mgf.factory":"var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\nvar y = myMGF( 0.1 )\n","base.dists.degenerate.mode":"var v = base.dists.degenerate.mode( 20.0 )\nv = base.dists.degenerate.mode( -10.0 )\n","base.dists.degenerate.pdf":"var y = base.dists.degenerate.pdf( 2.0, 3.0 )\ny = base.dists.degenerate.pdf( 3.0, 3.0 )\ny = base.dists.degenerate.pdf( NaN, 0.0 )\ny = base.dists.degenerate.pdf( 0.0, NaN )\n","base.dists.degenerate.pdf.factory":"var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\nvar y = myPDF( 10.0 )\n","base.dists.degenerate.pmf":"var y = base.dists.degenerate.pmf( 2.0, 3.0 )\ny = base.dists.degenerate.pmf( 3.0, 3.0 )\ny = base.dists.degenerate.pmf( NaN, 0.0 )\ny = base.dists.degenerate.pmf( 0.0, NaN )\n","base.dists.degenerate.pmf.factory":"var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\nvar y = myPMF( 10.0 )\n","base.dists.degenerate.quantile":"var y = base.dists.degenerate.quantile( 0.5, 2.0 )\ny = base.dists.degenerate.quantile( 0.9, 4.0 )\ny = base.dists.degenerate.quantile( 1.1, 0.0 )\ny = base.dists.degenerate.quantile( -0.2, 0.0 )\ny = base.dists.degenerate.quantile( NaN, 0.0 )\ny = base.dists.degenerate.quantile( 0.0, NaN )\n","base.dists.degenerate.quantile.factory":"var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.degenerate.stdev":"var v = base.dists.degenerate.stdev( 20.0 )\nv = base.dists.degenerate.stdev( -10.0 )\n","base.dists.degenerate.variance":"var v = base.dists.degenerate.variance( 20.0 )\nv = base.dists.degenerate.variance( -10.0 )\n","base.dists.discreteUniform.cdf":"var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.cdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n","base.dists.discreteUniform.cdf.factory":"var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.discreteUniform.DiscreteUniform":"var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\ndiscreteUniform.a\ndiscreteUniform.b\ndiscreteUniform.entropy\ndiscreteUniform.kurtosis\ndiscreteUniform.mean\ndiscreteUniform.median\ndiscreteUniform.skewness\ndiscreteUniform.stdev\ndiscreteUniform.variance\ndiscreteUniform.cdf( 0.8 )\ndiscreteUniform.logcdf( 0.5 )\ndiscreteUniform.logpmf( 1.0 )\ndiscreteUniform.mgf( 0.8 )\ndiscreteUniform.pmf( 0.0 )\ndiscreteUniform.quantile( 0.8 )\n","base.dists.discreteUniform.kurtosis":"var v = base.dists.discreteUniform.kurtosis( 0, 1 )\nv = base.dists.discreteUniform.kurtosis( 4, 12 )\nv = base.dists.discreteUniform.kurtosis( -4, 8 )\n","base.dists.discreteUniform.logcdf":"var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\ny 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base.dists.discreteUniform.pmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.pmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.pmf.factory":"var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\nvar y = myPMF( 7.0 )\ny = myPMF( 5.0 )\n","base.dists.discreteUniform.quantile":"var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\ny = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\ny = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\ny = base.dists.discreteUniform.quantile( NaN, -2, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\ny = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n","base.dists.discreteUniform.quantile.factory":"var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\nvar y = myQuantile( 0.8 )\n","base.dists.discreteUniform.skewness":"var v = base.dists.discreteUniform.skewness( -2, 2 )\nv = base.dists.discreteUniform.skewness( 4, 12 )\nv = base.dists.discreteUniform.skewness( 2, 8 )\n","base.dists.discreteUniform.stdev":"var v = base.dists.discreteUniform.stdev( 0, 1 )\nv = base.dists.discreteUniform.stdev( 4, 12 )\nv = base.dists.discreteUniform.stdev( 2, 8 )\n","base.dists.discreteUniform.variance":"var v = base.dists.discreteUniform.variance( 0, 1 )\nv = base.dists.discreteUniform.variance( 4, 12 )\nv = base.dists.discreteUniform.variance( 2, 8 )\n","base.dists.erlang.cdf":"var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 3, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\ny = base.dists.erlang.cdf( -1.0, 2, 2.0 )\ny = base.dists.erlang.cdf( PINF, 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base.dists.erlang.kurtosis( 8, 2.0 )\n","base.dists.erlang.logpdf":"var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.logpdf( NaN, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, 1, NaN )\ny = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n","base.dists.erlang.logpdf.factory":"var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\ny = myLogPDF( 7.0 )\n","base.dists.erlang.mean":"var v = base.dists.erlang.mean( 1, 1.0 )\nv = base.dists.erlang.mean( 4, 12.0 )\nv = base.dists.erlang.mean( 8, 2.0 )\n","base.dists.erlang.mgf":"var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\ny = base.dists.erlang.mgf( 2.0, 2, 3.0 )\ny = base.dists.erlang.mgf( -1.0, 2, 2.0 )\ny = base.dists.erlang.mgf( NaN, 1, 1.0 )\ny = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.mgf( 0.0, 1, NaN )\ny = base.dists.erlang.mgf( 0.2, -2, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 1, 0.0 )\ny = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n","base.dists.erlang.mgf.factory":"var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\nvar y = myMGF( 0.2 )\ny = myMGF( -0.5 )\n","base.dists.erlang.mode":"var v = base.dists.erlang.mode( 1, 1.0 )\nv = base.dists.erlang.mode( 4, 12.0 )\nv = base.dists.erlang.mode( 8, 2.0 )\n","base.dists.erlang.pdf":"var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.pdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.pdf( NaN, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.pdf( 0.0, 1, NaN )\ny = base.dists.erlang.pdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.5, 0.5 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1.0 )\nv = base.dists.erlang.skewness( 4, 12.0 )\nv = base.dists.erlang.skewness( 8, 2.0 )\n","base.dists.erlang.stdev":"var v = base.dists.erlang.stdev( 1, 1.0 )\nv = base.dists.erlang.stdev( 4, 12.0 )\nv = base.dists.erlang.stdev( 8, 2.0 )\n","base.dists.erlang.variance":"var v = base.dists.erlang.variance( 1, 1.0 )\nv = base.dists.erlang.variance( 4, 12.0 )\nv = base.dists.erlang.variance( 8, 2.0 )\n","base.dists.exponential.cdf":"var y = base.dists.exponential.cdf( 2.0, 0.1 )\ny = base.dists.exponential.cdf( 1.0, 2.0 )\ny = base.dists.exponential.cdf( -1.0, 4.0 )\ny = base.dists.exponential.cdf( NaN, 1.0 )\ny = base.dists.exponential.cdf( 0.0, NaN )\ny = base.dists.exponential.cdf( 2.0, -1.0 )\n","base.dists.exponential.cdf.factory":"var myCDF = base.dists.exponential.cdf.factory( 0.5 );\nvar y = myCDF( 3.0 )\n","base.dists.exponential.entropy":"var v = base.dists.exponential.entropy( 11.0 )\nv = base.dists.exponential.entropy( 4.5 )\n","base.dists.exponential.Exponential":"var exponential = base.dists.exponential.Exponential( 6.0 );\nexponential.lambda\nexponential.entropy\nexponential.kurtosis\nexponential.mean\nexponential.median\nexponential.mode\nexponential.skewness\nexponential.stdev\nexponential.variance\nexponential.cdf( 1.0 )\nexponential.logcdf( 1.0 )\nexponential.logpdf( 1.5 )\nexponential.mgf( -0.5 )\nexponential.pdf( 1.5 )\nexponential.quantile( 0.5 )\n","base.dists.exponential.kurtosis":"var v = base.dists.exponential.kurtosis( 11.0 )\nv = base.dists.exponential.kurtosis( 4.5 )\n","base.dists.exponential.logcdf":"var y = base.dists.exponential.logcdf( 2.0, 0.1 )\ny = base.dists.exponential.logcdf( 1.0, 2.0 )\ny = base.dists.exponential.logcdf( -1.0, 4.0 )\ny = base.dists.exponential.logcdf( NaN, 1.0 )\ny = base.dists.exponential.logcdf( 0.0, NaN )\ny = base.dists.exponential.logcdf( 2.0, -1.0 )\n","base.dists.exponential.logcdf.factory":"var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\nvar y = mylogCDF( 3.0 )\n","base.dists.exponential.logpdf":"var y = base.dists.exponential.logpdf( 0.3, 4.0 )\ny = base.dists.exponential.logpdf( 2.0, 0.7 )\ny = base.dists.exponential.logpdf( -1.0, 0.5 )\ny = base.dists.exponential.logpdf( 0, NaN )\ny = base.dists.exponential.logpdf( NaN, 2.0 )\ny = base.dists.exponential.logpdf( 2.0, -1.0 )\n","base.dists.exponential.logpdf.factory":"var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\nvar y = mylogpdf( 3.0 )\n","base.dists.exponential.mean":"var v = base.dists.exponential.mean( 11.0 )\nv = base.dists.exponential.mean( 4.5 )\n","base.dists.exponential.median":"var v = base.dists.exponential.median( 11.0 )\nv = base.dists.exponential.median( 4.5 )\n","base.dists.exponential.mgf":"var v = base.dists.exponential.mgf( 2.0, 3.0 )\nv = base.dists.exponential.mgf( 0.4, 1.2 )\nv = base.dists.exponential.mgf( 0.8, 1.6 )\nv = base.dists.exponential.mgf( 4.0, 3.0 )\nv = base.dists.exponential.mgf( NaN, 3.0 )\nv = base.dists.exponential.mgf( 2.0, NaN )\n","base.dists.exponential.mgf.factory":"var myMGF = base.dists.exponential.mgf.factory( 4.0 );\nvar y = myMGF( 3.0 )\ny = myMGF( 0.5 )\n","base.dists.exponential.mode":"var v = base.dists.exponential.mode( 11.0 )\nv = base.dists.exponential.mode( 4.5 )\n","base.dists.exponential.pdf":"var y = base.dists.exponential.pdf( 0.3, 4.0 )\ny = base.dists.exponential.pdf( 2.0, 0.7 )\ny = base.dists.exponential.pdf( -1.0, 0.5 )\ny = base.dists.exponential.pdf( 0, NaN )\ny = base.dists.exponential.pdf( NaN, 2.0 )\ny = base.dists.exponential.pdf( 2.0, -1.0 )\n","base.dists.exponential.pdf.factory":"var myPDF = base.dists.exponential.pdf.factory( 0.5 );\nvar y = myPDF( 3.0 )\n","base.dists.exponential.quantile":"var y = base.dists.exponential.quantile( 0.8, 1.0 )\ny = base.dists.exponential.quantile( 0.5, 4.0 )\ny = base.dists.exponential.quantile( 0.5, 0.1 )\ny = base.dists.exponential.quantile( -0.2, 0.1 )\ny = base.dists.exponential.quantile( NaN, 1.0 )\ny = base.dists.exponential.quantile( 0.0, NaN )\ny = base.dists.exponential.quantile( 0.5, -1.0 )\n","base.dists.exponential.quantile.factory":"var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.exponential.skewness":"var v = base.dists.exponential.skewness( 11.0 )\nv = base.dists.exponential.skewness( 4.5 )\n","base.dists.exponential.stdev":"var v = base.dists.exponential.stdev( 9.0 )\nv = base.dists.exponential.stdev( 1.0 )\n","base.dists.exponential.variance":"var v = base.dists.exponential.variance( 9.0 )\nv = base.dists.exponential.variance( 1.0 )\n","base.dists.f.cdf":"var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\nvar y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\nvar y = base.dists.f.cdf( PINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NaN, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 0.0, NaN, 1.0 )\nvar y = base.dists.f.cdf( 0.0, 1.0, NaN )\nvar y = base.dists.f.cdf( 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base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n","base.dists.frechet.logcdf":"var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.logcdf.factory":"var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 7.0 )\n","base.dists.frechet.logpdf":"var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\ny = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\ny = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\ny = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\ny = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n","base.dists.frechet.logpdf.factory":"var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\nvar y = mylogPDF( 10.0 )\ny = mylogPDF( 2.0 )\n","base.dists.frechet.mean":"var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mean( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mean( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mean( 1.0, 1.0, NaN )\n","base.dists.frechet.median":"var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.median( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.median( NaN, 1.0, 0.0 )\ny = base.dists.frechet.median( 1.0, NaN, 0.0 )\ny = base.dists.frechet.median( 1.0, 1.0, NaN )\n","base.dists.frechet.mode":"var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mode( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mode( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mode( 1.0, 1.0, NaN )\n","base.dists.frechet.pdf":"var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, NaN )\ny = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n","base.dists.frechet.pdf.factory":"var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.frechet.quantile":"var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\ny = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\ny = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\ny = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\ny = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.quantile.factory":"var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.2 )\n","base.dists.frechet.skewness":"var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\ny = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\ny = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n","base.dists.frechet.stdev":"var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\ny = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\ny = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n","base.dists.frechet.variance":"var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.variance( NaN, 1.0, 0.0 )\ny = base.dists.frechet.variance( 1.0, NaN, 0.0 )\ny = base.dists.frechet.variance( 1.0, 1.0, NaN )\n","base.dists.gamma.cdf":"var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.cdf.factory":"var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 6.0 )\ny = myCDF( 2.0 )\n","base.dists.gamma.entropy":"var v = base.dists.gamma.entropy( 1.0, 1.0 )\nv = base.dists.gamma.entropy( 4.0, 12.0 )\nv = base.dists.gamma.entropy( 8.0, 2.0 )\n","base.dists.gamma.Gamma":"var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\ngamma.alpha\ngamma.beta\ngamma.entropy\ngamma.kurtosis\ngamma.mean\ngamma.mode\ngamma.skewness\ngamma.stdev\ngamma.variance\ngamma.cdf( 0.8 )\ngamma.logcdf( 0.8 )\ngamma.logpdf( 1.0 )\ngamma.mgf( -0.5 )\ngamma.pdf( 1.0 )\ngamma.quantile( 0.8 )\n","base.dists.gamma.kurtosis":"var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\nv = base.dists.gamma.kurtosis( 4.0, 12.0 )\nv = base.dists.gamma.kurtosis( 8.0, 2.0 )\n","base.dists.gamma.logcdf":"var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.logcdf.factory":"var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\nvar y = mylogCDF( 2.0 )\n","base.dists.gamma.logpdf":"var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.logpdf.factory":"var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.gamma.mean":"var v = base.dists.gamma.mean( 1.0, 1.0 )\nv = base.dists.gamma.mean( 4.0, 12.0 )\nv = base.dists.gamma.mean( 8.0, 2.0 )\n","base.dists.gamma.mgf":"var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\ny = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\ny = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.mgf( 0.0, 1.0, NaN )\ny = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\ny = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.mgf.factory":"var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.gamma.mode":"var v = base.dists.gamma.mode( 1.0, 1.0 )\nv = base.dists.gamma.mode( 4.0, 12.0 )\nv = base.dists.gamma.mode( 8.0, 2.0 )\n","base.dists.gamma.pdf":"var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.pdf( 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)\n","base.dists.gamma.quantile.factory":"var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.gamma.skewness":"var v = base.dists.gamma.skewness( 1.0, 1.0 )\nv = base.dists.gamma.skewness( 4.0, 12.0 )\nv = base.dists.gamma.skewness( 8.0, 2.0 )\n","base.dists.gamma.stdev":"var v = base.dists.gamma.stdev( 1.0, 1.0 )\nv = base.dists.gamma.stdev( 4.0, 12.0 )\nv = base.dists.gamma.stdev( 8.0, 2.0 )\n","base.dists.gamma.variance":"var v = base.dists.gamma.variance( 1.0, 1.0 )\nv = base.dists.gamma.variance( 4.0, 12.0 )\nv = base.dists.gamma.variance( 8.0, 2.0 )\n","base.dists.geometric.cdf":"var y = base.dists.geometric.cdf( 2.0, 0.5 )\ny = base.dists.geometric.cdf( 2.0, 0.1 )\ny = base.dists.geometric.cdf( -1.0, 4.0 )\ny = base.dists.geometric.cdf( NaN, 0.5 )\ny = base.dists.geometric.cdf( 0.0, NaN )\ny = base.dists.geometric.cdf( 2.0, 1.4 )\n","base.dists.geometric.cdf.factory":"var mycdf = base.dists.geometric.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.geometric.entropy":"var v = base.dists.geometric.entropy( 0.1 )\nv = base.dists.geometric.entropy( 0.5 )\n","base.dists.geometric.Geometric":"var geometric = base.dists.geometric.Geometric( 0.6 );\ngeometric.p\ngeometric.entropy\ngeometric.kurtosis\ngeometric.mean\ngeometric.median\ngeometric.mode\ngeometric.skewness\ngeometric.stdev\ngeometric.variance\ngeometric.cdf( 3.0 )\ngeometric.logcdf( 3.0 )\ngeometric.logpmf( 4.0 )\ngeometric.mgf( 0.5 )\ngeometric.pmf( 2.0 )\ngeometric.quantile( 0.7 )\n","base.dists.geometric.kurtosis":"var v = base.dists.geometric.kurtosis( 0.1 )\nv = base.dists.geometric.kurtosis( 0.5 )\n","base.dists.geometric.logcdf":"var y = base.dists.geometric.logcdf( 2.0, 0.5 )\ny = base.dists.geometric.logcdf( 2.0, 0.1 )\ny = base.dists.geometric.logcdf( -1.0, 4.0 )\ny = base.dists.geometric.logcdf( NaN, 0.5 )\ny = base.dists.geometric.logcdf( 0.0, NaN )\ny = base.dists.geometric.logcdf( 2.0, 1.4 )\n","base.dists.geometric.logcdf.factory":"var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 1.0 )\n","base.dists.geometric.logpmf":"var y = base.dists.geometric.logpmf( 4.0, 0.3 )\ny = base.dists.geometric.logpmf( 2.0, 0.7 )\ny = base.dists.geometric.logpmf( -1.0, 0.5 )\ny = base.dists.geometric.logpmf( 0.0, NaN )\ny = base.dists.geometric.logpmf( NaN, 0.5 )\ny = base.dists.geometric.logpmf( 2.0, 1.5 )\n","base.dists.geometric.logpmf.factory":"var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.geometric.mean":"var v = base.dists.geometric.mean( 0.1 )\nv = base.dists.geometric.mean( 0.5 )\n","base.dists.geometric.median":"var v = base.dists.geometric.median( 0.1 )\nv = base.dists.geometric.median( 0.5 )\n","base.dists.geometric.mgf":"var y = base.dists.geometric.mgf( 0.2, 0.5 )\ny = base.dists.geometric.mgf( 0.4, 0.5 )\ny = base.dists.geometric.mgf( 0.8, 0.5 )\ny = base.dists.geometric.mgf( NaN, 0.0 )\ny = base.dists.geometric.mgf( 0.0, NaN )\ny = base.dists.geometric.mgf( -2.0, -1.0 )\ny = base.dists.geometric.mgf( 0.2, 2.0 )\n","base.dists.geometric.mgf.factory":"var mymgf = base.dists.geometric.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.geometric.mode":"var v = base.dists.geometric.mode( 0.1 )\nv = base.dists.geometric.mode( 0.5 )\n","base.dists.geometric.pmf":"var y = base.dists.geometric.pmf( 4.0, 0.3 )\ny = base.dists.geometric.pmf( 2.0, 0.7 )\ny = base.dists.geometric.pmf( -1.0, 0.5 )\ny = base.dists.geometric.pmf( 0.0, NaN )\ny = base.dists.geometric.pmf( NaN, 0.5 )\ny = base.dists.geometric.pmf( 2.0, 1.5 )\n","base.dists.geometric.pmf.factory":"var mypmf = base.dists.geometric.pmf.factory( 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.geometric.quantile":"var y = base.dists.geometric.quantile( 0.8, 0.4 )\ny = base.dists.geometric.quantile( 0.5, 0.4 )\ny = base.dists.geometric.quantile( 0.9, 0.1 )\ny = base.dists.geometric.quantile( -0.2, 0.1 )\ny = base.dists.geometric.quantile( NaN, 0.8 )\ny = base.dists.geometric.quantile( 0.4, NaN )\ny = base.dists.geometric.quantile( 0.5, -1.0 )\ny = base.dists.geometric.quantile( 0.5, 1.5 )\n","base.dists.geometric.quantile.factory":"var myquantile = base.dists.geometric.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.geometric.skewness":"var v = base.dists.geometric.skewness( 0.1 )\nv = base.dists.geometric.skewness( 0.5 )\n","base.dists.geometric.stdev":"var v = base.dists.geometric.stdev( 0.1 )\nv = base.dists.geometric.stdev( 0.5 )\n","base.dists.geometric.variance":"var v = base.dists.geometric.variance( 0.1 )\nv = base.dists.geometric.variance( 0.5 )\n","base.dists.gumbel.cdf":"var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.cdf.factory":"var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.gumbel.entropy":"var y = base.dists.gumbel.entropy( 0.0, 1.0 )\ny = base.dists.gumbel.entropy( 4.0, 2.0 )\ny = base.dists.gumbel.entropy( NaN, 1.0 )\ny = base.dists.gumbel.entropy( 0.0, NaN )\ny = base.dists.gumbel.entropy( 0.0, 0.0 )\n","base.dists.gumbel.Gumbel":"var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\ngumbel.mu\ngumbel.beta\ngumbel.entropy\ngumbel.kurtosis\ngumbel.mean\ngumbel.median\ngumbel.mode\ngumbel.skewness\ngumbel.stdev\ngumbel.variance\ngumbel.cdf( 0.8 )\ngumbel.logcdf( 0.8 )\ngumbel.logpdf( 1.0 )\ngumbel.mgf( 0.2 )\ngumbel.pdf( 1.0 )\ngumbel.quantile( 0.8 )\n","base.dists.gumbel.kurtosis":"var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\ny = base.dists.gumbel.kurtosis( 4.0, 2.0 )\ny = base.dists.gumbel.kurtosis( NaN, 1.0 )\ny = base.dists.gumbel.kurtosis( 0.0, NaN )\ny = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n","base.dists.gumbel.logcdf":"var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.logcdf.factory":"var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\nvar y = myLCDF( 10.0 )\ny = myLCDF( 2.0 )\n","base.dists.gumbel.logpdf":"var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.logpdf.factory":"var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\ny = mylogpdf( 12.0 )\n","base.dists.gumbel.mean":"var y = base.dists.gumbel.mean( 0.0, 1.0 )\ny = base.dists.gumbel.mean( 4.0, 2.0 )\ny = base.dists.gumbel.mean( NaN, 1.0 )\ny = base.dists.gumbel.mean( 0.0, NaN )\ny = base.dists.gumbel.mean( 0.0, 0.0 )\n","base.dists.gumbel.median":"var y = base.dists.gumbel.median( 0.0, 1.0 )\ny = base.dists.gumbel.median( 4.0, 2.0 )\ny = base.dists.gumbel.median( NaN, 1.0 )\ny = base.dists.gumbel.median( 0.0, NaN )\ny = base.dists.gumbel.median( 0.0, 0.0 )\n","base.dists.gumbel.mgf":"var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.mgf.factory":"var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\nvar y = myMGF( -1.5 )\ny = myMGF( -1.0 )\n","base.dists.gumbel.mode":"var y = base.dists.gumbel.mode( 0.0, 1.0 )\ny = base.dists.gumbel.mode( 4.0, 2.0 )\ny = base.dists.gumbel.mode( NaN, 1.0 )\ny = base.dists.gumbel.mode( 0.0, NaN )\ny = base.dists.gumbel.mode( 0.0, 0.0 )\n","base.dists.gumbel.pdf":"var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.pdf.factory":"var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 12.0 )\n","base.dists.gumbel.quantile":"var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\ny = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\ny = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n","base.dists.gumbel.quantile.factory":"var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.7 )\n","base.dists.gumbel.skewness":"var y = base.dists.gumbel.skewness( 0.0, 1.0 )\ny = base.dists.gumbel.skewness( 4.0, 2.0 )\ny = base.dists.gumbel.skewness( NaN, 1.0 )\ny = base.dists.gumbel.skewness( 0.0, NaN )\ny = base.dists.gumbel.skewness( 0.0, 0.0 )\n","base.dists.gumbel.stdev":"var y = base.dists.gumbel.stdev( 0.0, 1.0 )\ny = base.dists.gumbel.stdev( 4.0, 2.0 )\ny = base.dists.gumbel.stdev( NaN, 1.0 )\ny = base.dists.gumbel.stdev( 0.0, NaN )\ny = base.dists.gumbel.stdev( 0.0, 0.0 )\n","base.dists.gumbel.variance":"var y = base.dists.gumbel.variance( 0.0, 1.0 )\ny = base.dists.gumbel.variance( 4.0, 2.0 )\ny = base.dists.gumbel.variance( NaN, 1.0 )\ny = base.dists.gumbel.variance( 0.0, NaN )\ny = base.dists.gumbel.variance( 0.0, 0.0 )\n","base.dists.hypergeometric.cdf":"var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\ny = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.cdf.factory":"var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\nvar y = myCDF( 4.0 )\ny = myCDF( 1.0 )\n","base.dists.hypergeometric.Hypergeometric":"var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\nhypergeometric.N\nhypergeometric.K\nhypergeometric.n\nhypergeometric.kurtosis\nhypergeometric.mean\nhypergeometric.mode\nhypergeometric.skewness\nhypergeometric.stdev\nhypergeometric.variance\nhypergeometric.cdf( 2.9 )\nhypergeometric.logpmf( 10 )\nhypergeometric.pmf( 10 )\nhypergeometric.quantile( 0.8 )\n","base.dists.hypergeometric.kurtosis":"var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\nv = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\nv = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\nv = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n","base.dists.hypergeometric.logpmf":"var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.logpmf.factory":"var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\nvar y = mylogPMF( 4.0 )\ny = mylogPMF( 1.0 )\n","base.dists.hypergeometric.mean":"var v = base.dists.hypergeometric.mean( 16, 11, 4 )\nv = base.dists.hypergeometric.mean( 2, 1, 1 )\nv = base.dists.hypergeometric.mean( 10, 5, 12 )\nv = base.dists.hypergeometric.mean( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mean( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mean( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mean( NaN, 10, 4 )\nv = base.dists.hypergeometric.mean( 20, NaN, 4 )\nv = base.dists.hypergeometric.mean( 20, 10, NaN )\n","base.dists.hypergeometric.mode":"var v = base.dists.hypergeometric.mode( 16, 11, 4 )\nv = base.dists.hypergeometric.mode( 2, 1, 1 )\nv = base.dists.hypergeometric.mode( 10, 5, 12 )\nv = base.dists.hypergeometric.mode( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mode( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mode( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mode( NaN, 10, 4 )\nv = base.dists.hypergeometric.mode( 20, NaN, 4 )\nv = base.dists.hypergeometric.mode( 20, 10, NaN )\n","base.dists.hypergeometric.pmf":"var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.pmf.factory":"var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\nvar y = myPMF( 4.0 )\ny = myPMF( 1.0 )\n","base.dists.hypergeometric.quantile":"var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\ny = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\ny = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n","base.dists.hypergeometric.quantile.factory":"var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.hypergeometric.skewness":"var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\nv = base.dists.hypergeometric.skewness( 4, 2, 2 )\nv = base.dists.hypergeometric.skewness( 10, 5, 12 )\nv = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\nv = base.dists.hypergeometric.skewness( NaN, 10, 4 )\nv = base.dists.hypergeometric.skewness( 20, NaN, 4 )\nv = base.dists.hypergeometric.skewness( 20, 10, NaN )\n","base.dists.hypergeometric.stdev":"var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\nv = base.dists.hypergeometric.stdev( 2, 1, 1 )\nv = base.dists.hypergeometric.stdev( 10, 5, 12 )\nv = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\nv = base.dists.hypergeometric.stdev( NaN, 10, 4 )\nv = base.dists.hypergeometric.stdev( 20, NaN, 4 )\nv = base.dists.hypergeometric.stdev( 20, 10, NaN )\n","base.dists.hypergeometric.variance":"var v = base.dists.hypergeometric.variance( 16, 11, 4 )\nv = base.dists.hypergeometric.variance( 2, 1, 1 )\nv = base.dists.hypergeometric.variance( 10, 5, 12 )\nv = base.dists.hypergeometric.variance( 10.3, 10, 4 )\nv = base.dists.hypergeometric.variance( 10, 5.5, 4 )\nv = base.dists.hypergeometric.variance( 10, 5, 4.5 )\nv = base.dists.hypergeometric.variance( NaN, 10, 4 )\nv = base.dists.hypergeometric.variance( 20, NaN, 4 )\nv = base.dists.hypergeometric.variance( 20, 10, NaN )\n","base.dists.invgamma.cdf":"var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.cdf.factory":"var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 0.5 )\ny = myCDF( 2.0 )\n","base.dists.invgamma.entropy":"var v = base.dists.invgamma.entropy( 1.0, 1.0 )\nv = base.dists.invgamma.entropy( 4.0, 12.0 )\nv = base.dists.invgamma.entropy( 8.0, 2.0 )\n","base.dists.invgamma.InvGamma":"var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\ninvgamma.alpha\ninvgamma.beta\ninvgamma.entropy\ninvgamma.kurtosis\ninvgamma.mean\ninvgamma.mode\ninvgamma.skewness\ninvgamma.stdev\ninvgamma.variance\ninvgamma.cdf( 0.8 )\ninvgamma.pdf( 1.0 )\ninvgamma.logpdf( 1.0 )\ninvgamma.quantile( 0.8 )\n","base.dists.invgamma.kurtosis":"var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\nv = base.dists.invgamma.kurtosis( 6.0, 12.0 )\nv = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n","base.dists.invgamma.logpdf":"var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.logpdf.factory":"var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.invgamma.mean":"var v = base.dists.invgamma.mean( 4.0, 12.0 )\nv = base.dists.invgamma.mean( 8.0, 2.0 )\n","base.dists.invgamma.mode":"var v = base.dists.invgamma.mode( 1.0, 1.0 )\nv = base.dists.invgamma.mode( 4.0, 12.0 )\nv = base.dists.invgamma.mode( 8.0, 2.0 )\n","base.dists.invgamma.pdf":"var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.pdf.factory":"var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 2.0 )\n","base.dists.invgamma.quantile":"var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\ny = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n","base.dists.invgamma.quantile.factory":"var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.invgamma.skewness":"var v = base.dists.invgamma.skewness( 4.0, 12.0 )\nv = base.dists.invgamma.skewness( 8.0, 2.0 )\n","base.dists.invgamma.stdev":"var v = base.dists.invgamma.stdev( 5.0, 7.0 )\nv = base.dists.invgamma.stdev( 4.0, 12.0 )\nv = base.dists.invgamma.stdev( 8.0, 2.0 )\n","base.dists.invgamma.variance":"var v = base.dists.invgamma.variance( 5.0, 7.0 )\nv = base.dists.invgamma.variance( 4.0, 12.0 )\nv = base.dists.invgamma.variance( 8.0, 2.0 )\n","base.dists.kumaraswamy.cdf":"var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.cdf.factory":"var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.kumaraswamy.Kumaraswamy":"var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 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base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logcdf.factory":"var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.kumaraswamy.logpdf":"var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logpdf.factory":"var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.kumaraswamy.mean":"var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mean( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n","base.dists.kumaraswamy.median":"var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\nv = base.dists.kumaraswamy.median( 4.0, 12.0 )\nv = base.dists.kumaraswamy.median( 16.0, 8.0 )\n","base.dists.kumaraswamy.mode":"var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mode( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n","base.dists.kumaraswamy.pdf":"var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.pdf.factory":"var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.kumaraswamy.quantile":"var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.quantile.factory":"var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.3 )\n","base.dists.kumaraswamy.skewness":"var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\nv = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\nv = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n","base.dists.kumaraswamy.stdev":"var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\nv = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\nv = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n","base.dists.kumaraswamy.variance":"var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\nv = base.dists.kumaraswamy.variance( 4.0, 12.0 )\nv = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n","base.dists.laplace.cdf":"var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 2, NaN, 1.0 )\ny = base.dists.laplace.cdf( 2.0, 0.0, NaN )\ny = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.cdf.factory":"var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.laplace.entropy":"var y = base.dists.laplace.entropy( 0.0, 1.0 )\ny = base.dists.laplace.entropy( 4.0, 2.0 )\ny = base.dists.laplace.entropy( NaN, 1.0 )\ny = base.dists.laplace.entropy( 0.0, NaN )\ny = base.dists.laplace.entropy( 0.0, 0.0 )\n","base.dists.laplace.kurtosis":"var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\ny = base.dists.laplace.kurtosis( 4.0, 2.0 )\ny = base.dists.laplace.kurtosis( NaN, 1.0 )\ny = base.dists.laplace.kurtosis( 0.0, NaN )\ny = base.dists.laplace.kurtosis( 0.0, 0.0 )\n","base.dists.laplace.Laplace":"var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\nlaplace.mu\nlaplace.b\nlaplace.entropy\nlaplace.kurtosis\nlaplace.mean\nlaplace.median\nlaplace.mode\nlaplace.skewness\nlaplace.stdev\nlaplace.variance\nlaplace.cdf( 0.8 )\nlaplace.logcdf( 0.8 )\nlaplace.logpdf( 1.0 )\nlaplace.mgf( 0.2 )\nlaplace.pdf( 2.0 )\nlaplace.quantile( 0.9 )\n","base.dists.laplace.logcdf":"var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 2, NaN, 1.0 )\ny = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\ny = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.logcdf.factory":"var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 2.0 )\n","base.dists.laplace.logpdf":"var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\ny = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.logpdf.factory":"var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.laplace.mean":"var y = base.dists.laplace.mean( 0.0, 1.0 )\ny = base.dists.laplace.mean( 4.0, 2.0 )\ny = base.dists.laplace.mean( NaN, 1.0 )\ny = base.dists.laplace.mean( 0.0, NaN )\ny = base.dists.laplace.mean( 0.0, 0.0 )\n","base.dists.laplace.median":"var y = base.dists.laplace.median( 0.0, 1.0 )\ny = base.dists.laplace.median( 4.0, 2.0 )\ny = base.dists.laplace.median( NaN, 1.0 )\ny = base.dists.laplace.median( 0.0, NaN )\ny = base.dists.laplace.median( 0.0, 0.0 )\n","base.dists.laplace.mgf":"var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\ny = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, NaN )\ny = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\ny = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.mgf.factory":"var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\nvar y = mymgf( 0.2 )\ny = mymgf( 0.4 )\n","base.dists.laplace.mode":"var y = base.dists.laplace.mode( 0.0, 1.0 )\ny = base.dists.laplace.mode( 4.0, 2.0 )\ny = base.dists.laplace.mode( NaN, 1.0 )\ny = base.dists.laplace.mode( 0.0, NaN )\ny = base.dists.laplace.mode( 0.0, 0.0 )\n","base.dists.laplace.pdf":"var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.pdf( 0.0, 0.0, NaN )\ny = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.pdf.factory":"var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.laplace.quantile":"var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\ny = base.dists.laplace.quantile( 0.0, 0.0, NaN )\ny = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n","base.dists.laplace.quantile.factory":"var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.8 )\n","base.dists.laplace.skewness":"var y = base.dists.laplace.skewness( 0.0, 1.0 )\ny = base.dists.laplace.skewness( 4.0, 2.0 )\ny = base.dists.laplace.skewness( NaN, 1.0 )\ny = base.dists.laplace.skewness( 0.0, NaN )\ny = base.dists.laplace.skewness( 0.0, 0.0 )\n","base.dists.laplace.stdev":"var y = base.dists.laplace.stdev( 0.0, 1.0 )\ny = base.dists.laplace.stdev( 4.0, 2.0 )\ny = base.dists.laplace.stdev( NaN, 1.0 )\ny = base.dists.laplace.stdev( 0.0, NaN )\ny = base.dists.laplace.stdev( 0.0, 0.0 )\n","base.dists.laplace.variance":"var y = base.dists.laplace.variance( 0.0, 1.0 )\ny = base.dists.laplace.variance( 4.0, 2.0 )\ny = base.dists.laplace.variance( NaN, 1.0 )\ny = base.dists.laplace.variance( 0.0, NaN )\ny = base.dists.laplace.variance( 0.0, 0.0 )\n","base.dists.levy.cdf":"var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\ny = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.levy.cdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.cdf( 2, NaN, 1.0 )\ny = base.dists.levy.cdf( 2.0, 0.0, NaN )\ny = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.cdf.factory":"var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.levy.entropy":"var y = base.dists.levy.entropy( 0.0, 1.0 )\ny = base.dists.levy.entropy( 4.0, 2.0 )\ny = base.dists.levy.entropy( NaN, 1.0 )\ny = base.dists.levy.entropy( 0.0, NaN )\ny = base.dists.levy.entropy( 0.0, 0.0 )\n","base.dists.levy.Levy":"var levy = base.dists.levy.Levy( -2.0, 3.0 );\nlevy.mu\nlevy.c\nlevy.entropy\nlevy.mean\nlevy.median\nlevy.mode\nlevy.stdev\nlevy.variance\nlevy.cdf( 0.8 )\nlevy.logcdf( 0.8 )\nlevy.logpdf( 1.0 )\nlevy.pdf( 1.0 )\nlevy.quantile( 0.8 )\n","base.dists.levy.logcdf":"var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\ny = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.logcdf( 2, NaN, 1.0 )\ny = base.dists.levy.logcdf( 2.0, 0.0, NaN )\ny = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.logcdf.factory":"var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 2.0 )\n","base.dists.levy.logpdf":"var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.levy.logpdf( 0.0, 0.0, NaN )\ny = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.logpdf.factory":"var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 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myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 11.0 )\n","base.dists.levy.quantile":"var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.levy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.levy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.levy.quantile( 0.0, 0.0, NaN )\ny = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n","base.dists.levy.quantile.factory":"var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.levy.stdev":"var y = base.dists.levy.stdev( 0.0, 1.0 )\ny = base.dists.levy.stdev( 4.0, 3.0 )\ny = base.dists.levy.stdev( NaN, 1.0 )\ny = base.dists.levy.stdev( 0.0, NaN )\ny = base.dists.levy.stdev( 0.0, 0.0 )\n","base.dists.levy.variance":"var y = base.dists.levy.variance( 0.0, 1.0 )\ny = base.dists.levy.variance( 4.0, 3.0 )\ny = base.dists.levy.variance( NaN, 1.0 )\ny = base.dists.levy.variance( 0.0, NaN )\ny = base.dists.levy.variance( 0.0, 0.0 )\n","base.dists.logistic.cdf":"var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.logistic.cdf( 2.0, 0.0, NaN )\ny = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\ny = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n","base.dists.logistic.cdf.factory":"var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\nvar y = mycdf( 1.0 )\n","base.dists.logistic.entropy":"var y = base.dists.logistic.entropy( 0.0, 1.0 )\ny = base.dists.logistic.entropy( 4.0, 2.0 )\ny = base.dists.logistic.entropy( NaN, 1.0 )\ny = base.dists.logistic.entropy( 0.0, NaN )\ny = base.dists.logistic.entropy( 0.0, 0.0 )\n","base.dists.logistic.kurtosis":"var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\ny = base.dists.logistic.kurtosis( 4.0, 2.0 )\ny = base.dists.logistic.kurtosis( NaN, 1.0 )\ny = base.dists.logistic.kurtosis( 0.0, NaN )\ny = base.dists.logistic.kurtosis( 0.0, 0.0 )\n","base.dists.logistic.logcdf":"var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\ny = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\ny = base.dists.logistic.logcdf( 2, NaN, 1.0 )\ny = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n","base.dists.logistic.logcdf.factory":"var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\nvar y = mylogcdf( 1.0 )\n","base.dists.logistic.Logistic":"var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\nlogistic.mu\nlogistic.s\nlogistic.entropy\nlogistic.kurtosis\nlogistic.mean\nlogistic.median\nlogistic.mode\nlogistic.skewness\nlogistic.stdev\nlogistic.variance\nlogistic.cdf( 0.8 )\nlogistic.logcdf( 0.8 )\nlogistic.logpdf( 2.0 )\nlogistic.mgf( 0.2 )\nlogistic.pdf( 2.0 )\nlogistic.quantile( 0.9 )\n","base.dists.logistic.logpdf":"var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\ny = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.logistic.logpdf.factory":"var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\n","base.dists.logistic.mean":"var y = base.dists.logistic.mean( 0.0, 1.0 )\ny = base.dists.logistic.mean( 4.0, 2.0 )\ny = base.dists.logistic.mean( NaN, 1.0 )\ny = base.dists.logistic.mean( 0.0, NaN )\ny = base.dists.logistic.mean( 0.0, 0.0 )\n","base.dists.logistic.median":"var y = base.dists.logistic.median( 0.0, 1.0 )\ny = base.dists.logistic.median( 4.0, 2.0 )\ny = base.dists.logistic.median( NaN, 1.0 )\ny = base.dists.logistic.median( 0.0, NaN )\ny = base.dists.logistic.median( 0.0, 0.0 )\n","base.dists.logistic.mgf":"var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\ny = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\ny = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n","base.dists.logistic.mgf.factory":"var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\nvar y = mymgf( 0.5 )\ny = mymgf( 2.0 )\n","base.dists.logistic.mode":"var y = base.dists.logistic.mode( 0.0, 1.0 )\ny = base.dists.logistic.mode( 4.0, 2.0 )\ny = base.dists.logistic.mode( NaN, 1.0 )\ny = base.dists.logistic.mode( 0.0, NaN )\ny = base.dists.logistic.mode( 0.0, 0.0 )\n","base.dists.logistic.pdf":"var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.pdf( 0.0, 0.0, NaN )\ny = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n","base.dists.logistic.pdf.factory":"var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.logistic.quantile":"var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\ny = base.dists.logistic.quantile( 0.0, 0.0, NaN )\ny = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n","base.dists.logistic.quantile.factory":"var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.logistic.skewness":"var y = base.dists.logistic.skewness( 0.0, 1.0 )\ny = base.dists.logistic.skewness( 4.0, 2.0 )\ny = base.dists.logistic.skewness( NaN, 1.0 )\ny = base.dists.logistic.skewness( 0.0, NaN )\ny = base.dists.logistic.skewness( 0.0, 0.0 )\n","base.dists.logistic.stdev":"var y = base.dists.logistic.stdev( 0.0, 1.0 )\ny = base.dists.logistic.stdev( 4.0, 2.0 )\ny = base.dists.logistic.stdev( NaN, 1.0 )\ny = base.dists.logistic.stdev( 0.0, NaN )\ny = base.dists.logistic.stdev( 0.0, 0.0 )\n","base.dists.logistic.variance":"var y = base.dists.logistic.variance( 0.0, 1.0 )\ny = base.dists.logistic.variance( 4.0, 2.0 )\ny = base.dists.logistic.variance( NaN, 1.0 )\ny = base.dists.logistic.variance( 0.0, NaN )\ny = base.dists.logistic.variance( 0.0, 0.0 )\n","base.dists.lognormal.cdf":"var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\ny = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\ny = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.cdf.factory":"var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 4.0 )\n","base.dists.lognormal.entropy":"var y = base.dists.lognormal.entropy( 0.0, 1.0 )\ny = base.dists.lognormal.entropy( 5.0, 2.0 )\ny = base.dists.lognormal.entropy( NaN, 1.0 )\ny = base.dists.lognormal.entropy( 0.0, NaN )\ny = base.dists.lognormal.entropy( 0.0, 0.0 )\n","base.dists.lognormal.kurtosis":"var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\ny = base.dists.lognormal.kurtosis( 5.0, 2.0 )\ny = base.dists.lognormal.kurtosis( NaN, 1.0 )\ny = base.dists.lognormal.kurtosis( 0.0, NaN )\ny = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n","base.dists.lognormal.LogNormal":"var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\nlognormal.mu\nlognormal.sigma\nlognormal.entropy\nlognormal.kurtosis\nlognormal.mean\nlognormal.median\nlognormal.mode\nlognormal.skewness\nlognormal.stdev\nlognormal.variance\nlognormal.cdf( 0.8 )\nlognormal.logcdf( 0.8 )\nlognormal.logpdf( 2.0 )\nlognormal.pdf( 2.0 )\nlognormal.quantile( 0.9 )\n","base.dists.lognormal.logcdf":"var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\ny = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.lognormal.logcdf.factory":"var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.lognormal.logpdf":"var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.logpdf.factory":"var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\nvar y = mylogPDF( 10.0 )\ny = mylogPDF( 2.0 )\n","base.dists.lognormal.mean":"var y = base.dists.lognormal.mean( 0.0, 1.0 )\ny = base.dists.lognormal.mean( 4.0, 2.0 )\ny = base.dists.lognormal.mean( NaN, 1.0 )\ny = base.dists.lognormal.mean( 0.0, NaN )\ny = base.dists.lognormal.mean( 0.0, 0.0 )\n","base.dists.lognormal.median":"var y = base.dists.lognormal.median( 0.0, 1.0 )\ny = base.dists.lognormal.median( 5.0, 2.0 )\ny = base.dists.lognormal.median( NaN, 1.0 )\ny = base.dists.lognormal.median( 0.0, NaN )\ny = base.dists.lognormal.median( 0.0, 0.0 )\n","base.dists.lognormal.mode":"var y = base.dists.lognormal.mode( 0.0, 1.0 )\ny = base.dists.lognormal.mode( 5.0, 2.0 )\ny = base.dists.lognormal.mode( NaN, 1.0 )\ny = base.dists.lognormal.mode( 0.0, NaN )\ny = base.dists.lognormal.mode( 0.0, 0.0 )\n","base.dists.lognormal.pdf":"var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.pdf.factory":"var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.lognormal.quantile":"var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\ny = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n","base.dists.lognormal.quantile.factory":"var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.lognormal.skewness":"var y = base.dists.lognormal.skewness( 0.0, 1.0 )\ny = base.dists.lognormal.skewness( 5.0, 2.0 )\ny = base.dists.lognormal.skewness( NaN, 1.0 )\ny = base.dists.lognormal.skewness( 0.0, NaN )\ny = base.dists.lognormal.skewness( 0.0, 0.0 )\n","base.dists.lognormal.stdev":"var y = base.dists.lognormal.stdev( 0.0, 1.0 )\ny = base.dists.lognormal.stdev( 4.0, 2.0 )\ny = base.dists.lognormal.stdev( NaN, 1.0 )\ny = base.dists.lognormal.stdev( 0.0, NaN )\ny = base.dists.lognormal.stdev( 0.0, 0.0 )\n","base.dists.lognormal.variance":"var y = base.dists.lognormal.variance( 0.0, 1.0 )\ny = base.dists.lognormal.variance( 4.0, 2.0 )\ny = base.dists.lognormal.variance( NaN, 1.0 )\ny = base.dists.lognormal.variance( 0.0, NaN )\ny = base.dists.lognormal.variance( 0.0, 0.0 )\n","base.dists.negativeBinomial.cdf":"var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n","base.dists.negativeBinomial.cdf.factory":"var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\nvar y = myCDF( 3.0 )\ny = myCDF( 11.0 )\n","base.dists.negativeBinomial.kurtosis":"var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\nv = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n","base.dists.negativeBinomial.logpmf":"var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.logpmf.factory":"var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\nvar y = mylogPMF( 3.0 )\ny = mylogPMF( 5.0 )\n","base.dists.negativeBinomial.mean":"var v = base.dists.negativeBinomial.mean( 100, 0.2 )\nv = base.dists.negativeBinomial.mean( 20, 0.5 )\n","base.dists.negativeBinomial.mgf":"var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\ny = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\ny = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n","base.dists.negativeBinomial.mgf.factory":"var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\nvar y = myMGF( 0.2 )\ny = myMGF( 0.4 )\n","base.dists.negativeBinomial.mode":"var v = base.dists.negativeBinomial.mode( 100, 0.2 )\nv = base.dists.negativeBinomial.mode( 20, 0.5 )\n","base.dists.negativeBinomial.NegativeBinomial":"var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\nnbinomial.r\nnbinomial.p\nnbinomial.kurtosis\nnbinomial.mean\nnbinomial.mode\nnbinomial.skewness\nnbinomial.stdev\nnbinomial.variance\nnbinomial.cdf( 2.9 )\nnbinomial.logpmf( 3.0 )\nnbinomial.mgf( 0.2 )\nnbinomial.pmf( 3.0 )\nnbinomial.quantile( 0.8 )\n","base.dists.negativeBinomial.pmf":"var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.pmf.factory":"var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\nvar y = myPMF( 3.0 )\ny = myPMF( 5.0 )\n","base.dists.negativeBinomial.quantile":"var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\ny = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\ny = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\ny = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n","base.dists.negativeBinomial.quantile.factory":"var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\nvar y = myQuantile( 0.1 )\ny = myQuantile( 0.9 )\n","base.dists.negativeBinomial.skewness":"var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\nv = base.dists.negativeBinomial.skewness( 20, 0.5 )\n","base.dists.negativeBinomial.stdev":"var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\nv = base.dists.negativeBinomial.stdev( 20, 0.5 )\n","base.dists.negativeBinomial.variance":"var v = base.dists.negativeBinomial.variance( 100, 0.2 )\nv = base.dists.negativeBinomial.variance( 20, 0.5 )\n","base.dists.normal.cdf":"var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\ny = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.cdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.cdf( 0.0, 0.0, NaN )\ny = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n","base.dists.normal.cdf.factory":"var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 10.0 )\n","base.dists.normal.entropy":"var y = base.dists.normal.entropy( 0.0, 1.0 )\ny = base.dists.normal.entropy( 4.0, 3.0 )\ny = base.dists.normal.entropy( NaN, 1.0 )\ny = base.dists.normal.entropy( 0.0, NaN )\ny = base.dists.normal.entropy( 0.0, 0.0 )\n","base.dists.normal.kurtosis":"var y = base.dists.normal.kurtosis( 0.0, 1.0 )\ny = base.dists.normal.kurtosis( 4.0, 3.0 )\ny = base.dists.normal.kurtosis( NaN, 1.0 )\ny = base.dists.normal.kurtosis( 0.0, NaN )\ny = base.dists.normal.kurtosis( 0.0, 0.0 )\n","base.dists.normal.logcdf":"var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logcdf.factory":"var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.normal.logpdf":"var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logpdf.factory":"var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\nvar y = myLogPDF( 10.0 )\n","base.dists.normal.mean":"var y = base.dists.normal.mean( 0.0, 1.0 )\ny = base.dists.normal.mean( 4.0, 2.0 )\ny = base.dists.normal.mean( NaN, 1.0 )\ny = base.dists.normal.mean( 0.0, NaN )\ny = base.dists.normal.mean( 0.0, 0.0 )\n","base.dists.normal.median":"var y = base.dists.normal.median( 0.0, 1.0 )\ny = base.dists.normal.median( 4.0, 2.0 )\ny = base.dists.normal.median( NaN, 1.0 )\ny = base.dists.normal.median( 0.0, NaN )\ny = base.dists.normal.median( 0.0, 0.0 )\n","base.dists.normal.mgf":"var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.mgf( NaN, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, NaN, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, NaN )\ny = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n","base.dists.normal.mgf.factory":"var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.normal.mode":"var y = base.dists.normal.mode( 0.0, 1.0 )\ny = base.dists.normal.mode( 4.0, 2.0 )\ny = base.dists.normal.mode( NaN, 1.0 )\ny = base.dists.normal.mode( 0.0, NaN )\ny = base.dists.normal.mode( 0.0, 0.0 )\n","base.dists.normal.Normal":"var normal = base.dists.normal.Normal( -2.0, 3.0 );\nnormal.mu\nnormal.sigma\nnormal.entropy\nnormal.kurtosis\nnormal.mean\nnormal.median\nnormal.mode\nnormal.skewness\nnormal.stdev\nnormal.variance\nnormal.cdf( 0.8 )\nnormal.logcdf( 0.8 )\nnormal.logpdf( 2.0 )\nnormal.mgf( 0.2 )\nnormal.pdf( 2.0 )\nnormal.quantile( 0.9 )\n","base.dists.normal.pdf":"var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.pdf( 0.0, 0.0, NaN )\ny = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.pdf.factory":"var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.normal.quantile":"var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.normal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.normal.quantile( 0.0, 0.0, NaN )\ny = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\ny = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n","base.dists.normal.quantile.factory":"var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.normal.skewness":"var y = base.dists.normal.skewness( 0.0, 1.0 )\ny = base.dists.normal.skewness( 4.0, 3.0 )\ny = base.dists.normal.skewness( NaN, 1.0 )\ny = base.dists.normal.skewness( 0.0, NaN )\ny = base.dists.normal.skewness( 0.0, 0.0 )\n","base.dists.normal.stdev":"var y = base.dists.normal.stdev( 0.0, 1.0 )\ny = base.dists.normal.stdev( 4.0, 3.0 )\ny = base.dists.normal.stdev( NaN, 1.0 )\ny = base.dists.normal.stdev( 0.0, NaN )\ny = base.dists.normal.stdev( 0.0, 0.0 )\n","base.dists.normal.variance":"var y = base.dists.normal.variance( 0.0, 1.0 )\ny = base.dists.normal.variance( 4.0, 3.0 )\ny = base.dists.normal.variance( NaN, 1.0 )\ny = base.dists.normal.variance( 0.0, NaN )\ny = base.dists.normal.variance( 0.0, 0.0 )\n","base.dists.pareto1.cdf":"var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.cdf.factory":"var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 2.5 )\n","base.dists.pareto1.entropy":"var v = base.dists.pareto1.entropy( 0.8, 1.0 )\nv = base.dists.pareto1.entropy( 4.0, 12.0 )\nv = base.dists.pareto1.entropy( 8.0, 2.0 )\n","base.dists.pareto1.kurtosis":"var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\nv = base.dists.pareto1.kurtosis( 4.5, 12.0 )\nv = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n","base.dists.pareto1.logcdf":"var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.logcdf.factory":"var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\nvar y = mylogCDF( 3.0 )\ny = mylogCDF( 2.5 )\n","base.dists.pareto1.logpdf":"var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.logpdf.factory":"var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\nvar y = mylogPDF( 0.8 )\ny = mylogPDF( 2.0 )\n","base.dists.pareto1.mean":"var v = base.dists.pareto1.mean( 0.8, 1.0 )\nv = base.dists.pareto1.mean( 4.0, 12.0 )\nv = base.dists.pareto1.mean( 8.0, 2.0 )\n","base.dists.pareto1.median":"var v = base.dists.pareto1.median( 0.8, 1.0 )\nv = base.dists.pareto1.median( 4.0, 12.0 )\nv = base.dists.pareto1.median( 8.0, 2.0 )\n","base.dists.pareto1.mode":"var v = base.dists.pareto1.mode( 0.8, 1.0 )\nv = base.dists.pareto1.mode( 4.0, 12.0 )\nv = base.dists.pareto1.mode( 8.0, 2.0 )\n","base.dists.pareto1.Pareto1":"var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 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= base.dists.t.median( 11.0 )\nv = base.dists.t.median( 4.5 )\n","base.dists.t.mode":"var v = base.dists.t.mode( 11.0 )\nv = base.dists.t.mode( 4.5 )\n","base.dists.t.pdf":"var y = base.dists.t.pdf( 0.3, 4.0 )\ny = base.dists.t.pdf( 2.0, 0.7 )\ny = base.dists.t.pdf( -1.0, 0.5 )\ny = base.dists.t.pdf( 0.0, NaN )\ny = base.dists.t.pdf( NaN, 2.0 )\ny = base.dists.t.pdf( 2.0, -1.0 )\n","base.dists.t.pdf.factory":"var myPDF = base.dists.t.pdf.factory( 3.0 );\nvar y = myPDF( 1.0 )\n","base.dists.t.quantile":"var y = base.dists.t.quantile( 0.8, 1.0 )\ny = base.dists.t.quantile( 0.1, 1.0 )\ny = base.dists.t.quantile( 0.5, 0.1 )\ny = base.dists.t.quantile( -0.2, 0.1 )\ny = base.dists.t.quantile( NaN, 1.0 )\ny = base.dists.t.quantile( 0.0, NaN )\ny = base.dists.t.quantile( 0.5, -1.0 )\n","base.dists.t.quantile.factory":"var myQuantile = base.dists.t.quantile.factory( 4.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.t.skewness":"var v = base.dists.t.skewness( 11.0 )\nv = base.dists.t.skewness( 4.5 )\n","base.dists.t.stdev":"var v = base.dists.t.stdev( 9.0 )\nv = base.dists.t.stdev( 4.5 )\n","base.dists.t.T":"var t = base.dists.t.T( 6.0 );\nt.v\nt.entropy\nt.kurtosis\nt.mean\nt.median\nt.mode\nt.skewness\nt.stdev\nt.variance\nt.cdf( 1.0 )\nt.logcdf( 1.0 )\nt.logpdf( 1.5 )\nt.pdf( 1.5 )\nt.quantile( 0.8 )\n","base.dists.t.variance":"var v = base.dists.t.variance( 9.0 )\nv = base.dists.t.variance( 4.5 )\n","base.dists.triangular.cdf":"var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.cdf.factory":"var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.triangular.entropy":"var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n","base.dists.triangular.kurtosis":"var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n","base.dists.triangular.logcdf":"var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.logcdf.factory":"var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.triangular.logpdf":"var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.logpdf.factory":"var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\nvar y = mylogpdf( 2.0 )\ny = mylogpdf( 12.0 )\n","base.dists.triangular.mean":"var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n","base.dists.triangular.median":"var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.median( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n","base.dists.triangular.mgf":"var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n","base.dists.triangular.mgf.factory":"var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\nvar y = mymgf( -1.0 )\ny = mymgf( 2.0 )\n","base.dists.triangular.mode":"var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n","base.dists.triangular.pdf":"var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.pdf.factory":"var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\nvar y = mypdf( 2.0 )\ny = mypdf( 12.0 )\n","base.dists.triangular.quantile":"var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\ny = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n","base.dists.triangular.quantile.factory":"var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\n","base.dists.triangular.skewness":"var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n","base.dists.triangular.stdev":"var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n","base.dists.triangular.Triangular":"var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\ntriangular.a\ntriangular.b\ntriangular.c\ntriangular.entropy\ntriangular.kurtosis\ntriangular.mean\ntriangular.median\ntriangular.mode\ntriangular.skewness\ntriangular.stdev\ntriangular.variance\ntriangular.cdf( 0.8 )\ntriangular.logcdf( 0.8 )\ntriangular.logpdf( 0.8 )\ntriangular.mgf( 0.8 )\ntriangular.pdf( 0.8 )\ntriangular.quantile( 0.8 )\n","base.dists.triangular.variance":"var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n","base.dists.uniform.cdf":"var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.cdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.cdf.factory":"var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.uniform.entropy":"var v = base.dists.uniform.entropy( 0.0, 1.0 )\nv = base.dists.uniform.entropy( 4.0, 12.0 )\nv = base.dists.uniform.entropy( 2.0, 8.0 )\n","base.dists.uniform.kurtosis":"var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\nv = base.dists.uniform.kurtosis( 4.0, 12.0 )\nv = base.dists.uniform.kurtosis( 2.0, 8.0 )\n","base.dists.uniform.logcdf":"var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.logcdf.factory":"var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.uniform.logpdf":"var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.logpdf.factory":"var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 7.0 )\ny = mylogPDF( 5.0 )\n","base.dists.uniform.mean":"var v = base.dists.uniform.mean( 0.0, 1.0 )\nv = base.dists.uniform.mean( 4.0, 12.0 )\nv = base.dists.uniform.mean( 2.0, 8.0 )\n","base.dists.uniform.median":"var v = base.dists.uniform.median( 0.0, 1.0 )\nv = base.dists.uniform.median( 4.0, 12.0 )\nv = base.dists.uniform.median( 2.0, 8.0 )\n","base.dists.uniform.mgf":"var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\ny = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\ny = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n","base.dists.uniform.mgf.factory":"var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.uniform.pdf":"var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.pdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.pdf.factory":"var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.uniform.quantile":"var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\ny = base.dists.uniform.quantile( 0.0, 0.0, NaN )\ny = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n","base.dists.uniform.quantile.factory":"var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.uniform.skewness":"var v = base.dists.uniform.skewness( 0.0, 1.0 )\nv = base.dists.uniform.skewness( 4.0, 12.0 )\nv = base.dists.uniform.skewness( 2.0, 8.0 )\n","base.dists.uniform.stdev":"var v = base.dists.uniform.stdev( 0.0, 1.0 )\nv = base.dists.uniform.stdev( 4.0, 12.0 )\nv = base.dists.uniform.stdev( 2.0, 8.0 )\n","base.dists.uniform.Uniform":"var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\nuniform.a\nuniform.b\nuniform.entropy\nuniform.kurtosis\nuniform.mean\nuniform.median\nuniform.skewness\nuniform.stdev\nuniform.variance\nuniform.cdf( 0.8 )\nuniform.logcdf( 0.5 )\nuniform.logpdf( 1.0 )\nuniform.mgf( 0.8 )\nuniform.pdf( 0.8 )\nuniform.quantile( 0.8 )\n","base.dists.uniform.variance":"var v = base.dists.uniform.variance( 0.0, 1.0 )\nv = base.dists.uniform.variance( 4.0, 12.0 )\nv = base.dists.uniform.variance( 2.0, 8.0 )\n","base.dists.weibull.cdf":"var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.cdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.cdf.factory":"var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\nvar y = myCDF( 12.0 )\n","base.dists.weibull.entropy":"var v = base.dists.weibull.entropy( 1.0, 1.0 )\nv = base.dists.weibull.entropy( 4.0, 12.0 )\nv = base.dists.weibull.entropy( 8.0, 2.0 )\n","base.dists.weibull.kurtosis":"var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\nv = base.dists.weibull.kurtosis( 4.0, 12.0 )\nv = base.dists.weibull.kurtosis( 8.0, 2.0 )\n","base.dists.weibull.logcdf":"var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logcdf.factory":"var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\nvar y = mylogcdf( 12.0 )\n","base.dists.weibull.logpdf":"var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logpdf.factory":"var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\ny = mylofpdf( 7.0 )\n","base.dists.weibull.mean":"var v = base.dists.weibull.mean( 1.0, 1.0 )\nv = base.dists.weibull.mean( 4.0, 12.0 )\nv = base.dists.weibull.mean( 8.0, 2.0 )\n","base.dists.weibull.median":"var v = base.dists.weibull.median( 1.0, 1.0 )\nv = base.dists.weibull.median( 4.0, 12.0 )\nv = base.dists.weibull.median( 8.0, 2.0 )\n","base.dists.weibull.mgf":"var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\ny = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\ny = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\ny = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.mgf( 0.0, 1.0, NaN )\ny = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\ny = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n","base.dists.weibull.mgf.factory":"var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.08 )\n","base.dists.weibull.mode":"var v = base.dists.weibull.mode( 1.0, 1.0 )\nv = base.dists.weibull.mode( 4.0, 12.0 )\nv = base.dists.weibull.mode( 8.0, 2.0 )\n","base.dists.weibull.pdf":"var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.pdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.pdf.factory":"var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\nvar y = myPDF( 7.0 )\n","base.dists.weibull.quantile":"var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\ny = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\ny = base.dists.weibull.quantile( 0.0, 0.0, NaN )\ny = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n","base.dists.weibull.quantile.factory":"var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.weibull.skewness":"var v = base.dists.weibull.skewness( 1.0, 1.0 )\nv = base.dists.weibull.skewness( 4.0, 12.0 )\nv = base.dists.weibull.skewness( 8.0, 2.0 )\n","base.dists.weibull.stdev":"var v = base.dists.weibull.stdev( 1.0, 1.0 )\nv = base.dists.weibull.stdev( 4.0, 12.0 )\nv = base.dists.weibull.stdev( 8.0, 2.0 )\n","base.dists.weibull.variance":"var v = base.dists.weibull.variance( 1.0, 1.0 )\nv = base.dists.weibull.variance( 4.0, 12.0 )\nv = base.dists.weibull.variance( 8.0, 2.0 )\n","base.dists.weibull.Weibull":"var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\nweibull.k\nweibull.lambda\nweibull.entropy\nweibull.kurtosis\nweibull.mean\nweibull.median\nweibull.mode\nweibull.skewness\nweibull.stdev\nweibull.variance\nweibull.cdf( 3.0 )\nweibull.logcdf( 3.0 )\nweibull.logpdf( 1.0 )\nweibull.mgf( -0.5 )\nweibull.pdf( 3.0 )\nweibull.quantile( 0.8 )\n","base.ellipe":"var y = base.ellipe( 0.5 )\ny = base.ellipe( -1.0 )\ny = base.ellipe( 2.0 )\ny = base.ellipe( PINF )\ny = base.ellipe( NINF )\ny = base.ellipe( NaN )\n","base.ellipj":"var v = base.ellipj( 0.3, 0.5 )\nv = base.ellipj( 0.0, 0.0 )\nv = base.ellipj( Infinity, 1.0 )\nv = base.ellipj( 0.0, -2.0)\nv = base.ellipj( NaN, NaN )\n","base.ellipj.assign":"var out = new Float64Array( 4 );\nvar v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.ellipj.sn":"var v = base.ellipj.sn( 0.3, 0.5 )\n","base.ellipj.cn":"var v = base.ellipj.cn( 0.3, 0.5 )\n","base.ellipj.dn":"var v = base.ellipj.dn( 0.3, 0.5 )\n","base.ellipj.am":"var v = base.ellipj.am( 0.3, 0.5 )\n","base.ellipk":"var y = base.ellipk( 0.5 )\ny = base.ellipk( -1.0 )\ny = base.ellipk( 2.0 )\ny = base.ellipk( PINF )\ny = base.ellipk( NINF )\ny = base.ellipk( NaN )\n","base.epsdiff":"var d = base.epsdiff( 12.15, 12.149999999999999 )\nd = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\nfunction scale( x, y ) { return ( x > y ) ? y : x; };\nd = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n","base.erf":"var y = base.erf( 2.0 )\ny = base.erf( -1.0 )\ny = base.erf( -0.0 )\ny = base.erf( NaN )\n","base.erfc":"var y = base.erfc( 2.0 )\ny = base.erfc( -1.0 )\ny = base.erfc( 0.0 )\ny = base.erfc( PINF )\ny = base.erfc( NINF )\ny = base.erfc( NaN )\n","base.erfcinv":"var y = base.erfcinv( 0.5 )\ny = base.erfcinv( 0.8 )\ny = base.erfcinv( 0.0 )\ny = base.erfcinv( 2.0 )\ny = base.erfcinv( NaN )\n","base.erfcx":"var y = base.erfcx( 1.0 )\ny = base.erfcx( -1.0 )\ny = base.erfcx( 0.0 )\ny = base.erfcx( NaN )\n","base.erfinv":"var y = base.erfinv( 0.5 )\ny = base.erfinv( 0.8 )\ny = base.erfinv( 0.0 )\ny = base.erfinv( -0.0 )\ny = base.erfinv( -1.0 )\ny = base.erfinv( 1.0 )\ny = base.erfinv( NaN )\n","base.eta":"var y = base.eta( 0.0 )\ny = base.eta( -1.0 )\ny = base.eta( 1.0 )\ny = base.eta( 3.14 )\ny = base.eta( NaN )\n","base.evalpoly":"var arr = [ 3.0, 2.0, 1.0 ];\nvar v = base.evalpoly( arr, 10.0 )\n","base.evalpoly.factory":"var polyval = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\nvar v = polyval( 10.0 )\nv = polyval( 5.0 )\n","base.evalrational":"var P = [ -6.0, -5.0, 4.0, 2.0 ];\nvar Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\nvar v = base.evalrational( P, Q, 6.0 )\n","base.evalrational.factory":"var P = [ 20.0, 8.0, 3.0 ];\nvar Q = [ 10.0, 9.0, 1.0 ];\nvar rational = base.evalrational.factory( P, Q );\nvar v = rational( 10.0 )\nv = rational( 2.0 )\n","base.exp":"var y = base.exp( 4.0 )\ny = base.exp( -9.0 )\ny = base.exp( 0.0 )\ny = base.exp( NaN )\n","base.exp2":"var y = base.exp2( 3.0 )\ny = base.exp2( -9.0 )\ny = base.exp2( 0.0 )\ny = base.exp2( NaN )\n","base.exp10":"var y = base.exp10( 3.0 )\ny = base.exp10( -9.0 )\ny = base.exp10( 0.0 )\ny = base.exp10( NaN )\n","base.expit":"var y = base.expit( 0.0 )\ny = base.expit( 1.0 )\ny = base.expit( -1.0 )\ny = base.expit( Infinity )\ny = base.expit( NaN )\n","base.expm1":"var y = base.expm1( 0.2 )\ny = base.expm1( -9.0 )\ny = base.expm1( 0.0 )\ny = base.expm1( NaN )\n","base.expm1rel":"var y = base.expm1rel( 0.0 )\ny = base.expm1rel( 1.0 )\ny = base.expm1rel( -1.0 )\ny = base.expm1rel( NaN )\n","base.exponent":"var exponent = base.exponent( 3.14e-307 )\nexponent = base.exponent( -3.14 )\nexponent = base.exponent( 0.0 )\nexponent = base.exponent( NaN )\n","base.exponentf":"var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\nexponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\nexponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\nexponent = base.exponentf( 0.0 )\nexponent = base.exponentf( NaN )\n","base.factorial":"var y = base.factorial( 3.0 )\ny = base.factorial( -1.5 )\ny = base.factorial( -0.5 )\ny = base.factorial( 0.5 )\ny = base.factorial( -10.0 )\ny = base.factorial( 171.0 )\ny = base.factorial( NaN )\n","base.factorial2":"var y = base.factorial2( 3 )\ny = base.factorial2( 5 )\ny = base.factorial2( 6 )\ny = base.factorial2( 301 )\ny = base.factorial2( NaN )\n","base.factorialln":"var y = base.factorialln( 3.0 )\ny = base.factorialln( 2.4 )\ny = base.factorialln( -1.0 )\ny = base.factorialln( -1.5 )\ny = base.factorialln( NaN )\n","base.fallingFactorial":"var v = base.fallingFactorial( 0.9, 5 )\nv = base.fallingFactorial( -9.0, 3 )\nv = base.fallingFactorial( 0.0, 2 )\nv = base.fallingFactorial( 3.0, -2 )\n","base.fibonacci":"var y = base.fibonacci( 0 )\ny = base.fibonacci( 1 )\ny = base.fibonacci( 2 )\ny = base.fibonacci( 3 )\ny = base.fibonacci( 4 )\ny = base.fibonacci( 79 )\ny = base.fibonacci( NaN )\n","base.fibonacciIndex":"var n = base.fibonacciIndex( 2 )\nn = base.fibonacciIndex( 3 )\nn = base.fibonacciIndex( 5 )\nn = base.fibonacciIndex( NaN )\nn = base.fibonacciIndex( 1 )\n","base.fibpoly":"var v = base.fibpoly( 5, 2.0 )\n","base.fibpoly.factory":"var polyval = base.fibpoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.firstCodePoint":"var out = base.firstCodePoint( 'beep', 1 )\nout = base.firstCodePoint( 'Boop', 1 )\nout = base.firstCodePoint( 'foo bar', 5 )\n","base.firstCodeUnit":"var out = base.firstCodeUnit( 'beep', 1 )\nout = base.firstCodeUnit( 'Boop', 1 )\nout = base.firstCodeUnit( 'foo bar', 5 )\n","base.firstGraphemeCluster":"var out = base.firstGraphemeCluster( 'beep', 1 )\nout = base.firstGraphemeCluster( 'Boop', 1 )\nout = base.firstGraphemeCluster( 'foo bar', 5 )\n","base.flipsign":"var z = base.flipsign( -3.0, 10.0 )\nz = base.flipsign( -3.0, -1.0 )\nz = base.flipsign( 1.0, -0.0 )\nz = base.flipsign( -3.0, -0.0 )\nz = base.flipsign( -0.0, 1.0 )\nz = base.flipsign( 0.0, -1.0 )\n","base.flipsignf":"var z = base.flipsignf( -3.0, 10.0 )\nz = base.flipsignf( -3.0, -1.0 )\nz = base.flipsignf( 1.0, -0.0 )\nz = base.flipsignf( -3.0, -0.0 )\nz = base.flipsignf( -0.0, 1.0 )\nz = base.flipsignf( 0.0, -1.0 )\n","base.float32ToInt32":"var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\ny = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( NaN ) )\ny = base.float32ToInt32( FLOAT32_PINF )\ny = base.float32ToInt32( FLOAT32_NINF )\n","base.float32ToUint32":"var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\ny = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( NaN ) )\ny = base.float32ToUint32( FLOAT32_PINF )\ny = base.float32ToUint32( FLOAT32_NINF )\n","base.float64ToFloat32":"var y = base.float64ToFloat32( 1.337 )\n","base.float64ToInt32":"var y = base.float64ToInt32( 4294967295.0 )\ny = base.float64ToInt32( 3.14 )\ny = base.float64ToInt32( -3.14 )\ny = base.float64ToInt32( NaN )\ny = base.float64ToInt32( PINF )\ny = base.float64ToInt32( NINF )\n","base.float64ToInt64Bytes":"var y = base.float64ToInt64Bytes( 4294967297.0 )\n","base.float64ToInt64Bytes.assign":"var out = new Uint8Array( 16 );\nvar y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n","base.float64ToUint32":"var y = base.float64ToUint32( 4294967297.0 )\ny = base.float64ToUint32( 3.14 )\ny = base.float64ToUint32( -3.14 )\ny = base.float64ToUint32( NaN )\ny = base.float64ToUint32( PINF )\ny = base.float64ToUint32( NINF )\n","base.floor":"var y = base.floor( 3.14 )\ny = base.floor( -4.2 )\ny = base.floor( -4.6 )\ny = base.floor( 9.5 )\ny = base.floor( -0.0 )\n","base.floor2":"var y = base.floor2( 3.14 )\ny = base.floor2( -4.2 )\ny = base.floor2( -4.6 )\ny = base.floor2( 9.5 )\ny = base.floor2( 13.0 )\ny = base.floor2( -13.0 )\ny = base.floor2( -0.0 )\n","base.floor10":"var y = base.floor10( 3.14 )\ny = base.floor10( -4.2 )\ny = base.floor10( -4.6 )\ny = base.floor10( 9.5 )\ny = base.floor10( 13.0 )\ny = base.floor10( -13.0 )\ny = base.floor10( -0.0 )\n","base.floorb":"var y = base.floorb( 3.14159, -4, 10 )\ny = base.floorb( 3.14159, 0, 2 )\ny = base.floorb( 5.0, 1, 2 )\n","base.floorf":"var y = base.floorf( 3.14 )\ny = base.floorf( -4.2 )\ny = base.floorf( -4.6 )\ny = base.floorf( 9.5 )\ny = base.floorf( -0.0 )\n","base.floorn":"var y = base.floorn( 3.14159, -4 )\ny = base.floorn( 3.14159, 0 )\ny = base.floorn( 12368.0, 3 )\n","base.floorsd":"var y = base.floorsd( 3.14159, 5 )\ny = base.floorsd( 3.14159, 1 )\ny = base.floorsd( 12368.0, 2 )\ny = base.floorsd( 0.0313, 2, 2 )\n","base.forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachChar( 'hello world!', fcn );\nn\n","base.forEachCodePoint":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePoint( 'hello world!', fcn );\nn\n","base.forEachGraphemeCluster":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachGraphemeCluster( 'hello world!', fcn );\nn\n","base.fresnel":"var y = base.fresnel( 0.0 )\ny = base.fresnel( 1.0 )\ny = base.fresnel( PINF )\ny = base.fresnel( NINF )\ny = base.fresnel( NaN )\n","base.fresnel.assign":"var out = new Float64Array( 2 );\nvar v = base.fresnel.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.fresnelc":"var y = base.fresnelc( 0.0 )\ny = base.fresnelc( 1.0 )\ny = base.fresnelc( PINF )\ny = base.fresnelc( NINF )\ny = base.fresnelc( NaN )\n","base.fresnels":"var y = base.fresnels( 0.0 )\ny = base.fresnels( 1.0 )\ny = base.fresnels( PINF )\ny = base.fresnels( NINF )\ny = base.fresnels( NaN )\n","base.frexp":"var out = base.frexp( 4.0 )\nout = base.frexp( 0.0 )\nout = base.frexp( -0.0 )\nout = base.frexp( NaN )\nout = base.frexp( PINF )\nout = base.frexp( NINF )\n","base.frexp.assign":"var out = new Float64Array( 2 );\nvar y = base.frexp.assign( 4.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.fromBinaryString":"var bstr;\nbstr = '0100000000010000000000000000000000000000000000000000000000000000';\nvar val = base.fromBinaryString( bstr )\nbstr = '0100000000001001001000011111101101010100010001000010110100011000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111100001110011001111001110000101111010111100100010100000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000001100011010011';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000001';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111111000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\n","base.fromBinaryStringf":"var bstr = '01000000100000000000000000000000';\nvar val = base.fromBinaryStringf( bstr )\nbstr = '01000000010010010000111111011011';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111011011000011101000110011';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000010110';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000001';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111110000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\n","base.fromBinaryStringUint8":"var bstr = '01010101';\nvar val = base.fromBinaryStringUint8( bstr )\nbstr = '00000000';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '00000010';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '11111111';\nval = base.fromBinaryStringUint8( bstr )\n","base.fromBinaryStringUint16":"var bstr = '0101010101010101';\nvar val = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000000';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000010';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '1111111111111111';\nval = base.fromBinaryStringUint16( bstr )\n","base.fromBinaryStringUint32":"var bstr = '01010101010101010101010101010101';\nvar val = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000010';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '11111111111111111111111111111111';\nval = base.fromBinaryStringUint32( bstr )\n","base.fromInt64Bytes":"var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\nvar y = base.fromInt64Bytes( bytes, 1, 0 )\n","base.fromWordf":"var word = 1068180177; // => 0 01111111 01010110010001011010001\nvar f32 = base.fromWordf( word ) // when printed, promoted to float64\n","base.fromWords":"var v = base.fromWords( 1774486211, 2479577218 )\nv = base.fromWords( 3221823995, 1413754136 )\nv = base.fromWords( 0, 0 )\nv = base.fromWords( 2147483648, 0 )\nv = base.fromWords( 2146959360, 0 )\nv = base.fromWords( 2146435072, 0 )\nv = base.fromWords( 4293918720, 0 )\n","base.gamma":"var y = base.gamma( 4.0 )\ny = base.gamma( -1.5 )\ny = base.gamma( -0.5 )\ny = base.gamma( 0.5 )\ny = base.gamma( 0.0 )\ny = base.gamma( -0.0 )\ny = base.gamma( NaN )\n","base.gamma1pm1":"var y = base.gamma1pm1( 0.2 )\ny = base.gamma1pm1( -6.7 )\ny = base.gamma1pm1( 0.0 )\ny = base.gamma1pm1( NaN )\n","base.gammaDeltaRatio":"var y = base.gammaDeltaRatio( 2.0, 3.0 )\ny = base.gammaDeltaRatio( 4.0, 0.5 )\ny = base.gammaDeltaRatio( 100.0, 0.0 )\ny = base.gammaDeltaRatio( NaN, 3.0 )\ny = base.gammaDeltaRatio( 5.0, NaN )\ny = base.gammaDeltaRatio( NaN, NaN )\n","base.gammainc":"var y = base.gammainc( 6.0, 2.0 )\ny = base.gammainc( 1.0, 2.0, true, true )\ny = base.gammainc( 7.0, 5.0 )\ny = base.gammainc( 7.0, 5.0, false )\ny = base.gammainc( NaN, 2.0 )\ny = base.gammainc( 6.0, NaN )\n","base.gammaincinv":"var y = base.gammaincinv( 0.5, 2.0 )\ny = base.gammaincinv( 0.1, 10.0 )\ny = base.gammaincinv( 0.75, 3.0 )\ny = base.gammaincinv( 0.75, 3.0, true )\ny = base.gammaincinv( 0.75, NaN )\ny = base.gammaincinv( NaN, 3.0 )\n","base.gammaLanczosSum":"var y = base.gammaLanczosSum( 4.0 )\ny = base.gammaLanczosSum( -1.5 )\ny = base.gammaLanczosSum( -0.5 )\ny = base.gammaLanczosSum( 0.5 )\ny = base.gammaLanczosSum( 0.0 )\ny = base.gammaLanczosSum( NaN )\n","base.gammaLanczosSumExpGScaled":"var y = base.gammaLanczosSumExpGScaled( 4.0 )\ny = base.gammaLanczosSumExpGScaled( -1.5 )\ny = base.gammaLanczosSumExpGScaled( -0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.0 )\ny = base.gammaLanczosSumExpGScaled( NaN )\n","base.gammaln":"var y = base.gammaln( 1.0 )\ny = base.gammaln( 2.0 )\ny = base.gammaln( 4.0 )\ny = base.gammaln( -0.5 )\ny = base.gammaln( 0.5 )\ny = base.gammaln( 0.0 )\ny = base.gammaln( NaN )\n","base.gcd":"var v = base.gcd( 48, 18 )\n","base.getHighWord":"var w = base.getHighWord( 3.14e201 )\n","base.getLowWord":"var w = base.getLowWord( 3.14e201 )\n","base.hacovercos":"var y = base.hacovercos( 3.14 )\ny = base.hacovercos( -4.2 )\ny = base.hacovercos( -4.6 )\ny = base.hacovercos( 9.5 )\ny = base.hacovercos( -0.0 )\n","base.hacoversin":"var y = base.hacoversin( 3.14 )\ny = base.hacoversin( -4.2 )\ny = base.hacoversin( -4.6 )\ny = base.hacoversin( 9.5 )\ny = base.hacoversin( -0.0 )\n","base.havercos":"var y = base.havercos( 3.14 )\ny = base.havercos( -4.2 )\ny = base.havercos( -4.6 )\ny = base.havercos( 9.5 )\ny = base.havercos( -0.0 )\n","base.haversin":"var y = base.haversin( 3.14 )\ny = base.haversin( -4.2 )\ny = base.haversin( -4.6 )\ny = base.haversin( 9.5 )\ny = base.haversin( -0.0 )\n","base.heaviside":"var y = base.heaviside( 3.14 )\ny = base.heaviside( -3.14 )\ny = base.heaviside( 0.0 )\ny = base.heaviside( 0.0, 'half-maximum' )\ny = base.heaviside( 0.0, 'left-continuous' )\ny = base.heaviside( 0.0, 'right-continuous' )\n","base.hermitepoly":"var y = base.hermitepoly( 1, 0.5 )\ny = base.hermitepoly( -1, 0.5 )\ny = base.hermitepoly( 0, 0.5 )\ny = base.hermitepoly( 2, 0.5 )\n","base.hermitepoly.factory":"var polyval = base.hermitepoly.factory( 2 );\nvar v = polyval( 0.5 )\n","base.hypot":"var h = base.hypot( -5.0, 12.0 )\nh = base.hypot( NaN, 12.0 )\nh = base.hypot( -0.0, -0.0 )\n","base.hypotf":"var h = base.hypotf( -5.0, 12.0 )\nh = base.hypotf( NaN, 12.0 )\nh = base.hypotf( -0.0, -0.0 )\n","base.identity":"var y = base.identity( -1.0 )\ny = base.identity( 2.0 )\ny = base.identity( 0.0 )\ny = base.identity( -0.0 )\ny = base.identity( NaN )\n","base.identityf":"var y = base.identityf( -1.0 )\ny = base.identityf( 2.0 )\ny = base.identityf( 0.0 )\ny = base.identityf( -0.0 )\ny = base.identityf( NaN )\n","base.imul":"var v = base.imul( -10|0, 4|0 )\n","base.imuldw":"var v = base.imuldw( 1, 10 )\n","base.imuldw.assign":"var out = [ 0, 0 ];\nvar v = base.imuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.int32ToUint32":"var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\ny = base.int32ToUint32( base.float64ToInt32( 3 ) )\n","base.inv":"var y = base.inv( -1.0 )\ny = base.inv( 2.0 )\ny = base.inv( 0.0 )\ny = base.inv( -0.0 )\ny = base.inv( NaN )\n","base.invf":"var y = base.invf( -1.0 )\ny = base.invf( 2.0 )\ny = base.invf( 0.0 )\ny = base.invf( -0.0 )\ny = base.invf( NaN )\n","base.isComposite":"var bool = base.isComposite( 10.0 )\nbool = base.isComposite( 11.0 )\n","base.isCoprime":"var bool = base.isCoprime( 14.0, 15.0 )\nbool = base.isCoprime( 14.0, 21.0 )\n","base.isEven":"var bool = base.isEven( 5.0 )\nbool = base.isEven( -2.0 )\nbool = base.isEven( 0.0 )\nbool = base.isEven( NaN )\n","base.isEvenInt32":"var bool = base.isEvenInt32( 5 )\nbool = base.isEvenInt32( -2 )\nbool = base.isEvenInt32( 0 )\n","base.isFinite":"var bool = base.isFinite( 5.0 )\nbool = base.isFinite( -2.0e64 )\nbool = base.isFinite( PINF )\nbool = base.isFinite( NINF )\n","base.isFinitef":"var bool = base.isFinitef( 5.0 )\nbool = base.isFinitef( -1.0e38 )\nbool = base.isFinitef( FLOAT32_PINF )\nbool = base.isFinitef( FLOAT32_NINF )\n","base.isInfinite":"var bool = base.isInfinite( PINF )\nbool = base.isInfinite( NINF )\nbool = base.isInfinite( 5.0 )\nbool = base.isInfinite( NaN )\n","base.isInfinitef":"var bool = base.isInfinitef( FLOAT32_PINF )\nbool = base.isInfinitef( FLOAT32_NINF )\nbool = base.isInfinitef( 5.0 )\nbool = base.isInfinitef( NaN )\n","base.isInteger":"var bool = base.isInteger( 1.0 )\nbool = base.isInteger( 3.14 )\n","base.isnan":"var bool = base.isnan( NaN )\nbool = base.isnan( 7.0 )\n","base.isnanf":"var bool = base.isnanf( NaN )\nbool = base.isnanf( 7.0 )\n","base.isNegativeInteger":"var bool = base.isNegativeInteger( -1.0 )\nbool = base.isNegativeInteger( 0.0 )\nbool = base.isNegativeInteger( 10.0 )\n","base.isNegativeZero":"var bool = base.isNegativeZero( -0.0 )\nbool = base.isNegativeZero( 0.0 )\n","base.isNegativeZerof":"var bool = base.isNegativeZerof( -0.0 )\nbool = base.isNegativeZerof( 0.0 )\n","base.isNonNegativeInteger":"var bool = base.isNonNegativeInteger( 1.0 )\nbool = base.isNonNegativeInteger( 0.0 )\nbool = base.isNonNegativeInteger( -10.0 )\n","base.isNonPositiveInteger":"var bool = base.isNonPositiveInteger( -1.0 )\nbool = base.isNonPositiveInteger( 0.0 )\nbool = base.isNonPositiveInteger( 10.0 )\n","base.isOdd":"var bool = base.isOdd( 5.0 )\nbool = base.isOdd( -2.0 )\nbool = base.isOdd( 0.0 )\nbool = base.isOdd( NaN )\n","base.isOddInt32":"var bool = base.isOddInt32( 5 )\nbool = base.isOddInt32( -2 )\nbool = base.isOddInt32( 0 )\n","base.isPositiveInteger":"var bool = base.isPositiveInteger( 1.0 )\nbool = base.isPositiveInteger( 0.0 )\nbool = base.isPositiveInteger( -10.0 )\n","base.isPositiveZero":"var bool = base.isPositiveZero( 0.0 )\nbool = base.isPositiveZero( -0.0 )\n","base.isPositiveZerof":"var bool = base.isPositiveZerof( 0.0 )\nbool = base.isPositiveZerof( -0.0 )\n","base.isPow2Uint32":"var bool = base.isPow2Uint32( 2 )\nbool = base.isPow2Uint32( 5 )\n","base.isPrime":"var bool = base.isPrime( 11.0 )\nbool = base.isPrime( 3.14 )\n","base.isProbability":"var bool = base.isProbability( 0.5 )\nbool = base.isProbability( 3.14 )\nbool = base.isProbability( NaN )\n","base.isSafeInteger":"var bool = base.isSafeInteger( 1.0 )\nbool = base.isSafeInteger( 2.0e200 )\nbool = base.isSafeInteger( 3.14 )\n","base.kernelBetainc":"var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\nout = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n","base.kernelBetainc.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\nvar bool = ( v === out )\n","base.kernelBetaincinv":"var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\ny = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n","base.kernelCos":"var out = base.kernelCos( 0.0, 0.0 )\nout = base.kernelCos( PI/6.0, 0.0 )\nout = base.kernelCos( 0.785, -1.144e-17 )\nout = base.kernelCos( NaN )\n","base.kernelSin":"var y = base.kernelSin( 0.0, 0.0 )\ny = base.kernelSin( PI/6.0, 0.0 )\ny = base.kernelSin( 0.619, 9.279e-18 )\ny = base.kernelSin( NaN, 0.0 )\ny = base.kernelSin( 2.0, NaN )\ny = base.kernelSin( NaN, NaN )\n","base.kernelTan":"var out = base.kernelTan( PI/4.0, 0.0, 1 )\nout = base.kernelTan( PI/4.0, 0.0, -1 )\nout = base.kernelTan( PI/6.0, 0.0, 1 )\nout = base.kernelTan( 0.664, 5.288e-17, 1 )\nout = base.kernelTan( NaN, 0.0, 1 )\nout = base.kernelTan( 3.0, NaN, 1 )\nout = base.kernelTan( 3.0, 0.0, NaN )\n","base.kroneckerDelta":"var y = base.kroneckerDelta( 3.14, 0.0 )\ny = base.kroneckerDelta( 3.14, 3.14 )\n","base.kroneckerDeltaf":"var y = base.kroneckerDeltaf( 3.14, 0.0 )\ny = base.kroneckerDeltaf( 3.14, 3.14 )\n","base.labs":"var v = base.labs( -1|0 )\nv = base.labs( 2|0 )\nv = base.labs( 0|0 )\n","base.lcm":"var v = base.lcm( 21, 6 )\n","base.ldexp":"var x = base.ldexp( 0.5, 3 )\nx = base.ldexp( 4.0, -2 )\nx = base.ldexp( 0.0, 20 )\nx = base.ldexp( -0.0, 39 )\nx = base.ldexp( NaN, -101 )\nx = base.ldexp( PINF, 11 )\nx = base.ldexp( NINF, -118 )\n","base.ln":"var y = base.ln( 4.0 )\ny = base.ln( 0.0 )\ny = base.ln( PINF )\ny = base.ln( NaN )\ny = base.ln( -4.0 )\n","base.log":"var y = base.log( 100.0, 10.0 )\ny = base.log( 16.0, 2.0 )\ny = base.log( 5.0, 1.0 )\ny = base.log( NaN, 2.0 )\ny = base.log( 1.0, NaN )\ny = base.log( -4.0, 2.0 )\ny = base.log( 4.0, -2.0 )\n","base.log1mexp":"var y = base.log1mexp( -10.0 )\ny = base.log1mexp( 0.0 )\ny = base.log1mexp( 5.0 )\ny = base.log1mexp( 10.0 )\ny = base.log1mexp( NaN )\n","base.log1p":"var y = base.log1p( 4.0 )\ny = base.log1p( -1.0 )\ny = base.log1p( 0.0 )\ny = base.log1p( -0.0 )\ny = base.log1p( -2.0 )\ny = base.log1p( NaN )\n","base.log1pexp":"var y = base.log1pexp( -10.0 )\ny = base.log1pexp( 0.0 )\ny = base.log1pexp( 5.0 )\ny = base.log1pexp( 34.0 )\ny = base.log1pexp( NaN )\n","base.log1pmx":"base.log1pmx( 1.1 )\nbase.log1pmx( 0.99 )\nbase.log1pmx( -0.99 )\nbase.log1pmx( -1.1 )\nbase.log1pmx( NaN )\n","base.log2":"var y = base.log2( 4.0 )\ny = base.log2( 8.0 )\ny = base.log2( 0.0 )\ny = base.log2( PINF )\ny = base.log2( NaN )\ny = base.log2( -4.0 )\n","base.log10":"var y = base.log10( 100.0 )\ny = base.log10( 8.0 )\ny = base.log10( 0.0 )\ny = base.log10( PINF )\ny = base.log10( NaN )\ny = base.log10( -4.0 )\n","base.logaddexp":"var v = base.logaddexp( 90.0, 90.0 )\nv = base.logaddexp( -20.0, 90.0 )\nv = base.logaddexp( 0.0, -100.0 )\nv = base.logaddexp( NaN, NaN )\n","base.logit":"var y = base.logit( 0.2 )\ny = base.logit( 0.9 )\ny = base.logit( -4.0 )\ny = base.logit( 1.5 )\ny = base.logit( NaN )\n","base.lucas":"var y = base.lucas( 0 )\ny = base.lucas( 1 )\ny = base.lucas( 2 )\ny = base.lucas( 3 )\ny = base.lucas( 4 )\ny = base.lucas( 77 )\ny = base.lucas( NaN )\n","base.lucaspoly":"var v = base.lucaspoly( 5, 2.0 )\n","base.lucaspoly.factory":"var polyval = base.lucaspoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.max":"var v = base.max( 3.14, 4.2 )\nv = base.max( 3.14, NaN )\nv = base.max( +0.0, -0.0 )\n","base.maxabs":"var v = base.maxabs( 3.14, -4.2 )\nv = base.maxabs( 3.14, NaN )\nv = base.maxabs( +0.0, -0.0 )\n","base.maxn":"var v = base.maxn( 3.14, 4.2 )\nv = base.maxn( 5.9, 3.14, 4.2 )\nv = base.maxn( 3.14, NaN )\nv = base.maxn( +0.0, -0.0 )\n","base.min":"var v = base.min( 3.14, 4.2 )\nv = base.min( 3.14, NaN )\nv = base.min( +0.0, -0.0 )\n","base.minabs":"var v = base.minabs( 3.14, -4.2 )\nv = base.minabs( 3.14, NaN )\nv = base.minabs( +0.0, -0.0 )\n","base.minmax":"var v = base.minmax( 3.14, 4.2 )\nv = base.minmax( 3.14, NaN )\nv = base.minmax( +0.0, -0.0 )\n","base.minmax.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabs":"var v = base.minmaxabs( 3.14, 4.2 )\nv = base.minmaxabs( -5.9, 3.14)\nv = base.minmaxabs( 3.14, NaN )\nv = base.minmaxabs( +0.0, -0.0 )\n","base.minmaxabs.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minn":"var v = base.minn( 3.14, 4.2 )\nv = base.minn( 5.9, 3.14, 4.2 )\nv = base.minn( 3.14, NaN )\nv = base.minn( +0.0, -0.0 )\n","base.modf":"var parts = base.modf( 3.14 )\nparts = base.modf( 3.14 )\nparts = base.modf( +0.0 )\nparts = base.modf( -0.0 )\nparts = base.modf( PINF )\nparts = base.modf( NINF )\nparts = base.modf( NaN )\n","base.modf.assign":"var out = new Float64Array( 2 );\nvar parts = base.modf.assign( 3.14, out, 1, 0 )\nvar bool = ( parts === out )\n","base.mul":"var v = base.mul( -1.0, 5.0 )\nv = base.mul( 2.0, 5.0 )\nv = base.mul( 0.0, 5.0 )\nv = base.mul( -0.0, 0.0 )\nv = base.mul( NaN, NaN )\n","base.mulf":"var v = base.mulf( -1.0, 5.0 )\nv = base.mulf( 2.0, 5.0 )\nv = base.mulf( 0.0, 5.0 )\nv = base.mulf( -0.0, 0.0 )\nv = base.mulf( NaN, NaN )\n","base.ndarray":"var b = [ 1, 2, 3, 4 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40 );\narr.get( 1, 1 )\narr.iset( 3, 99 );\narr.get( 1, 1 )\n","base.ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","base.ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","base.ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","base.ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","base.ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","base.ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","base.ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","base.ndarray.prototype.order: string":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","base.ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","base.ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","base.ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","base.ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","base.ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","base.ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","base.ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","base.ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","base.ndarrayUnary":"var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dtype = 'float64';\nvar shape = [ 2, 2 ];\nvar sx = [ 2, 1 ];\nvar sy = [ 2, 1 ];\nvar ox = 0;\nvar oy = 0;\nvar order = 'row-major';\nvar x = ndarray( dtype, xbuf, shape, sx, ox, order );\nvar y = ndarray( dtype, ybuf, shape, sy, oy, order );\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\nx = {\n 'dtype': dtype,\n 'data': xbuf,\n 'shape': shape,\n 'strides': sx,\n 'offset': ox,\n 'order': order\n };\ny = {\n 'dtype': dtype,\n 'data': ybuf,\n 'shape': shape,\n 'strides': sy,\n 'offset': oy,\n 'order': order\n };\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\n","base.ndzeros":"var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = arr.shape\nvar dt = arr.dtype\n","base.ndzerosLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = base.ndzerosLike( x )\nsh = y.shape\ndt = y.dtype\n","base.negafibonacci":"var y = base.negafibonacci( 0 )\ny = base.negafibonacci( -1 )\ny = base.negafibonacci( -2 )\ny = base.negafibonacci( -3 )\ny = base.negafibonacci( -4 )\ny = base.negafibonacci( -79 )\ny = base.negafibonacci( -80 )\ny = base.negafibonacci( NaN )\n","base.negalucas":"var y = base.negalucas( 0 )\ny = base.negalucas( -1 )\ny = base.negalucas( -2 )\ny = base.negalucas( -3 )\ny = base.negalucas( -4 )\ny = base.negalucas( -77 )\ny = base.negalucas( -78 )\ny = base.negalucas( NaN )\n","base.nonfibonacci":"var v = base.nonfibonacci( 1 )\nv = base.nonfibonacci( 2 )\nv = base.nonfibonacci( 3 )\nv = base.nonfibonacci( NaN )\n","base.normalize":"var out = base.normalize( 3.14e-319 )\nvar y = out[ 0 ];\nvar exponent = out[ 1 ];\nvar bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\nout = base.normalize( 0.0 )\nout = base.normalize( PINF )\nout = base.normalize( NINF )\nout = base.normalize( NaN )\n","base.normalize.assign":"var out = new Float64Array( 2 )\nvar v = base.normalize.assign( 3.14e-319, out, 1, 0 )\nvar bool = ( v === out )\n","base.normalizef":"var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\nvar y = out[ 0 ];\nvar exp = out[ 1 ];\nvar bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\nout = base.normalizef( FLOAT32_PINF )\nout = base.normalizef( FLOAT32_NINF )\nout = base.normalizef( NaN )\n","base.normalizef.assign":"out = new Float32Array( 2 );\nvar v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\nbool = ( v === out )\n","base.normhermitepoly":"var y = base.normhermitepoly( 1, 0.5 )\ny = base.normhermitepoly( -1, 0.5 )\ny = base.normhermitepoly( 0, 0.5 )\ny = base.normhermitepoly( 2, 0.5 )\n","base.normhermitepoly.factory":"var polyval = base.normhermitepoly.factory( 2 );\nvar v = polyval( 0.5 )\n","base.pdiff":"var v = base.pdiff( 5.9, 3.14 )\nv = base.pdiff( 3.14, 4.2 )\nv = base.pdiff( 3.14, NaN )\nv = base.pdiff( -0.0, +0.0 )\n","base.pdifff":"var v = base.pdifff( 5.9, 3.15 )\nv = base.pdifff( 3.14, 4.2 )\nv = base.pdifff( 3.14, NaN )\nv = base.pdifff( -0.0, +0.0 )\n","base.polygamma":"var v = base.polygamma( 3, 1.2 )\nv = base.polygamma( 5, 1.2 )\nv = base.polygamma( 3, -4.9 )\nv = base.polygamma( -1, 5.3 )\nv = base.polygamma( 2, -1.0 )\n","base.pow":"var y = base.pow( 2.0, 3.0 )\ny = base.pow( 4.0, 0.5 )\ny = base.pow( 100.0, 0.0 )\ny = base.pow( PI, 5.0 )\ny = base.pow( PI, -0.2 )\ny = base.pow( NaN, 3.0 )\ny = base.pow( 5.0, NaN )\ny = base.pow( NaN, NaN )\n","base.powm1":"var y = base.powm1( 2.0, 3.0 )\ny = base.powm1( 4.0, 0.5 )\ny = base.powm1( 0.0, 100.0 )\ny = base.powm1( 100.0, 0.0 )\ny = base.powm1( 0.0, 0.0 )\ny = base.powm1( PI, 5.0 )\ny = base.powm1( NaN, 3.0 )\ny = base.powm1( 5.0, NaN )\n","base.rad2deg":"var d = base.rad2deg( PI/2.0 )\nd = base.rad2deg( -PI/4.0 )\nd = base.rad2deg( NaN )\nd = base.rad2deg( PI/6.0 )\n","base.ramp":"var y = base.ramp( 3.14 )\ny = base.ramp( -3.14 )\n","base.rampf":"var y = base.rampf( 3.14 )\ny = base.rampf( -3.14 )\n","base.random.arcsine":"var r = base.random.arcsine( 2.0, 5.0 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base.random.arcsine.byteLength;\n","base.random.arcsine.toJSON":"var o = base.random.arcsine.toJSON()\n","base.random.bernoulli":"var r = base.random.bernoulli( 0.8 );\n","base.random.bernoulli.factory":"var rand = base.random.bernoulli.factory();\nvar r = rand( 0.3 );\nr = rand( 0.59 );\nrand = base.random.bernoulli.factory( 0.3 );\nr = rand();\nr = rand();\n","base.random.bernoulli.NAME":"var str = base.random.bernoulli.NAME\n","base.random.bernoulli.PRNG":"var prng = base.random.bernoulli.PRNG;\n","base.random.bernoulli.seed":"var seed = base.random.bernoulli.seed;\n","base.random.bernoulli.seedLength":"var len = base.random.bernoulli.seedLength;\n","base.random.bernoulli.state":"var r = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nvar state = base.random.bernoulli.state\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nbase.random.bernoulli.state = state;\nr = base.random.bernoulli( 0.3 )\nr = 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base.random.randn();\n","base.random.randn.factory":"var rand = base.random.randn.factory();\nvar r = rand();\nr = rand();\nvar rand = base.random.randn.factory({ 'name': 'box-muller' });\nr = rand();\nr = rand();\n","base.random.randn.NAME":"var str = base.random.randn.NAME\n","base.random.randn.PRNG":"var prng = base.random.randn.PRNG;\n","base.random.randn.seed":"var seed = base.random.randn.seed;\n","base.random.randn.seedLength":"var len = base.random.randn.seedLength;\n","base.random.randn.state":"var r = base.random.randn()\nr = base.random.randn()\nr = base.random.randn()\nvar state = base.random.randn.state;\nr = base.random.randn()\nr = base.random.randn()\nbase.random.randn.state = state;\nr = base.random.randn()\nr = base.random.randn()\n","base.random.randn.stateLength":"var len = base.random.randn.stateLength;\n","base.random.randn.byteLength":"var sz = base.random.randn.byteLength;\n","base.random.randn.toJSON":"var o = base.random.randn.toJSON()\n","base.random.randu":"var r = base.random.randu();\n","base.random.randu.factory":"var rand = base.random.randu.factory();\nvar r = rand();\nr = rand();\nvar rand = base.random.randu.factory({ 'name': 'minstd' });\nr = rand();\nr = rand();\n","base.random.randu.NAME":"var str = base.random.randu.NAME\n","base.random.randu.PRNG":"var prng = base.random.randu.PRNG;\n","base.random.randu.MIN":"var v = base.random.randu.MIN;\n","base.random.randu.MAX":"var v = base.random.randu.MAX;\n","base.random.randu.seed":"var seed = base.random.randu.seed;\n","base.random.randu.seedLength":"var len = base.random.randu.seedLength;\n","base.random.randu.state":"var r = base.random.randu()\nr = base.random.randu()\nr = base.random.randu()\nvar state = base.random.randu.state;\nr = base.random.randu()\nr = base.random.randu()\nbase.random.randu.state = state;\nr = base.random.randu()\nr = base.random.randu()\n","base.random.randu.stateLength":"var len = base.random.randu.stateLength;\n","base.random.randu.byteLength":"var sz = base.random.randu.byteLength;\n","base.random.randu.toJSON":"var o = base.random.randu.toJSON()\n","base.random.rayleigh":"var r = base.random.rayleigh( 2.5 );\n","base.random.rayleigh.factory":"var rand = base.random.rayleigh.factory();\nvar r = rand( 5.0 );\nr = rand( 10.0 );\nrand = base.random.rayleigh.factory( 5.0 );\nr = rand();\nr = rand();\n","base.random.rayleigh.NAME":"var str = base.random.rayleigh.NAME\n","base.random.rayleigh.PRNG":"var prng = base.random.rayleigh.PRNG;\n","base.random.rayleigh.seed":"var seed = base.random.rayleigh.seed;\n","base.random.rayleigh.seedLength":"var len = base.random.rayleigh.seedLength;\n","base.random.rayleigh.state":"var r = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nvar state = base.random.rayleigh.state\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nbase.random.rayleigh.state = state;\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\n","base.random.rayleigh.stateLength":"var len = base.random.rayleigh.stateLength;\n","base.random.rayleigh.byteLength":"var sz = base.random.rayleigh.byteLength;\n","base.random.rayleigh.toJSON":"var o = base.random.rayleigh.toJSON()\n","base.random.t":"var r = base.random.t( 2.0 );\n","base.random.t.factory":"var rand = base.random.t.factory();\nvar r = rand( 5.0 );\nr = rand( 3.14 );\nrand = base.random.t.factory( 5.0 );\nr = rand();\nr = rand();\n","base.random.t.NAME":"var str = base.random.t.NAME\n","base.random.t.PRNG":"var prng = base.random.t.PRNG;\n","base.random.t.seed":"var seed = base.random.t.seed;\n","base.random.t.seedLength":"var len = base.random.t.seedLength;\n","base.random.t.state":"var r = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\nvar state = base.random.t.state\nr = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\nbase.random.t.state = state;\nr = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\n","base.random.t.stateLength":"var len = base.random.t.stateLength;\n","base.random.t.byteLength":"var sz = base.random.t.byteLength;\n","base.random.t.toJSON":"var o = base.random.t.toJSON()\n","base.random.triangular":"var r = base.random.triangular( 2.0, 5.0, 3.33 );\n","base.random.triangular.factory":"var rand = base.random.triangular.factory();\nvar r = rand( 0.0, 1.0, 0.5 );\nr = rand( -2.0, 2.0, 1.0 );\nrand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\nr = rand();\nr = rand();\n","base.random.triangular.NAME":"var str = base.random.triangular.NAME\n","base.random.triangular.PRNG":"var prng = base.random.triangular.PRNG;\n","base.random.triangular.seed":"var seed = base.random.triangular.seed;\n","base.random.triangular.seedLength":"var len = base.random.triangular.seedLength;\n","base.random.triangular.state":"var r = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nvar state = base.random.triangular.state\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nbase.random.triangular.state = state;\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\n","base.random.triangular.stateLength":"var len = base.random.triangular.stateLength;\n","base.random.triangular.byteLength":"var sz = base.random.triangular.byteLength;\n","base.random.triangular.toJSON":"var o = base.random.triangular.toJSON()\n","base.random.uniform":"var r = base.random.uniform( 2.0, 5.0 );\n","base.random.uniform.factory":"var rand = base.random.uniform.factory();\nvar r = rand( 0.0, 1.0 );\nr = rand( -2.0, 2.0 );\nrand = base.random.uniform.factory( 0.0, 1.0 );\nr = rand();\nr = rand();\n","base.random.uniform.NAME":"var str = base.random.uniform.NAME\n","base.random.uniform.PRNG":"var prng = base.random.uniform.PRNG;\n","base.random.uniform.seed":"var seed = base.random.uniform.seed;\n","base.random.uniform.seedLength":"var len = base.random.uniform.seedLength;\n","base.random.uniform.state":"var r = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nvar state = base.random.uniform.state\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nbase.random.uniform.state = state;\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\n","base.random.uniform.stateLength":"var len = base.random.uniform.stateLength;\n","base.random.uniform.byteLength":"var sz = base.random.uniform.byteLength;\n","base.random.uniform.toJSON":"var o = base.random.uniform.toJSON()\n","base.random.weibull":"var r = base.random.weibull( 2.0, 5.0 );\n","base.random.weibull.factory":"var rand = base.random.weibull.factory();\nvar r = rand( 0.1, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.weibull.factory( 0.1, 1.5 );\nr = rand();\nr = rand();\n","base.random.weibull.NAME":"var str = base.random.weibull.NAME\n","base.random.weibull.PRNG":"var prng = base.random.weibull.PRNG;\n","base.random.weibull.seed":"var seed = base.random.weibull.seed;\n","base.random.weibull.seedLength":"var len = base.random.weibull.seedLength;\n","base.random.weibull.state":"var r = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nvar state = base.random.weibull.state\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nbase.random.weibull.state = state;\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\n","base.random.weibull.stateLength":"var len = base.random.weibull.stateLength;\n","base.random.weibull.byteLength":"var sz = base.random.weibull.byteLength;\n","base.random.weibull.toJSON":"var o = base.random.weibull.toJSON()\n","base.reldiff":"var d = base.reldiff( 2.0, 5.0 )\nd = base.reldiff( -1.0, 3.14 )\nd = base.reldiff( -2.0, 5.0, 'max-abs' )\nd = base.reldiff( -2.0, 5.0, 'max' )\nd = base.reldiff( -2.0, 5.0, 'min-abs' )\nd = base.reldiff( -2.0, 5.0, 'min' )\nd = base.reldiff( -2.0, 5.0, 'mean-abs' )\nd = base.reldiff( -2.0, 5.0, 'mean' )\nd = base.reldiff( -2.0, 5.0, 'x' )\nd = base.reldiff( 5.0, -2.0, 'x' )\nd = base.reldiff( -2.0, 5.0, 'y' )\nd = base.reldiff( 5.0, -2.0, 'y' )\nfunction scale( x, y ) {\n var s;\n\n x = base.abs( x );\n y = base.abs( y );\n\n // Maximum absolute value:\n s = (x < y ) ? y : x;\n\n // Scale in units of epsilon:\n return s * EPS;\n };\nd = base.reldiff( 12.15, 12.149999999999999, scale )\n","base.rempio2":"var y = [ 0.0, 0.0 ];\nvar n = base.rempio2( 128.0, y )\nvar y1 = y[ 0 ]\nvar y2 = y[ 1 ]\n","base.risingFactorial":"var v = base.risingFactorial( 0.9, 5 )\nv = base.risingFactorial( -9.0, 3 )\nv = base.risingFactorial( 0.0, 2 )\nv = base.risingFactorial( 3.0, -2 )\n","base.rotl32":"var x = 2147483649;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotl32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.rotr32":"var x = 1;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotr32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.round":"var y = base.round( 3.14 )\ny = base.round( -4.2 )\ny = base.round( -4.6 )\ny = base.round( 9.5 )\ny = base.round( -0.0 )\n","base.round2":"var y = base.round2( 3.14 )\ny = base.round2( -4.2 )\ny = base.round2( -4.6 )\ny = base.round2( 9.5 )\ny = base.round2( 13.0 )\ny = base.round2( -13.0 )\ny = base.round2( -0.0 )\n","base.round10":"var y = base.round10( 3.14 )\ny = base.round10( -4.2 )\ny = base.round10( -4.6 )\ny = base.round10( 9.5 )\ny = base.round10( 13.0 )\ny = base.round10( -13.0 )\ny = base.round10( -0.0 )\n","base.roundb":"var y = base.roundb( 3.14159, -2, 10 )\ny = base.roundb( 3.14159, 0, 2 )\ny = base.roundb( 5.0, 1, 2 )\n","base.roundn":"var y = base.roundn( 3.14159, -2 )\ny = base.roundn( 3.14159, 0 )\ny = base.roundn( 12368.0, 3 )\n","base.roundsd":"var y = base.roundsd( 3.14159, 3 )\ny = base.roundsd( 3.14159, 1 )\ny = base.roundsd( 12368.0, 2 )\ny = base.roundsd( 0.0313, 2, 2 )\n","base.rsqrt":"var y = base.rsqrt( 4.0 )\ny = base.rsqrt( 100.0 )\ny = base.rsqrt( 0.0 )\ny = base.rsqrt( Infinity )\ny = base.rsqrt( -4.0 )\ny = base.rsqrt( NaN )\n","base.rsqrtf":"var y = base.rsqrtf( 4.0 )\ny = base.rsqrtf( 0.0 )\ny = base.rsqrtf( Infinity )\ny = base.rsqrtf( -4.0 )\ny = base.rsqrtf( NaN )\n","base.scalar2ndarray":"var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar v = x.get()\n","base.setHighWord":"var high = 1072693248 >>> 0;\nvar y = base.setHighWord( PINF, high )\n","base.setLowWord":"var low = 5 >>> 0;\nvar x = 3.14e201;\nvar y = base.setLowWord( x, low )\nvar low = 12345678;\nvar y = base.setLowWord( PINF, low )\ny = base.setLowWord( NINF, low )\ny = base.setLowWord( NaN, low )\n","base.sici":"var y = base.sici( 3.0 )\ny = base.sici( 0.0 )\ny = base.sici( -9.0 )\ny = base.sici( NaN )\n","base.sici.assign":"var out = new Float64Array( 2 );\nvar y = base.sici.assign( 3.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.signbit":"var bool = base.signbit( 4.0 )\nbool = base.signbit( -9.14e-34 )\nbool = base.signbit( 0.0 )\nbool = base.signbit( -0.0 )\n","base.signbitf":"var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\nbool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\nbool = base.signbitf( 0.0 )\nbool = base.signbitf( -0.0 )\n","base.significandf":"var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\ns = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\ns = base.significandf( base.float64ToFloat32( -3.14 ) )\ns = base.significandf( 0.0 )\ns = base.significandf( NaN )\n","base.signum":"var sign = base.signum( -5.0 )\nsign = base.signum( 5.0 )\nsign = base.signum( -0.0 )\nsign = base.signum( 0.0 )\nsign = base.signum( NaN )\n","base.signumf":"var sign = base.signumf( -5.0 )\nsign = base.signumf( 5.0 )\nsign = base.signumf( -0.0 )\nsign = base.signumf( 0.0 )\nsign = base.signumf( NaN )\n","base.sin":"var y = base.sin( 0.0 )\ny = base.sin( PI/2.0 )\ny = base.sin( -PI/6.0 )\ny = base.sin( NaN )\n","base.sinc":"var y = base.sinc( 0.5 )\ny = base.sinc( -1.2 )\ny = base.sinc( 0.0 )\ny = base.sinc( NaN )\n","base.sincos":"var y = base.sincos( 0.0 )\ny = base.sincos( PI/2.0 )\ny = base.sincos( -PI/6.0 )\ny = base.sincos( NaN )\nvar out = new Float64Array( 2 );\nvar v = base.sincos.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sincospi":"var y = base.sincospi( 0.0 )\ny = base.sincospi( 0.5 )\ny = base.sincospi( 0.1 )\ny = base.sincospi( NaN )\n","base.sincospi.assign":"var out = new Float64Array( 2 );\nvar v = base.sincospi.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sinh":"var y = base.sinh( 0.0 )\ny = base.sinh( 2.0 )\ny = base.sinh( -2.0 )\ny = base.sinh( NaN )\n","base.sinpi":"var y = base.sinpi( 0.0 )\ny = base.sinpi( 0.5 )\ny = base.sinpi( 0.9 )\ny = base.sinpi( NaN )\n","base.spence":"var y = base.spence( 3.0 )\ny = base.spence( 0.0 )\ny = base.spence( -9.0 )\ny = base.spence( NaN )\n","base.sqrt":"var y = base.sqrt( 4.0 )\ny = base.sqrt( 9.0 )\ny = base.sqrt( 0.0 )\ny = base.sqrt( -4.0 )\ny = base.sqrt( NaN )\n","base.sqrt1pm1":"var y = base.sqrt1pm1( 3.0 )\ny = base.sqrt1pm1( 0.5 )\ny = base.sqrt1pm1( 0.02 )\ny = base.sqrt1pm1( -0.5 )\ny = base.sqrt1pm1( -1.1 )\ny = base.sqrt1pm1( NaN )\n","base.sqrtf":"var y = base.sqrtf( 4.0 )\ny = base.sqrtf( 9.0 )\ny = base.sqrtf( 0.0 )\ny = base.sqrtf( -4.0 )\ny = base.sqrtf( NaN )\n","base.sqrtpi":"var y = base.sqrtpi( 4.0 )\ny = base.sqrtpi( 10.0 )\ny = base.sqrtpi( 0.0 )\ny = base.sqrtpi( -4.0 )\ny = base.sqrtpi( NaN )\n","base.strided.binary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary( [ x, y, z ], shape, strides, f );\nz\n","base.strided.binary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\nz\n","base.strided.binaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n","base.strided.binarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\nvar t = {\n 'default': base.add,\n 'complex64': base.caddf,\n 'complex128': base.cadd\n };\nvar out = base.strided.binarySignatureCallbacks( t, sigs )\n","base.strided.ccopy":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy( x.length, x, 1, y, 1 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imag( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy( 2, x, -2, y, 1 );\nz = y.get( 0 );\nre = realf( z )\nim = imag( z )\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.ccopy( 2, x1, -2, y1, 1 );\nz = y0.get( 2 );\nre = realf( z )\nim = imag( z )\n","base.strided.ccopy.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imag( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\nz = y.get( y.length-1 );\nre = realf( z )\nim = imag( z )\n","base.strided.cmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap( x.length, x, 1, y, 1, base.cidentityf );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\ny = new Complex64Array( x.length );\nbase.strided.cmap( 2, x, 2, y, -1, base.cidentityf );\nv = y.get( 0 )\nre = real( v )\nim = imag( v )\nvar x0 = new Complex64Array( xbuf );\nvar y0 = new Complex64Array( x0.length );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf );\nv = y1.get( 0 )\nre = real( v )\nim = imag( v )\n","base.strided.cmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\nx = new Complex64Array( xbuf );\ny = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\nv = y.get( y.length-1 )\nre = real( v )\nim = imag( v )\n","base.strided.cswap":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap( x.length, x, 1, y, 1 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap( 2, x, -2, y, 1 );\nz = y.get( 0 );\nre = realf( z )\nim = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cswap( 2, x1, -2, y1, 1 );\nz = y0.get( 2 );\nre = realf( z )\nim = imagf( z )\nz = x0.get( 1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cswap.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\nz = y.get( y.length-1 );\nre = realf( z )\nim = imagf( z )\nz = x.get( 1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cumax":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumax( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumax( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumax.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumaxabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumaxabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumaxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumin":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumin( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumin( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumin.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cuminabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cuminabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cuminabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.cuminabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs2":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs2.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dapx":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.dapx.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dapxsum( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dapxsum( N, 5.0, x1, stride )\n","base.strided.dapxsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dapxsum.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn( 3, 5.0, x1, 2)\n","base.strided.dapxsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dapxsumkbn2( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dapxsumkbn2( N, 5.0, x1, stride )\n","base.strided.dapxsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.dapxsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dapxsumors( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dapxsumors( N, 5.0, x1, stride )\n","base.strided.dapxsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dapxsumors.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.dapxsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dapxsumpw( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dapxsumpw( N, 5.0, x1, stride )\n","base.strided.dapxsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.dasum":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum( x.length, x, 1 )\ns = base.strided.dasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.dasum( 3, x1, 2 )\n","base.strided.dasum.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.dasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dasumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dasumpw( N, x1, stride )\n","base.strided.dasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dasumpw.ndarray( N, x, 2, 1 )\n","base.strided.daxpy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.daxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.daxpy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.dceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcopy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dcopy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumax( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcumax( N, x1, 2, y1, 1 )\ny0\n","base.strided.dcumax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcumaxabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.dcumaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumin( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcumin( N, x1, 2, y1, 1 )\ny0\n","base.strided.dcumin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcuminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcuminabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcuminabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.dcuminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcusumkbn( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcusumkbn( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcusumkbn2( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcusumkbn2( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcusumors( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcusumors( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcusumpw( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcusumpw( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ddeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.ddeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddot":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.ddot( 3, x1, -2, y1, 1 )\n","base.strided.ddot.ndarray":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dfill":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.dfill.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dfloor":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.dfloor.ndarray":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.dinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( x.length, x, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( 2, x, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap( 2, x1, -2, y1, 1, base.identity )\ny0\n","base.strided.dmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n","base.strided.dmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\nz0\n","base.strided.dmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n","base.strided.dmax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmax( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmax( N, x1, stride )\n","base.strided.dmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmax.ndarray( N, x, 2, 1 )\n","base.strided.dmaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmaxabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmaxabs( N, x1, stride )\n","base.strided.dmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmaxabs.ndarray( N, x, 2, 1 )\n","base.strided.dmaxabssorted":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmaxabssorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmaxabssorted( N, x1, stride )\n","base.strided.dmaxabssorted.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmaxabssorted.ndarray( N, x, 2, 1 )\n","base.strided.dmaxsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmaxsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmaxsorted( N, x1, stride )\n","base.strided.dmaxsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmaxsorted.ndarray( N, x, 2, 1 )\n","base.strided.dmean":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmean( N, x1, stride )\n","base.strided.dmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmean.ndarray( N, x, 2, 1 )\n","base.strided.dmeankbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeankbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeankbn( N, x1, stride )\n","base.strided.dmeankbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeankbn.ndarray( N, x, 2, 1 )\n","base.strided.dmeankbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeankbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeankbn2( N, x1, stride )\n","base.strided.dmeankbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n","base.strided.dmeanli":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanli( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanli( N, x1, stride )\n","base.strided.dmeanli.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanli.ndarray( N, x, 2, 1 )\n","base.strided.dmeanlipw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanlipw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanlipw( N, x1, stride )\n","base.strided.dmeanlipw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n","base.strided.dmeanors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanors( N, x1, stride )\n","base.strided.dmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dmeanpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanpn( N, x1, stride )\n","base.strided.dmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dmeanpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanpw( N, x1, stride )\n","base.strided.dmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanpw.ndarray( N, x, 2, 1 )\n","base.strided.dmeanstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanstdev( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanstdevpn( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvar":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanvar( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanvar.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvarpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanvarpn( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanvarpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanwd( N, x1, stride )\n","base.strided.dmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dmediansorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmediansorted( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dmediansorted( N, x1, 2 )\n","base.strided.dmediansorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmediansorted.ndarray( N, x, 2, 1 )\n","base.strided.dmidrange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmidrange( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmidrange( N, x1, stride )\n","base.strided.dmidrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmidrange.ndarray( N, x, 2, 1 )\n","base.strided.dmin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmin( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmin( N, x1, stride )\n","base.strided.dmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmin.ndarray( N, x, 2, 1 )\n","base.strided.dminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dminabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dminabs( N, x1, stride )\n","base.strided.dminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dminabs.ndarray( N, x, 2, 1 )\n","base.strided.dminsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dminsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dminsorted( N, x1, stride )\n","base.strided.dminsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dminsorted.ndarray( N, x, 2, 1 )\n","base.strided.dmskabs":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskabs2":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskdeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskdeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskfloor":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskfloor.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.dmskmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.dmskmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\nz0\n","base.strided.dmskmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n","base.strided.dmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dmskmax( N, x1, 2, mask1, 2 )\n","base.strided.dmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dmskmin( N, x1, 2, mask1, 2 )\n","base.strided.dmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dmskrange( N, x1, 2, mask1, 2 )\n","base.strided.dmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskrsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskrsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsksqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsksqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsktrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsktrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dnanasum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanasum( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanasum( N, x1, stride )\n","base.strided.dnanasum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanasum.ndarray( N, x, 2, 1 )\n","base.strided.dnanasumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanasumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanasumors( N, x1, stride )\n","base.strided.dnanasumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanasumors.ndarray( N, x, 2, 1 )\n","base.strided.dnanmax":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmax( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmax( N, x1, stride )\n","base.strided.dnanmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmax.ndarray( N, x, 2, 1 )\n","base.strided.dnanmaxabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmaxabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmaxabs( N, x1, stride )\n","base.strided.dnanmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmaxabs.ndarray( N, x, 2, 1 )\n","base.strided.dnanmean":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmean( N, x1, stride )\n","base.strided.dnanmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmean.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanors( N, x1, stride )\n","base.strided.dnanmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanpn( N, x1, stride )\n","base.strided.dnanmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanpw( N, x1, stride )\n","base.strided.dnanmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanwd( N, x1, stride )\n","base.strided.dnanmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dnanmin":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmin( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmin( N, x1, stride )\n","base.strided.dnanmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmin.ndarray( N, x, 2, 1 )\n","base.strided.dnanminabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanminabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanminabs( N, x1, stride )\n","base.strided.dnanminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanminabs.ndarray( N, x, 2, 1 )\n","base.strided.dnanmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnannsum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnannsum( N, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( N, x1, 2, out, 1 )\n","base.strided.dnannsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( N, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnannsumkbn( N, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( N, x1, 2, out, 1 )\n","base.strided.dnannsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnannsumkbn2( N, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( N, x1, 2, out, 1 )\n","base.strided.dnannsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( N, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnannsumors( N, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( N, x1, 2, out, 1 )\n","base.strided.dnannsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( N, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnannsumpw( N, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( N, x1, 2, out, 1 )\n","base.strided.dnannsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( N, x, 2, 1, out, 1, 0 )\n","base.strided.dnanrange":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanrange( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanrange( N, x1, stride )\n","base.strided.dnanrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanrange.ndarray( N, x, 2, 1 )\n","base.strided.dnanstdev":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdev( N, 1, x1, stride )\n","base.strided.dnanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevch":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevch( N, 1, x1, stride )\n","base.strided.dnanstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevpn( N, 1, x1, stride )\n","base.strided.dnanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevtk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevtk( N, 1, x1, stride )\n","base.strided.dnanstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevwd( N, 1, x1, stride )\n","base.strided.dnanstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevyc":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevyc( N, 1, x1, stride )\n","base.strided.dnanstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnansum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansum( 4, x1, 2 )\n","base.strided.dnansum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnansumkbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnansumkbn( N, x1, stride )\n","base.strided.dnansumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnansumkbn.ndarray( N, x, 2, 1 )\n","base.strided.dnansumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnansumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnansumkbn2( N, x1, stride )\n","base.strided.dnansumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnansumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.dnansumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnansumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnansumors( N, x1, stride )\n","base.strided.dnansumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnansumors.ndarray( N, x, 2, 1 )\n","base.strided.dnansumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnansumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnansumpw( N, x1, stride )\n","base.strided.dnansumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnansumpw.ndarray( N, x, 2, 1 )\n","base.strided.dnanvariance":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariance( N, 1, x1, stride )\n","base.strided.dnanvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancech":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancech( N, 1, x1, stride )\n","base.strided.dnanvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancepn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancepn( N, 1, x1, stride )\n","base.strided.dnanvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancetk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancetk( N, 1, x1, stride )\n","base.strided.dnanvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancewd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancewd( N, 1, x1, stride )\n","base.strided.dnanvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvarianceyc( N, 1, x1, stride )\n","base.strided.dnanvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnrm2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnrm2( 3, x1, 2 )\n","base.strided.dnrm2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.dramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.dramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.drange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.drange( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.drange( N, x1, stride )\n","base.strided.drange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.drange.ndarray( N, x, 2, 1 )\n","base.strided.drev":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.drev( 3, x1, 2 )\nx0\n","base.strided.drev.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.drev.ndarray( 3, x, 2, 1 )\n","base.strided.drsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.drsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.drsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsum( 3, 5.0, x1, 2 )\n","base.strided.dsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsapxsumpw( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsapxsumpw( N, 5.0, x1, stride )\n","base.strided.dsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.dscal":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.dscal.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\ndot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n","base.strided.dsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dsem":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsem( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsem( N, 1, x1, stride )\n","base.strided.dsem.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsem.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemch( N, 1, x1, stride )\n","base.strided.dsemch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsempn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsempn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsempn( N, 1, x1, stride )\n","base.strided.dsempn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemtk( N, 1, x1, stride )\n","base.strided.dsemtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemwd( N, 1, x1, stride )\n","base.strided.dsemwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemyc( N, 1, x1, stride )\n","base.strided.dsemyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmean( N, x1, stride )\n","base.strided.dsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmean.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanors( N, x1, stride )\n","base.strided.dsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanpn( N, x1, stride )\n","base.strided.dsmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanpw( N, x1, stride )\n","base.strided.dsmeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanwd( N, x1, stride )\n","base.strided.dsmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmean( N, x1, stride )\n","base.strided.dsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmean.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanors( N, x1, stride )\n","base.strided.dsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanpn( N, x1, stride )\n","base.strided.dsnanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanwd( N, x1, stride )\n","base.strided.dsnanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dsnannsumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors( x.length, x, 1, out, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnannsumors( N, x, 2, out, 1 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( N, x1, 2, out, 1 )\n","base.strided.dsnannsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( N, x, 2, 1, out, 1, 0 )\n","base.strided.dsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnansum( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnansum( N, x1, stride )\n","base.strided.dsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnansum.ndarray( N, x, 2, 1 )\n","base.strided.dsnansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnansumors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnansumors( N, x1, stride )\n","base.strided.dsnansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnansumors.ndarray( N, x, 2, 1 )\n","base.strided.dsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnansumpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnansumpw( N, x1, stride )\n","base.strided.dsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnansumpw.ndarray( N, x, 2, 1 )\n","base.strided.dsort2hp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2hp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2ins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2ins( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2ins( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2ins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2sh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2sh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsorthp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsorthp( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsorthp( N, 1, x1, 2 )\nx0\n","base.strided.dsorthp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsortins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortins( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsortins( N, 1, x1, 2 )\nx0\n","base.strided.dsortins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsortsh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsortsh( N, 1, x1, 2 )\nx0\n","base.strided.dsortsh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssum( 3, x1, 2 )\n","base.strided.dssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssum.ndarray(3, x, 2, 1 )\n","base.strided.dssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dssumors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dssumors( N, x1, stride )\n","base.strided.dssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dssumors.ndarray( N, x, 2, 1 )\n","base.strided.dssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dssumpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dssumpw( N, x1, stride )\n","base.strided.dssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dssumpw.ndarray( N, x, 2, 1 )\n","base.strided.dstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdev( N, 1, x1, stride )\n","base.strided.dstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevch( N, 1, x1, stride )\n","base.strided.dstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevpn( N, 1, x1, stride )\n","base.strided.dstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevtk( N, 1, x1, stride )\n","base.strided.dstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevwd( N, 1, x1, stride )\n","base.strided.dstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevyc( N, 1, x1, stride )\n","base.strided.dstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsum( 3, x1, 2 )\n","base.strided.dsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsum.ndarray( 3, x, 2, 1 )\n","base.strided.dsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsumkbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsumkbn( N, x1, stride )\n","base.strided.dsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsumkbn.ndarray( N, x, 2, 1 )\n","base.strided.dsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsumkbn2( N, x1, stride )\n","base.strided.dsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.dsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsumors( N, x1, stride )\n","base.strided.dsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsumors.ndarray( N, x, 2, 1 )\n","base.strided.dsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsumpw( N, x1, stride )\n","base.strided.dsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsumpw.ndarray( N, x, 2, 1 )\n","base.strided.dsvariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsvariance( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsvariance( N, 1, x1, stride )\n","base.strided.dsvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsvariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsvariancepn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsvariancepn( N, 1, x1, stride )\n","base.strided.dsvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dswap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dswap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dtrunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.dtrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dvariance":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariance( N, 1, x1, stride )\n","base.strided.dvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancech":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancech( N, 1, x1, stride )\n","base.strided.dvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancepn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancepn( N, 1, x1, stride )\n","base.strided.dvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancetk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancetk( N, 1, x1, stride )\n","base.strided.dvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancewd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancewd( N, 1, x1, stride )\n","base.strided.dvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvarianceyc( N, 1, x1, stride )\n","base.strided.dvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvarm":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarm( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarm( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarm.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.dvarmpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmpn( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarmpn( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarmpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.dvarmtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmtk( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarmtk( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarmtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.gapx":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gapx( x.length, alpha, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.gapx( N, alpha, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nalpha = 5.0;\nstride = 2;\nbase.strided.gapx( N, alpha, x1, stride )\nx0\n","base.strided.gapx.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n","base.strided.gapxsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsum( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsum( N, 5.0, x1, stride )\n","base.strided.gapxsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumkbn( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumkbn( N, 5.0, x1, stride )\n","base.strided.gapxsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumkbn2( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumkbn2( N, 5.0, x1, stride )\n","base.strided.gapxsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumors( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumors( N, 5.0, x1, stride )\n","base.strided.gapxsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumpw( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumpw( N, 5.0, x1, stride )\n","base.strided.gapxsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gasum":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum( x.length, x, 1 )\ns = base.strided.gasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.gasum( 3, x1, 2 )\n","base.strided.gasum.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\ns = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.gasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gasumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gasumpw( N, x1, stride )\n","base.strided.gasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.gasumpw.ndarray( N, x, 2, 1 )\n","base.strided.gaxpy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.gaxpy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcopy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gcopy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusum":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusum( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusum( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumkbn( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn2( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumkbn2( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumors":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumors( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumors( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumpw":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumpw( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumpw( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gdot":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.gdot( 3, x1, -2, y1, 1 )\n","base.strided.gdot.ndarray":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nout = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.gfill":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfill( N, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gfill( N, 5.0, x1, 2 )\nx0\n","base.strided.gfill.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gfillBy":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy( x.length, x, 1, fill )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfillBy( N, x, 2, fill )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gfillBy( N, x1, 2, fill )\nx0\n","base.strided.gfillBy.ndarray":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n","base.strided.gnannsumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( x.length, x, 1, out, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nout = [ 0.0, 0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnannsumkbn( N, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( N, x1, 2, out, 1 )\n","base.strided.gnannsumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n","base.strided.gnansum":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansum( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansum( N, x1, stride )\n","base.strided.gnansum.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansum.ndarray( N, x, 2, 1 )\n","base.strided.gnansumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumkbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumkbn( N, x1, stride )\n","base.strided.gnansumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n","base.strided.gnansumkbn2":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumkbn2( N, x1, stride )\n","base.strided.gnansumkbn2.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.gnansumors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumors( N, x1, stride )\n","base.strided.gnansumors.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumors.ndarray( N, x, 2, 1 )\n","base.strided.gnansumpw":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumpw( N, x1, stride )\n","base.strided.gnansumpw.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumpw.ndarray( N, x, 2, 1 )\n","base.strided.gnrm2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnrm2( 3, x1, 2 )\n","base.strided.gnrm2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.grev":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev( x.length, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.grev( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.grev( N, x1, 2 )\nx0\n","base.strided.grev.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.grev.ndarray( N, x, 2, 1 )\n","base.strided.gscal":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gscal( x.length, alpha, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.gscal.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gsort2hp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2hp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2ins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2ins( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2ins( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2ins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2sh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2sh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsorthp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsorthp( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsorthp( N, 1, x1, 2 )\nx0\n","base.strided.gsorthp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsortins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortins( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsortins( N, 1, x1, 2 )\nx0\n","base.strided.gsortins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsortsh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortsh( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsortsh( N, 1, x1, 2 )\nx0\n","base.strided.gsortsh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsum( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsum( N, x1, stride )\n","base.strided.gsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsum.ndarray( N, x, 2, 1 )\n","base.strided.gsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumkbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumkbn( N, x1, stride )\n","base.strided.gsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumkbn.ndarray( N, x, 2, 1 )\n","base.strided.gsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumkbn2( N, x1, stride )\n","base.strided.gsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.gsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumors( N, x1, stride )\n","base.strided.gsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumors.ndarray( N, x, 2, 1 )\n","base.strided.gsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumpw( N, x1, stride )\n","base.strided.gsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumpw.ndarray( N, x, 2, 1 )\n","base.strided.gswap":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gswap.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.mapBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\ny0\n","base.strided.mapBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n","base.strided.mapBy2":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\nz0\n","base.strided.mapBy2.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 1.0, 1.0, 2.0, 2.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n","base.strided.max":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.max( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.max( N, x1, stride )\n","base.strided.max.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.max.ndarray( N, x, 2, 1 )\n","base.strided.maxabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.maxabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.maxabs( N, x1, stride )\n","base.strided.maxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxabs.ndarray( N, x, 2, 1 )\n","base.strided.maxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.maxBy( N, x1, 2, accessor )\n","base.strided.maxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.maxsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.maxsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.maxsorted( N, x1, stride )\n","base.strided.maxsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxsorted.ndarray( N, x, 2, 1 )\n","base.strided.mean":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.mean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.mean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.mean( N, x1, stride )\n","base.strided.mean.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.mean.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mean.ndarray( N, x, 2, 1 )\n","base.strided.meankbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meankbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meankbn( N, x1, stride )\n","base.strided.meankbn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meankbn.ndarray( N, x, 2, 1 )\n","base.strided.meankbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meankbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meankbn2( N, x1, stride )\n","base.strided.meankbn2.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meankbn2.ndarray( N, x, 2, 1 )\n","base.strided.meanors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanors( N, x1, stride )\n","base.strided.meanors.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanors.ndarray( N, x, 2, 1 )\n","base.strided.meanpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanpn( N, x1, stride )\n","base.strided.meanpn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanpn.ndarray( N, x, 2, 1 )\n","base.strided.meanpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanpw( N, x1, stride )\n","base.strided.meanpw.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanpw.ndarray( N, x, 2, 1 )\n","base.strided.meanwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanwd( N, x1, stride )\n","base.strided.meanwd.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanwd.ndarray( N, x, 2, 1 )\n","base.strided.mediansorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mediansorted( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mediansorted( N, x1, 2 )\n","base.strided.mediansorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mediansorted.ndarray( N, x, 2, 1 )\n","base.strided.min":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.min( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.min( N, x1, stride )\n","base.strided.min.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.min.ndarray( N, x, 2, 1 )\n","base.strided.minabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.minabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.minabs( N, x1, stride )\n","base.strided.minabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minabs.ndarray( N, x, 2, 1 )\n","base.strided.minBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.minBy( N, x1, 2, accessor )\n","base.strided.minBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.minsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.minsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.minsorted( N, x1, stride )\n","base.strided.minsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minsorted.ndarray( N, x, 2, 1 )\n","base.strided.mskmax":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskmax( N, x1, 2, mask1, 2 )\n","base.strided.mskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskmin":"var x = [ 1.0, -2.0, -4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskmin( N, x1, 2, mask1, 2 )\n","base.strided.mskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskrange":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskrange( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskrange( N, x1, 2, mask1, 2 )\n","base.strided.mskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskunary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nbase.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\ny\n","base.strided.mskunary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nbase.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.mskunaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.mskunaryDtypeSignatures( dt, dt )\n","base.strided.mskunarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.mskunarySignatureCallbacks( t, sigs )\n","base.strided.nanmax":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmax( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmax( N, x1, stride )\n","base.strided.nanmax.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmax.ndarray( N, x, 2, 1 )\n","base.strided.nanmaxabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmaxabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmaxabs( N, x1, stride )\n","base.strided.nanmaxabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n","base.strided.nanmaxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmaxBy( N, x1, 2, accessor )\n","base.strided.nanmaxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanmean":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmean( N, x1, stride )\n","base.strided.nanmean.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmean.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanors( N, x1, stride )\n","base.strided.nanmeanors.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanpn( N, x1, stride )\n","base.strided.nanmeanpn.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanwd( N, x1, stride )\n","base.strided.nanmeanwd.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.nanmin":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmin( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmin( N, x1, stride )\n","base.strided.nanmin.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmin.ndarray( N, x, 2, 1 )\n","base.strided.nanminabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanminabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanminabs( N, x1, stride )\n","base.strided.nanminabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminabs.ndarray( N, x, 2, 1 )\n","base.strided.nanminBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanminBy( N, x1, 2, accessor )\n","base.strided.nanminBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanmskmax":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.nanmskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskmin":"var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.nanmskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskrange":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskrange( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.nanmskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanrange":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanrange( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanrange( N, x1, stride )\n","base.strided.nanrange.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrange.ndarray( N, x, 2, 1 )\n","base.strided.nanrangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanrangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrangeBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanrangeBy( N, x1, 2, accessor )\n","base.strided.nanrangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanstdev":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdev( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdev( N, 1, x1, 2 )\n","base.strided.nanstdev.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevch":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevch( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevch( N, 1, x1, 2 )\n","base.strided.nanstdevch.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevpn( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevpn( N, 1, x1, 2 )\n","base.strided.nanstdevpn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevtk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevtk( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevtk( N, 1, x1, 2 )\n","base.strided.nanstdevtk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevwd( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevwd( N, 1, x1, 2 )\n","base.strided.nanstdevwd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevyc( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevyc( N, 1, x1, 2 )\n","base.strided.nanstdevyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariance":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariance( N, 1, x1, stride )\n","base.strided.nanvariance.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancech":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancech( N, 1, x1, stride )\n","base.strided.nanvariancech.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancepn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancepn( N, 1, x1, stride )\n","base.strided.nanvariancepn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancetk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancetk( N, 1, x1, stride )\n","base.strided.nanvariancetk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancewd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancewd( N, 1, x1, stride )\n","base.strided.nanvariancewd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvarianceyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvarianceyc( N, 1, x1, stride )\n","base.strided.nanvarianceyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.nullary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary( [ x ], shape, strides, fcn );\nx\n","base.strided.nullary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1 ];\nvar offsets = [ 0 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\nx\n","base.strided.quaternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\nu\n","base.strided.quaternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\nu\n","base.strided.quinary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\nv\n","base.strided.quinary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\nv\n","base.strided.range":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.range( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.range( N, x1, stride )\n","base.strided.range.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.range.ndarray( N, x, 2, 1 )\n","base.strided.rangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.rangeBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.rangeBy( N, x1, 2, accessor )\n","base.strided.rangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.sabs":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sabs2":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs2.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sapx":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.sapx.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsum( 3, 5.0, x1, 2 )\n","base.strided.sapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n","base.strided.sapxsumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sapxsumkbn2( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sapxsumkbn2( N, 5.0, x1, stride )\n","base.strided.sapxsumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.sapxsumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sapxsumors( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sapxsumors( N, 5.0, x1, stride )\n","base.strided.sapxsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.sapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.sapxsumpw( 3, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sapxsumpw( 3, 5.0, x1, stride )\n","base.strided.sapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sasum":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum( x.length, x, 1 )\ns = base.strided.sasum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.sasum( 3, x1, 2 )\n","base.strided.sasum.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.sasumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sasumpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sasumpw( N, x1, stride )\n","base.strided.sasumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sasumpw.ndarray( N, x, 2, 1 )\n","base.strided.saxpy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.saxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.saxpy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.scbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.scbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.sceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scopy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.scopy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumax( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scumax( N, x1, 2, y1, 1 )\ny0\n","base.strided.scumax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scumaxabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.scumaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumin( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scumin( N, x1, 2, y1, 1 )\ny0\n","base.strided.scumin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scuminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scuminabs( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scuminabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.scuminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumkbn( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumkbn2( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sdeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.sdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdot( 3, x1, -2, y1, 1 )\n","base.strided.sdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsum( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n","base.strided.sdsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsmean( N, x1, stride )\n","base.strided.sdsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsmean.ndarray( N, x, 2, 1 )\n","base.strided.sdsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsmeanors( N, x1, stride )\n","base.strided.sdsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n","base.strided.sdsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmean( N, x1, stride )\n","base.strided.sdsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n","base.strided.sdsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmeanors( N, x1, stride )\n","base.strided.sdsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.sdsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnansum( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnansum( N, x1, stride )\n","base.strided.sdsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnansum.ndarray( N, x, 2, 1 )\n","base.strided.sdsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnansumpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnansumpw( N, x1, stride )\n","base.strided.sdsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnansumpw.ndarray( N, x, 2, 1 )\n","base.strided.sdssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdssum( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdssum( N, x1, stride )\n","base.strided.sdssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdssum.ndarray( N, x, 2, 1 )\n","base.strided.sdssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdssumpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdssumpw( N, x1, stride )\n","base.strided.sdssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdssumpw.ndarray( N, x, 2, 1 )\n","base.strided.sfill":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sfill( N, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.sfill( N, 5.0, x1, 2 )\nx0\n","base.strided.sfill.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sfill.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.sfloor":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.sfloor.ndarray":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.sinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.smap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( x.length, x, 1, y, 1, base.identityf )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( 2, x, 2, y, -1, base.identityf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap( 2, x1, -2, y1, 1, base.identityf )\ny0\n","base.strided.smap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n","base.strided.smap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\nz0\n","base.strided.smap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n","base.strided.smax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smax( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smax( N, x1, stride )\n","base.strided.smax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smax.ndarray( N, x, 2, 1 )\n","base.strided.smaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smaxabs( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smaxabs( N, x1, stride )\n","base.strided.smaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smaxabs.ndarray( N, x, 2, 1 )\n","base.strided.smaxabssorted":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smaxabssorted( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smaxabssorted( N, x1, stride )\n","base.strided.smaxabssorted.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smaxabssorted.ndarray( N, x, 2, 1 )\n","base.strided.smaxsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smaxsorted( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smaxsorted( N, x1, stride )\n","base.strided.smaxsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smaxsorted.ndarray( N, x, 2, 1 )\n","base.strided.smean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smean( N, x1, stride )\n","base.strided.smean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smean.ndarray( N, x, 2, 1 )\n","base.strided.smeankbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeankbn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeankbn( N, x1, stride )\n","base.strided.smeankbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeankbn.ndarray( N, x, 2, 1 )\n","base.strided.smeankbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeankbn2( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeankbn2( N, x1, stride )\n","base.strided.smeankbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeankbn2.ndarray( N, x, 2, 1 )\n","base.strided.smeanli":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanli( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanli( N, x1, stride )\n","base.strided.smeanli.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanli.ndarray( N, x, 2, 1 )\n","base.strided.smeanlipw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanlipw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanlipw( N, x1, stride )\n","base.strided.smeanlipw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanlipw.ndarray( N, x, 2, 1 )\n","base.strided.smeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanors( N, x1, stride )\n","base.strided.smeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanors.ndarray( N, x, 2, 1 )\n","base.strided.smeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanpn( N, x1, stride )\n","base.strided.smeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanpn.ndarray( N, x, 2, 1 )\n","base.strided.smeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanpw( N, x1, stride )\n","base.strided.smeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanpw.ndarray( N, x, 2, 1 )\n","base.strided.smeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanwd( N, x1, stride )\n","base.strided.smeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanwd.ndarray( N, x, 2, 1 )\n","base.strided.smediansorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smediansorted( N, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smediansorted( N, x1, 2 )\n","base.strided.smediansorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smediansorted.ndarray( N, x, 2, 1 )\n","base.strided.smidrange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smidrange( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smidrange( N, x1, stride )\n","base.strided.smidrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smidrange.ndarray( N, x, 2, 1 )\n","base.strided.smin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smin( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smin( N, x1, stride )\n","base.strided.smin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smin.ndarray( N, x, 2, 1 )\n","base.strided.sminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sminabs( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sminabs( N, x1, stride )\n","base.strided.sminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sminabs.ndarray( N, x, 2, 1 )\n","base.strided.sminsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sminsorted( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sminsorted( N, x1, stride )\n","base.strided.sminsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sminsorted.ndarray( N, x, 2, 1 )\n","base.strided.smskabs":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskabs2":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs2.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskcbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskcbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskfloor":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskfloor.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskmap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.smskmap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.smskmap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\nz0\n","base.strided.smskmap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n","base.strided.smskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmax( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smskmax( N, x1, 2, mask1, 2 )\n","base.strided.smskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.smskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmin( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smskmin( N, x1, 2, mask1, 2 )\n","base.strided.smskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.smskramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskrange( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smskrange( N, x1, 2, mask1, 2 )\n","base.strided.smskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.smskrsqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskrsqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsksqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsksqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsktrunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsktrunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.snanmax":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmax( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmax( N, x1, stride )\n","base.strided.snanmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmax.ndarray( N, x, 2, 1 )\n","base.strided.snanmaxabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmaxabs( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmaxabs( N, x1, stride )\n","base.strided.snanmaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmaxabs.ndarray( N, x, 2, 1 )\n","base.strided.snanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmean( N, x1, stride )\n","base.strided.snanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmean.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanors( N, x1, stride )\n","base.strided.snanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanpn( N, x1, stride )\n","base.strided.snanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanwd( N, x1, stride )\n","base.strided.snanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.snanmin":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmin( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmin( N, x1, stride )\n","base.strided.snanmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmin.ndarray( N, x, 2, 1 )\n","base.strided.snanminabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanminabs( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanminabs( N, x1, stride )\n","base.strided.snanminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanminabs.ndarray( N, x, 2, 1 )\n","base.strided.snanmskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.snanmskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.snanmskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.snanmskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanrange":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanrange( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanrange( N, x1, stride )\n","base.strided.snanrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanrange.ndarray( N, x, 2, 1 )\n","base.strided.snanstdev":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdev( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdev( N, 1, x1, stride )\n","base.strided.snanstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevch":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevch( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevch( N, 1, x1, stride )\n","base.strided.snanstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevpn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevpn( N, 1, x1, stride )\n","base.strided.snanstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevtk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevtk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevtk( N, 1, x1, stride )\n","base.strided.snanstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevwd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevwd( N, 1, x1, stride )\n","base.strided.snanstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevyc( N, 1, x1, stride )\n","base.strided.snanstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snansum( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snansum( N, x1, stride )\n","base.strided.snansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snansum.ndarray( N, x, 2, 1 )\n","base.strided.snansumkbn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snansumkbn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snansumkbn( N, x1, stride )\n","base.strided.snansumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snansumkbn.ndarray( N, x, 2, 1 )\n","base.strided.snansumkbn2":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snansumkbn2( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snansumkbn2( N, x1, stride )\n","base.strided.snansumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snansumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.snansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snansumors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snansumors( N, x1, stride )\n","base.strided.snansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snansumors.ndarray( N, x, 2, 1 )\n","base.strided.snansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snansumpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snansumpw( N, x1, stride )\n","base.strided.snansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snansumpw.ndarray( N, x, 2, 1 )\n","base.strided.snanvariance":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariance( N, 1, x1, 2 )\n","base.strided.snanvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancech":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancech( N, 1, x1, 2 )\n","base.strided.snanvariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancepn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancepn( N, 1, x1, 2 )\n","base.strided.snanvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancetk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancetk( N, 1, x1, 2 )\n","base.strided.snanvariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancewd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancewd( N, 1, x1, 2 )\n","base.strided.snanvariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvarianceyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x1, 2 )\n","base.strided.snanvarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snrm2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.snrm2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snrm2( 3, x1, 2 )\n","base.strided.snrm2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.snrm2.ndarray( 3, x, 2, 1 )\n","base.strided.sramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.sramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.srange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.srange( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.srange( N, x1, stride )\n","base.strided.srange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.srange.ndarray( N, x, 2, 1 )\n","base.strided.srev":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srev( 3, x1, 2 )\nx0\n","base.strided.srev.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.srev.ndarray( 3, x, 2, 1 )\n","base.strided.srsqrt":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.srsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.srsqrt.ndarray":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sscal":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.sscal.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.ssort2hp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2hp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2ins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssort2ins( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssort2ins( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2ins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2sh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2sh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssorthp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssorthp( N, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssorthp( N, 1, x1, 2 )\nx0\n","base.strided.ssorthp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssorthp.ndarray( N, 1, x, 2, 1 )\n","base.strided.ssortins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssortins( N, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssortins( N, 1, x1, 2 )\nx0\n","base.strided.ssortins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssortins.ndarray( N, 1, x, 2, 1 )\n","base.strided.ssortsh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssortsh( N, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssortsh( N, 1, x1, 2 )\nx0\n","base.strided.ssortsh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.ssqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.ssqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sstdev":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdev( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdev( N, 1, x1, stride )\n","base.strided.sstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevch":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevch( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevch( N, 1, x1, stride )\n","base.strided.sstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevpn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevpn( N, 1, x1, stride )\n","base.strided.sstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevtk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevtk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevtk( N, 1, x1, stride )\n","base.strided.sstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevwd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevwd( N, 1, x1, stride )\n","base.strided.sstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevyc( N, 1, x1, stride )\n","base.strided.sstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.ssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.ssum( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.ssum( N, x1, stride )\n","base.strided.ssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssum.ndarray( N, x, 2, 1 )\n","base.strided.ssumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn( 3, x1, 2 )\n","base.strided.ssumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn2( 3, x1, 2 )\n","base.strided.ssumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.ssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumors( 3, x1, 2 )\n","base.strided.ssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumors.ndarray( 3, x, 2, 1 )\n","base.strided.ssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumpw( 3, x1, 2 )\n","base.strided.ssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sswap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.sswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.sswap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.stdev":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdev( N, 1, x1, stride )\n","base.strided.stdev.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevch":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevch( N, 1, x1, stride )\n","base.strided.stdevch.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevpn( N, 1, x1, stride )\n","base.strided.stdevpn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevtk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevtk( N, 1, x1, stride )\n","base.strided.stdevtk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevwd( N, 1, x1, stride )\n","base.strided.stdevwd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevyc( N, 1, x1, stride )\n","base.strided.stdevyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.strunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.strunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.strunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.svariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariance( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariance( N, 1, x1, stride )\n","base.strided.svariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancech":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancech( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancech( N, 1, x1, stride )\n","base.strided.svariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancepn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancepn( N, 1, x1, stride )\n","base.strided.svariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancetk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancetk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancetk( N, 1, x1, stride )\n","base.strided.svariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancewd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancewd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancewd( N, 1, x1, stride )\n","base.strided.svariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.svarianceyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svarianceyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svarianceyc( N, 1, x1, stride )\n","base.strided.svarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.ternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary( [ x, y, z, w ], shape, strides, f );\nw\n","base.strided.ternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\nw\n","base.strided.unary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nbase.strided.unary( [ x, y ], shape, strides, base.abs );\ny\n","base.strided.unary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar offsets = [ 0, 0 ];\nbase.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.unaryBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nsh = [ 2 ];\nst = [ -2, 1 ];\nbase.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\ny1\ny0\n","base.strided.unaryBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nvar o = [ 0, 0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\no = [ 1, y.length-1 ];\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\n","base.strided.unaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.unaryDtypeSignatures( dt, dt )\n","base.strided.unarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.unaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.unarySignatureCallbacks( t, sigs )\n","base.strided.variance":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variance( N, 1, x1, stride )\n","base.strided.variance.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variance.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancech":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancech( N, 1, x1, stride )\n","base.strided.variancech.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancepn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancepn( N, 1, x1, stride )\n","base.strided.variancepn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancetk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancetk( N, 1, x1, stride )\n","base.strided.variancetk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancewd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancewd( N, 1, x1, stride )\n","base.strided.variancewd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.varianceyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.varianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.varianceyc( N, 1, x1, stride )\n","base.strided.varianceyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.zmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap( x.length, x, 1, y, 1, base.cidentity );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\ny = new Complex128Array( x.length );\nbase.strided.zmap( 2, x, 2, y, -1, base.cidentity );\nv = y.get( 0 )\nre = real( v )\nim = imag( v )\nvar x0 = new Complex128Array( xbuf );\nvar y0 = new Complex128Array( x0.length );\nvar x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.zmap( 2, x1, -2, y1, 1, base.cidentity );\nv = y1.get( 0 )\nre = real( v )\nim = imag( v )\n","base.strided.zmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\nx = new Complex128Array( xbuf );\ny = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\nv = y.get( y.length-1 )\nre = real( v )\nim = imag( v )\n","base.sub":"var v = base.sub( -1.0, 5.0 )\nv = base.sub( 2.0, 5.0 )\nv = base.sub( 0.0, 5.0 )\nv = base.sub( -0.0, 0.0 )\nv = base.sub( NaN, NaN )\n","base.subf":"var v = base.subf( -1.0, 5.0 )\nv = base.subf( 2.0, 5.0 )\nv = base.subf( 0.0, 5.0 )\nv = base.subf( -0.0, 0.0 )\nv = base.subf( NaN, NaN )\n","base.sumSeries":"function* geometricSeriesGenerator( x ) {\n var exponent = 0;\n while ( true ) {\n yield Math.pow( x, exponent );\n exponent += 1;\n }\n };\nvar gen = geometricSeriesGenerator( 0.9 );\nvar out = base.sumSeries( gen )\nfunction geometricSeriesClosure( x ) {\n var exponent = -1;\n return function() {\n exponent += 1;\n return Math.pow( x, exponent );\n };\n };\ngen = geometricSeriesClosure( 0.9 );\nout = base.sumSeries( gen )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n","base.tan":"var y = base.tan( 0.0 )\ny = base.tan( -PI/4.0 )\ny = base.tan( PI/4.0 )\ny = base.tan( NaN )\n","base.tanh":"var y = base.tanh( 0.0 )\nvar y = base.tanh( -0.0 )\ny = base.tanh( 2.0 )\ny = base.tanh( -2.0 )\ny = base.tanh( NaN )\n","base.toBinaryString":"var str = base.toBinaryString( 4.0 )\nstr = base.toBinaryString( PI )\nstr = base.toBinaryString( -1.0e308 )\nstr = base.toBinaryString( -3.14e-320 )\nstr = base.toBinaryString( 5.0e-324 )\nstr = base.toBinaryString( 0.0 )\nstr = base.toBinaryString( -0.0 )\nstr = base.toBinaryString( NaN )\nstr = base.toBinaryString( PINF )\nstr = base.toBinaryString( NINF )\n","base.toBinaryStringf":"var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( PI ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\nstr = base.toBinaryStringf( 0.0 )\nstr = base.toBinaryStringf( -0.0 )\nstr = base.toBinaryStringf( NaN )\nstr = base.toBinaryStringf( FLOAT32_PINF )\nstr = base.toBinaryStringf( FLOAT32_NINF )\n","base.toBinaryStringUint8":"var a = new Uint8Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint8( a[ 0 ] )\nstr = base.toBinaryStringUint8( a[ 1 ] )\nstr = base.toBinaryStringUint8( a[ 2 ] )\n","base.toBinaryStringUint16":"var a = new Uint16Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint16( a[ 0 ] )\nstr = base.toBinaryStringUint16( a[ 1 ] )\nstr = base.toBinaryStringUint16( a[ 2 ] )\n","base.toBinaryStringUint32":"var a = new Uint32Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint32( a[ 0 ] )\nstr = base.toBinaryStringUint32( a[ 1 ] )\nstr = base.toBinaryStringUint32( a[ 2 ] )\n","base.toWordf":"var f32 = base.float64ToFloat32( 1.337 )\nvar w = base.toWordf( f32 )\n","base.toWords":"var w = base.toWords( 3.14e201 )\n","base.toWords.assign":"var out = new Uint32Array( 2 );\nvar w = base.toWords.assign( 3.14e201, out, 1, 0 )\nvar bool = ( w === out )\n","base.transpose":"var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nvar sh = x.shape\nvar y = base.transpose( x )\nsh = y.shape\nvar bool = ( x.data === y.data )\nbool = ( x.get( 0, 1 ) === y.get( 1, 0 ) )\n","base.tribonacci":"var y = base.tribonacci( 0 )\ny = base.tribonacci( 1 )\ny = base.tribonacci( 2 )\ny = base.tribonacci( 3 )\ny = base.tribonacci( 4 )\ny = base.tribonacci( 64 )\ny = base.tribonacci( NaN )\n","base.trigamma":"var y = base.trigamma( -2.5 )\ny = base.trigamma( 1.0 )\ny = base.trigamma( 10.0 )\ny = base.trigamma( NaN )\ny = base.trigamma( -1.0 )\n","base.trunc":"var y = base.trunc( 3.14 )\ny = base.trunc( -4.2 )\ny = base.trunc( -4.6 )\ny = base.trunc( 9.5 )\ny = base.trunc( -0.0 )\n","base.trunc2":"var y = base.trunc2( 3.14 )\ny = base.trunc2( -4.2 )\ny = base.trunc2( -4.6 )\ny = base.trunc2( 9.5 )\ny = base.trunc2( 13.0 )\ny = base.trunc2( -13.0 )\ny = base.trunc2( -0.0 )\n","base.trunc10":"var y = base.trunc10( 3.14 )\ny = base.trunc10( -4.2 )\ny = base.trunc10( -4.6 )\ny = base.trunc10( 9.5 )\ny = base.trunc10( 13.0 )\ny = base.trunc10( -13.0 )\ny = base.trunc10( -0.0 )\n","base.truncb":"var y = base.truncb( 3.14159, -4, 10 )\ny = base.truncb( 3.14159, 0, 2 )\ny = base.truncb( 5.0, 1, 2 )\n","base.truncf":"var y = base.truncf( 3.14 )\ny = base.truncf( -4.2 )\ny = base.truncf( -4.6 )\ny = base.truncf( 9.5 )\ny = base.truncf( -0.0 )\n","base.truncn":"var y = base.truncn( 3.14159, -4 )\ny = base.truncn( 3.14159, 0 )\ny = base.truncn( 12368.0, 3 )\n","base.truncsd":"var y = base.truncsd( 3.14159, 5 )\ny = base.truncsd( 3.14159, 1 )\ny = base.truncsd( 12368.0, 2 )\ny = base.truncsd( 0.0313, 2, 2 )\n","base.umul":"var v = base.umul( 10>>>0, 4>>>0 )\n","base.umuldw":"var v = base.umuldw( 1, 10 )\n","base.umuldw.assign":"var out = [ 0, 0 ];\nvar v = base.umuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.uint32ToInt32":"var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\ny = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n","base.vercos":"var y = base.vercos( 3.14 )\ny = base.vercos( -4.2 )\ny = base.vercos( -4.6 )\ny = base.vercos( 9.5 )\ny = base.vercos( -0.0 )\n","base.versin":"var y = base.versin( 3.14 )\ny = base.versin( -4.2 )\ny = base.versin( -4.6 )\ny = base.versin( 9.5 )\ny = base.versin( -0.0 )\n","base.wrap":"var y = base.wrap( 3.14, 0.0, 5.0 )\ny = base.wrap( -3.14, 0.0, 5.0 )\ny = base.wrap( 3.14, 0.0, 3.0 )\ny = base.wrap( -0.0, 0.0, 5.0 )\ny = base.wrap( 0.0, -3.14, -0.0 )\ny = base.wrap( NaN, 0.0, 5.0 )\n","base.xlog1py":"var out = base.xlog1py( 3.0, 2.0 )\nout = base.xlog1py( 1.5, 5.9 )\nout = base.xlog1py( 0.9, 1.0 )\nout = base.xlog1py( 1.0, 0.0 )\nout = base.xlog1py( 0.0, -2.0 )\nout = base.xlog1py( 1.5, NaN )\nout = base.xlog1py( 0.0, NaN )\nout = base.xlog1py( NaN, 2.3 )\n","base.xlogy":"var out = base.xlogy( 3.0, 2.0 )\nout = base.xlogy( 1.5, 5.9 )\nout = base.xlogy( 0.9, 1.0 )\nout = base.xlogy( 0.0, -2.0 )\nout = base.xlogy( 1.5, NaN )\nout = base.xlogy( 0.0, NaN )\nout = base.xlogy( NaN, 2.3 )\n","base.zeta":"var y = base.zeta( 1.1 )\ny = base.zeta( -4.0 )\ny = base.zeta( 70.0 )\ny = base.zeta( 0.5 )\ny = base.zeta( NaN )\ny = base.zeta( 1.0 )\n","BERNDT_CPS_WAGES_1985":"var data = BERNDT_CPS_WAGES_1985()\n","bifurcate":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar f = [ true, true, false, true ];\nvar out = bifurcate( collection, f )\nf = [ 1, 1, 0, 1 ];\nout = bifurcate( collection, f )\nf = [ true, true, false, true ];\nvar opts = { 'returns': 'indices' };\nout = bifurcate( collection, opts, f )\nopts = { 'returns': '*' };\nout = bifurcate( collection, opts, f )\n","bifurcateBy":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = bifurcateBy( collection, predicate )\nvar opts = { 'returns': 'indices' };\nout = bifurcateBy( collection, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateBy( collection, opts, predicate )\n","bifurcateByAsync":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, predicate, done )\nvar opts = { 'returns': 'indices' };\nbifurcateByAsync( arr, opts, predicate, done )\nopts = { 'returns': '*' };\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\n","bifurcateByAsync.factory":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = bifurcateByAsync.factory( opts, predicate );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","bifurcateIn":"function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nfunction predicate( v ) { return v[ 0 ] === 'b'; };\nvar out = bifurcateIn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateIn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateIn( obj, opts, predicate )\n","bifurcateOwn":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = bifurcateOwn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateOwn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateOwn( obj, opts, predicate )\n","BigInt":"var v = ( BigInt ) ? BigInt( '1' ) : null\n","binomialTest":"var out = binomialTest( 682, 925 )\nout = binomialTest( [ 682, 925 - 682 ] )\nout = binomialTest( 21, 40, {\n 'p': 0.4,\n 'alternative': 'greater'\n })\n","Boolean":"var b = new Boolean( null )\nb = Boolean( null )\nb = Boolean( [] )\n","Boolean.prototype.toString":"var b = new Boolean( true )\nb.toString()\n","Boolean.prototype.valueOf":"var b = new Boolean( true )\nb.valueOf()\n","broadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = broadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","broadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = broadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","Buffer":"var b = new Buffer( 4 )\nvar b1 = new Buffer( [ 1, 2, 3, 4 ] );\nvar b2 = new Buffer( b1 )\nvar b = new Buffer( [ 1, 2, 3, 4 ] )\nvar b = new Buffer( 'beep boop' )\n","buffer2json":"var buf = new allocUnsafe( 2 );\nbuf[ 0 ] = 1;\nbuf[ 1 ] = 2;\nvar json = buffer2json( buf )\n","BYTE_ORDER":"BYTE_ORDER\n","camelcase":"var out = camelcase( 'Hello World!' )\nout = camelcase( 'beep boop' )\n","capitalize":"var out = capitalize( 'beep' )\nout = capitalize( 'Boop' )\n","capitalizeKeys":"var obj = { 'aa': 1, 'bb': 2 };\nvar out = capitalizeKeys( obj )\n","CATALAN":"CATALAN\n","CBRT_EPS":"CBRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"var data = CDC_NCHS_US_BIRTHS_1969_1988()\n","CDC_NCHS_US_BIRTHS_1994_2003":"var data = CDC_NCHS_US_BIRTHS_1994_2003()\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n","chdir":"var err = chdir( '/path/to/current/working/directory' )\n","chi2gof":"var x = [ 89, 37, 30, 28, 2 ];\nvar p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nvar out = chi2gof( x, p );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.01 };\nout = chi2gof( x, p, opts );\nout.toString()\nx = [ 89, 37, 30, 28, 2 ];\np = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nopts = { 'simulate': true, 'iterations': 1000 };\nout = chi2gof( x, p, opts );\nout.toString()\nvar lambda = 3.0;\nvar rpois = base.random.poisson.factory( lambda );\nvar len = 400;\nx = [];\nfor ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\nvar freqs = new Int32Array( len );\nfor ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\nout = chi2gof( freqs, 'poisson', lambda );\nout.toString()\n","chi2test":"var x = [ [ 20, 30 ], [ 30, 20 ] ];\nvar out = chi2test( x );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.1 };\nout = chi2test( x, opts );\no = out.toJSON()\nout.toString()\nopts = { 'correct': false };\nout = chi2test( x, opts );\nout.toString()\n","circarray2iterator":"var it = circarray2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","circularArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","circularArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = circularArrayStream.factory( opts );\n","circularArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","CircularBuffer":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.length\nb.count\nb.push( 'boop' )\n","CircularBuffer.prototype.clear":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.count\nb.clear();\nb.count\n","CircularBuffer.prototype.count":"var b = CircularBuffer( 3 );\nb.count\nb.push( 'foo' );\nb.count\nb.push( 'bar' );\nb.count\n","CircularBuffer.prototype.full":"var b = CircularBuffer( 3 );\nb.full\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.full\n","CircularBuffer.prototype.iterator":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar it = b.iterator( b.length );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","CircularBuffer.prototype.length":"var b = CircularBuffer( [ 0, 0, 0 ] );\nvar len = b.length\n","CircularBuffer.prototype.push":"var b = CircularBuffer( 3 );\nb.push( 'foo' )\nb.push( 'bar' )\nb.push( 'beep' )\nb.push( 'boop' )\n","CircularBuffer.prototype.toArray":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar vals = b.toArray()\n","CircularBuffer.prototype.toJSON":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar o = b.toJSON()\n","close":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nvar fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close( fd, done ); };\n","close.sync":"var fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","CMUDICT":"var data = CMUDICT();\nvar dict = data.dict\nvar phones = data.phones\nvar symbols = data.symbols\nvar vp = data.vp\n","codePointAt":"var out = codePointAt( 'last man standing', 4 )\nout = codePointAt( 'presidential election', 8, true )\nout = codePointAt( 'अनुच्छेद', 2 )\nout = codePointAt( '🌷', 1, true )\n","commonKeys":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeys( obj1, obj2 )\n","commonKeysIn":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeysIn( obj1, obj2 )\n","complex":"var z = complex( 5.0, 3.0, 'float64' )\nz = complex( 5.0, 3.0, 'float32' )\n","Complex64":"var z = new Complex64( 5.0, 3.0 )\nz.re\nz.im\n","COMPLEX64_NAN":"COMPLEX64_NAN\n","COMPLEX64_NUM_BYTES":"COMPLEX64_NUM_BYTES\n","COMPLEX64_ZERO":"COMPLEX64_ZERO\n","Complex128":"var z = new Complex128( 5.0, 3.0 )\nz.re\nz.im\n","COMPLEX128_NAN":"COMPLEX128_NAN\n","COMPLEX128_NUM_BYTES":"COMPLEX128_NUM_BYTES\n","COMPLEX128_ZERO":"COMPLEX128_ZERO\n","complexarray":"var arr = complexarray()\narr = complexarray( 'complex64' )\nvar arr = complexarray( 5 )\narr = complexarray( 5, 'complex64' )\nvar arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\nvar arr2 = complexarray( arr1, 'complex64' )\nvar arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\nvar arr2 = complexarray( arr1, 'complex64' )\nvar buf = new ArrayBuffer( 64 );\nvar arr = complexarray( buf, 0, 8, 'complex64' )\n","complexarrayCtors":"var ctor = complexarrayCtors( 'complex64' )\nctor = complexarrayCtors( 'float32' )\n","complexarrayDataTypes":"var out = complexarrayDataTypes()\n","complexCtors":"var ctor = complexCtors( 'complex128' )\nctor = complexCtors( 'complex' )\n","complexDataType":"var v = new Complex128( 1.0, 2.0 );\nvar dt = complexDataType( v )\ndt = complexDataType( 'beep' )\n","complexDataTypes":"var out = complexDataTypes()\n","complexPromotionRules":"var out = complexPromotionRules( 'complex128', 'complex64' )\n","compose":"function a( x ) {\nreturn 2 * x;\n }\nfunction b( x ) {\nreturn x + 3;\n }\nfunction c( x ) {\nreturn x / 5;\n }\nvar f = compose( c, b, a );\nvar z = f( 6 )\n","composeAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x/5 );\n}\n };\nvar f = composeAsync( c, b, a );\nfunction done( error, result ) {\nif ( error ) {\n throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","configdir":"var dir = configdir()\ndir = configdir( 'appname/config' )\n","conj":"var z = new Complex128( 5.0, 3.0 );\nz.toString()\nvar v = conj( z );\nv.toString()\n","conjf":"var z = new Complex64( 5.0, 3.0 );\nz.toString()\nvar v = conjf( z );\nv.toString()\n","constantcase":"var out = constantcase( 'Hello World!' )\nout = constantcase( 'I am a tiny little teapot' )\n","constantFunction":"var fcn = constantFunction( 3.14 );\nvar v = fcn()\nv = fcn()\nv = fcn()\n","constantStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream( 'beep', opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","constantStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = constantStream.factory( opts );\n","constantStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream.objectMode( 3.14, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","constructorName":"var v = constructorName( 'a' )\nv = constructorName( {} )\nv = constructorName( true )\n","contains":"var bool = contains( 'Hello World', 'World' )\nbool = contains( 'Hello World', 'world' )\nbool = contains( [ 1, 2, 3, 4 ], 2 )\nbool = contains( [ NaN, 2, 3, 4 ], NaN )\nbool = contains( 'Hello World', 'Hello', 6 )\nbool = contains( [ true, NaN, false ], true, 1 )\n","convertArray":"var arr = [ 1.0, 2.0, 3.0, 4.0 ];\nvar out = convertArray( arr, 'float32' )\n","convertArraySame":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = new Float32Array( 0 );\nvar out = convertArraySame( x, y )\n","convertPath":"var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\nout = convertPath( '/c/foo/bar/beep.c', 'mixed' )\nout = convertPath( '/c/foo/bar/beep.c', 'posix' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n","copy":"var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nvar out = copy( value )\nvar bool = ( value[ 0 ].c === out[ 0 ].c )\nvalue = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nout = copy( value, 1 );\nbool = ( value[ 0 ] === out[ 0 ] )\nbool = ( value[ 0 ].c === out[ 0 ].c )\n","copyBuffer":"var b1 = array2buffer( [ 1, 2, 3, 4 ] );\nvar b2 = copyBuffer( b1 )\n","countBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = countBy( collection, indicator )\n","countByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\n","countByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = countByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 500 ];\nf( arr, done )\n","currentYear":"var y = currentYear()\n","curry":"function add( x, y ) { return x + y; };\nvar f = curry( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curry( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curry( obj.greet, obj );\nvar str = f( 'Hello' )( 'there' )\n","curryRight":"function add( x, y ) { return x + y; };\nvar f = curryRight( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curryRight( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curryRight( obj.greet, obj );\nvar str = f( 'there' )( 'Hello' )\n","cwd":"var dir = cwd()\n","DALE_CHALL_NEW":"var list = DALE_CHALL_NEW()\n","datasets":"var out = datasets( 'MONTH_NAMES_EN' )\nvar opts = { 'data': 'cities' };\nout = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n","DataView":"var buf = new ArrayBuffer( 5 )\nvar dv = new DataView( buf )\n","DataView.prototype.buffer":"var buf1 = new ArrayBuffer( 5 );\nvar dv = new DataView( buf1 );\nvar buf2 = dv.buffer\nvar b = ( buf1 === buf2 )\n","DataView.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf );\ndv.byteLength\n","DataView.prototype.byteOffset":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf, 2 );\ndv.byteLength\ndv.byteOffset\n","datespace":"var stop = '2014-12-02T07:00:54.973Z';\nvar start = new Date( stop ) - 60000;\nvar arr = datespace( start, stop, 6 )\nvar opts = { 'round': 'ceil' };\narr = datespace( 1417503655000, 1417503655001, 3, opts )\n","dayOfQuarter":"var day = dayOfQuarter()\nday = dayOfQuarter( new Date() )\nday = dayOfQuarter( 12, 31, 2017 )\nday = dayOfQuarter( 'dec', 31, 2017 )\nday = dayOfQuarter( 'december', 31, 2017 )\n","dayOfYear":"var day = dayOfYear()\nday = dayOfYear( new Date() )\nday = dayOfYear( 12, 31, 2016 )\nday = dayOfYear( 'dec', 31, 2016 )\nday = dayOfYear( 'december', 31, 2016 )\n","daysInMonth":"var num = daysInMonth()\nnum = daysInMonth( 2 )\nnum = daysInMonth( 2, 2016 )\nnum = daysInMonth( 2, 2017 )\nnum = daysInMonth( 'feb', 2016 )\nnum = daysInMonth( 'february', 2016 )\n","daysInYear":"var num = daysInYear()\nnum = daysInYear( 2016 )\nnum = daysInYear( 2017 )\n","ddot":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\nddot( x, y )\n","debugSinkStream":"var s = debugSinkStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugSinkStream.factory( opts );\n","debugSinkStream.objectMode":"var s = debugSinkStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","debugStream":"var s = debugStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugStream.factory( opts );\n","debugStream.objectMode":"var s = debugStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","decorateAfter":"function f( v ) { return -v; };\nvar fcn = decorateAfter( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","decorateAfter.factory":"function f( v ) { return -v; };\nvar fcn = decorateAfter.factory( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","deepEqual":"var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\nbool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\nbool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n","deepGet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a.b.c' )\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n","deepGet.factory":"var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = dget( obj )\n","deepHasOwnProp":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepHasOwnProp( obj, 'a.b.c' )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasOwnProp.factory":"var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = has( obj )\n","deepHasProp":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar obj = { 'a': new Foo() };\nvar bool = deepHasProp( obj, 'a.b.c' )\nbool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasProp.factory":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': new Foo() };\nvar bool = has( obj )\n","deepPluck":"var arr = [\n { 'a': { 'b': { 'c': 1 } } },\n { 'a': { 'b': { 'c': 2 } } }\n ];\nvar out = deepPluck( arr, 'a.b.c' )\narr = [\n { 'a': [ 0, 1, 2 ] },\n { 'a': [ 3, 4, 5 ] }\n ];\nout = deepPluck( arr, [ 'a', 1 ] )\n","deepSet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepSet( obj, 'a.b.c', 'beep' )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\nobj\nbool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\nobj\n","deepSet.factory":"var dset = deepSet.factory( 'a/b/c', {\n 'create': true,\n 'sep': '/'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = dset( obj, 'beep' )\nobj\n","defineMemoizedProperty":"var obj = {};\nfunction foo() {\n return 'bar';\n };\ndefineMemoizedProperty( obj, 'foo', {\n 'configurable': false,\n 'enumerable': true,\n 'writable': false,\n 'value': foo\n });\nobj.foo\n","defineProperties":"var obj = {};\ndefineProperties( obj, {\n 'foo': {\n 'value': 'bar',\n 'writable': false,\n 'configurable': false,\n 'enumerable': true\n },\n 'baz': {\n 'value': 13\n }\n });\nobj.foo\nobj.baz\n","defineProperty":"var obj = {};\ndefineProperty( obj, 'foo', {\n 'value': 'bar',\n 'enumerable': true,\n 'writable': false\n });\nobj.foo = 'boop';\nobj\n","dirname":"var dir = dirname( './foo/bar/index.js' )\n","dotcase":"var out = dotcase( 'Hello World!' )\nout = dotcase( 'beep boop' )\n","DoublyLinkedList":"var list = DoublyLinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","doUntil":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoUntil( beep, predicate )\n","doUntilAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ndoUntilAsync( fcn, predicate, done )\n","doUntilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoUntilEach( arr, logger, predicate )\n","doUntilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoUntilEachRight( arr, logger, predicate )\n","doWhile":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoWhile( beep, predicate )\n","doWhileAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ndoWhileAsync( fcn, predicate, done )\n","doWhileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoWhileEach( arr, logger, predicate )\n","doWhileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoWhileEachRight( arr, logger, predicate )\n","dswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ndswap( x, y );\nx.data\ny.data\n","E":"E\n","EMOJI":"var data = EMOJI()\n","EMOJI_CODE_PICTO":"var out = EMOJI_CODE_PICTO()\n","EMOJI_PICTO_CODE":"var out = EMOJI_PICTO_CODE()\n","emptyStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = emptyStream();\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","emptyStream.factory":"var opts = { 'objectMode': true };\nvar createStream = emptyStream.factory( opts );\n","emptyStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = emptyStream.objectMode();\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","endsWith":"var bool = endsWith( 'beep', 'ep' )\nbool = endsWith( 'Beep', 'op' )\nbool = endsWith( 'Beep', 'ee', 3 )\nbool = endsWith( 'Beep', 'ee', -1 )\nbool = endsWith( 'beep', '' )\n","enumerableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = enumerableProperties( obj )\n","enumerablePropertiesIn":"var props = enumerablePropertiesIn( [] )\n","enumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbols( obj )\n","enumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbolsIn( obj )\n","ENV":"var user = ENV.USER\n","EPS":"EPS\n","error2json":"var err = new Error( 'beep' );\nvar json = error2json( err )\n","EULERGAMMA":"EULERGAMMA\n","every":"var arr = [ 1, 1, 1, 1, 1 ];\nvar bool = every( arr )\n","everyBy":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyBy( arr, positive )\n","everyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\n","everyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","everyByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyByRight( arr, positive )\n","everyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\n","everyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","evil":"var v = evil( '5*4*3*2*1' )\n","EXEC_PATH":"EXEC_PATH\n","exists":"function done( error, bool ) { console.log( bool ); };\nexists( './beep/boop', done );\n","exists.sync":"var bool = exists.sync( './beep/boop' )\n","expandAcronyms":"var str = 'LOL, this is fun. I am ROFL.';\nvar out = expandAcronyms( str )\nstr = 'brb, I need to check my mail. thx!';\nout = expandAcronyms( str )\n","expandContractions":"var str = 'I won\\'t be able to get y\\'all out of this one.';\nvar out = expandContractions( str )\nstr = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\nout = expandContractions( str )\n","extname":"var ext = extname( 'index.js' )\n","FancyArray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","FancyArray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","FancyArray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","FancyArray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","FancyArray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","FancyArray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","FancyArray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","FancyArray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","FancyArray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","FancyArray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","FancyArray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","FancyArray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","FancyArray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","FancyArray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","FancyArray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","FancyArray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","fastmath.abs":"var v = fastmath.abs( -1.0 )\nv = fastmath.abs( 2.0 )\nv = fastmath.abs( 0.0 )\nv = fastmath.abs( -0.0 )\nv = fastmath.abs( NaN )\n","fastmath.acosh":"var v = fastmath.acosh( 1.0 )\nv = fastmath.acosh( 2.0 )\nv = fastmath.acosh( NaN )\nv = fastmath.acosh( 1.0e308 )\n","fastmath.ampbm":"var h = fastmath.ampbm( 5.0, 12.0 )\n","fastmath.ampbm.factory":"var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n","fastmath.asinh":"var v = fastmath.asinh( 0.0 )\nv = fastmath.asinh( 2.0 )\nv = fastmath.asinh( -2.0 )\nv = fastmath.asinh( NaN )\nv = fastmath.asinh( 1.0e200 )\nv = fastmath.asinh( 1.0e-50 )\n","fastmath.atanh":"var v = fastmath.atanh( 0.0 )\nv = fastmath.atanh( 0.9 )\nv = fastmath.atanh( 1.0 )\nv = fastmath.atanh( -1.0 )\nv = fastmath.atanh( NaN )\nv = fastmath.atanh( 1.0e-17 )\n","fastmath.hypot":"var h = fastmath.hypot( -5.0, 12.0 )\nh = fastmath.hypot( 1.0e154, 1.0e154 )\nh = fastmath.hypot( 1e-200, 1.0e-200 )\n","fastmath.log2Uint32":"var v = fastmath.log2Uint32( 4 >>> 0 )\nv = fastmath.log2Uint32( 8 >>> 0 )\nv = fastmath.log2Uint32( 9 >>> 0 )\n","fastmath.max":"var v = fastmath.max( 3.14, 4.2 )\nv = fastmath.max( 3.14, NaN )\nv = fastmath.max( NaN, 3.14 )\nv = fastmath.max( -0.0, +0.0 )\nv = fastmath.max( +0.0, -0.0 )\n","fastmath.min":"var v = fastmath.min( 3.14, 4.2 )\nv = fastmath.min( 3.14, NaN )\nv = fastmath.min( NaN, 3.14 )\nv = fastmath.min( -0.0, +0.0 )\nv = fastmath.min( +0.0, -0.0 )\n","fastmath.powint":"var v = fastmath.powint( 2.0, 3 )\nv = fastmath.powint( 3.14, 0 )\nv = fastmath.powint( 2.0, -2 )\nv = fastmath.powint( 0.0, 0 )\nv = fastmath.powint( -3.14, 1 )\nv = fastmath.powint( NaN, 0 )\n","fastmath.sqrtUint32":"var v = fastmath.sqrtUint32( 9 >>> 0 )\nv = fastmath.sqrtUint32( 2 >>> 0 )\nv = fastmath.sqrtUint32( 3 >>> 0 )\nv = fastmath.sqrtUint32( 0 >>> 0 )\n","FEMALE_FIRST_NAMES_EN":"var list = FEMALE_FIRST_NAMES_EN()\n","FIFO":"var q = FIFO();\nq.push( 'foo' ).push( 'bar' );\nq.length\nq.pop()\nq.length\nq.pop()\nq.length\n","filledarray":"var arr = filledarray()\narr = filledarray( 'float32' )\nvar arr = filledarray( 1.0, 5 )\narr = filledarray( 1, 5, 'int32' )\nvar arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n","filledarrayBy":"var arr = filledarrayBy()\narr = filledarrayBy( 'float32' )\nfunction clbk() { return 1.0; };\nvar arr = filledarrayBy( 5, clbk )\narr = filledarrayBy( 5, 'int32', clbk )\nvar arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n","filterArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v !== 2 ); };\nvar bar = filterArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","find":"var data = [ 30, 20, 50, 60, 10 ];\nfunction condition( val ) { return val > 20; };\nvar vals = find( data, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nvar opts = { 'k': 2, 'returns': 'values' };\nvals = find( data, opts, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nopts = { 'k': -2, 'returns': '*' };\nvals = find( data, opts, condition )\n","firstChar":"var out = firstChar( 'beep' )\nout = firstChar( 'Boop', 1 )\nout = firstChar( 'foo bar', 5 )\n","FIVETHIRTYEIGHT_FFQ":"var data = FIVETHIRTYEIGHT_FFQ()\n","flattenArray":"var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nvar out = flattenArray( arr )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2 } )\nvar bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2, 'copy': true } )\nbool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n","flattenArray.factory":"var flatten = flattenArray.factory( [ 2, 2 ], {\n 'copy': false\n });\nvar out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\nout = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n","flattenObject":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flattenObject( obj )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'depth': 1 } )\nvar bool = ( obj.a.b === out[ 'a.b' ] )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'delimiter': '-|-' } )\nobj = { 'a': { 'b': [ 1, 2, 3 ] } };\nout = flattenObject( obj, { 'flattenArrays': true } )\n","flattenObject.factory":"var flatten = flattenObject.factory({\n 'depth': 1,\n 'copy': true,\n 'delimiter': '|'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flatten( obj )\n","flignerTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = flignerTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = flignerTest( arr, { 'groups': groups } )\n","FLOAT_WORD_ORDER":"FLOAT_WORD_ORDER\n","FLOAT16_CBRT_EPS":"FLOAT16_CBRT_EPS\n","FLOAT16_EPS":"FLOAT16_EPS\n","FLOAT16_EXPONENT_BIAS":"FLOAT16_EXPONENT_BIAS\n","FLOAT16_MAX":"FLOAT16_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"FLOAT16_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"FLOAT16_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"FLOAT16_NINF\n","FLOAT16_NUM_BYTES":"FLOAT16_NUM_BYTES\n","FLOAT16_PINF":"FLOAT16_PINF\n","FLOAT16_PRECISION":"FLOAT16_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"FLOAT16_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"FLOAT16_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"FLOAT16_SQRT_EPS\n","FLOAT32_CBRT_EPS":"FLOAT32_CBRT_EPS\n","FLOAT32_EPS":"FLOAT32_EPS\n","FLOAT32_EXPONENT_BIAS":"FLOAT32_EXPONENT_BIAS\n","FLOAT32_MAX":"FLOAT32_MAX\n","FLOAT32_MAX_SAFE_INTEGER":"FLOAT32_MAX_SAFE_INTEGER\n","FLOAT32_MIN_SAFE_INTEGER":"FLOAT32_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"FLOAT32_NAN\n","FLOAT32_NINF":"FLOAT32_NINF\n","FLOAT32_NUM_BYTES":"FLOAT32_NUM_BYTES\n","FLOAT32_PINF":"FLOAT32_PINF\n","FLOAT32_PRECISION":"FLOAT32_PRECISION\n","FLOAT32_SMALLEST_NORMAL":"FLOAT32_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"FLOAT32_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"FLOAT32_SQRT_EPS\n","Float32Array":"var arr = new Float32Array()\nvar arr = new Float32Array( 5 )\nvar arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float32Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Float32Array( buf, 0, 4 )\n","Float32Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float32Array.of":"var arr = Float32Array.of( 2.0, -2.0 )\n","Float32Array.BYTES_PER_ELEMENT":"Float32Array.BYTES_PER_ELEMENT\n","Float32Array.name":"Float32Array.name\n","Float32Array.prototype.buffer":"var arr = new Float32Array( 5 );\narr.buffer\n","Float32Array.prototype.byteLength":"var arr = new Float32Array( 5 );\narr.byteLength\n","Float32Array.prototype.byteOffset":"var arr = new Float32Array( 5 );\narr.byteOffset\n","Float32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float32Array.prototype.length":"var arr = new Float32Array( 5 );\narr.length\n","Float32Array.prototype.copyWithin":"var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float32Array.prototype.entries":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.every":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float32Array.prototype.fill":"var arr = new Float32Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float32Array.prototype.filter":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float32Array.prototype.find":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float32Array.prototype.findIndex":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float32Array.prototype.forEach":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float32Array.prototype.includes":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float32Array.prototype.indexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float32Array.prototype.join":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float32Array.prototype.keys":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.lastIndexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float32Array.prototype.map":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn );\n","Float32Array.prototype.reduce":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float32Array.prototype.reduceRight":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float32Array.prototype.reverse":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float32Array.prototype.set":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float32Array.prototype.slice":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float32Array.prototype.some":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float32Array.prototype.sort":"var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float32Array.prototype.subarray":"var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float32Array.prototype.toLocaleString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float32Array.prototype.toString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float32Array.prototype.values":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","FLOAT64_EXPONENT_BIAS":"FLOAT64_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"FLOAT64_HIGH_WORD_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n","FLOAT64_MAX":"FLOAT64_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"FLOAT64_MAX_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"FLOAT64_MAX_SAFE_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MIN_BASE2_EXPONENT":"FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE10_EXPONENT":"FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"FLOAT64_MIN_LN\n","FLOAT64_MIN_SAFE_INTEGER":"FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"FLOAT64_NUM_BYTES\n","FLOAT64_PRECISION":"FLOAT64_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"FLOAT64_SMALLEST_NORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"FLOAT64_SMALLEST_SUBNORMAL\n","Float64Array":"var arr = new Float64Array()\nvar arr = new Float64Array( 5 )\nvar arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float64Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float64Array( arr1 )\nvar buf = new ArrayBuffer( 32 );\nvar arr = new Float64Array( buf, 0, 4 )\n","Float64Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float64Array.of":"var arr = Float64Array.of( 2.0, -2.0 )\n","Float64Array.BYTES_PER_ELEMENT":"Float64Array.BYTES_PER_ELEMENT\n","Float64Array.name":"Float64Array.name\n","Float64Array.prototype.buffer":"var arr = new Float64Array( 5 );\narr.buffer\n","Float64Array.prototype.byteLength":"var arr = new Float64Array( 5 );\narr.byteLength\n","Float64Array.prototype.byteOffset":"var arr = new Float64Array( 5 );\narr.byteOffset\n","Float64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float64Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float64Array.prototype.length":"var arr = new Float64Array( 5 );\narr.length\n","Float64Array.prototype.copyWithin":"var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float64Array.prototype.entries":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.every":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float64Array.prototype.fill":"var arr = new Float64Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float64Array.prototype.filter":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float64Array.prototype.find":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float64Array.prototype.findIndex":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float64Array.prototype.forEach":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float64Array.prototype.includes":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float64Array.prototype.indexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float64Array.prototype.join":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float64Array.prototype.keys":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.lastIndexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float64Array.prototype.map":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn );\n","Float64Array.prototype.reduce":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float64Array.prototype.reduceRight":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float64Array.prototype.reverse":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float64Array.prototype.set":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float64Array.prototype.slice":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float64Array.prototype.some":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float64Array.prototype.sort":"var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float64Array.prototype.subarray":"var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float64Array.prototype.toLocaleString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float64Array.prototype.toString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float64Array.prototype.values":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","forEach":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEach( arr, logger )\n","forEachAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\n","forEachAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nforEachChar( 'hello world!', fcn );\nn\n","forEachRight":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEachRight( arr, logger )\n","forEachRightAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\n","forEachRightAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachRightAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","forIn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nfunction Foo() { return this; };\nFoo.prototype.beep = 'boop';\nvar obj = new Foo();\nforIn( obj, logger )\n","forOwn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nforOwn( obj, logger )\n","FOURTH_PI":"FOURTH_PI\n","FOURTH_ROOT_EPS":"FOURTH_ROOT_EPS\n","FRB_SF_WAGE_RIGIDITY":"var data = FRB_SF_WAGE_RIGIDITY()\n","fromCodePoint":"var out = fromCodePoint( 9731 )\nout = fromCodePoint( [ 9731 ] )\nout = fromCodePoint( 97, 98, 99 )\nout = fromCodePoint( [ 97, 98, 99 ] )\n","Function":"var f = new Function( 'x', 'y', 'return x + y' );\nf( 1, 2 )\n","Function.prototype.apply":"var f = new Function( 'x', 'y', 'return x + y' );\nf.apply( null, [ 1, 2 ] )\n","Function.prototype.call":"var f = new Function( 'x', 'y', 'return x + y' );\nf.call( null, 1, 2 )\n","Function.prototype.bind":"var f = new Function( 'x', 'y', 'return x + y' );\nvar g = f.bind( null, 1 );\ng( 2 )\n","Function.prototype.toString":"var f = new Function( 'x', 'y', 'return x + y' );\nf.toString()\n","Function.prototype.length":"var f = new Function( 'x', 'y', 'return x + y' );\nf.length\n","Function.prototype.name":"var f = new Function( 'x', 'y', 'return x + y' );\nf.name\nvar f = new Function( 'x', 'y', 'return x + y' );\nf.name = 'add';\nf.name\n","Function.prototype.prototype":"var f = new Function( 'x', 'y', 'return x + y' );\nf.prototype\n","function2string":"function2string( base.erf )\n","functionName":"var v = functionName( String )\nv = functionName( function foo(){} )\nv = functionName( function(){} )\n","functionSequence":"function a( x ) { return 2 * x; };\nfunction b( x ) { return x + 3; };\nfunction c( x ) { return x / 5; };\nvar f = functionSequence( a, b, c );\nvar z = f( 6 )\n","functionSequenceAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x/5 );\n}\n };\nvar f = functionSequenceAsync( a, b, c );\nfunction done( error, result ) {\nif ( error ) {\n throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","GAMMA_LANCZOS_G":"GAMMA_LANCZOS_G\n","gdot":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngdot( x, y )\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngdot( x, y )\n","getegid":"var gid = getegid()\n","geteuid":"var uid = geteuid()\n","getgid":"var gid = getgid()\n","getGlobal":"var g = getGlobal()\n","getPrototypeOf":"var proto = getPrototypeOf( {} )\n","getuid":"var uid = getuid()\n","GLAISHER":"GLAISHER\n","graphemeClusters2iterator":"var it = graphemeClusters2iterator( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","graphemeClusters2iteratorRight":"var it = graphemeClusters2iteratorRight( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","group":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar groups = [ 'b', 'b', 'f', 'b' ];\nvar out = group( collection, groups )\ngroups = [ 1, 1, 2, 1 ];\nout = group( collection, groups )\ngroups = [ 'b', 'b', 'f', 'b' ];\nvar opts = { 'returns': 'indices' };\nout = group( collection, opts, groups )\nopts = { 'returns': '*' };\nout = group( collection, opts, groups )\n","groupBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = groupBy( collection, indicator )\nvar opts = { 'returns': 'indices' };\nout = groupBy( collection, opts, indicator )\nopts = { 'returns': '*' };\nout = groupBy( collection, opts, indicator )\n","groupByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, indicator, done )\nvar opts = { 'returns': 'indices' };\ngroupByAsync( arr, opts, indicator, done )\nopts = { 'returns': '*' };\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\n","groupByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = groupByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","groupIn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nfunction Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nvar out = groupIn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupIn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupIn( obj, opts, indicator )\n","groupOwn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = groupOwn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupOwn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupOwn( obj, opts, indicator )\n","gswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngswap( x, y );\nx.data\ny.data\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngswap( x, y );\nx\ny\n","HALF_LN2":"HALF_LN2\n","HALF_PI":"HALF_PI\n","HARRISON_BOSTON_HOUSE_PRICES":"var data = HARRISON_BOSTON_HOUSE_PRICES()\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n","hasArrayBufferSupport":"var bool = hasArrayBufferSupport()\n","hasAsyncAwaitSupport":"var bool = hasAsyncAwaitSupport()\n","hasAsyncIteratorSymbolSupport":"var bool = hasAsyncIteratorSymbolSupport()\n","hasBigInt64ArraySupport":"var bool = hasBigInt64ArraySupport()\n","hasBigIntSupport":"var bool = hasBigIntSupport()\n","hasBigUint64ArraySupport":"var bool = hasBigUint64ArraySupport()\n","hasClassSupport":"var bool = hasClassSupport()\n","hasDataViewSupport":"var bool = hasDataViewSupport()\n","hasDefinePropertiesSupport":"var bool = hasDefinePropertiesSupport()\n","hasDefinePropertySupport":"var bool = hasDefinePropertySupport()\n","hasFloat32ArraySupport":"var bool = hasFloat32ArraySupport()\n","hasFloat64ArraySupport":"var bool = hasFloat64ArraySupport()\n","hasFunctionNameSupport":"var bool = hasFunctionNameSupport()\n","hasGeneratorSupport":"var bool = hasGeneratorSupport()\n","hasGlobalThisSupport":"var bool = hasGlobalThisSupport()\n","hasInt8ArraySupport":"var bool = hasInt8ArraySupport()\n","hasInt16ArraySupport":"var bool = hasInt16ArraySupport()\n","hasInt32ArraySupport":"var bool = hasInt32ArraySupport()\n","hasIteratorSymbolSupport":"var bool = hasIteratorSymbolSupport()\n","hasMapSupport":"var bool = hasMapSupport()\n","hasNodeBufferSupport":"var bool = hasNodeBufferSupport()\n","hasOwnProp":"var beep = { 'boop': true };\nvar bool = hasOwnProp( beep, 'boop' )\nbool = hasOwnProp( beep, 'bop' )\n","hasProp":"var beep = { 'boop': true };\nvar bool = hasProp( beep, 'boop' )\nbool = hasProp( beep, 'toString' )\nbool = hasProp( beep, 'bop' )\n","hasProxySupport":"var bool = hasProxySupport()\n","hasSetSupport":"var bool = hasSetSupport()\n","hasSharedArrayBufferSupport":"var bool = hasSharedArrayBufferSupport()\n","hasSymbolSupport":"var bool = hasSymbolSupport()\n","hasToStringTagSupport":"var bool = hasToStringTagSupport()\n","hasUint8ArraySupport":"var bool = hasUint8ArraySupport()\n","hasUint8ClampedArraySupport":"var bool = hasUint8ClampedArraySupport()\n","hasUint16ArraySupport":"var bool = hasUint16ArraySupport()\n","hasUint32ArraySupport":"var bool = hasUint32ArraySupport()\n","hasUTF16SurrogatePairAt":"var out = hasUTF16SurrogatePairAt( '🌷', 0 )\nout = hasUTF16SurrogatePairAt( '🌷', 1 )\n","hasWeakMapSupport":"var bool = hasWeakMapSupport()\n","hasWeakSetSupport":"var bool = hasWeakSetSupport()\n","hasWebAssemblySupport":"var bool = hasWebAssemblySupport()\n","headercase":"var out = headercase( 'Hello World!' )\nout = headercase( 'beep boop' )\n","HERNDON_VENUS_SEMIDIAMETERS":"var d = HERNDON_VENUS_SEMIDIAMETERS()\n","homedir":"var home = homedir()\n","HOURS_IN_DAY":"var days = 3.14;\nvar hrs = days * HOURS_IN_DAY\n","HOURS_IN_WEEK":"var wks = 3.14;\nvar hrs = wks * HOURS_IN_WEEK\n","hoursInMonth":"var num = hoursInMonth()\nnum = hoursInMonth( 2 )\nnum = hoursInMonth( 2, 2016 )\nnum = hoursInMonth( 2, 2017 )\nnum = hoursInMonth( 'feb', 2016 )\nnum = hoursInMonth( 'february', 2016 )\n","hoursInYear":"var num = hoursInYear()\nnum = hoursInYear( 2016 )\nnum = hoursInYear( 2017 )\n","httpServer":"var createServer = httpServer()\nfunction onRequest( request, response ) {\nconsole.log( request.url );\nresponse.end( 'OK' );\n };\ncreateServer = httpServer( onRequest )\nvar opts = { 'port': 7331 };\ncreateServer = httpServer( opts )\n","identity":"var v = identity( 3.14 )\n","ifelse":"var z = ifelse( true, 1.0, -1.0 )\nz = ifelse( false, 1.0, -1.0 )\n","ifelseAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, true );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nifelseAsync( predicate, 'beep', 'boop', done )\n","ifthen":"function x() { return 1.0; };\nfunction y() { return -1.0; };\nvar z = ifthen( true, x, y )\nz = ifthen( false, x, y )\n","ifthenAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, false );\n }\n };\nfunction x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'beep' );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nifthenAsync( predicate, x, y, done )\n","imag":"var z = new Complex128( 5.0, 3.0 );\nvar im = imag( z )\n","imagf":"var z = new Complex64( 5.0, 3.0 );\nvar im = imagf( z )\n","IMG_ACANTHUS_MOLLIS":"var img = IMG_ACANTHUS_MOLLIS()\n","IMG_AIRPLANE_FROM_ABOVE":"var img = IMG_AIRPLANE_FROM_ABOVE()\n","IMG_ALLIUM_OREOPHILUM":"var img = IMG_ALLIUM_OREOPHILUM()\n","IMG_BLACK_CANYON":"var img = IMG_BLACK_CANYON()\n","IMG_DUST_BOWL_HOME":"var img = IMG_DUST_BOWL_HOME()\n","IMG_FRENCH_ALPINE_LANDSCAPE":"var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n","IMG_LOCOMOTION_HOUSE_CAT":"var img = IMG_LOCOMOTION_HOUSE_CAT()\n","IMG_LOCOMOTION_NUDE_MALE":"var img = IMG_LOCOMOTION_NUDE_MALE()\n","IMG_MARCH_PASTORAL":"var img = IMG_MARCH_PASTORAL()\n","IMG_NAGASAKI_BOATS":"var img = IMG_NAGASAKI_BOATS()\n","incrapcorr":"var accumulator = incrapcorr();\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator()\n","incrBinaryClassification":"var opts = {};\nopts.intercept = true;\nopts.lambda = 1.0e-5;\nvar acc = incrBinaryClassification( 3, opts );\nvar buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\nvar x = array( buf );\nvar coefs = acc( x, 1 )\nbuf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\nx = array( buf );\nvar yhat = acc.predict( x )\n","incrcount":"var accumulator = incrcount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrcovariance":"var accumulator = incrcovariance();\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator()\n","incrcovmat":"var accumulator = incrcovmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrcv":"var accumulator = incrcv();\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator()\n","increwmean":"var accumulator = increwmean( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","increwstdev":"var accumulator = increwstdev( 0.5 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","increwvariance":"var accumulator = increwvariance( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrgmean":"var accumulator = incrgmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrgrubbs":"var acc = incrgrubbs();\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrhmean":"var accumulator = incrhmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrkmeans":"var accumulator = incrkmeans( 5, 2 );\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v );\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v );\n","incrkurtosis":"var accumulator = incrkurtosis();\nvar v = accumulator( 2.0 )\nv = accumulator( 2.0 )\nv = accumulator( -4.0 )\nv = accumulator( -4.0 )\n","incrmaape":"var accumulator = incrmaape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmae":"var accumulator = incrmae();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmapcorr":"var accumulator = incrmapcorr( 3 );\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator( 3.0, -1.0 )\nar = accumulator( 5.0, -9.5 )\nar = accumulator()\n","incrmape":"var accumulator = incrmape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmax":"var accumulator = incrmax();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmaxabs":"var accumulator = incrmaxabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmcovariance":"var accumulator = incrmcovariance( 3 );\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator( 3.0, -1.0 )\nv = accumulator( 5.0, -9.5 )\nv = accumulator()\n","incrmcv":"var accumulator = incrmcv( 3 );\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator( 3.0 )\ncv = accumulator( 7.0 )\ncv = accumulator()\n","incrmda":"var accumulator = incrmda();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 4.0 )\nm = accumulator()\n","incrme":"var accumulator = incrme();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmean":"var accumulator = incrmean();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs":"var accumulator = incrmeanabs();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs2":"var accumulator = incrmeanabs2();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanstdev":"var accumulator = incrmeanstdev();\nvar ms = accumulator()\nms = accumulator( 2.0 )\nms = accumulator( -5.0 )\nms = accumulator( 3.0 )\nms = accumulator( 5.0 )\nms = accumulator()\n","incrmeanvar":"var accumulator = incrmeanvar();\nvar mv = accumulator()\nmv = accumulator( 2.0 )\nmv = accumulator( -5.0 )\nmv = accumulator( 3.0 )\nmv = accumulator( 5.0 )\nmv = accumulator()\n","incrmgmean":"var accumulator = incrmgmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmgrubbs":"var acc = incrmgrubbs( 20 );\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrmhmean":"var accumulator = incrmhmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmidrange":"var accumulator = incrmidrange();\nvar v = accumulator()\nv = accumulator( 3.14 )\nv = accumulator( -5.0 )\nv = accumulator( 10.1 )\nv = accumulator()\n","incrmin":"var accumulator = incrmin();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminabs":"var accumulator = incrminabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminmax":"var accumulator = incrminmax();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrminmaxabs":"var accumulator = incrminmaxabs();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmaape":"var accumulator = incrmmaape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmae":"var accumulator = incrmmae( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmape":"var accumulator = incrmmape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmax":"var accumulator = incrmmax( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmaxabs":"var accumulator = incrmmaxabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmda":"var accumulator = incrmmda( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 4.0, 5.0 )\nm = accumulator()\n","incrmme":"var accumulator = incrmme( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmean":"var accumulator = incrmmean( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs":"var accumulator = incrmmeanabs( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs2":"var accumulator = incrmmeanabs2( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmeanstdev":"var accumulator = incrmmeanstdev( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmeanvar":"var accumulator = incrmmeanvar( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmidrange":"var accumulator = incrmmidrange( 3 );\nvar mr = accumulator()\nmr = accumulator( 2.0 )\nmr = accumulator( -5.0 )\nmr = accumulator( 3.0 )\nmr = accumulator( 5.0 )\nmr = accumulator()\n","incrmmin":"var accumulator = incrmmin( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminabs":"var accumulator = incrmminabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminmax":"var accumulator = incrmminmax( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmminmaxabs":"var accumulator = incrmminmaxabs( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmpe":"var accumulator = incrmmpe( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmse":"var accumulator = incrmmse( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmpcorr":"var accumulator = incrmpcorr( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator( 3.0, -1.0 )\nr = accumulator( 5.0, -9.5 )\nr = accumulator()\n","incrmpcorr2":"var accumulator = incrmpcorr2( 3 );\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator( 3.0, -1.0 )\nr2 = accumulator( 5.0, -9.5 )\nr2 = accumulator()\n","incrmpcorrdist":"var accumulator = incrmpcorrdist( 3 );\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator( 3.0, -1.0 )\nd = accumulator( 5.0, -9.5 )\nd = accumulator()\n","incrmpe":"var accumulator = incrmpe();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmprod":"var accumulator = incrmprod( 3 );\nvar p = accumulator()\np = accumulator( 2.0 )\np = accumulator( -5.0 )\np = accumulator( 3.0 )\np = accumulator( 5.0 )\np = accumulator()\n","incrmrange":"var accumulator = incrmrange( 3 );\nvar r = accumulator()\nr = accumulator( 2.0 )\nr = accumulator( -5.0 )\nr = accumulator( 3.0 )\nr = accumulator( 5.0 )\nr = accumulator()\n","incrmrmse":"var accumulator = incrmrmse( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmrss":"var accumulator = incrmrss( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmse":"var accumulator = incrmse();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmstdev":"var accumulator = incrmstdev( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsum":"var accumulator = incrmsum( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsumabs":"var accumulator = incrmsumabs( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumabs2":"var accumulator = incrmsumabs2( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsummary":"var accumulator = incrmsummary( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumprod":"var accumulator = incrmsumprod( 3 );\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator( 3.0, -2.0 )\ns = accumulator( 5.0, 3.0 )\ns = accumulator()\n","incrmvariance":"var accumulator = incrmvariance( 3 );\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator( 3.0 )\ns2 = accumulator( 5.0 )\ns2 = accumulator()\n","incrmvmr":"var accumulator = incrmvmr( 3 );\nvar F = accumulator()\nF = accumulator( 2.0 )\nF = accumulator( 1.0 )\nF = accumulator( 3.0 )\nF = accumulator( 7.0 )\nF = accumulator()\n","incrnancount":"var accumulator = incrnancount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrnansum":"var accumulator = incrnansum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs":"var accumulator = incrnansumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs2":"var accumulator = incrnansumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrpcorr":"var accumulator = incrpcorr();\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator()\n","incrpcorr2":"var accumulator = incrpcorr2();\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator()\n","incrpcorrdist":"var accumulator = incrpcorrdist();\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator()\n","incrpcorrdistmat":"var accumulator = incrpcorrdistmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrpcorrmat":"var accumulator = incrpcorrmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrprod":"var accumulator = incrprod();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrrange":"var accumulator = incrrange();\nvar v = accumulator()\nv = accumulator( -2.0 )\nv = accumulator( 1.0 )\nv = accumulator( 3.0 )\nv = accumulator()\n","incrrmse":"var accumulator = incrrmse();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrrss":"var accumulator = incrrss();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrskewness":"var accumulator = incrskewness();\nvar v = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( -10.0 )\nv = accumulator()\n","incrspace":"var arr = incrspace( 0, 11, 2 )\n","incrstdev":"var accumulator = incrstdev();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsum":"var accumulator = incrsum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs":"var accumulator = incrsumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs2":"var accumulator = incrsumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsummary":"var accumulator = incrsummary();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumprod":"var accumulator = incrsumprod();\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator()\n","incrvariance":"var accumulator = incrvariance();\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator()\n","incrvmr":"var accumulator = incrvmr();\nvar D = accumulator()\nD = accumulator( 2.0 )\nD = accumulator( 1.0 )\nD = accumulator()\n","incrwmean":"var accumulator = incrwmean();\nvar mu = accumulator()\nmu = accumulator( 2.0, 1.0 )\nmu = accumulator( 2.0, 0.5 )\nmu = accumulator( 3.0, 1.5 )\nmu = accumulator()\n","ind2sub":"var d = [ 3, 3, 3 ];\nvar s = ind2sub( d, 17 )\n","ind2sub.assign":"var d = [ 3, 3, 3 ];\nvar out = [ 0, 0, 0 ];\nvar s = ind2sub.assign( d, 17, out )\nvar bool = ( s === out )\n","indexOf":"var arr = [ 4, 3, 2, 1 ];\nvar idx = indexOf( arr, 3 )\narr = [ 4, 3, 2, 1 ];\nidx = indexOf( arr, 5 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, 3 )\narr = [ 1, 2, 3, 4, 2, 5 ];\nidx = indexOf( arr, 2, 10 )\narr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\nidx = indexOf( arr, 2, -4 )\nidx = indexOf( arr, 2, -1 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, -10 )\nvar str = 'bebop';\nidx = indexOf( str, 'o' )\n","inherit":"function Foo() { return this; };\nFoo.prototype.beep = function beep() { return 'boop'; };\nfunction Bar() { Foo.call( this ); return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar v = bar.beep()\n","inheritedEnumerableProperties":"var props = inheritedEnumerableProperties( {} )\n","inheritedEnumerablePropertySymbols":"var symbols = inheritedEnumerablePropertySymbols( [] )\n","inheritedKeys":"var keys = inheritedKeys( {} )\n","inheritedNonEnumerableProperties":"var props = inheritedNonEnumerableProperties( {} )\n","inheritedNonEnumerablePropertyNames":"var keys = inheritedNonEnumerablePropertyNames( {} )\n","inheritedNonEnumerablePropertySymbols":"var symbols = inheritedNonEnumerablePropertySymbols( [] )\n","inheritedProperties":"var symbols = inheritedProperties( [] )\n","inheritedPropertyDescriptor":"var desc = inheritedPropertyDescriptor( {}, 'toString' )\n","inheritedPropertyDescriptors":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = inheritedPropertyDescriptors( obj )\n","inheritedPropertyNames":"var keys = inheritedPropertyNames( [] )\n","inheritedPropertySymbols":"var symbols = inheritedPropertySymbols( [] )\n","inheritedWritableProperties":"var props = inheritedWritableProperties( {} )\n","inheritedWritablePropertyNames":"var keys = inheritedWritablePropertyNames( {} )\n","inheritedWritablePropertySymbols":"var symbols = inheritedWritablePropertySymbols( [] )\n","inmap":"function foo( v, i ) { return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmap( arr, foo )\nvar bool = ( out === arr )\n","inmapAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\n","inmapAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","inmapRight":"function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmapRight( arr, foo )\nvar bool = ( out === arr )\n","inmapRightAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\n","inmapRightAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapRightAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","inspectSinkStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectSinkStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","inspectStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","instanceOf":"var bool = instanceOf( [], Array )\nbool = instanceOf( {}, Object )\nbool = instanceOf( null, Object )\n","INT8_MAX":"INT8_MAX\n","INT8_MIN":"INT8_MIN\n","INT8_NUM_BYTES":"INT8_NUM_BYTES\n","Int8Array":"var arr = new Int8Array()\nvar arr = new Int8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Int8Array( buf, 0, 4 )\n","Int8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int8Array.from( [ 1, 2 ], mapFcn )\n","Int8Array.of":"var arr = Int8Array.of( 1, 2 )\n","Int8Array.BYTES_PER_ELEMENT":"Int8Array.BYTES_PER_ELEMENT\n","Int8Array.name":"Int8Array.name\n","Int8Array.prototype.buffer":"var arr = new Int8Array( 5 );\narr.buffer\n","Int8Array.prototype.byteLength":"var arr = new Int8Array( 5 );\narr.byteLength\n","Int8Array.prototype.byteOffset":"var arr = new Int8Array( 5 );\narr.byteOffset\n","Int8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int8Array.prototype.length":"var arr = new Int8Array( 5 );\narr.length\n","Int8Array.prototype.copyWithin":"var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int8Array.prototype.entries":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.every":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int8Array.prototype.fill":"var arr = new Int8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int8Array.prototype.filter":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int8Array.prototype.find":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int8Array.prototype.findIndex":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int8Array.prototype.forEach":"var arr = new Int8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int8Array.prototype.includes":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int8Array.prototype.indexOf":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int8Array.prototype.join":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int8Array.prototype.keys":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.lastIndexOf":"var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int8Array.prototype.map":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn );\n","Int8Array.prototype.reduce":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int8Array.prototype.reduceRight":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int8Array.prototype.reverse":"var arr = new Int8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int8Array.prototype.set":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int8Array.prototype.slice":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int8Array.prototype.some":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int8Array.prototype.sort":"var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int8Array.prototype.subarray":"var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int8Array.prototype.toLocaleString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int8Array.prototype.toString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toString()\n","Int8Array.prototype.values":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","INT16_MAX":"INT16_MAX\n","INT16_MIN":"INT16_MIN\n","INT16_NUM_BYTES":"INT16_NUM_BYTES\n","Int16Array":"var arr = new Int16Array()\nvar arr = new Int16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Int16Array( buf, 0, 4 )\n","Int16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int16Array.from( [ 1, 2 ], mapFcn )\n","Int16Array.of":"var arr = Int16Array.of( 1, 2 )\n","Int16Array.BYTES_PER_ELEMENT":"Int16Array.BYTES_PER_ELEMENT\n","Int16Array.name":"Int16Array.name\n","Int16Array.prototype.buffer":"var arr = new Int16Array( 5 );\narr.buffer\n","Int16Array.prototype.byteLength":"var arr = new Int16Array( 5 );\narr.byteLength\n","Int16Array.prototype.byteOffset":"var arr = new Int16Array( 5 );\narr.byteOffset\n","Int16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int16Array.prototype.length":"var arr = new Int16Array( 5 );\narr.length\n","Int16Array.prototype.copyWithin":"var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int16Array.prototype.entries":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.every":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int16Array.prototype.fill":"var arr = new Int16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int16Array.prototype.filter":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int16Array.prototype.find":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int16Array.prototype.findIndex":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int16Array.prototype.forEach":"var arr = new Int16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int16Array.prototype.includes":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int16Array.prototype.indexOf":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int16Array.prototype.join":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int16Array.prototype.keys":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.lastIndexOf":"var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int16Array.prototype.map":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn );\n","Int16Array.prototype.reduce":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int16Array.prototype.reduceRight":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int16Array.prototype.reverse":"var arr = new Int16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int16Array.prototype.set":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int16Array.prototype.slice":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int16Array.prototype.some":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int16Array.prototype.sort":"var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int16Array.prototype.subarray":"var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int16Array.prototype.toLocaleString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int16Array.prototype.toString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toString()\n","Int16Array.prototype.values":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","INT32_MAX":"INT32_MAX\n","INT32_MIN":"INT32_MIN\n","INT32_NUM_BYTES":"INT32_NUM_BYTES\n","Int32Array":"var arr = new Int32Array()\nvar arr = new Int32Array( 5 )\nvar arr1 = new Int16Array( [ 5, 5, 5 ] );\nvar arr2 = new Int32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Int32Array( buf, 0, 4 )\n","Int32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int32Array.from( [ 1, 2 ], mapFcn )\n","Int32Array.of":"var arr = Int32Array.of( 1, 2 )\n","Int32Array.BYTES_PER_ELEMENT":"Int32Array.BYTES_PER_ELEMENT\n","Int32Array.name":"Int32Array.name\n","Int32Array.prototype.buffer":"var arr = new Int32Array( 5 );\narr.buffer\n","Int32Array.prototype.byteLength":"var arr = new Int32Array( 5 );\narr.byteLength\n","Int32Array.prototype.byteOffset":"var arr = new Int32Array( 5 );\narr.byteOffset\n","Int32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int32Array.prototype.length":"var arr = new Int32Array( 5 );\narr.length\n","Int32Array.prototype.copyWithin":"var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int32Array.prototype.entries":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.every":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int32Array.prototype.fill":"var arr = new Int32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int32Array.prototype.filter":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int32Array.prototype.find":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int32Array.prototype.findIndex":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int32Array.prototype.forEach":"var arr = new Int32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int32Array.prototype.includes":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int32Array.prototype.indexOf":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int32Array.prototype.join":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int32Array.prototype.keys":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.lastIndexOf":"var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int32Array.prototype.map":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn );\n","Int32Array.prototype.reduce":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int32Array.prototype.reduceRight":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int32Array.prototype.reverse":"var arr = new Int32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int32Array.prototype.set":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int32Array.prototype.slice":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int32Array.prototype.some":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int32Array.prototype.sort":"var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int32Array.prototype.subarray":"var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int32Array.prototype.toLocaleString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int32Array.prototype.toString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toString()\n","Int32Array.prototype.values":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","IS_BIG_ENDIAN":"IS_BIG_ENDIAN\n","IS_BROWSER":"IS_BROWSER\n","IS_DARWIN":"IS_DARWIN\n","IS_ELECTRON":"IS_ELECTRON\n","IS_ELECTRON_MAIN":"IS_ELECTRON_MAIN\n","IS_ELECTRON_RENDERER":"IS_ELECTRON_RENDERER\n","IS_LITTLE_ENDIAN":"IS_LITTLE_ENDIAN\n","IS_NODE":"IS_NODE\n","IS_WEB_WORKER":"IS_WEB_WORKER\n","IS_WINDOWS":"IS_WINDOWS\n","isAbsolutePath":"var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath( '/foo/bar/baz' )\n","isAbsolutePath.posix":"var bool = isAbsolutePath.posix( '/foo/bar/baz' )\nbool = isAbsolutePath.posix( 'foo/bar/baz' )\n","isAbsolutePath.win32":"var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n","isAccessorArray":"var bool = isAccessorArray( new Complex64Array( 10 ) )\nbool = isAccessorArray( [] )\nbool = isAccessorArray( { 'length': 0 } )\nbool = isAccessorArray( {} )\n","isAccessorProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorProperty( obj, 'boop' )\nbool = isAccessorProperty( obj, 'beep' )\n","isAccessorPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorPropertyIn( obj, 'boop' )\nbool = isAccessorPropertyIn( obj, 'beep' )\n","isAlphagram":"var out = isAlphagram( 'beep' )\nout = isAlphagram( 'zba' )\nout = isAlphagram( '' )\n","isAlphaNumeric":"var bool = isAlphaNumeric( 'abc0123456789' )\nbool = isAlphaNumeric( 'abcdef' )\nbool = isAlphaNumeric( '0xff' )\nbool = isAlphaNumeric( '' )\n","isAnagram":"var str1 = 'I am a weakish speller';\nvar str2 = 'William Shakespeare';\nvar bool = isAnagram( str1, str2 )\nbool = isAnagram( 'bat', 'tabba' )\n","isArguments":"function foo() { return arguments; };\nvar bool = isArguments( foo() )\nbool = isArguments( [] )\n","isArray":"var bool = isArray( [] )\nbool = isArray( {} )\n","isArrayArray":"var bool = isArrayArray( [ [], [] ] )\nbool = isArrayArray( [ {}, {} ] )\nbool = isArrayArray( [] )\n","isArrayBuffer":"var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\nbool = isArrayBuffer( [] )\n","isArrayBufferView":"var bool = isArrayBufferView( new Int8Array() )\nbool = isArrayBufferView( [] )\n","isArrayLength":"var bool = isArrayLength( 5 )\nbool = isArrayLength( 2.0e200 )\nbool = isArrayLength( -3.14 )\nbool = isArrayLength( null )\n","isArrayLike":"var bool = isArrayLike( [] )\nbool = isArrayLike( { 'length': 10 } )\nbool = isArrayLike( 'beep' )\nbool = isArrayLike( null )\n","isArrayLikeObject":"var bool = isArrayLikeObject( [] )\nbool = isArrayLikeObject( { 'length': 10 } )\nbool = isArrayLikeObject( 'beep' )\n","isASCII":"var str = 'beep boop';\nvar bool = isASCII( str )\nbool = isASCII( fromCodePoint( 130 ) )\n","isBetween":"var bool = isBetween( 3.14, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.0, 4.0 )\nbool = isBetween( 4.0, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.14, 4.0 )\nbool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\nbool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n","isBetweenArray":"var arr = [ 3.0, 3.14, 4.0 ];\nvar bool = isBetweenArray( arr, 3.0, 4.0 )\nbool = isBetweenArray( arr, 3.14, 4.0 )\nbool = isBetweenArray( arr, 3.0, 3.14 )\nbool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\nbool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n","isBigInt":"var bool = isBigInt( BigInt( '1' ) )\nbool = isBigInt( Object( BigInt( '1' ) ) )\nbool = isBigInt( {} )\nbool = isBigInt( null )\nbool = isBigInt( true )\n","isBigInt64Array":"var bool = isBigInt64Array( new BigInt64Array( 10 ) )\nbool = isBigInt64Array( [] )\n","isBigUint64Array":"var bool = isBigUint64Array( new BigUint64Array( 10 ) )\nbool = isBigUint64Array( [] )\n","isBinaryString":"var bool = isBinaryString( '1000101' )\nbool = isBinaryString( 'beep' )\nbool = isBinaryString( '' )\n","isBlankString":"var bool = isBlankString( ' ' )\nbool = isBlankString( 'beep' )\nbool = isBlankString( null )\n","isBoolean":"var bool = isBoolean( false )\nbool = isBoolean( new Boolean( false ) )\n","isBoolean.isPrimitive":"var bool = isBoolean.isPrimitive( true )\nbool = isBoolean.isPrimitive( false )\nbool = isBoolean.isPrimitive( new Boolean( true ) )\n","isBoolean.isObject":"var bool = isBoolean.isObject( true )\nbool = isBoolean.isObject( new Boolean( false ) )\n","isBooleanArray":"var bool = isBooleanArray( [ true, false, true ] )\nbool = isBooleanArray( [ true, 'abc', false ] )\n","isBooleanArray.primitives":"var bool = isBooleanArray.primitives( [ true, false ] )\nbool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n","isBooleanArray.objects":"var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\nbool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n","isBoxedPrimitive":"var bool = isBoxedPrimitive( new Boolean( false ) )\nbool = isBoxedPrimitive( true )\n","isBuffer":"var bool = isBuffer( new Buffer( 'beep' ) )\nbool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\nbool = isBuffer( {} )\nbool = isBuffer( [] )\n","isCapitalized":"var bool = isCapitalized( 'Hello' )\nbool = isCapitalized( 'world' )\n","isCentrosymmetricMatrix":"var buf = [ 2, 1, 1, 2 ];\nvar M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isCentrosymmetricMatrix( M )\nbool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isCentrosymmetricMatrix( 3.14 )\nbool = isCentrosymmetricMatrix( {} )\n","isCircular":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircular( obj )\nbool = isCircular( {} )\nbool = isCircular( null )\n","isCircularArray":"var arr = [ 1, 2, 3 ];\narr.push( arr );\nvar bool = isCircularArray( arr )\nbool = isCircularArray( [] )\nbool = isCircularArray( null )\n","isCircularPlainObject":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircularPlainObject( obj )\nbool = isCircularPlainObject( {} )\nbool = isCircularPlainObject( null )\n","isClass":"var bool = isClass( class Person {} )\nbool = isClass( function Person() {} )\nbool = isClass( {} )\nbool = isClass( null )\nbool = isClass( true )\n","isCollection":"var bool = isCollection( [] )\nbool = isCollection( { 'length': 0 } )\nbool = isCollection( {} )\n","isComplex":"var bool = isComplex( new Complex64( 2.0, 2.0 ) )\nbool = isComplex( new Complex128( 3.0, 1.0 ) )\nbool = isComplex( 3.14 )\nbool = isComplex( {} )\n","isComplex64":"var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\nbool = isComplex64( new Complex128( 3.0, 1.0 ) )\nbool = isComplex64( 3.14 )\nbool = isComplex64( {} )\n","isComplex64Array":"var bool = isComplex64Array( new Complex64Array( 10 ) )\nbool = isComplex64Array( [] )\n","isComplex64MatrixLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64MatrixLike( M )\nbool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64MatrixLike( 3.14 )\nbool = isComplex64MatrixLike( {} )\n","isComplex64ndarrayLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64ndarrayLike( M )\nbool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64ndarrayLike( 3.14 )\nbool = isComplex64ndarrayLike( {} )\n","isComplex64VectorLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64VectorLike( M )\nbool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64VectorLike( 3.14 )\nbool = isComplex64VectorLike( {} )\n","isComplex128":"var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\nbool = isComplex128( new Complex64( 2.0, 2.0 ) )\nbool = isComplex128( 3.14 )\nbool = isComplex128( {} )\n","isComplex128Array":"var bool = isComplex128Array( new Complex128Array( 10 ) )\nbool = isComplex128Array( [] )\n","isComplex128MatrixLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128MatrixLike( M )\nbool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128MatrixLike( 3.14 )\nbool = isComplex128MatrixLike( {} )\n","isComplex128ndarrayLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128ndarrayLike( M )\nbool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128ndarrayLike( 3.14 )\nbool = isComplex128ndarrayLike( {} )\n","isComplex128VectorLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128VectorLike( M )\nbool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128VectorLike( 3.14 )\nbool = isComplex128VectorLike( {} )\n","isComplexLike":"var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\nbool = isComplexLike( new Complex128( 3.0, 1.0 ) )\nbool = isComplexLike( 3.14 )\nbool = isComplexLike( {} )\n","isComplexTypedArray":"var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n","isComplexTypedArrayLike":"var bool = isComplexTypedArrayLike( new Complex128Array() )\nbool = isComplexTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4,\n'get': function get() {},\n'set': function set() {}\n })\n","isComposite":"var bool = isComposite( 4.0 )\nbool = isComposite( new Number( 4.0 ) )\nbool = isComposite( 3.14 )\nbool = isComposite( -4.0 )\nbool = isComposite( null )\n","isComposite.isPrimitive":"var bool = isComposite.isPrimitive( 4.0 )\nbool = isComposite.isPrimitive( new Number( 4.0 ) )\n","isComposite.isObject":"var bool = isComposite.isObject( 4.0 )\nbool = isComposite.isObject( new Number( 4.0 ) )\n","isConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurableProperty( obj, 'boop' )\nbool = isConfigurableProperty( obj, 'beep' )\n","isConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurablePropertyIn( obj, 'boop' )\nbool = isConfigurablePropertyIn( obj, 'beep' )\n","isCubeNumber":"var bool = isCubeNumber( 8.0 )\nbool = isCubeNumber( new Number( 8.0 ) )\nbool = isCubeNumber( 3.14 )\nbool = isCubeNumber( -5.0 )\nbool = isCubeNumber( null )\n","isCubeNumber.isPrimitive":"var bool = isCubeNumber.isPrimitive( 8.0 )\nbool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n","isCubeNumber.isObject":"var bool = isCubeNumber.isObject( 8.0 )\nbool = isCubeNumber.isObject( new Number( 8.0 ) )\n","isDataProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataProperty( obj, 'boop' )\nbool = isDataProperty( obj, 'beep' )\n","isDataPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataPropertyIn( obj, 'boop' )\nbool = isDataPropertyIn( obj, 'beep' )\n","isDataView":"var buf = new ArrayBuffer( 10 );\nvar bool = isDataView( new DataView( buf ) )\nbool = isDataView( [] )\n","isDateObject":"var bool = isDateObject( new Date() )\nbool = isDateObject( '2017-01-01' )\n","isDateObjectArray":"var bool = isDateObjectArray( [ new Date(), new Date() ] )\nbool = isDateObjectArray( [ {}, {} ] )\nbool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\nbool = isDateObjectArray( [] )\n","isDigitString":"var bool = isDigitString( '0123456789' )\nbool = isDigitString( 'abcdef' )\nbool = isDigitString( '0xff' )\nbool = isDigitString( '' )\n","isEmailAddress":"var bool = isEmailAddress( 'beep@boop.com' )\nbool = isEmailAddress( 'beep' )\nbool = isEmailAddress( null )\n","isEmptyArray":"var bool = isEmptyArray( [] )\nbool = isEmptyArray( [ 1, 2, 3 ] )\nbool = isEmptyArray( {} )\n","isEmptyArrayLikeObject":"var bool = isEmptyArrayLikeObject( [] )\nbool = isEmptyArrayLikeObject( { 'length': 0 } )\nbool = isEmptyArrayLikeObject( '' )\n","isEmptyCollection":"var bool = isEmptyCollection( [] )\nbool = isEmptyCollection( { 'length': 0 } )\nbool = isEmptyCollection( [ 1, 2, 3 ] )\nbool = isEmptyCollection( {} )\n","isEmptyObject":"var bool = isEmptyObject( {} )\nbool = isEmptyObject( { 'beep': 'boop' } )\nbool = isEmptyObject( [] )\n","isEmptyString":"var bool = isEmptyString( '' )\nbool = isEmptyString( new String( '' ) )\nbool = isEmptyString( 'beep' )\nbool = isEmptyString( [] )\n","isEmptyString.isPrimitive":"var bool = isEmptyString.isPrimitive( '' )\nbool = isEmptyString.isPrimitive( new String( '' ) )\n","isEmptyString.isObject":"var bool = isEmptyString.isObject( new String( '' ) )\nbool = isEmptyString.isObject( '' )\n","isEnumerableProperty":"var beep = { 'boop': true };\nvar bool = isEnumerableProperty( beep, 'boop' )\nbool = isEnumerableProperty( beep, 'hasOwnProperty' )\n","isEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isEnumerablePropertyIn( obj, 'boop' )\nbool = isEnumerablePropertyIn( obj, 'beep' )\n","isError":"var bool = isError( new Error( 'beep' ) )\nbool = isError( {} )\n","isEvalError":"var bool = isEvalError( new EvalError( 'beep' ) )\nbool = isEvalError( {} )\n","isEven":"var bool = isEven( 4.0 )\nbool = isEven( new Number( 4.0 ) )\nbool = isEven( 3.0 )\nbool = isEven( -3.14 )\nbool = isEven( null )\n","isEven.isPrimitive":"var bool = isEven.isPrimitive( -4.0 )\nbool = isEven.isPrimitive( new Number( -4.0 ) )\n","isEven.isObject":"var bool = isEven.isObject( 4.0 )\nbool = isEven.isObject( new Number( 4.0 ) )\n","isFalsy":"var bool = isFalsy( false )\nbool = isFalsy( '' )\nbool = isFalsy( 0 )\nbool = isFalsy( null )\nbool = isFalsy( void 0 )\nbool = isFalsy( NaN )\nbool = isFalsy( {} )\nbool = isFalsy( [] )\n","isFalsyArray":"var bool = isFalsyArray( [ null, '' ] )\nbool = isFalsyArray( [ {}, [] ] )\nbool = isFalsyArray( [] )\n","isFinite":"var bool = isFinite( 5.0 )\nbool = isFinite( new Number( 5.0 ) )\nbool = isFinite( 1.0/0.0 )\nbool = isFinite( null )\n","isFinite.isPrimitive":"var bool = isFinite.isPrimitive( -3.0 )\nbool = isFinite.isPrimitive( new Number( -3.0 ) )\n","isFinite.isObject":"var bool = isFinite.isObject( 3.0 )\nbool = isFinite.isObject( new Number( 3.0 ) )\n","isFiniteArray":"var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n","isFiniteArray.primitives":"var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\nbool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isFiniteArray.objects":"var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n","isFloat32Array":"var bool = isFloat32Array( new Float32Array( 10 ) )\nbool = isFloat32Array( [] )\n","isFloat32MatrixLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32MatrixLike( M )\nbool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32MatrixLike( 3.14 )\nbool = isFloat32MatrixLike( {} )\n","isFloat32ndarrayLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32ndarrayLike( M )\nbool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32ndarrayLike( 3.14 )\nbool = isFloat32ndarrayLike( {} )\n","isFloat32VectorLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32VectorLike( M )\nbool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32VectorLike( 3.14 )\nbool = isFloat32VectorLike( {} )\n","isFloat64Array":"var bool = isFloat64Array( new Float64Array( 10 ) )\nbool = isFloat64Array( [] )\n","isFloat64MatrixLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64MatrixLike( M )\nbool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64MatrixLike( 3.14 )\nbool = isFloat64MatrixLike( {} )\n","isFloat64ndarrayLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64ndarrayLike( M )\nbool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64ndarrayLike( 3.14 )\nbool = isFloat64ndarrayLike( {} )\n","isFloat64VectorLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64VectorLike( M )\nbool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64VectorLike( 3.14 )\nbool = isFloat64VectorLike( {} )\n","isFunction":"function beep() {};\nvar bool = isFunction( beep )\nbool = isFunction( {} )\n","isFunctionArray":"function beep() {};\nfunction boop() {};\nvar bool = isFunctionArray( [ beep, boop ] )\nbool = isFunctionArray( [ {}, beep ] )\nbool = isFunctionArray( [] )\n","isGeneratorObject":"function* generateID() {\n var idx = 0;\n while ( idx < idx+1 ) {\n yield idx;\n idx += 1;\n }\n };\nvar bool = isGeneratorObject( generateID() )\nbool = isGeneratorObject( generateID )\nbool = isGeneratorObject( {} )\nbool = isGeneratorObject( null )\n","isGeneratorObjectLike":"var obj = {\n 'next': function noop() {},\n 'return': function noop() {},\n 'throw': function noop() {}\n };\nvar bool = isGeneratorObjectLike( obj )\nbool = isGeneratorObjectLike( {} )\nbool = isGeneratorObjectLike( null )\n","isgzipBuffer":"var buf = new Uint8Array( 20 );\nbuf[ 0 ] = 31; // 0x1f => magic number\nbuf[ 1 ] = 139; // 0x8b\nbuf[ 2 ] = 8; // 0x08 => compression method\nvar bool = isgzipBuffer( buf )\nbool = isgzipBuffer( [] )\n","isHexString":"var bool = isHexString( '0123456789abcdefABCDEF' )\nbool = isHexString( '0xffffff' )\nbool = isHexString( 'x' )\nbool = isHexString( '' )\n","isInfinite":"var bool = isInfinite( 1.0/0.0 )\nbool = isInfinite( new Number( -1.0/0.0 ) )\nbool = isInfinite( 5.0 )\nbool = isInfinite( '1.0/0.0' )\n","isInfinite.isPrimitive":"var bool = isInfinite.isPrimitive( -1.0/0.0 )\nbool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isInfinite.isObject":"var bool = isInfinite.isObject( 1.0/0.0 )\nbool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n","isInheritedProperty":"var beep = { 'boop': true };\nvar bool = isInheritedProperty( beep, 'boop' )\nbool = isInheritedProperty( beep, 'toString' )\nbool = isInheritedProperty( beep, 'bop' )\n","isInt8Array":"var bool = isInt8Array( new Int8Array( 10 ) )\nbool = isInt8Array( [] )\n","isInt16Array":"var bool = isInt16Array( new Int16Array( 10 ) )\nbool = isInt16Array( [] )\n","isInt32Array":"var bool = isInt32Array( new Int32Array( 10 ) )\nbool = isInt32Array( [] )\n","isInteger":"var bool = isInteger( 5.0 )\nbool = isInteger( new Number( 5.0 ) )\nbool = isInteger( -3.14 )\nbool = isInteger( null )\n","isInteger.isPrimitive":"var bool = isInteger.isPrimitive( -3.0 )\nbool = isInteger.isPrimitive( new Number( -3.0 ) )\n","isInteger.isObject":"var bool = isInteger.isObject( 3.0 )\nbool = isInteger.isObject( new Number( 3.0 ) )\n","isIntegerArray":"var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isIntegerArray( [ -3.0, '3.0' ] )\n","isIntegerArray.primitives":"var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\nbool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isIntegerArray.objects":"var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n","isIterableLike":"var bool = isIterableLike( [ 1, 2, 3 ] )\nbool = isIterableLike( {} )\nbool = isIterableLike( null )\n","isIteratorLike":"var obj = {\n 'next': function noop() {}\n };\nvar bool = isIteratorLike( obj )\nbool = isIteratorLike( {} )\nbool = isIteratorLike( null )\n","isJSON":"var bool = isJSON( '{\"a\":5}' )\nbool = isJSON( '{a\":5}' )\n","isLeapYear":"var bool = isLeapYear( new Date() )\nbool = isLeapYear( 1996 )\nbool = isLeapYear( 2001 )\n","isLocalhost":"var bool = isLocalhost( 'localhost' )\nbool = isLocalhost( '127.0.0.1' )\nbool = isLocalhost( 'stdlib.io' )\n","isLowercase":"var bool = isLowercase( 'hello' )\nbool = isLowercase( 'World' )\n","isMatrixLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isMatrixLike( M )\nbool = isMatrixLike( [ 1, 2, 3, 4 ] )\nbool = isMatrixLike( 3.14 )\nbool = isMatrixLike( {} )\n","isMethod":"var beep = { 'boop': function beep() { return 'beep'; } };\nvar bool = isMethod( beep, 'boop' )\nbool = isMethod( beep, 'toString' )\n","isMethodIn":"var beep = { 'boop': true };\nvar bool = isMethodIn( beep, 'toString' )\nbool = isMethodIn( beep, 'boop' )\nbool = isMethodIn( beep, 'bop' )\n","isMultiSlice":"var bool = isMultiSlice( new MultiSlice() )\nbool = isMultiSlice( 3.14 )\nbool = isMultiSlice( {} )\n","isNamedTypedTupleLike":"var Point = namedtypedtuple( [ 'x', 'y' ] );\nvar p = new Point();\nvar bool = isNamedTypedTupleLike( p )\nbool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\nbool = isNamedTypedTupleLike( 3.14 )\nbool = isNamedTypedTupleLike( {} )\n","isnan":"var bool = isnan( NaN )\nbool = isnan( new Number( NaN ) )\nbool = isnan( 3.14 )\nbool = isnan( null )\n","isnan.isPrimitive":"var bool = isnan.isPrimitive( NaN )\nbool = isnan.isPrimitive( 3.14 )\nbool = isnan.isPrimitive( new Number( NaN ) )\n","isnan.isObject":"var bool = isnan.isObject( NaN )\nbool = isnan.isObject( new Number( NaN ) )\n","isNaNArray":"var bool = isNaNArray( [ NaN, NaN, NaN ] )\nbool = isNaNArray( [ NaN, 2 ] )\n","isNaNArray.primitives":"var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\nbool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n","isNaNArray.objects":"var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n","isNativeFunction":"var bool = isNativeFunction( Date )\nfunction beep() {};\nbool = isNativeFunction( beep )\nbool = isNativeFunction( {} )\n","isndarrayLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLike( M )\nbool = isndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isndarrayLike( 3.14 )\nbool = isndarrayLike( {} )\n","isNegativeInteger":"var bool = isNegativeInteger( -5.0 )\nbool = isNegativeInteger( new Number( -5.0 ) )\nbool = isNegativeInteger( 5.0 )\nbool = isNegativeInteger( -3.14 )\nbool = isNegativeInteger( null )\n","isNegativeInteger.isPrimitive":"var bool = isNegativeInteger.isPrimitive( -3.0 )\nbool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n","isNegativeInteger.isObject":"var bool = isNegativeInteger.isObject( -3.0 )\nbool = isNegativeInteger.isObject( new Number( -3.0 ) )\n","isNegativeIntegerArray":"var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n","isNegativeIntegerArray.primitives":"var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeIntegerArray.objects":"var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumber":"var bool = isNegativeNumber( -5.0 )\nbool = isNegativeNumber( new Number( -5.0 ) )\nbool = isNegativeNumber( -3.14 )\nbool = isNegativeNumber( 5.0 )\nbool = isNegativeNumber( null )\n","isNegativeNumber.isPrimitive":"var bool = isNegativeNumber.isPrimitive( -3.0 )\nbool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n","isNegativeNumber.isObject":"var bool = isNegativeNumber.isObject( -3.0 )\nbool = isNegativeNumber.isObject( new Number( -3.0 ) )\n","isNegativeNumberArray":"var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n","isNegativeNumberArray.primitives":"var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumberArray.objects":"var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeZero":"var bool = isNegativeZero( -0.0 )\nbool = isNegativeZero( new Number( -0.0 ) )\nbool = isNegativeZero( -3.14 )\nbool = isNegativeZero( 0.0 )\nbool = isNegativeZero( null )\n","isNegativeZero.isPrimitive":"var bool = isNegativeZero.isPrimitive( -0.0 )\nbool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n","isNegativeZero.isObject":"var bool = isNegativeZero.isObject( -0.0 )\nbool = isNegativeZero.isObject( new Number( -0.0 ) )\n","isNodeBuiltin":"var bool = isNodeBuiltin( 'cluster' )\nbool = isNodeBuiltin( 'crypto' )\nbool = isNodeBuiltin( 'fs-extra' )\nbool = isNodeBuiltin( '' )\n","isNodeDuplexStreamLike":"var Stream = require( 'stream' ).Duplex;\ns = new Stream();\nvar bool = isNodeDuplexStreamLike( s )\nbool = isNodeDuplexStreamLike( {} )\n","isNodeReadableStreamLike":"var Stream = require( 'stream' ).Readable;\ns = new Stream();\nvar bool = isNodeReadableStreamLike( s )\nbool = isNodeReadableStreamLike( {} )\n","isNodeREPL":"var bool = isNodeREPL()\n","isNodeStreamLike":"var Stream = require( 'stream' ).Stream;\ns = new Stream();\nvar bool = isNodeStreamLike( s )\nbool = isNodeStreamLike( {} )\n","isNodeTransformStreamLike":"var Stream = require( 'stream' ).Transform;\ns = new Stream();\nvar bool = isNodeTransformStreamLike( s )\nbool = isNodeTransformStreamLike( {} )\n","isNodeWritableStreamLike":"var Stream = require( 'stream' ).Writable;\ns = new Stream();\nvar bool = isNodeWritableStreamLike( s )\nbool = isNodeWritableStreamLike( {} )\n","isNonConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurableProperty( obj, 'boop' )\nbool = isNonConfigurableProperty( obj, 'beep' )\n","isNonConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurablePropertyIn( obj, 'boop' )\nbool = isNonConfigurablePropertyIn( obj, 'beep' )\n","isNonEnumerableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerableProperty( obj, 'boop' )\nbool = isNonEnumerableProperty( obj, 'beep' )\n","isNonEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerablePropertyIn( obj, 'boop' )\nbool = isNonEnumerablePropertyIn( obj, 'beep' )\n","isNonNegativeFinite":"var bool = isNonNegativeFinite( 5.0 )\nbool = isNonNegativeFinite( new Number( 5.0 ) )\nbool = isNonNegativeFinite( 3.14 )\nbool = isNonNegativeFinite( -5.0 )\nbool = isNonNegativeFinite( null )\nbool = isNonNegativeFinite( PINF )\n","isNonNegativeFinite.isPrimitive":"var bool = isNonNegativeFinite.isPrimitive( 3.0 )\nbool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeFinite.isObject":"var bool = isNonNegativeFinite.isObject( 3.0 )\nbool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n","isNonNegativeInteger":"var bool = isNonNegativeInteger( 5.0 )\nbool = isNonNegativeInteger( new Number( 5.0 ) )\nbool = isNonNegativeInteger( 3.14 )\nbool = isNonNegativeInteger( -5.0 )\nbool = isNonNegativeInteger( null )\n","isNonNegativeInteger.isPrimitive":"var bool = isNonNegativeInteger.isPrimitive( 3.0 )\nbool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeInteger.isObject":"var bool = isNonNegativeInteger.isObject( 3.0 )\nbool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n","isNonNegativeIntegerArray":"var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n","isNonNegativeIntegerArray.primitives":"var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeIntegerArray.objects":"var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumber":"var bool = isNonNegativeNumber( 5.0 )\nbool = isNonNegativeNumber( new Number( 5.0 ) )\nbool = isNonNegativeNumber( 3.14 )\nbool = isNonNegativeNumber( -5.0 )\nbool = isNonNegativeNumber( null )\n","isNonNegativeNumber.isPrimitive":"var bool = isNonNegativeNumber.isPrimitive( 3.0 )\nbool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeNumber.isObject":"var bool = isNonNegativeNumber.isObject( 3.0 )\nbool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n","isNonNegativeNumberArray":"var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n","isNonNegativeNumberArray.primitives":"var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumberArray.objects":"var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonPositiveInteger":"var bool = isNonPositiveInteger( -5.0 )\nbool = isNonPositiveInteger( new Number( -5.0 ) )\nbool = isNonPositiveInteger( 5.0 )\nbool = isNonPositiveInteger( -3.14 )\nbool = isNonPositiveInteger( null )\n","isNonPositiveInteger.isPrimitive":"var bool = isNonPositiveInteger.isPrimitive( -3.0 )\nbool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveInteger.isObject":"var bool = isNonPositiveInteger.isObject( -3.0 )\nbool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n","isNonPositiveIntegerArray":"var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n","isNonPositiveIntegerArray.primitives":"var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveIntegerArray.objects":"var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumber":"var bool = isNonPositiveNumber( -5.0 )\nbool = isNonPositiveNumber( new Number( -5.0 ) )\nbool = isNonPositiveNumber( -3.14 )\nbool = isNonPositiveNumber( 5.0 )\nbool = isNonPositiveNumber( null )\n","isNonPositiveNumber.isPrimitive":"var bool = isNonPositiveNumber.isPrimitive( -3.0 )\nbool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveNumber.isObject":"var bool = isNonPositiveNumber.isObject( -3.0 )\nbool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n","isNonPositiveNumberArray":"var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n","isNonPositiveNumberArray.primitives":"var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumberArray.objects":"var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonSymmetricMatrix":"var buf = [ 1, 2, 3, 4 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isNonSymmetricMatrix( M )\nbool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isNonSymmetricMatrix( 3.14 )\nbool = isNonSymmetricMatrix( {} )\n","isNull":"var bool = isNull( null )\nbool = isNull( true )\n","isNullArray":"var bool = isNullArray( [ null, null, null ] )\nbool = isNullArray( [ NaN, 2, null ] )\n","isNumber":"var bool = isNumber( 3.14 )\nbool = isNumber( new Number( 3.14 ) )\nbool = isNumber( NaN )\nbool = isNumber( null )\n","isNumber.isPrimitive":"var bool = isNumber.isPrimitive( 3.14 )\nbool = isNumber.isPrimitive( NaN )\nbool = isNumber.isPrimitive( new Number( 3.14 ) )\n","isNumber.isObject":"var bool = isNumber.isObject( 3.14 )\nbool = isNumber.isObject( new Number( 3.14 ) )\n","isNumberArray":"var bool = isNumberArray( [ 1, 2, 3 ] )\nbool = isNumberArray( [ '1', 2, 3 ] )\n","isNumberArray.primitives":"var arr = [ 1, 2, 3 ];\nvar bool = isNumberArray.primitives( arr )\narr = [ 1, new Number( 2 ) ];\nbool = isNumberArray.primitives( arr )\n","isNumberArray.objects":"var arr = [ new Number( 1 ), new Number( 2 ) ];\nvar bool = isNumberArray.objects( arr )\narr = [ new Number( 1 ), 2 ];\nbool = isNumberArray.objects( arr )\n","isNumericArray":"var bool = isNumericArray( new Int8Array( 10 ) )\nbool = isNumericArray( [ 1, 2, 3 ] )\nbool = isNumericArray( [ '1', '2', '3' ] )\n","isObject":"var bool = isObject( {} )\nbool = isObject( true )\n","isObjectArray":"var bool = isObjectArray( [ {}, new Number(3.0) ] )\nbool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isObjectArray( [ {}, '3.0' ] )\n","isObjectLike":"var bool = isObjectLike( {} )\nbool = isObjectLike( [] )\nbool = isObjectLike( null )\n","isOdd":"var bool = isOdd( 5.0 )\nbool = isOdd( new Number( 5.0 ) )\nbool = isOdd( 4.0 )\nbool = isOdd( new Number( 4.0 ) )\nbool = isOdd( -3.14 )\nbool = isOdd( null )\n","isOdd.isPrimitive":"var bool = isOdd.isPrimitive( -5.0 )\nbool = isOdd.isPrimitive( new Number( -5.0 ) )\n","isOdd.isObject":"var bool = isOdd.isObject( 5.0 )\nbool = isOdd.isObject( new Number( 5.0 ) )\n","isoWeeksInYear":"var num = isoWeeksInYear()\nnum = isoWeeksInYear( 2015 )\nnum = isoWeeksInYear( 2017 )\n","isPersymmetricMatrix":"var buf = [ 1, 2, 3, 1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isPersymmetricMatrix( M )\nbool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isPersymmetricMatrix( 3.14 )\nbool = isPersymmetricMatrix( {} )\n","isPlainObject":"var bool = isPlainObject( {} )\nbool = isPlainObject( null )\n","isPlainObjectArray":"var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isPlainObjectArray( [ {}, new Number(3.0) ] )\nbool = isPlainObjectArray( [ {}, '3.0' ] )\n","isPositiveInteger":"var bool = isPositiveInteger( 5.0 )\nbool = isPositiveInteger( new Number( 5.0 ) )\nbool = isPositiveInteger( 3.14 )\nbool = isPositiveInteger( -5.0 )\nbool = isPositiveInteger( null )\n","isPositiveInteger.isPrimitive":"var bool = isPositiveInteger.isPrimitive( 3.0 )\nbool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n","isPositiveInteger.isObject":"var bool = isPositiveInteger.isObject( 3.0 )\nbool = isPositiveInteger.isObject( new Number( 3.0 ) )\n","isPositiveIntegerArray":"var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n","isPositiveIntegerArray.primitives":"var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveIntegerArray.objects":"var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveNumber":"var bool = isPositiveNumber( 5.0 )\nbool = isPositiveNumber( new Number( 5.0 ) )\nbool = isPositiveNumber( 3.14 )\nbool = isPositiveNumber( -5.0 )\nbool = isPositiveNumber( null )\n","isPositiveNumber.isPrimitive":"var bool = isPositiveNumber.isPrimitive( 3.0 )\nbool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n","isPositiveNumber.isObject":"var bool = isPositiveNumber.isObject( 3.0 )\nbool = isPositiveNumber.isObject( new Number( 3.0 ) )\n","isPositiveNumberArray":"var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n","isPositiveNumberArray.primitives":"var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveNumberArray.objects":"var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveZero":"var bool = isPositiveZero( 0.0 )\nbool = isPositiveZero( new Number( 0.0 ) )\nbool = isPositiveZero( -3.14 )\nbool = isPositiveZero( -0.0 )\nbool = isPositiveZero( null )\n","isPositiveZero.isPrimitive":"var bool = isPositiveZero.isPrimitive( 0.0 )\nbool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n","isPositiveZero.isObject":"var bool = isPositiveZero.isObject( 0.0 )\nbool = isPositiveZero.isObject( new Number( 0.0 ) )\n","isPrime":"var bool = isPrime( 5.0 )\nbool = isPrime( new Number( 5.0 ) )\nbool = isPrime( 3.14 )\nbool = isPrime( -5.0 )\nbool = isPrime( null )\n","isPrime.isPrimitive":"var bool = isPrime.isPrimitive( 5.0 )\nbool = isPrime.isPrimitive( new Number( 5.0 ) )\n","isPrime.isObject":"var bool = isPrime.isObject( 5.0 )\nbool = isPrime.isObject( new Number( 5.0 ) )\n","isPrimitive":"var bool = isPrimitive( true )\nbool = isPrimitive( {} )\n","isPrimitiveArray":"var bool = isPrimitiveArray( [ '3', 2, null ] )\nbool = isPrimitiveArray( [ {}, 2, 1 ] )\nbool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n","isPRNGLike":"var bool = isPRNGLike( base.random.randu )\nbool = isPRNGLike( [ 1, 2, 3, 4 ] )\nbool = isPRNGLike( 3.14 )\nbool = isPRNGLike( {} )\n","isProbability":"var bool = isProbability( 0.5 )\nbool = isProbability( new Number( 0.5 ) )\nbool = isProbability( 3.14 )\nbool = isProbability( -5.0 )\nbool = isProbability( null )\n","isProbability.isPrimitive":"var bool = isProbability.isPrimitive( 0.3 )\nbool = isProbability.isPrimitive( new Number( 0.3 ) )\n","isProbability.isObject":"var bool = isProbability.isObject( 0.77 )\nbool = isProbability.isObject( new Number( 0.77 ) )\n","isProbabilityArray":"var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\nbool = isProbabilityArray( [ 0.8, 1.2 ] )\nbool = isProbabilityArray( [ 0.8, '0.2' ] )\n","isProbabilityArray.primitives":"var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\nbool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n","isProbabilityArray.objects":"var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\nbool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n","isPropertyKey":"var out = isPropertyKey( 'foo' )\nout = isPropertyKey( 1 )\nout = isPropertyKey( true )\n","isPrototypeOf":"function Foo() { return this; };\nfunction Bar() { return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar bool = isPrototypeOf( bar, Foo.prototype )\n","isRangeError":"var bool = isRangeError( new RangeError( 'beep' ) )\nbool = isRangeError( {} )\n","isReadableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadableProperty( obj, 'boop' )\nbool = isReadableProperty( obj, 'beep' )\n","isReadablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadablePropertyIn( obj, 'boop' )\nbool = isReadablePropertyIn( obj, 'beep' )\n","isReadOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyProperty( obj, 'boop' )\nbool = isReadOnlyProperty( obj, 'beep' )\n","isReadOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyPropertyIn( obj, 'boop' )\nbool = isReadOnlyPropertyIn( obj, 'beep' )\n","isReadWriteProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWriteProperty( obj, 'boop' )\nbool = isReadWriteProperty( obj, 'beep' )\n","isReadWritePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWritePropertyIn( obj, 'boop' )\nbool = isReadWritePropertyIn( obj, 'beep' )\n","isReferenceError":"var bool = isReferenceError( new ReferenceError( 'beep' ) )\nbool = isReferenceError( {} )\n","isRegExp":"var bool = isRegExp( /\\.+/ )\nbool = isRegExp( {} )\n","isRegExpString":"var bool = isRegExpString( '/beep/' )\nbool = isRegExpString( 'beep' )\nbool = isRegExpString( '' )\nbool = isRegExpString( null )\n","isRelativePath":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( './foo/bar/baz' )\n","isRelativePath.posix":"var bool = isRelativePath.posix( './foo/bar/baz' )\nbool = isRelativePath.posix( '/foo/../bar/baz' )\n","isRelativePath.win32":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n","isSafeInteger":"var bool = isSafeInteger( 5.0 )\nbool = isSafeInteger( new Number( 5.0 ) )\nbool = isSafeInteger( 2.0e200 )\nbool = isSafeInteger( -3.14 )\nbool = isSafeInteger( null )\n","isSafeInteger.isPrimitive":"var bool = isSafeInteger.isPrimitive( -3.0 )\nbool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n","isSafeInteger.isObject":"var bool = isSafeInteger.isObject( 3.0 )\nbool = isSafeInteger.isObject( new Number( 3.0 ) )\n","isSafeIntegerArray":"var arr = [ -3.0, new Number(0.0), 2.0 ];\nvar bool = isSafeIntegerArray( arr )\narr = [ -3.0, '3.0' ];\nbool = isSafeIntegerArray( arr )\n","isSafeIntegerArray.primitives":"var arr = [ -1.0, 10.0 ];\nvar bool = isSafeIntegerArray.primitives( arr )\narr = [ -1.0, 0.0, 5.0 ];\nbool = isSafeIntegerArray.primitives( arr )\narr = [ -3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.primitives( arr )\n","isSafeIntegerArray.objects":"var arr = [ new Number(1.0), new Number(3.0) ];\nvar bool = isSafeIntegerArray.objects( arr )\narr = [ -1.0, 0.0, 3.0 ];\nbool = isSafeIntegerArray.objects( arr )\narr = [ 3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.objects( arr )\n","isSameArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArray( x, y )\n","isSameComplex64":"var x = new Complex64( 1.0, 2.0 );\nvar y = new Complex64( 1.0, 2.0 );\nvar bool = isSameComplex64( x, y )\nx = new Complex64( NaN, NaN );\ny = new Complex64( NaN, NaN );\nbool = isSameComplex64( x, y )\n","isSameComplex64Array":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex64Array( x, y )\nx = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex64Array( x, y )\n","isSameComplex128":"var x = new Complex128( 1.0, 2.0 );\nvar y = new Complex128( 1.0, 2.0 );\nvar bool = isSameComplex128( x, y )\nx = new Complex128( NaN, NaN );\ny = new Complex128( NaN, NaN );\nbool = isSameComplex128( x, y )\n","isSameComplex128Array":"var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex128Array( x, y )\nx = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex128Array( x, y )\n","isSameFloat32Array":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat32Array( x, y )\nx = new Float32Array( [ NaN, NaN, NaN ] );\ny = new Float32Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat32Array( x, y )\n","isSameFloat64Array":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat64Array( x, y )\nx = new Float64Array( [ NaN, NaN, NaN ] );\ny = new Float64Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat64Array( x, y )\n","isSameNativeClass":"var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\nbool = isSameNativeClass( 'beep', 'boop' )\nbool = isSameNativeClass( {}, [] )\n","isSameType":"var bool = isSameType( true, true )\nbool = isSameType( {}, [] )\nbool = isSameType( 3.12, -3.12 )\nbool = isSameType( 0.0, '0.0' )\n","isSameValue":"var bool = isSameValue( true, true )\nbool = isSameValue( {}, {} )\nbool = isSameValue( -0.0, -0.0 )\nbool = isSameValue( -0.0, 0.0 )\nbool = isSameValue( NaN, NaN )\n","isSameValueZero":"var bool = isSameValueZero( true, true )\nbool = isSameValueZero( {}, {} )\nbool = isSameValueZero( -0.0, -0.0 )\nbool = isSameValueZero( -0.0, 0.0 )\nbool = isSameValueZero( NaN, NaN )\n","isSharedArrayBuffer":"var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\nbool = isSharedArrayBuffer( [] )\n","isSkewCentrosymmetricMatrix":"var buf = [ 2, 1, -1, -2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewCentrosymmetricMatrix( M )\nbool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewCentrosymmetricMatrix( 3.14 )\nbool = isSkewCentrosymmetricMatrix( {} )\n","isSkewPersymmetricMatrix":"var buf = [ 1, 0, 0, -1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewPersymmetricMatrix( M )\nbool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewPersymmetricMatrix( 3.14 )\nbool = isSkewPersymmetricMatrix( {} )\n","isSkewSymmetricMatrix":"var buf = [ 0, -1, 1, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewSymmetricMatrix( M )\nbool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewSymmetricMatrix( 3.14 )\nbool = isSkewSymmetricMatrix( {} )\n","isSlice":"var bool = isSlice( new Slice( 10 ) )\nbool = isSlice( 3.14 )\nbool = isSlice( {} )\n","isSquareMatrix":"var buf = [ 0, 0, 0, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSquareMatrix( M )\nbool = isSquareMatrix( [ 1, 2, 3, 4 ] )\nbool = isSquareMatrix( 3.14 )\nbool = isSquareMatrix( {} )\n","isSquareNumber":"var bool = isSquareNumber( 4.0 )\nbool = isSquareNumber( new Number( 4.0 ) )\nbool = isSquareNumber( 3.14 )\nbool = isSquareNumber( -5.0 )\nbool = isSquareNumber( null )\n","isSquareNumber.isPrimitive":"var bool = isSquareNumber.isPrimitive( 4.0 )\nbool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n","isSquareNumber.isObject":"var bool = isSquareNumber.isObject( 4.0 )\nbool = isSquareNumber.isObject( new Number( 4.0 ) )\n","isSquareTriangularNumber":"var bool = isSquareTriangularNumber( 36.0 )\nbool = isSquareTriangularNumber( new Number( 36.0 ) )\nbool = isSquareTriangularNumber( 3.14 )\nbool = isSquareTriangularNumber( -5.0 )\nbool = isSquareTriangularNumber( null )\n","isSquareTriangularNumber.isPrimitive":"var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\nbool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isSquareTriangularNumber.isObject":"var bool = isSquareTriangularNumber.isObject( 36.0 )\nbool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n","isStrictEqual":"var bool = isStrictEqual( true, true )\nbool = isStrictEqual( {}, {} )\nbool = isStrictEqual( -0.0, -0.0 )\nbool = isStrictEqual( -0.0, 0.0 )\nbool = isStrictEqual( NaN, NaN )\n","isString":"var bool = isString( 'beep' )\nbool = isString( new String( 'beep' ) )\nbool = isString( 5 )\n","isString.isPrimitive":"var bool = isString.isPrimitive( 'beep' )\nbool = isString.isPrimitive( new String( 'beep' ) )\n","isString.isObject":"var bool = isString.isObject( new String( 'beep' ) )\nbool = isString.isObject( 'beep' )\n","isStringArray":"var bool = isStringArray( [ 'abc', 'def' ] )\nbool = isStringArray( [ 'abc', 123 ] )\n","isStringArray.primitives":"var arr = [ 'abc', 'def' ];\nvar bool = isStringArray.primitives( arr )\narr = [ 'abc', new String( 'def' ) ];\nbool = isStringArray.primitives( arr )\n","isStringArray.objects":"var arr = [ new String( 'ab' ), new String( 'cd' ) ];\nvar bool = isStringArray.objects( arr )\narr = [ new String( 'abc' ), 'def' ];\nbool = isStringArray.objects( arr )\n","isSymbol":"var bool = isSymbol( Symbol( 'beep' ) )\nbool = isSymbol( Object( Symbol( 'beep' ) ) )\nbool = isSymbol( {} )\nbool = isSymbol( null )\nbool = isSymbol( true )\n","isSymbolArray":"var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\nbool = isSymbolArray( Symbol( 'beep' ) )\nbool = isSymbolArray( [] )\nbool = isSymbolArray( {} )\nbool = isSymbolArray( null )\nbool = isSymbolArray( true )\n","isSymbolArray.primitives":"var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.primitives( [] )\nbool = isSymbolArray.primitives( {} )\nbool = isSymbolArray.primitives( null )\nbool = isSymbolArray.primitives( true )\n","isSymbolArray.objects":"var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.objects( [] )\nbool = isSymbolArray.objects( {} )\nbool = isSymbolArray.objects( null )\nbool = isSymbolArray.objects( true )\n","isSymmetricMatrix":"var buf = [ 0, 1, 1, 2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSymmetricMatrix( M )\nbool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSymmetricMatrix( 3.14 )\nbool = isSymmetricMatrix( {} )\n","isSyntaxError":"var bool = isSyntaxError( new SyntaxError( 'beep' ) )\nbool = isSyntaxError( {} )\n","isTriangularNumber":"var bool = isTriangularNumber( 36.0 )\nbool = isTriangularNumber( new Number( 36.0 ) )\nbool = isTriangularNumber( 3.14 )\nbool = isTriangularNumber( -5.0 )\nbool = isTriangularNumber( null )\n","isTriangularNumber.isPrimitive":"var bool = isTriangularNumber.isPrimitive( 36.0 )\nbool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isTriangularNumber.isObject":"var bool = isTriangularNumber.isObject( 36.0 )\nbool = isTriangularNumber.isObject( new Number( 36.0 ) )\n","isTruthy":"var bool = isTruthy( true )\nbool = isTruthy( {} )\nbool = isTruthy( [] )\nbool = isTruthy( false )\nbool = isTruthy( '' )\nbool = isTruthy( 0 )\nbool = isTruthy( null )\nbool = isTruthy( void 0 )\nbool = isTruthy( NaN )\n","isTruthyArray":"var bool = isTruthyArray( [ {}, [] ] )\nbool = isTruthyArray( [ null, '' ] )\nbool = isTruthyArray( [] )\n","isTypedArray":"var bool = isTypedArray( new Int8Array( 10 ) )\n","isTypedArrayLength":"var bool = isTypedArrayLength( 5 )\nbool = isTypedArrayLength( 2.0e200 )\nbool = isTypedArrayLength( -3.14 )\nbool = isTypedArrayLength( null )\n","isTypedArrayLike":"var bool = isTypedArrayLike( new Int16Array() )\nbool = isTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4\n })\n","isTypeError":"var bool = isTypeError( new TypeError( 'beep' ) )\nbool = isTypeError( {} )\n","isUint8Array":"var bool = isUint8Array( new Uint8Array( 10 ) )\nbool = isUint8Array( [] )\n","isUint8ClampedArray":"var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\nbool = isUint8ClampedArray( [] )\n","isUint16Array":"var bool = isUint16Array( new Uint16Array( 10 ) )\nbool = isUint16Array( [] )\n","isUint32Array":"var bool = isUint32Array( new Uint32Array( 10 ) )\nbool = isUint32Array( [] )\n","isUNCPath":"var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\nbool = isUNCPath( '/foo/bar/baz' )\n","isUndefined":"var bool = isUndefined( void 0 )\nbool = isUndefined( null )\n","isUndefinedOrNull":"var bool = isUndefinedOrNull( void 0 )\nbool = isUndefinedOrNull( null )\nbool = isUndefinedOrNull( false )\n","isUnityProbabilityArray":"var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\nbool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\nbool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\nbool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n","isUppercase":"var bool = isUppercase( 'HELLO' )\nbool = isUppercase( 'World' )\n","isURI":"var bool = isURI( 'http://google.com' )\nbool = isURI( 'http://localhost/' )\nbool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\nbool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\nbool = isURI( '' )\nbool = isURI( 'foo@bar' )\nbool = isURI( '://foo/' )\nbool = isURI( 'http://' )\nbool = isURI( 'http:////foo.html' )\nbool = isURI( 'http://example.w3.org/%a' )\n","isURIError":"var bool = isURIError( new URIError( 'beep' ) )\nbool = isURIError( {} )\n","isVectorLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isVectorLike( M )\nbool = isVectorLike( [ 1, 2, 3, 4 ] )\nbool = isVectorLike( 3.14 )\nbool = isVectorLike( {} )\n","isWhitespace":"var bool = isWhitespace( ' ' )\nbool = isWhitespace( 'abcdef' )\nbool = isWhitespace( '' )\n","isWritableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritableProperty( obj, 'boop' )\nbool = isWritableProperty( obj, 'beep' )\n","isWritablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritablePropertyIn( obj, 'boop' )\nbool = isWritablePropertyIn( obj, 'beep' )\n","isWriteOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyProperty( obj, 'boop' )\nbool = isWriteOnlyProperty( obj, 'beep' )\n","isWriteOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyPropertyIn( obj, 'boop' )\nbool = isWriteOnlyPropertyIn( obj, 'beep' )\n","iterAbs":"var it = iterAbs( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAbs2":"var it = iterAbs2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAcos":"var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcosh":"var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcot":"var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoth":"var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcovercos":"var it = iterAcovercos( random.iterators.uniform( -2.0, 0.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoversin":"var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAdd":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterAdd( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterAdvance":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar it = iterAdvance( arr, 4 );\nvar v = it.next().value\nvar bool = it.next().done\n","iterAhavercos":"var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAhaversin":"var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAny":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterAny( arr )\n","iterAnyBy":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v === 1 ); };\nvar bool = iterAnyBy( arr, fcn )\n","iterAsin":"var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAsinh":"var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan":"var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan2":"var x = random.iterators.uniform( -2.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterAtan2( y, x );\nvar r = it.next().value\nr = it.next().value\n","iterAtanh":"var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterator2array":"var opts = { 'iter': 10 };\nvar arr = iterator2array( random.iterators.randu( opts ) )\n","iterator2arrayview":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayview( it, out, 5, 15 )\n","iterator2arrayviewRight":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayviewRight( it, out, 5, 15 )\n","iteratorStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream( it );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","iteratorStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = iteratorStream.factory( opts );\n","iteratorStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream.objectMode( it );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","IteratorSymbol":"var s = IteratorSymbol\n","iterAvercos":"var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAversin":"var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterawgn":"var src = iterSineWave();\nvar it = iterawgn( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawln":"var src = iterSineWave();\nvar it = iterawln( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawun":"var src = iterSineWave();\nvar it = iterawun( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterBartlettHannPulse":"var it = iterBartlettHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBartlettPulse":"var it = iterBartlettPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBesselj0":"var it = iterBesselj0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBesselj1":"var it = iterBesselj1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely0":"var it = iterBessely0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely1":"var it = iterBessely1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBeta":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBeta( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBetaln":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBetaln( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBinet":"var it = iterBinet( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCbrt":"var it = iterCbrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil":"var it = iterCeil( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil2":"var it = iterCeil2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil10":"var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterCompositesSeq":"var it = iterCompositesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterConcat":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = array2iterator( [ 3, 4 ] );\nvar it = iterConcat( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterConstant":"var it = iterConstant( 3.14 );\nvar v = it.next().value\nv = it.next().value\n","iterContinuedFraction":"var terms = array2iterator( [ 3, 4, 12, 4 ] );\nvar v = iterContinuedFraction( terms )\n","iterContinuedFractionSeq":"var it = iterContinuedFractionSeq( 3.245 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\nit = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n","iterCos":"var it = iterCos( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCosh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterCosh( r );\nvar v = it.next().value\nv = it.next().value\n","iterCosineWave":"var it = iterCosineWave();\nvar v = it.next().value\nv = it.next().value\n","iterCosm1":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCosm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterCospi":"var it = iterCospi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCounter":"var it = iterCounter( random.iterators.randu() );\nvar v = it.next().value\nv = it.next().value\n","iterCovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterCoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterCubesSeq":"var it = iterCubesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","itercugmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercugmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercuhmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercuhmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumax( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumaxabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumean( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs2( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumidrange( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumin( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuminabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuprod( arr );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itercurange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercurange( arr );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\nr = it.next().value\n","itercusum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusum( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs2( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterDatespace":"var t1 = new Date();\nvar it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\nvar v = it.next().value\nv = it.next().value\n","iterDedupe":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nvar it = iterDedupe( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDedupeBy":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nfunction fcn( v ) { return v; };\nvar it = iterDedupeBy( arr, fcn );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDeg2rad":"var r = random.iterators.uniform( -360.0, 360.0 );\nvar it = iterDeg2rad( r );\nvar v = it.next().value\nv = it.next().value\n","iterDigamma":"var r = random.iterators.uniform( 0.01, 5.0 );\nvar it = iterDigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterDiracComb":"var it = iterDiracComb();\nvar v = it.next().value\nv = it.next().value\n","iterDiracDelta":"var it = iterDiracDelta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterDivide":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterDivide( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterEllipe":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipe( r );\nvar v = it.next().value\nv = it.next().value\n","iterEllipk":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipk( r );\nvar v = it.next().value\nv = it.next().value\n","iterEmpty":"var it = iterEmpty();\nvar bool = it.next().done\n","iterErf":"var it = iterErf( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfc":"var it = iterErfc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfcinv":"var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterErfinv":"var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterEta":"var it = iterEta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterEvenIntegersSeq":"var it = iterEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterEvery":"var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\nvar bool = iterEvery( arr )\n","iterEveryBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterEveryBy( arr, fcn )\n","iterExp":"var it = iterExp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterExp2":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp2( r );\nvar v = it.next().value\nv = it.next().value\n","iterExp10":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp10( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterExpit( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterExpm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1rel":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExpm1rel( r );\nvar v = it.next().value\nv = it.next().value\n","iterFactorial":"var it = iterFactorial( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialln":"var it = iterFactorialln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialsSeq":"var it = iterFactorialsSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFibonacciSeq":"var it = iterFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterFifthPowersSeq":"var it = iterFifthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFill":"var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterFilter":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilter( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFilterMap":"function f( v ) { if ( v > 2 ) { return v * 10 }; };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilterMap( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFirst":"var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\nvar v = iterFirst( arr )\n","iterFlatTopPulse":"var it = iterFlatTopPulse();\nvar v = it.next().value\nv = it.next().value\n","iterFloor":"var it = iterFloor( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFloor2":"var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFloor10":"var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFlow":"var o = {};\no.head = iterHead;\no.some = iterSome;\nvar fiter = iterFlow( o )\n","iterForEach":"function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterForEach( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterFourthPowersSeq":"var it = iterFourthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFresnelc":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnelc( r );\nvar v = it.next().value\nv = it.next().value\n","iterFresnels":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnels( r );\nvar v = it.next().value\nv = it.next().value\n","iterGamma":"var it = iterGamma( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterGamma1pm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterGamma1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterGammaln":"var it = iterGammaln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterHacovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHacoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHannPulse":"var it = iterHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterHavercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHavercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHaversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHaversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHead":"var it = iterHead( random.iterators.randu(), 5 );\nvar r = it.next().value\nr = it.next().value\n","iterIncrspace":"var it = iterIncrspace( 0, 101, 2 );\nvar v = it.next().value\nv = it.next().value\n","iterIntegersSeq":"var it = iterIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterIntersection":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterIntersection( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterIntersectionByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nfunction f( v ) { return v.toString(); };\nvar it = iterIntersectionByHash( it1, it2, f );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterInv":"var it = iterInv( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLanczosPulse":"var it = iterLanczosPulse();\nvar v = it.next().value\nv = it.next().value\n","iterLast":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar v = iterLast( arr )\n","iterLength":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar len = iterLength( arr )\n","iterLinspace":"var it = iterLinspace( 0, 99, 100 );\nvar v = it.next().value\nv = it.next().value\n","iterLn":"var it = iterLn( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog":"var x = random.iterators.uniform( 0.0, 100.0 );\nvar y = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterLog( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterLog1mexp":"var it = iterLog1mexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1p":"var it = iterLog1p( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1pexp":"var it = iterLog1pexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog2":"var it = iterLog2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog10":"var it = iterLog10( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLogit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterLogit( r );\nvar v = it.next().value\nv = it.next().value\n","iterLogspace":"var it = iterLogspace( 0, 3, 4 );\nvar v = it.next().value\nv = it.next().value\n","iterLucasSeq":"var it = iterLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterMap":"function f( v ) { return v * 10.0; };\nvar it = iterMap( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterMapN":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nfunction fcn( x, y ) { return x + y; };\nvar it = iterMapN( it1, it2, fcn );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermax":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermax( arr )\n","itermaxabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermaxabs( arr )\n","itermean":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = itermean( arr )\n","itermeanabs":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs( arr )\n","itermeanabs2":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs2( arr )\n","itermidrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = itermidrange( arr )\n","itermin":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermin( arr )\n","iterminabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = iterminabs( arr )\n","itermmax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmax( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmaxabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmean( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs2( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmidrange( arr, 3 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itermmin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmin( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermminabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","iterMod":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterMod( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermprod( arr, 3 );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itermrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermrange( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermsum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsum( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs2( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterMultiply":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterMultiply( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterNegaFibonacciSeq":"var it = iterNegaFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegaLucasSeq":"var it = iterNegaLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeEvenIntegersSeq":"var it = iterNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeIntegersSeq":"var it = iterNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeOddIntegersSeq":"var it = iterNegativeOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNone":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterNone( arr )\n","iterNoneBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v <= 0 ); };\nvar bool = iterNoneBy( arr, fcn )\n","iterNonFibonacciSeq":"var it = iterNonFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeEvenIntegersSeq":"var it = iterNonNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeIntegersSeq":"var it = iterNonNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveEvenIntegersSeq":"var it = iterNonPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveIntegersSeq":"var it = iterNonPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonSquaresSeq":"var it = iterNonSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterNth":"var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\nvar v = iterNth( arr, 3 )\n","iterOddIntegersSeq":"var it = iterOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterPeriodicSinc":"var it = iterPeriodicSinc( 7 );\nvar v = it.next().value\nv = it.next().value\n","iterPipeline":"var it1 = iterThunk( iterHead, 100 );\nfunction f( r ) { return ( r > 0.95 ); };\nvar it2 = iterThunk( iterSomeBy, 5, f );\nvar p = iterPipeline( it1, it2 );\nvar bool = p( random.iterators.randu() )\n","iterPop":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPop( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterPositiveEvenIntegersSeq":"var it = iterPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveIntegersSeq":"var it = iterPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveOddIntegersSeq":"var it = iterPositiveOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPow":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterPow( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterPrimesSeq":"var it = iterPrimesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterprod":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = iterprod( arr )\n","iterPulse":"var it = iterPulse();\nvar v = it.next().value\nv = it.next().value\n","iterPush":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPush( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterRad2deg":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterRad2deg( r );\nvar v = it.next().value\nv = it.next().value\n","iterRamp":"var it = iterRamp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = iterrange( arr )\n","iterReject":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterReject( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterReplicate":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nvar it2 = iterReplicate( it1, 2 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterReplicateBy":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nfunction f( v, i ) { return i + 1; };\nvar it2 = iterReplicateBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterRound":"var it = iterRound( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterRound2":"var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRound10":"var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRsqrt":"var it = iterRsqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSawtoothWave":"var it = iterSawtoothWave();\nvar v = it.next().value\nv = it.next().value\n","iterShift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterShift( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterSignum":"var it = iterSignum( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSin":"var it = iterSin( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSinc":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinc( r );\nvar v = it.next().value\nv = it.next().value\n","iterSineWave":"var it = iterSineWave();\nvar v = it.next().value\nv = it.next().value\n","iterSinh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinh( r );\nvar v = it.next().value\nv = it.next().value\n","iterSinpi":"var it = iterSinpi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSlice":"var it = iterSlice( random.iterators.randu(), 5, 10 );\nvar r = it.next().value\nr = it.next().value\n","iterSome":"var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = iterSome( arr, 3 )\n","iterSomeBy":"var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterSomeBy( arr, 3, fcn )\n","iterSpence":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSpence( r );\nvar v = it.next().value\nv = it.next().value\n","iterSqrt":"var it = iterSqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSqrt1pm1":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSqrt1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterSquaredTriangularSeq":"var it = iterSquaredTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquaresSeq":"var it = iterSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquareWave":"var it = iterSquareWave();\nvar v = it.next().value\nv = it.next().value\n","iterstdev":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar m = iterstdev( arr )\n","iterStep":"var it = iterStep( 0, 2, 10 );\nvar v = it.next().value\nv = it.next().value\n","iterStrided":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nvar it = iterStrided( arr, 2, 1 );\nvar r = it.next().value\nr = it.next().value\n","iterStridedBy":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nfunction stride( v, i ) { return (i % 10)+1; };\nvar it = iterStridedBy( arr, stride );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterSubtract":"var it1 = array2iterator( [ 1.0, 5.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterSubtract( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itersum":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = itersum( arr )\n","itersumabs":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs( arr )\n","itersumabs2":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs2( arr )\n","iterTan":"var r = random.iterators.uniform( -1.57, 1.57 );\nvar it = iterTan( r );\nvar v = it.next().value\nv = it.next().value\n","iterTanh":"var r = random.iterators.uniform( -4.0, 4.0 );\nvar it = iterTanh( r );\nvar v = it.next().value\nv = it.next().value\n","iterThunk":"var fcn = iterThunk( iterSome, 3 );\nvar arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = fcn( arr )\n","iterTriangleWave":"var it = iterTriangleWave();\nvar v = it.next().value\nv = it.next().value\n","iterTriangularSeq":"var it = iterTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterTrigamma":"var r = random.iterators.uniform( 0.01, 50.0 );\nvar it = iterTrigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterTrunc":"var it = iterTrunc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc2":"var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc10":"var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterUnion":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterUnion( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterUnique":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = iterUnique( it1 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueBy":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( a, b ) { return ( a !== b ); };\nvar it2 = iterUniqueBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( v ) { return v.toString(); };\nvar it2 = iterUniqueByHash( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUnitspace":"var it = iterUnitspace( 0, 99 );\nvar v = it.next().value\nv = it.next().value\n","iterUnshift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterUnshift( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","itervariance":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar s2 = itervariance( arr )\n","iterVercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterVersin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVersin( r );\nvar v = it.next().value\nv = it.next().value\n","iterZeta":"var r = random.iterators.uniform( 1.1, 50.0 );\nvar it = iterZeta( r );\nvar v = it.next().value\nv = it.next().value\n","joinStream":"var s = joinStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = joinStream.factory( opts );\nvar s = createStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.objectMode":"var s = joinStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","kde2d":"var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\nvar y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\nvar out = kde2d( x, y )\n","kebabcase":"var out = kebabcase( 'Hello World!' )\nout = kebabcase( 'I am a tiny little teapot' )\n","keyBy":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyBy( arr, toKey )\n","keyByRight":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyByRight( arr, toKey )\n","keysIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = keysIn( obj )\n","kruskalTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = kruskalTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = kruskalTest( arr, { 'groups': groups } )\n","kstest":"var rnorm = base.random.normal.factory({ 'seed': 4839 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\nvar out = kstest( x, 'normal', 0.0, 1.0 )\nout = kstest( x, 'normal', 3.0, 1.0 )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0 )\nout.print()\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\nx = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\nout = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n","leveneTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = leveneTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = leveneTest( arr, { 'groups': groups } )\n","LinkedList":"var list = LinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","linspace":"var arr = linspace( 0.0, 100.0, 6 )\narr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\narr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n","linspace.assign":"var arr = [ 0, 0, 0, 0, 0, 0 ];\nvar out = linspace.assign( 0, 100, arr )\nvar bool = ( arr === out )\narr = [ 0, 0, 0, 0, 0 ];\nout = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n","LIU_NEGATIVE_OPINION_WORDS_EN":"var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n","LIU_POSITIVE_OPINION_WORDS_EN":"var list = LIU_POSITIVE_OPINION_WORDS_EN()\n","LN_HALF":"LN_HALF\n","LN_PI":"LN_PI\n","LN_SQRT_TWO_PI":"LN_SQRT_TWO_PI\n","LN_TWO_PI":"LN_TWO_PI\n","LN2":"LN2\n","LN10":"LN10\n","LOG2E":"LOG2E\n","LOG10E":"LOG10E\n","logspace":"var arr = logspace( 0, 2, 6 )\n","lowercase":"var out = lowercase( 'bEEp' )\n","lowercaseKeys":"var obj = { 'A': 1, 'B': 2 };\nvar out = lowercaseKeys( obj )\n","lowess":"var x = new Float64Array( 100 );\nvar y = new Float64Array( x.length );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = i;\n y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n }\nvar out = lowess( x, y );\nvar yhat = out.y;\nvar h = Plot( [ x, x ], [ y, yhat ] );\nh.lineStyle = [ 'none', '-' ];\nh.symbols = [ 'closed-circle', 'none' ];\nh.view( 'window' );\n","lpad":"var out = lpad( 'a', 5 )\nout = lpad( 'beep', 10, 'b' )\nout = lpad( 'boop', 12, 'beep' )\n","ltrim":"var out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n","MALE_FIRST_NAMES_EN":"var list = MALE_FIRST_NAMES_EN()\n","map":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = map( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = map( arr, f );\nvar v = out.get( 1, 1 )\n","map.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","map2":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2( x, y, f );\nvar v = out.get( 1, 1 )\n","map2.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map2d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\nvar out = map2d( arr, f );\nout[ 0 ]\nout[ 1 ]\n","map2Right":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2Right( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2Right( x, y, f );\nvar v = out.get( 1, 1 )\n","map2Right.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2Right.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2Right.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map3d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\nvar out = map3d( arr, f );\nout[ 0 ][ 0 ]\nout[ 1 ][ 0 ]\n","map4d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\nvar out = map4d( arr, f );\nout[ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ]\n","map5d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\nvar out = map5d( arr, f );\nout[ 0 ][ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ][ 0 ]\n","mapArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nfunction clbk( v ) { return v * 2; };\nvar bar = mapArguments( foo, clbk );\nvar out = bar( 1, 2, 3 )\n","mapFun":"function fcn( i ) { return i; };\nvar arr = mapFun( fcn, 5 )\n","mapFunAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nmapFunAsync( fcn, 10, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nvar opts = { 'limit': 2 };\nmapFunAsync( fcn, 10, opts, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nvar opts = { 'series': true };\nmapFunAsync( fcn, 10, opts, done )\n","mapFunAsync.factory":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nvar opts = { 'series': true };\nvar f = mapFunAsync.factory( opts, fcn );\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nf( 10, done )\n","mapKeys":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapKeys( obj, transform )\n","mapKeysAsync":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapKeysAsync( obj, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\n","mapKeysAsync.factory":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapKeysAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","mapReduce":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduce( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduce( arr, 0.0, f1, f2 )\n","mapReduceRight":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduceRight( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduceRight( arr, 0.0, f1, f2 )\n","mapRight":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = mapRight( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapRight( arr, f );\nvar v = out.get( 1, 1 )\n","mapRight.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmapRight.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmapRight.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","mapValues":"function transform( value, key ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapValues( obj, transform )\n","mapValuesAsync":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapValuesAsync( obj, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\n","mapValuesAsync.factory":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapValuesAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","maskArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = maskArguments( foo, [ 1, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","MAX_ARRAY_LENGTH":"MAX_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"MAX_TYPED_ARRAY_LENGTH\n","maybeBroadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","maybeBroadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = maybeBroadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","memoize":"function factorial( n ) {\n var prod;\n var i;\n prod = 1;\n for ( i = n; i > 1; i-- ) {\n prod *= i;\n }\n return prod;\n };\nvar memoized = memoize( factorial );\nvar v = memoized( 5 )\nv = memoized( 5 )\n","merge":"var target = { 'a': 'beep' };\nvar source = { 'a': 'boop', 'b': 'bap' };\nvar out = merge( target, source )\nvar bool = ( out === target )\n","merge.factory":"var opts = {\n 'level': 100,\n 'copy': true,\n 'override': true,\n 'extend': true\n };\nvar merge = merge.factory( opts )\nmerge = merge.factory( { 'level': 2 } );\nvar target = {\n '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n };\nvar source = {\n '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n };\nvar out = merge( target, source )\nmerge = merge.factory( { 'copy': false } );\ntarget = {};\nsource = { 'a': [ 1, 2, 3 ] };\nout = merge( target, source );\nvar bool = ( out.a === source.a )\nmerge = merge.factory( { 'override': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'a': null, 'c': 'bop' };\nout = merge( target, source )\nfunction strategy( a, b, key ) {\n // a => target value\n // b => source value\n // key => object key\n if ( key === 'a' ) {\n return b;\n }\n if ( key === 'b' ) {\n return a;\n }\n return 'bebop';\n };\nmerge = merge.factory( { 'override': strategy } );\ntarget = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\nsource = { 'a': null, 'b': {}, 'c': 'bop' };\nout = merge( target, source )\nmerge = merge.factory( { 'extend': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'b': 'hello', 'c': 'world' };\nout = merge( target, source )\n","MILLISECONDS_IN_DAY":"var days = 3.14;\nvar ms = days * MILLISECONDS_IN_DAY\n","MILLISECONDS_IN_HOUR":"var hrs = 3.14;\nvar ms = hrs * MILLISECONDS_IN_HOUR\n","MILLISECONDS_IN_MINUTE":"var mins = 3.14;\nvar ms = mins * MILLISECONDS_IN_MINUTE\n","MILLISECONDS_IN_SECOND":"var secs = 3.14;\nvar ms = secs * MILLISECONDS_IN_SECOND\n","MILLISECONDS_IN_WEEK":"var weeks = 3.14;\nvar ms = weeks * MILLISECONDS_IN_WEEK\n","MINARD_NAPOLEONS_MARCH":"var data = MINARD_NAPOLEONS_MARCH();\nvar army = data.army\nvar cities = data.cities\nvar labels = data.labels\nvar river = data.river\nvar t = data.temperature\n","MINUTES_IN_DAY":"var days = 3.14;\nvar mins = days * MINUTES_IN_DAY\n","MINUTES_IN_HOUR":"var hrs = 3.14;\nvar mins = hrs * MINUTES_IN_HOUR\n","MINUTES_IN_WEEK":"var wks = 3.14;\nvar mins = wks * MINUTES_IN_WEEK\n","minutesInMonth":"var num = minutesInMonth()\nnum = minutesInMonth( 2 )\nnum = minutesInMonth( 2, 2016 )\nnum = minutesInMonth( 2, 2017 )\nnum = minutesInMonth( 'feb', 2016 )\nnum = minutesInMonth( 'february', 2016 )\n","minutesInYear":"var num = minutesInYear()\nnum = minutesInYear( 2016 )\nnum = minutesInYear( 2017 )\n","MOBY_DICK":"var data = MOBY_DICK()\n","MONTH_NAMES_EN":"var list = MONTH_NAMES_EN()\n","MONTHS_IN_YEAR":"var yrs = 3.14;\nvar mons = yrs * MONTHS_IN_YEAR\n","moveProperty":"var obj1 = { 'a': 'b' };\nvar obj2 = {};\nvar bool = moveProperty( obj1, 'a', obj2 )\nbool = moveProperty( obj1, 'c', obj2 )\n","MultiSlice":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\n","MultiSlice.prototype.ndims":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.ndims\n","MultiSlice.prototype.data":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.data\n","MultiSlice.prototype.toString":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.toString()\n","MultiSlice.prototype.toJSON":"var s = new Slice( 2, 10, 1 );\nvar ms = new MultiSlice( 2, s );\nms.toJSON()\n","namedtypedtuple":"var opts = {};\nopts.name = 'Point';\nvar factory = namedtypedtuple( [ 'x', 'y' ], opts );\nvar tuple = factory();\n","NAN":"NAN\n","naryFunction":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = naryFunction( foo, 2 );\nvar out = bar( 1, 2, 3 )\n","nativeClass":"var str = nativeClass( 'a' )\nstr = nativeClass( 5 )\nfunction Beep(){};\nstr = nativeClass( new Beep() )\n","ndarray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","ndarray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","ndarray2array":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2array( arr )\n","ndarrayCastingModes":"var out = ndarrayCastingModes()\n","ndarrayDataBuffer":"var opts = { 'dtype': 'float64' };\nvar out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataType":"var opts = { 'dtype': 'float64' };\nvar dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataTypes":"var out = ndarrayDataTypes()\nout = ndarrayDataTypes( 'floating_point' )\n","ndarrayDispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\nvar xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\nf( x, y );\nybuf\n","ndarrayFlag":"var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n","ndarrayFlags":"var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayIndexModes":"var out = ndarrayIndexModes()\n","ndarrayMinDataType":"var dt = ndarrayMinDataType( 3.141592653589793 )\ndt = ndarrayMinDataType( 3 )\ndt = ndarrayMinDataType( -3 )\ndt = ndarrayMinDataType( '-3' )\n","ndarrayMostlySafeCasts":"var out = ndarrayMostlySafeCasts( 'float32' )\n","ndarrayNextDataType":"var out = ndarrayNextDataType( 'float32' )\n","ndarrayOffset":"var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayOrder":"var opts = { 'order': 'row-major' };\nvar dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayOrders":"var out = ndarrayOrders()\n","ndarrayPromotionRules":"var out = ndarrayPromotionRules( 'float32', 'int32' )\n","ndarraySafeCasts":"var out = ndarraySafeCasts( 'float32' )\n","ndarraySameKindCasts":"var out = ndarraySameKindCasts( 'float32' )\n","ndarrayShape":"var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayStride":"var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n","ndarrayStrides":"var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n","ndat":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nndat( x, 0, 1 )\nndat( x, 1, 0 )\n","ndempty":"var arr = ndempty( [ 2, 2 ] )\nvar sh = arr.shape\nvar dt = arr.dtype\n","ndemptyLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = ndemptyLike( x )\nsh = y.shape\ndt = y.dtype\n","ndims":"var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n","nditerColumnEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumnEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerColumns":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumns( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerEntries( x );\nvar v = it.next().value\nv = it.next().value\n","nditerIndices":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerIndices( x.shape );\nvar v = it.next().value\nv = it.next().value\n","nditerMatrices":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrices( x );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrixEntries":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrixEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRowEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRowEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRows":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRows( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerValues":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerValues( x );\nvar v = it.next().value\nv = it.next().value\n","ndslice":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar s = new MultiSlice( null, 1 )\nvar y = ndslice( x, s )\ny.shape\nndarray2array( y )\n","ndsliceAssign":"var y = ndzeros( [ 2, 2 ] )\nvar x = scalar2ndarray( 3.0 )\nvar s = new MultiSlice( null, 1 )\nvar out = ndsliceAssign( x, y, s )\nvar bool = ( out === y )\nndarray2array( y )\n","ndsliceDimension":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimension( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionFrom( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceFrom( x, 0, 1 )\ny.shape\nndarray2array( y )\n","ndsliceTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndzeros":"var arr = ndzeros( [ 2, 2 ] )\nvar sh = arr.shape\nvar dt = arr.dtype\n","ndzerosLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = ndzerosLike( x )\nsh = y.shape\ndt = y.dtype\n","nextGraphemeClusterBreak":"var out = nextGraphemeClusterBreak( 'last man standing', 4 )\nout = nextGraphemeClusterBreak( 'presidential election', 8 )\nout = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\nout = nextGraphemeClusterBreak( '🌷' )\n","nextTick":"function f() { console.log( 'beep' ); };\nnextTick( f )\n","NIGHTINGALES_ROSE":"var data = NIGHTINGALES_ROSE()\n","NINF":"NINF\n","NODE_VERSION":"NODE_VERSION\n","none":"var arr = [ 0, 0, 0, 0, 0 ];\nvar bool = none( arr )\n","noneBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = noneBy( arr, negative )\n","noneByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\n","noneByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","noneByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ -1, -2, -3, -4 ];\nvar bool = noneByRight( arr, positive )\n","noneByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\n","noneByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","nonEnumerableProperties":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar props = nonEnumerableProperties( obj )\n","nonEnumerablePropertiesIn":"var props = nonEnumerablePropertiesIn( [] )\n","nonEnumerablePropertyNames":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNames( obj )\n","nonEnumerablePropertyNamesIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNamesIn( obj )\n","nonEnumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbols( obj )\n","nonEnumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbolsIn( obj )\n","nonIndexKeys":"function Foo() { this.beep = 'boop'; this[0] = 3.14; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = nonIndexKeys( obj )\n","noop":"noop();\n","now":"var ts = now()\n","NUM_CPUS":"NUM_CPUS\n","num2words":"var out = num2words( 123 )\nout = num2words( 16.31 )\nout = num2words( 123, { 'lang': 'de' } )\n","Number":"var v = new Number( 5 )\n","numel":"var n = numel( ndzeros( [ 3, 3, 3 ] ) )\n","numelDimension":"var out = numelDimension( ndzeros( [ 4, 2, 3 ] ), 0 )\n","numGraphemeClusters":"var out = numGraphemeClusters( 'beep' )\nout = numGraphemeClusters( '🌷' )\n","Object":"var o = new Object( null )\no = new Object( 5.0 )\no = new Object( 'beep' )\n","Object.assign":"var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n","Object.create":"var o = Object.create( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperties":"var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperty":"var o = Object.defineProperty( {}, 'a', {\n","Object.entries":"var o = Object.entries( { 'a': 1, 'b': 2 } )\n","Object.freeze":"var o = Object.freeze( { 'a': 1 } )\n","Object.getOwnPropertyDescriptor":"var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n","Object.getOwnPropertyDescriptors":"var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertyNames":"var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertySymbols":"var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n","Object.getPrototypeOf":"var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n","Object.hasOwn":"var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n","Object.is":"var o = Object.is( 1, 1 )\nvar o = Object.is( 1, '1' )\n","Object.isExtensible":"var o = Object.isExtensible( { 'a': 1 } )\n","Object.isFrozen":"var o = Object.isFrozen( { 'a': 1 } )\nvar o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n","Object.isSealed":"var o = Object.isSealed( { 'a': 1 } )\nvar o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n","Object.keys":"var o = Object.keys( { 'a': 1, 'b': 2 } )\n","Object.preventExtensions":"var o = Object.preventExtensions( { 'a': 1 } )\no.b = 2;\no\n","Object.seal":"var o = Object.seal( { 'a': 1 } )\no.b = 2;\no\ndelete o.a;\no\n","Object.setPrototypeOf":"var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\no.b\n","Object.values":"var o = Object.values( { 'a': 1, 'b': 2 } )\n","Object.prototype.toLocaleString":"var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.toString":"var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.valueOf":"var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.hasOwnProperty":"var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n","Object.prototype.isPrototypeOf":"var p = { 'a': 1 };\nvar o = { '__proto__': p };\nvar b = o.isPrototypeOf( p );\n","Object.prototype.propertyIsEnumerable":"var o = { 'a': 1, 'b': 2 };\nvar bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n","Object.prototype.constructor":"var o = new Object( null );\nvar ctr = o.constructor;\n","objectEntries":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar entries = objectEntries( obj )\n","objectEntriesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar entries = objectEntriesIn( obj )\n","objectFromEntries":"var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\nvar obj = objectFromEntries( entries )\n","objectInverse":"var obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverse( obj )\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverse( obj )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverse( obj, { 'duplicates': false } )\n","objectInverseBy":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverseBy( obj, transform )\nfunction transform( key, value ) { return value; };\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverseBy( obj, transform )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverseBy( obj, { 'duplicates': false }, transform )\n","objectKeys":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = objectKeys( obj )\n","objectValues":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar vals = objectValues( obj )\n","objectValuesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar values = objectValuesIn( obj )\n","omit":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omit( obj1, 'b' )\n","omitBy":"function predicate( key, value ) { return ( value > 1 ); };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omitBy( obj1, predicate )\n","open":"function onOpen( error, fd ) {\n if ( error ) {\n console.error( error.message );\n } else {\n close.sync( fd );\n }\n };\nopen( './beep/boop.txt', onOpen );\n","open.sync":"var fd = open.sync( './beep/boop.txt' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","openURL":"var out = openURL( 'https://google.com' );\n","ordinalize":"var out = ordinalize( '1' )\nout = ordinalize( 2, { 'suffixOnly': true } )\nout = ordinalize( '3', { 'lang': 'es' } )\n","PACE_BOSTON_HOUSE_PRICES":"var data = PACE_BOSTON_HOUSE_PRICES()\n","pad":"var out = pad( 'a', 5 )\nout = pad( 'a', 10, { 'lpad': 'b' } )\nout = pad( 'a', 12, { 'rpad': 'b' } )\nvar opts = { 'lpad': 'a', 'rpad': 'c' };\nout = pad( 'b', 11, opts )\nopts.centerRight = false;\nout = pad( 'b', 10, opts )\nopts.centerRight = true;\nout = pad( 'b', 10, opts )\nopts = { 'lpad': 'boop', 'rpad': 'woot' };\nout = pad( 'beep', 10, opts )\nout = pad( 'beep', 2 )\nopts = { 'lpad': 'b' };\nout = pad( 'beep', 2, opts )\nopts = { 'lpad': '@', 'rpad': '!' };\nout = pad( 'beep', 2, opts )\nout = pad( 'abcdef', 3, opts )\nopts.centerRight = true;\nout = pad( 'abcdef', 3, opts )\n","padjust":"var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\nvar out = padjust( pvalues, 'bh' )\nout = padjust( pvalues, 'bonferroni' )\nout = padjust( pvalues, 'by' )\nout = padjust( pvalues, 'holm' )\nout = padjust( pvalues, 'hommel' )\n","papply":"function add( x, y ) { return x + y; };\nvar add2 = papply( add, 2 );\nvar sum = add2( 3 )\n","papplyRight":"function say( text, name ) { return text + ', ' + name + '.'; };\nvar toGrace = papplyRight( say, 'Grace Hopper' );\nvar str = toGrace( 'Hello' )\nstr = toGrace( 'Thank you' )\n","parallel":"function done( error ) { if ( error ) { throw error; } };\nvar files = [ './a.js', './b.js' ];\nparallel( files, done );\nvar opts = { 'workers': 8 };\nparallel( files, opts, done );\n","parseJSON":"var obj = parseJSON( '{\"beep\":\"boop\"}' )\nfunction reviver( key, value ) {\n if ( key === '' ) { return value; }\n if ( key === 'beep' ) { return value; }\n };\nvar str = '{\"beep\":\"boop\",\"a\":\"b\"}';\nvar out = parseJSON( str, reviver )\n","pascalcase":"var out = pascalcase( 'Hello World!' )\nout = pascalcase( 'beep boop' )\n","PATH_DELIMITER":"PATH_DELIMITER\nvar path = '/usr/bin:/bin:/usr/sbin';\nvar parts = path.split( PATH_DELIMITER )\npath = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\nparts = path.split( PATH_DELIMITER )\n","PATH_DELIMITER_POSIX":"PATH_DELIMITER_POSIX\nvar PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\nvar paths = PATH.split( PATH_DELIMITER_POSIX )\n","PATH_DELIMITER_WIN32":"PATH_DELIMITER_WIN32\nvar PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\nvar paths = PATH.split( PATH_DELIMITER_WIN32 )\n","PATH_SEP":"PATH_SEP\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\nparts = 'foo/bar/baz'.split( PATH_SEP )\n","PATH_SEP_POSIX":"PATH_SEP_POSIX\nvar parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n","PATH_SEP_WIN32":"PATH_SEP_WIN32\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n","pcorrtest":"var rho = 0.5;\nvar x = new Array( 300 );\nvar y = new Array( 300 );\nfor ( var i = 0; i < 300; i++ ) {\nx[ i ] = base.random.normal( 0.0, 1.0 );\ny[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\nbase.sqrt( 1.0 - (rho*rho) ) );\n }\nvar out = pcorrtest( x, y )\nvar table = out.print()\n","percentEncode":"var out = percentEncode( '☃' )\n","PHI":"PHI\n","PI":"PI\n","PI_SQUARED":"PI_SQUARED\n","pick":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pick( obj1, 'b' )\n","pickArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = pickArguments( foo, [ 0, 2 ] );\nvar out = bar( 1, 2, 3 )\n","pickBy":"function predicate( key, value ) {\n return ( value > 1 );\n };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pickBy( obj1, predicate )\n","PINF":"PINF\n","pkg2alias":"var v = pkg2alias( '@stdlib/math/base/special/sin' )\nv = pkg2alias( '@stdlib/math-base-special-sin' )\n","pkg2related":"var v = pkg2related( '@stdlib/math/base/special/sin' )\nv = pkg2related( '@stdlib/math-base-special-sin' )\n","pkg2standalone":"var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n","PLATFORM":"PLATFORM\n","plot":"var plot = plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = plot( x, y )\n","Plot":"var plot = Plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = Plot( x, y )\n","pluck":"var arr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nvar out = pluck( arr, 'a' )\narr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nout = pluck( arr, 'a', { 'copy': false } )\nvar bool = ( arr[ 0 ] === out[ 0 ] )\n","pop":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = pop( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = pop( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = pop( arr )\n","porterStemmer":"var out = porterStemmer( 'walking' )\nout = porterStemmer( 'walked' )\nout = porterStemmer( 'walks' )\nout = porterStemmer( '' )\n","prepend":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = prepend( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = prepend( arr, [ 3.0, 4.0 ] )\narr = { 'length': 1, '0': 1.0 };\narr = prepend( arr, [ 2.0, 3.0 ] )\n","prevGraphemeClusterBreak":"var out = prevGraphemeClusterBreak( 'last man standing', 4 )\nout = prevGraphemeClusterBreak( 'presidential election', 8 )\nout = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\nout = prevGraphemeClusterBreak( '🌷', 1 )\n","PRIMES_100K":"var list = PRIMES_100K()\n","properties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = properties( obj )\n","propertiesIn":"var props = propertiesIn( [] )\n","propertyDescriptor":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptor( obj, 'a' )\n","propertyDescriptorIn":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptorIn( obj, 'a' )\n","propertyDescriptors":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptors( obj )\n","propertyDescriptorsIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = propertyDescriptorsIn( obj )\n","propertyNames":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNames( obj )\n","propertyNamesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNamesIn( obj )\n","propertySymbols":"var s = propertySymbols( {} )\n","propertySymbolsIn":"var s = propertySymbolsIn( [] )\n","Proxy":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = new Proxy( {}, h );\np.a = 3.14;\np.a\n","Proxy.revocable":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = Proxy.revocable( {}, h );\np.proxy.a = 3.14;\np.proxy.a\np.revoke();\n","push":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = push( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = push( arr, 3.0, 4.0 )\narr = { 'length': 0 };\narr = push( arr, 1.0, 2.0 )\n","quarterOfYear":"var q = quarterOfYear( new Date() )\nq = quarterOfYear( 4 )\nq = quarterOfYear( 'June' )\nq = quarterOfYear( 'April' )\nq = quarterOfYear( 'apr' )\n","random.array.arcsine":"var out = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.arcsine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.arcsine.factory":"var fcn = random.array.arcsine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.arcsine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.arcsine.PRNG":"var prng = random.array.arcsine.PRNG;\n","random.array.arcsine.seed":"var seed = random.array.arcsine.seed;\n","random.array.arcsine.seedLength":"var len = random.array.arcsine.seedLength;\n","random.array.arcsine.state":"var out = random.array.arcsine( 3, 2.0, 5.0 )\nvar state = random.array.arcsine.state\nout = random.array.arcsine( 3, 2.0, 5.0 )\nout = random.array.arcsine( 3, 2.0, 5.0 )\nrandom.array.arcsine.state = state;\nout = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.stateLength":"var len = random.array.arcsine.stateLength;\n","random.array.arcsine.byteLength":"var sz = random.array.arcsine.byteLength;\n","random.array.bernoulli":"var out = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.bernoulli.assign( 0.5, x )\nvar bool = ( out === x )\n","random.array.bernoulli.factory":"var fcn = random.array.bernoulli.factory();\nvar out = fcn( 3, 0.5 )\nfcn = random.array.bernoulli.factory( 0.5 );\nout = fcn( 3 )\n","random.array.bernoulli.PRNG":"var prng = random.array.bernoulli.PRNG;\n","random.array.bernoulli.seed":"var seed = random.array.bernoulli.seed;\n","random.array.bernoulli.seedLength":"var len = random.array.bernoulli.seedLength;\n","random.array.bernoulli.state":"var out = random.array.bernoulli( 3, 0.5 )\nvar state = random.array.bernoulli.state\nout = random.array.bernoulli( 3, 0.5 )\nout = random.array.bernoulli( 3, 0.5 )\nrandom.array.bernoulli.state = state;\nout = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.stateLength":"var len = random.array.bernoulli.stateLength;\n","random.array.bernoulli.byteLength":"var sz = random.array.bernoulli.byteLength;\n","random.array.beta":"var out = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.beta.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.beta.factory":"var fcn = random.array.beta.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.beta.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.beta.PRNG":"var prng = random.array.beta.PRNG;\n","random.array.beta.seed":"var seed = random.array.beta.seed;\n","random.array.beta.seedLength":"var len = random.array.beta.seedLength;\n","random.array.beta.state":"var out = random.array.beta( 3, 2.0, 5.0 )\nvar state = random.array.beta.state\nout = random.array.beta( 3, 2.0, 5.0 )\nout = random.array.beta( 3, 2.0, 5.0 )\nrandom.array.beta.state = state;\nout = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.stateLength":"var len = random.array.beta.stateLength;\n","random.array.beta.byteLength":"var sz = random.array.beta.byteLength;\n","random.array.betaprime":"var out = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.betaprime.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.betaprime.factory":"var fcn = random.array.betaprime.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.betaprime.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.betaprime.PRNG":"var prng = random.array.betaprime.PRNG;\n","random.array.betaprime.seed":"var seed = random.array.betaprime.seed;\n","random.array.betaprime.seedLength":"var len = random.array.betaprime.seedLength;\n","random.array.betaprime.state":"var out = random.array.betaprime( 3, 2.0, 5.0 )\nvar state = random.array.betaprime.state\nout = random.array.betaprime( 3, 2.0, 5.0 )\nout = random.array.betaprime( 3, 2.0, 5.0 )\nrandom.array.betaprime.state = state;\nout = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.stateLength":"var len = random.array.betaprime.stateLength;\n","random.array.betaprime.byteLength":"var sz = random.array.betaprime.byteLength;\n","random.array.binomial":"var out = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.binomial.assign( 17, 0.5, x )\nvar bool = ( out === x )\n","random.array.binomial.factory":"var fcn = random.array.binomial.factory();\nvar out = fcn( 3, 17, 0.5 )\nfcn = random.array.binomial.factory( 17, 0.5 );\nout = fcn( 3 )\n","random.array.binomial.PRNG":"var prng = random.array.binomial.PRNG;\n","random.array.binomial.seed":"var seed = random.array.binomial.seed;\n","random.array.binomial.seedLength":"var len = random.array.binomial.seedLength;\n","random.array.binomial.state":"var out = random.array.binomial( 3, 17, 0.5 )\nvar state = random.array.binomial.state\nout = random.array.binomial( 3, 17, 0.5 )\nout = random.array.binomial( 3, 17, 0.5 )\nrandom.array.binomial.state = state;\nout = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.stateLength":"var len = random.array.binomial.stateLength;\n","random.array.binomial.byteLength":"var sz = random.array.binomial.byteLength;\n","random.array.cauchy":"var out = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cauchy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cauchy.factory":"var fcn = random.array.cauchy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cauchy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cauchy.PRNG":"var prng = random.array.cauchy.PRNG;\n","random.array.cauchy.seed":"var seed = random.array.cauchy.seed;\n","random.array.cauchy.seedLength":"var len = random.array.cauchy.seedLength;\n","random.array.cauchy.state":"var out = random.array.cauchy( 3, 2.0, 5.0 )\nvar state = random.array.cauchy.state\nout = random.array.cauchy( 3, 2.0, 5.0 )\nout = random.array.cauchy( 3, 2.0, 5.0 )\nrandom.array.cauchy.state = state;\nout = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.stateLength":"var len = random.array.cauchy.stateLength;\n","random.array.cauchy.byteLength":"var sz = random.array.cauchy.byteLength;\n","random.array.chi":"var out = random.array.chi( 3, 2.0 )\n","random.array.chi.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chi.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chi.factory":"var fcn = random.array.chi.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chi.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chi.PRNG":"var prng = random.array.chi.PRNG;\n","random.array.chi.seed":"var seed = random.array.chi.seed;\n","random.array.chi.seedLength":"var len = random.array.chi.seedLength;\n","random.array.chi.state":"var out = random.array.chi( 3, 2.0 )\nvar state = random.array.chi.state\nout = random.array.chi( 3, 2.0 )\nout = random.array.chi( 3, 2.0 )\nrandom.array.chi.state = state;\nout = random.array.chi( 3, 2.0 )\n","random.array.chi.stateLength":"var len = random.array.chi.stateLength;\n","random.array.chi.byteLength":"var sz = random.array.chi.byteLength;\n","random.array.chisquare":"var out = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chisquare.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chisquare.factory":"var fcn = random.array.chisquare.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chisquare.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chisquare.PRNG":"var prng = random.array.chisquare.PRNG;\n","random.array.chisquare.seed":"var seed = random.array.chisquare.seed;\n","random.array.chisquare.seedLength":"var len = random.array.chisquare.seedLength;\n","random.array.chisquare.state":"var out = random.array.chisquare( 3, 2.0 )\nvar state = random.array.chisquare.state\nout = random.array.chisquare( 3, 2.0 )\nout = random.array.chisquare( 3, 2.0 )\nrandom.array.chisquare.state = state;\nout = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.stateLength":"var len = random.array.chisquare.stateLength;\n","random.array.chisquare.byteLength":"var sz = random.array.chisquare.byteLength;\n","random.array.cosine":"var out = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cosine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cosine.factory":"var fcn = random.array.cosine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cosine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cosine.PRNG":"var prng = random.array.cosine.PRNG;\n","random.array.cosine.seed":"var seed = random.array.cosine.seed;\n","random.array.cosine.seedLength":"var len = random.array.cosine.seedLength;\n","random.array.cosine.state":"var out = random.array.cosine( 3, 2.0, 5.0 )\nvar state = random.array.cosine.state\nout = random.array.cosine( 3, 2.0, 5.0 )\nout = random.array.cosine( 3, 2.0, 5.0 )\nrandom.array.cosine.state = state;\nout = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.stateLength":"var len = random.array.cosine.stateLength;\n","random.array.cosine.byteLength":"var sz = random.array.cosine.byteLength;\n","random.array.discreteUniform":"var out = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.discreteUniform.assign( -10, 10, x )\nvar bool = ( out === x )\n","random.array.discreteUniform.factory":"var fcn = random.array.discreteUniform.factory();\nvar out = fcn( 3, -10, 10 )\nfcn = random.array.discreteUniform.factory( -10, 10 );\nout = fcn( 3 )\n","random.array.discreteUniform.PRNG":"var prng = random.array.discreteUniform.PRNG;\n","random.array.discreteUniform.seed":"var seed = random.array.discreteUniform.seed;\n","random.array.discreteUniform.seedLength":"var len = random.array.discreteUniform.seedLength;\n","random.array.discreteUniform.state":"var out = random.array.discreteUniform( 3, -10, 10 )\nvar state = random.array.discreteUniform.state\nout = random.array.discreteUniform( 3, -10, 10 )\nout = random.array.discreteUniform( 3, -10, 10 )\nrandom.array.discreteUniform.state = state;\nout = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.stateLength":"var len = random.array.discreteUniform.stateLength;\n","random.array.discreteUniform.byteLength":"var sz = random.array.discreteUniform.byteLength;\n","random.array.erlang":"var out = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.erlang.assign( 2, 5.0, x )\nvar bool = ( out === x )\n","random.array.erlang.factory":"var fcn = random.array.erlang.factory();\nvar out = fcn( 3, 2, 5.0 )\nfcn = random.array.erlang.factory( 2, 5.0 );\nout = fcn( 3 )\n","random.array.erlang.PRNG":"var prng = random.array.erlang.PRNG;\n","random.array.erlang.seed":"var seed = random.array.erlang.seed;\n","random.array.erlang.seedLength":"var len = random.array.erlang.seedLength;\n","random.array.erlang.state":"var out = random.array.erlang( 3, 2, 5.0 )\nvar state = random.array.erlang.state\nout = random.array.erlang( 3, 2, 5.0 )\nout = random.array.erlang( 3, 2, 5.0 )\nrandom.array.erlang.state = state;\nout = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.stateLength":"var len = random.array.erlang.stateLength;\n","random.array.erlang.byteLength":"var sz = random.array.erlang.byteLength;\n","random.array.exponential":"var out = random.array.exponential( 3, 2.0 )\n","random.array.exponential.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.exponential.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.exponential.factory":"var fcn = random.array.exponential.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.exponential.factory( 2.0 );\nout = fcn( 3 )\n","random.array.exponential.PRNG":"var prng = random.array.exponential.PRNG;\n","random.array.exponential.seed":"var seed = random.array.exponential.seed;\n","random.array.exponential.seedLength":"var len = random.array.exponential.seedLength;\n","random.array.exponential.state":"var out = random.array.exponential( 3, 2.0 )\nvar state = random.array.exponential.state\nout = random.array.exponential( 3, 2.0 )\nout = random.array.exponential( 3, 2.0 )\nrandom.array.exponential.state = state;\nout = random.array.exponential( 3, 2.0 )\n","random.array.exponential.stateLength":"var len = random.array.exponential.stateLength;\n","random.array.exponential.byteLength":"var sz = random.array.exponential.byteLength;\n","random.array.f":"var out = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.f.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.f.factory":"var fcn = random.array.f.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.f.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.f.PRNG":"var prng = random.array.f.PRNG;\n","random.array.f.seed":"var seed = random.array.f.seed;\n","random.array.f.seedLength":"var len = random.array.f.seedLength;\n","random.array.f.state":"var out = random.array.f( 3, 2.0, 5.0 )\nvar state = random.array.f.state\nout = random.array.f( 3, 2.0, 5.0 )\nout = random.array.f( 3, 2.0, 5.0 )\nrandom.array.f.state = state;\nout = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.stateLength":"var len = random.array.f.stateLength;\n","random.array.f.byteLength":"var sz = random.array.f.byteLength;\n","random.array.frechet":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.frechet.factory":"var fcn = random.array.frechet.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.frechet.PRNG":"var prng = random.array.frechet.PRNG;\n","random.array.frechet.seed":"var seed = random.array.frechet.seed;\n","random.array.frechet.seedLength":"var len = random.array.frechet.seedLength;\n","random.array.frechet.state":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.frechet.state\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nrandom.array.frechet.state = state;\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.stateLength":"var len = random.array.frechet.stateLength;\n","random.array.frechet.byteLength":"var sz = random.array.frechet.byteLength;\n","random.array.gamma":"var out = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gamma.factory":"var fcn = random.array.gamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gamma.PRNG":"var prng = random.array.gamma.PRNG;\n","random.array.gamma.seed":"var seed = random.array.gamma.seed;\n","random.array.gamma.seedLength":"var len = random.array.gamma.seedLength;\n","random.array.gamma.state":"var out = random.array.gamma( 3, 2.0, 5.0 )\nvar state = random.array.gamma.state\nout = random.array.gamma( 3, 2.0, 5.0 )\nout = random.array.gamma( 3, 2.0, 5.0 )\nrandom.array.gamma.state = state;\nout = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.stateLength":"var len = random.array.gamma.stateLength;\n","random.array.gamma.byteLength":"var sz = random.array.gamma.byteLength;\n","random.array.geometric":"var out = random.array.geometric( 3, 0.01 )\n","random.array.geometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.geometric.assign( 0.01, x )\nvar bool = ( out === x )\n","random.array.geometric.factory":"var fcn = random.array.geometric.factory();\nvar out = fcn( 3, 0.01 )\nfcn = random.array.geometric.factory( 0.01 );\nout = fcn( 3 )\n","random.array.geometric.PRNG":"var prng = random.array.geometric.PRNG;\n","random.array.geometric.seed":"var seed = random.array.geometric.seed;\n","random.array.geometric.seedLength":"var len = random.array.geometric.seedLength;\n","random.array.geometric.state":"var out = random.array.geometric( 3, 0.01 )\nvar state = random.array.geometric.state\nout = random.array.geometric( 3, 0.01 )\nout = random.array.geometric( 3, 0.01 )\nrandom.array.geometric.state = state;\nout = random.array.geometric( 3, 0.01 )\n","random.array.geometric.stateLength":"var len = random.array.geometric.stateLength;\n","random.array.geometric.byteLength":"var sz = random.array.geometric.byteLength;\n","random.array.gumbel":"var out = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gumbel.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gumbel.factory":"var fcn = random.array.gumbel.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gumbel.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gumbel.PRNG":"var prng = random.array.gumbel.PRNG;\n","random.array.gumbel.seed":"var seed = random.array.gumbel.seed;\n","random.array.gumbel.seedLength":"var len = random.array.gumbel.seedLength;\n","random.array.gumbel.state":"var out = random.array.gumbel( 3, 2.0, 5.0 )\nvar state = random.array.gumbel.state\nout = random.array.gumbel( 3, 2.0, 5.0 )\nout = random.array.gumbel( 3, 2.0, 5.0 )\nrandom.array.gumbel.state = state;\nout = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.stateLength":"var len = random.array.gumbel.stateLength;\n","random.array.gumbel.byteLength":"var sz = random.array.gumbel.byteLength;\n","random.array.hypergeometric":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.hypergeometric.assign( 20, 10, 7, x )\nvar bool = ( out === x )\n","random.array.hypergeometric.factory":"var fcn = random.array.hypergeometric.factory();\nvar out = fcn( 3, 20, 10, 7 )\nfcn = random.array.hypergeometric.factory( 20, 10, 7 );\nout = fcn( 3 )\n","random.array.hypergeometric.PRNG":"var prng = random.array.hypergeometric.PRNG;\n","random.array.hypergeometric.seed":"var seed = random.array.hypergeometric.seed;\n","random.array.hypergeometric.seedLength":"var len = random.array.hypergeometric.seedLength;\n","random.array.hypergeometric.state":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\nvar state = random.array.hypergeometric.state\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nrandom.array.hypergeometric.state = state;\nout = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.stateLength":"var len = random.array.hypergeometric.stateLength;\n","random.array.hypergeometric.byteLength":"var sz = random.array.hypergeometric.byteLength;\n","random.array.invgamma":"var out = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.invgamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.invgamma.factory":"var fcn = random.array.invgamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.invgamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.invgamma.PRNG":"var prng = random.array.invgamma.PRNG;\n","random.array.invgamma.seed":"var seed = random.array.invgamma.seed;\n","random.array.invgamma.seedLength":"var len = random.array.invgamma.seedLength;\n","random.array.invgamma.state":"var out = random.array.invgamma( 3, 2.0, 5.0 )\nvar state = random.array.invgamma.state\nout = random.array.invgamma( 3, 2.0, 5.0 )\nout = random.array.invgamma( 3, 2.0, 5.0 )\nrandom.array.invgamma.state = state;\nout = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.stateLength":"var len = random.array.invgamma.stateLength;\n","random.array.invgamma.byteLength":"var sz = random.array.invgamma.byteLength;\n","random.array.kumaraswamy":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.kumaraswamy.factory":"var fcn = random.array.kumaraswamy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.kumaraswamy.PRNG":"var prng = random.array.kumaraswamy.PRNG;\n","random.array.kumaraswamy.seed":"var seed = random.array.kumaraswamy.seed;\n","random.array.kumaraswamy.seedLength":"var len = random.array.kumaraswamy.seedLength;\n","random.array.kumaraswamy.state":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\nvar state = random.array.kumaraswamy.state\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nrandom.array.kumaraswamy.state = state;\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.stateLength":"var len = random.array.kumaraswamy.stateLength;\n","random.array.kumaraswamy.byteLength":"var sz = random.array.kumaraswamy.byteLength;\n","random.array.laplace":"var out = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.laplace.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.laplace.factory":"var fcn = random.array.laplace.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.laplace.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.laplace.PRNG":"var prng = random.array.laplace.PRNG;\n","random.array.laplace.seed":"var seed = random.array.laplace.seed;\n","random.array.laplace.seedLength":"var len = random.array.laplace.seedLength;\n","random.array.laplace.state":"var out = random.array.laplace( 3, 2.0, 5.0 )\nvar state = random.array.laplace.state\nout = random.array.laplace( 3, 2.0, 5.0 )\nout = random.array.laplace( 3, 2.0, 5.0 )\nrandom.array.laplace.state = state;\nout = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.stateLength":"var len = random.array.laplace.stateLength;\n","random.array.laplace.byteLength":"var sz = random.array.laplace.byteLength;\n","random.array.levy":"var out = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.levy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.levy.factory":"var fcn = random.array.levy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.levy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.levy.PRNG":"var prng = random.array.levy.PRNG;\n","random.array.levy.seed":"var seed = random.array.levy.seed;\n","random.array.levy.seedLength":"var len = random.array.levy.seedLength;\n","random.array.levy.state":"var out = random.array.levy( 3, 2.0, 5.0 )\nvar state = random.array.levy.state\nout = random.array.levy( 3, 2.0, 5.0 )\nout = random.array.levy( 3, 2.0, 5.0 )\nrandom.array.levy.state = state;\nout = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.stateLength":"var len = random.array.levy.stateLength;\n","random.array.levy.byteLength":"var sz = random.array.levy.byteLength;\n","random.array.logistic":"var out = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.logistic.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.logistic.factory":"var fcn = random.array.logistic.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.logistic.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.logistic.PRNG":"var prng = random.array.logistic.PRNG;\n","random.array.logistic.seed":"var seed = random.array.logistic.seed;\n","random.array.logistic.seedLength":"var len = random.array.logistic.seedLength;\n","random.array.logistic.state":"var out = random.array.logistic( 3, 2.0, 5.0 )\nvar state = random.array.logistic.state\nout = random.array.logistic( 3, 2.0, 5.0 )\nout = random.array.logistic( 3, 2.0, 5.0 )\nrandom.array.logistic.state = state;\nout = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.stateLength":"var len = random.array.logistic.stateLength;\n","random.array.logistic.byteLength":"var sz = random.array.logistic.byteLength;\n","random.array.lognormal":"var out = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.lognormal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.lognormal.factory":"var fcn = random.array.lognormal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.lognormal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.lognormal.PRNG":"var prng = random.array.lognormal.PRNG;\n","random.array.lognormal.seed":"var seed = random.array.lognormal.seed;\n","random.array.lognormal.seedLength":"var len = random.array.lognormal.seedLength;\n","random.array.lognormal.state":"var out = random.array.lognormal( 3, 2.0, 5.0 )\nvar state = random.array.lognormal.state\nout = random.array.lognormal( 3, 2.0, 5.0 )\nout = random.array.lognormal( 3, 2.0, 5.0 )\nrandom.array.lognormal.state = state;\nout = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.stateLength":"var len = random.array.lognormal.stateLength;\n","random.array.lognormal.byteLength":"var sz = random.array.lognormal.byteLength;\n","random.array.minstd":"var out = random.array.minstd( 3 )\n","random.array.minstd.normalized":"var out = random.array.minstd.normalized( 3 )\n","random.array.minstd.factory":"var fcn = random.array.minstd.factory();\nvar out = fcn( 3 )\n","random.array.minstd.PRNG":"var prng = random.array.minstd.PRNG;\n","random.array.minstd.seed":"var seed = random.array.minstd.seed;\n","random.array.minstd.seedLength":"var len = random.array.minstd.seedLength;\n","random.array.minstd.state":"var out = random.array.minstd( 3 )\nvar state = random.array.minstd.state;\nout = random.array.minstd( 3 )\nout = random.array.minstd( 3 )\nrandom.array.minstd.state = state;\nout = random.array.minstd( 3 )\n","random.array.minstd.stateLength":"var len = random.array.minstd.stateLength;\n","random.array.minstd.byteLength":"var sz = random.array.minstd.byteLength;\n","random.array.minstdShuffle":"var out = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.normalized":"var out = random.array.minstdShuffle.normalized( 3 )\n","random.array.minstdShuffle.factory":"var fcn = random.array.minstdShuffle.factory();\nvar out = fcn( 3 )\n","random.array.minstdShuffle.PRNG":"var prng = random.array.minstdShuffle.PRNG;\n","random.array.minstdShuffle.seed":"var seed = random.array.minstdShuffle.seed;\n","random.array.minstdShuffle.seedLength":"var len = random.array.minstdShuffle.seedLength;\n","random.array.minstdShuffle.state":"var out = random.array.minstdShuffle( 3 )\nvar state = random.array.minstdShuffle.state;\nout = random.array.minstdShuffle( 3 )\nout = random.array.minstdShuffle( 3 )\nrandom.array.minstdShuffle.state = state;\nout = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.stateLength":"var len = random.array.minstdShuffle.stateLength;\n","random.array.minstdShuffle.byteLength":"var sz = random.array.minstdShuffle.byteLength;\n","random.array.mt19937":"var out = random.array.mt19937( 3 )\n","random.array.mt19937.normalized":"var out = random.array.mt19937.normalized( 3 )\n","random.array.mt19937.factory":"var fcn = random.array.mt19937.factory();\nvar out = fcn( 3 )\n","random.array.mt19937.PRNG":"var prng = random.array.mt19937.PRNG;\n","random.array.mt19937.seed":"var seed = random.array.mt19937.seed;\n","random.array.mt19937.seedLength":"var len = random.array.mt19937.seedLength;\n","random.array.mt19937.state":"var out = random.array.mt19937( 3 )\nvar state = random.array.mt19937.state;\nout = random.array.mt19937( 3 )\nout = random.array.mt19937( 3 )\nrandom.array.mt19937.state = state;\nout = random.array.mt19937( 3 )\n","random.array.mt19937.stateLength":"var len = random.array.mt19937.stateLength;\n","random.array.mt19937.byteLength":"var sz = random.array.mt19937.byteLength;\n","random.array.negativeBinomial":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.negativeBinomial.assign( 10, 0.5, x )\nvar bool = ( out === x )\n","random.array.negativeBinomial.factory":"var fcn = random.array.negativeBinomial.factory();\nvar out = fcn( 3, 10, 0.5 )\nfcn = random.array.negativeBinomial.factory( 10, 0.5 );\nout = fcn( 3 )\n","random.array.negativeBinomial.PRNG":"var prng = random.array.negativeBinomial.PRNG;\n","random.array.negativeBinomial.seed":"var seed = random.array.negativeBinomial.seed;\n","random.array.negativeBinomial.seedLength":"var len = random.array.negativeBinomial.seedLength;\n","random.array.negativeBinomial.state":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\nvar state = random.array.negativeBinomial.state\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nrandom.array.negativeBinomial.state = state;\nout = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.stateLength":"var len = random.array.negativeBinomial.stateLength;\n","random.array.negativeBinomial.byteLength":"var sz = random.array.negativeBinomial.byteLength;\n","random.array.normal":"var out = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.normal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.normal.factory":"var fcn = random.array.normal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.normal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.normal.PRNG":"var prng = random.array.normal.PRNG;\n","random.array.normal.seed":"var seed = random.array.normal.seed;\n","random.array.normal.seedLength":"var len = random.array.normal.seedLength;\n","random.array.normal.state":"var out = random.array.normal( 3, 2.0, 5.0 )\nvar state = random.array.normal.state\nout = random.array.normal( 3, 2.0, 5.0 )\nout = random.array.normal( 3, 2.0, 5.0 )\nrandom.array.normal.state = state;\nout = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.stateLength":"var len = random.array.normal.stateLength;\n","random.array.normal.byteLength":"var sz = random.array.normal.byteLength;\n","random.array.pareto1":"var out = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.pareto1.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.pareto1.factory":"var fcn = random.array.pareto1.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.pareto1.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.pareto1.PRNG":"var prng = random.array.pareto1.PRNG;\n","random.array.pareto1.seed":"var seed = random.array.pareto1.seed;\n","random.array.pareto1.seedLength":"var len = random.array.pareto1.seedLength;\n","random.array.pareto1.state":"var out = random.array.pareto1( 3, 2.0, 5.0 )\nvar state = random.array.pareto1.state\nout = random.array.pareto1( 3, 2.0, 5.0 )\nout = random.array.pareto1( 3, 2.0, 5.0 )\nrandom.array.pareto1.state = state;\nout = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.stateLength":"var len = random.array.pareto1.stateLength;\n","random.array.pareto1.byteLength":"var sz = random.array.pareto1.byteLength;\n","random.array.poisson":"var out = random.array.poisson( 3, 2.0 )\n","random.array.poisson.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.poisson.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.poisson.factory":"var fcn = random.array.poisson.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.poisson.factory( 2.0 );\nout = fcn( 3 )\n","random.array.poisson.PRNG":"var prng = random.array.poisson.PRNG;\n","random.array.poisson.seed":"var seed = random.array.poisson.seed;\n","random.array.poisson.seedLength":"var len = random.array.poisson.seedLength;\n","random.array.poisson.state":"var out = random.array.poisson( 3, 2.0 )\nvar state = random.array.poisson.state\nout = random.array.poisson( 3, 2.0 )\nout = random.array.poisson( 3, 2.0 )\nrandom.array.poisson.state = state;\nout = random.array.poisson( 3, 2.0 )\n","random.array.poisson.stateLength":"var len = random.array.poisson.stateLength;\n","random.array.poisson.byteLength":"var sz = random.array.poisson.byteLength;\n","random.array.randu":"var out = random.array.randu( 3 )\n","random.array.randu.factory":"var fcn = random.array.randu.factory();\nvar out = fcn( 3 )\n","random.array.randu.PRNG":"var prng = random.array.randu.PRNG;\n","random.array.randu.seed":"var seed = random.array.randu.seed;\n","random.array.randu.seedLength":"var len = random.array.randu.seedLength;\n","random.array.randu.state":"var out = random.array.randu( 3 )\nvar state = random.array.randu.state;\nout = random.array.randu( 3 )\nout = random.array.randu( 3 )\nrandom.array.randu.state = state;\nout = random.array.randu( 3 )\n","random.array.randu.stateLength":"var len = random.array.randu.stateLength;\n","random.array.randu.byteLength":"var sz = random.array.randu.byteLength;\n","random.array.rayleigh":"var out = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.rayleigh.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.rayleigh.factory":"var fcn = random.array.rayleigh.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.rayleigh.factory( 2.0 );\nout = fcn( 3 )\n","random.array.rayleigh.PRNG":"var prng = random.array.rayleigh.PRNG;\n","random.array.rayleigh.seed":"var seed = random.array.rayleigh.seed;\n","random.array.rayleigh.seedLength":"var len = random.array.rayleigh.seedLength;\n","random.array.rayleigh.state":"var out = random.array.rayleigh( 3, 2.0 )\nvar state = random.array.rayleigh.state\nout = random.array.rayleigh( 3, 2.0 )\nout = random.array.rayleigh( 3, 2.0 )\nrandom.array.rayleigh.state = state;\nout = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.stateLength":"var len = random.array.rayleigh.stateLength;\n","random.array.rayleigh.byteLength":"var sz = random.array.rayleigh.byteLength;\n","random.array.t":"var out = random.array.t( 3, 2.0 )\n","random.array.t.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.t.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.t.factory":"var fcn = random.array.t.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.t.factory( 2.0 );\nout = fcn( 3 )\n","random.array.t.PRNG":"var prng = random.array.t.PRNG;\n","random.array.t.seed":"var seed = random.array.t.seed;\n","random.array.t.seedLength":"var len = random.array.t.seedLength;\n","random.array.t.state":"var out = random.array.t( 3, 2.0 )\nvar state = random.array.t.state\nout = random.array.t( 3, 2.0 )\nout = random.array.t( 3, 2.0 )\nrandom.array.t.state = state;\nout = random.array.t( 3, 2.0 )\n","random.array.t.stateLength":"var len = random.array.t.stateLength;\n","random.array.t.byteLength":"var sz = random.array.t.byteLength;\n","random.array.triangular":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.triangular.factory":"var fcn = random.array.triangular.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.triangular.PRNG":"var prng = random.array.triangular.PRNG;\n","random.array.triangular.seed":"var seed = random.array.triangular.seed;\n","random.array.triangular.seedLength":"var len = random.array.triangular.seedLength;\n","random.array.triangular.state":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.triangular.state\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nrandom.array.triangular.state = state;\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.stateLength":"var len = random.array.triangular.stateLength;\n","random.array.triangular.byteLength":"var sz = random.array.triangular.byteLength;\n","random.array.uniform":"var out = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.uniform.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.uniform.factory":"var fcn = random.array.uniform.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.uniform.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.uniform.PRNG":"var prng = random.array.uniform.PRNG;\n","random.array.uniform.seed":"var seed = random.array.uniform.seed;\n","random.array.uniform.seedLength":"var len = random.array.uniform.seedLength;\n","random.array.uniform.state":"var out = random.array.uniform( 3, 2.0, 5.0 )\nvar state = random.array.uniform.state\nout = random.array.uniform( 3, 2.0, 5.0 )\nout = random.array.uniform( 3, 2.0, 5.0 )\nrandom.array.uniform.state = state;\nout = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.stateLength":"var len = random.array.uniform.stateLength;\n","random.array.uniform.byteLength":"var sz = random.array.uniform.byteLength;\n","random.array.weibull":"var out = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.weibull.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.weibull.factory":"var fcn = random.array.weibull.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.weibull.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.weibull.PRNG":"var prng = random.array.weibull.PRNG;\n","random.array.weibull.seed":"var seed = random.array.weibull.seed;\n","random.array.weibull.seedLength":"var len = random.array.weibull.seedLength;\n","random.array.weibull.state":"var out = random.array.weibull( 3, 2.0, 5.0 )\nvar state = random.array.weibull.state\nout = random.array.weibull( 3, 2.0, 5.0 )\nout = random.array.weibull( 3, 2.0, 5.0 )\nrandom.array.weibull.state = state;\nout = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.stateLength":"var len = random.array.weibull.stateLength;\n","random.array.weibull.byteLength":"var sz = random.array.weibull.byteLength;\n","random.iterators.arcsine":"var it = random.iterators.arcsine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.bernoulli":"var it = random.iterators.bernoulli( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.beta":"var it = random.iterators.beta( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.betaprime":"var it = random.iterators.betaprime( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.binomial":"var it = random.iterators.binomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.boxMuller":"var it = random.iterators.boxMuller();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cauchy":"var it = random.iterators.cauchy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chi":"var it = random.iterators.chi( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chisquare":"var it = random.iterators.chisquare( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cosine":"var it = random.iterators.cosine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.discreteUniform":"var it = random.iterators.discreteUniform( 0, 3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.erlang":"var it = random.iterators.erlang( 1, 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.exponential":"var it = random.iterators.exponential( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.f":"var it = random.iterators.f( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.frechet":"var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gamma":"var it = random.iterators.gamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.geometric":"var it = random.iterators.geometric( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gumbel":"var it = random.iterators.gumbel( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.hypergeometric":"var it = random.iterators.hypergeometric( 20, 10, 7 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.improvedZiggurat":"var it = random.iterators.improvedZiggurat();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.invgamma":"var it = random.iterators.invgamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.kumaraswamy":"var it = random.iterators.kumaraswamy( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.laplace":"var it = random.iterators.laplace( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.levy":"var it = random.iterators.levy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.logistic":"var it = random.iterators.logistic( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.lognormal":"var it = random.iterators.lognormal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstd":"var it = random.iterators.minstd();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstdShuffle":"var it = random.iterators.minstdShuffle();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.mt19937":"var it = random.iterators.mt19937();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.negativeBinomial":"var it = random.iterators.negativeBinomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.normal":"var it = random.iterators.normal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.pareto1":"var it = random.iterators.pareto1( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.poisson":"var it = random.iterators.poisson( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randi":"var it = random.iterators.randi();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randn":"var it = random.iterators.randn();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randu":"var it = random.iterators.randu();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.rayleigh":"var it = random.iterators.rayleigh( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.t":"var it = random.iterators.t( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.triangular":"var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.uniform":"var it = random.iterators.uniform( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.weibull":"var it = random.iterators.weibull( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.streams.arcsine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.arcsine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.arcsine.factory( opts );\n","random.streams.arcsine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.bernoulli":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.bernoulli.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.bernoulli.factory( opts );\n","random.streams.bernoulli.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.beta":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.beta.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.beta.factory( opts );\n","random.streams.beta.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.betaprime":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.betaprime.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.betaprime.factory( opts );\n","random.streams.betaprime.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.binomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial( 20, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.binomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.binomial.factory( opts );\n","random.streams.binomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial.objectMode( 20, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.boxMuller":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.boxMuller.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.boxMuller.factory( opts );\n","random.streams.boxMuller.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cauchy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cauchy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cauchy.factory( opts );\n","random.streams.cauchy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chi.factory( opts );\n","random.streams.chi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chisquare":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chisquare.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chisquare.factory( opts );\n","random.streams.chisquare.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cosine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cosine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cosine.factory( opts );\n","random.streams.cosine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.discreteUniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform( 2, 5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.discreteUniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.discreteUniform.factory( opts );\n","random.streams.discreteUniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform.objectMode( 2, 5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.erlang":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang( 2, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.erlang.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.erlang.factory( opts );\n","random.streams.erlang.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang.objectMode( 2, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.exponential":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.exponential.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.exponential.factory( opts );\n","random.streams.exponential.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.f":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.f.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.f.factory( opts );\n","random.streams.f.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.frechet":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.frechet.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.frechet.factory( opts );\n","random.streams.frechet.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gamma.factory( opts );\n","random.streams.gamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.geometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.geometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.geometric.factory( opts );\n","random.streams.geometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gumbel":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gumbel.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gumbel.factory( opts );\n","random.streams.gumbel.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.hypergeometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric( 5, 3, 2, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.hypergeometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.hypergeometric.factory( opts );\n","random.streams.hypergeometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.improvedZiggurat.factory( opts );\n","random.streams.improvedZiggurat.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.invgamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.invgamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.invgamma.factory( opts );\n","random.streams.invgamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.kumaraswamy.factory( opts );\n","random.streams.kumaraswamy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.laplace":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.laplace.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.laplace.factory( opts );\n","random.streams.laplace.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.levy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.levy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.levy.factory( opts );\n","random.streams.levy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.logistic":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.logistic.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.logistic.factory( opts );\n","random.streams.logistic.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.lognormal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.lognormal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.lognormal.factory( opts );\n","random.streams.lognormal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstd":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstd.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstd.factory( opts );\n","random.streams.minstd.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstdShuffle.factory( opts );\n","random.streams.minstdShuffle.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.mt19937":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.mt19937.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.mt19937.factory( opts );\n","random.streams.mt19937.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial( 20.0, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.negativeBinomial.factory( opts );\n","random.streams.negativeBinomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.normal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.normal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.normal.factory( opts );\n","random.streams.normal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.pareto1":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.pareto1.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.pareto1.factory( opts );\n","random.streams.pareto1.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.poisson":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.poisson.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.poisson.factory( opts );\n","random.streams.poisson.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randi.factory( opts );\n","random.streams.randi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randn":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randn.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randn.factory( opts );\n","random.streams.randn.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randu":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randu.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randu.factory( opts );\n","random.streams.randu.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.rayleigh":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.rayleigh.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.rayleigh.factory( opts );\n","random.streams.rayleigh.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.t":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.t.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.t.factory( opts );\n","random.streams.t.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.triangular":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.triangular.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.triangular.factory( opts );\n","random.streams.triangular.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.uniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.uniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.uniform.factory( opts );\n","random.streams.uniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.weibull":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.weibull.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.weibull.factory( opts );\n","random.streams.weibull.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.strided.arcsine":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n","random.strided.arcsine.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.bernoulli":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n","random.strided.bernoulli.factory":"var fcn = random.strided.bernoulli.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.PRNG":"var prng = random.strided.bernoulli.PRNG;\n","random.strided.bernoulli.seed":"var seed = random.strided.bernoulli.seed;\n","random.strided.bernoulli.seedLength":"var len = random.strided.bernoulli.seedLength;\n","random.strided.bernoulli.state":"var out = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nvar state = random.strided.bernoulli.state\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nrandom.strided.bernoulli.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.stateLength":"var len = random.strided.bernoulli.stateLength;\n","random.strided.bernoulli.byteLength":"var sz = random.strided.bernoulli.byteLength;\n","random.strided.beta":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta( 3, a, -2, b, 1, out, 1 )\n","random.strided.beta.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.betaprime":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n","random.strided.betaprime.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.chi":"var out = azeros( 5, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chi.factory":"var fcn = random.strided.chi.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.PRNG":"var prng = random.strided.chi.PRNG;\n","random.strided.chi.seed":"var seed = random.strided.chi.seed;\n","random.strided.chi.seedLength":"var len = random.strided.chi.seedLength;\n","random.strided.chi.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chi.state\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chi.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.stateLength":"var len = random.strided.chi.stateLength;\n","random.strided.chi.byteLength":"var sz = random.strided.chi.byteLength;\n","random.strided.chisquare":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chisquare.factory":"var fcn = random.strided.chisquare.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.PRNG":"var prng = random.strided.chisquare.PRNG;\n","random.strided.chisquare.seed":"var seed = random.strided.chisquare.seed;\n","random.strided.chisquare.seedLength":"var len = random.strided.chisquare.seedLength;\n","random.strided.chisquare.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chisquare.state\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chisquare.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.stateLength":"var len = random.strided.chisquare.stateLength;\n","random.strided.chisquare.byteLength":"var sz = random.strided.chisquare.byteLength;\n","random.strided.cosine":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n","random.strided.cosine.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n","random.strided.discreteUniform":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.discreteUniform.ndarray":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.exponential":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.exponential.factory":"var fcn = random.strided.exponential.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.PRNG":"var prng = random.strided.exponential.PRNG;\n","random.strided.exponential.seed":"var seed = random.strided.exponential.seed;\n","random.strided.exponential.seedLength":"var len = random.strided.exponential.seedLength;\n","random.strided.exponential.state":"var out = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.exponential.state\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.exponential.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.stateLength":"var len = random.strided.exponential.stateLength;\n","random.strided.exponential.byteLength":"var sz = random.strided.exponential.byteLength;\n","random.strided.gamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.gamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.geometric":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n","random.strided.geometric.factory":"var fcn = random.strided.geometric.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.PRNG":"var prng = random.strided.geometric.PRNG;\n","random.strided.geometric.seed":"var seed = random.strided.geometric.seed;\n","random.strided.geometric.seedLength":"var len = random.strided.geometric.seedLength;\n","random.strided.geometric.state":"var out = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nvar state = random.strided.geometric.state\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nrandom.strided.geometric.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.stateLength":"var len = random.strided.geometric.stateLength;\n","random.strided.geometric.byteLength":"var sz = random.strided.geometric.byteLength;\n","random.strided.invgamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.invgamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.lognormal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.lognormal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.minstd":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd( out.length, out, 1 )\n","random.strided.minstd.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.ndarray( out.length, out, 1, 0 )\n","random.strided.minstd.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized( out.length, out, 1 )\n","random.strided.minstd.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle( out.length, out, 1 )\n","random.strided.minstdShuffle.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized( out.length, out, 1 )\n","random.strided.minstdShuffle.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937( out.length, out, 1 )\n","random.strided.mt19937.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized( out.length, out, 1 )\n","random.strided.mt19937.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.normal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.normal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.poisson":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.poisson.factory":"var fcn = random.strided.poisson.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.PRNG":"var prng = random.strided.poisson.PRNG;\n","random.strided.poisson.seed":"var seed = random.strided.poisson.seed;\n","random.strided.poisson.seedLength":"var len = random.strided.poisson.seedLength;\n","random.strided.poisson.state":"var out = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.poisson.state\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.poisson.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.stateLength":"var len = random.strided.poisson.stateLength;\n","random.strided.poisson.byteLength":"var sz = random.strided.poisson.byteLength;\n","random.strided.randu":"var out = azeros( 5, 'generic' );\nrandom.strided.randu( out.length, out, 1 )\n","random.strided.randu.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.randu.ndarray( out.length, out, 1, 0 )\n","random.strided.rayleigh":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.rayleigh.factory":"var fcn = random.strided.rayleigh.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.PRNG":"var prng = random.strided.rayleigh.PRNG;\n","random.strided.rayleigh.seed":"var seed = random.strided.rayleigh.seed;\n","random.strided.rayleigh.seedLength":"var len = random.strided.rayleigh.seedLength;\n","random.strided.rayleigh.state":"var out = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.rayleigh.state\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.rayleigh.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.stateLength":"var len = random.strided.rayleigh.stateLength;\n","random.strided.rayleigh.byteLength":"var sz = random.strided.rayleigh.byteLength;\n","random.strided.t":"var out = azeros( 5, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.t.factory":"var fcn = random.strided.t.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.PRNG":"var prng = random.strided.t.PRNG;\n","random.strided.t.seed":"var seed = random.strided.t.seed;\n","random.strided.t.seedLength":"var len = random.strided.t.seedLength;\n","random.strided.t.state":"var out = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.t.state\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.t.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.stateLength":"var len = random.strided.t.stateLength;\n","random.strided.t.byteLength":"var sz = random.strided.t.byteLength;\n","random.strided.uniform":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.uniform.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","ranks":"var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\nvar out = ranks( arr )\narr = [ 2, 2, 1, 4, 3 ];\nout = ranks( arr )\narr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\nout = ranks( arr )\n","readDir":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadDir( './beep/boop', onRead );\n","readDir.sync":"var out = readDir.sync( './beep/boop' );\n","readFile":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadFile( './beep/boop.js', onRead );\n","readFile.sync":"var out = readFile.sync( './beep/boop.js' );\n","readFileList":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nvar filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nreadFileList( filepaths, onRead );\n","readFileList.sync":"var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nvar out = readFileList.sync( filepaths );\n","readJSON":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadJSON( './beep/boop.json', onRead );\n","readJSON.sync":"var out = readJSON.sync( './beep/boop.json' );\n","readWASM":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadWASM( './beep/boop.wasm', onRead );\n","readWASM.sync":"var out = readWASM.sync( './beep/boop.wasm' );\n","real":"var z = new Complex128( 5.0, 3.0 );\nvar re = real( z )\n","realarray":"var arr = realarray()\narr = realarray( 'float32' )\nvar arr = realarray( 5 )\narr = realarray( 5, 'int32' )\nvar arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = realarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = realarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = realarray( buf, 0, 4, 'float32' )\n","realarrayCtors":"var ctor = realarrayCtors( 'float64' )\nctor = realarrayCtors( 'float' )\n","realarrayDataTypes":"var out = realarrayDataTypes()\n","realf":"var z = new Complex64( 5.0, 3.0 );\nvar re = realf( z )\n","realmax":"var m = realmax( 'float16' )\nm = realmax( 'float32' )\n","realmin":"var m = realmin( 'float16' )\nm = realmin( 'float32' )\n","reBasename":"var RE = reBasename()\nvar RE_POSIX = reBasename( 'posix' );\nvar RE_WIN32 = reBasename( 'win32' );\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reBasename.REGEXP":"var RE = reBasename.REGEXP\n","reBasename.REGEXP_POSIX":"var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reBasename.REGEXP_WIN32":"var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reBasenamePosix":"var RE_BASENAME_POSIX = reBasenamePosix();\nvar base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n","reBasenamePosix.REGEXP":"var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n","reBasenameWindows":"var RE_BASENAME_WINDOWS = reBasenameWindows();\nvar base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n","reBasenameWindows.REGEXP":"var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n","reColorHexadecimal":"var RE = reColorHexadecimal();\nvar bool = RE.test( 'ffffff' )\nbool = RE.test( '000' )\nbool = RE.test( 'beep' )\n","reColorHexadecimal.REGEXP":"var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP.test( '000' )\nbool = reColorHexadecimal.REGEXP.test( 'beep' )\n","reColorHexadecimal.REGEXP_SHORTHAND":"var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n","reColorHexadecimal.REGEXP_EITHER":"var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n","reDecimalNumber":"var RE = reDecimalNumber();\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\nbool = RE.test( '0.0' )\nbool = RE.test( '.0' )\nbool = RE.test( '0' )\nbool = RE.test( 'beep' )\nvar re = reDecimalNumber({ 'flags': 'g' });\nvar str = '1.234 5.6, 7.8';\nvar out = str.match( re )\n","reDecimalNumber.REGEXP":"var RE = reDecimalNumber.REGEXP;\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\n","reDecimalNumber.REGEXP_CAPTURE":"var RE = reDecimalNumber.REGEXP_CAPTURE;\nvar str = '1.02';\nvar out = replace( str, RE, '$1 x $1' )\n","reDirname":"var RE = reDirname()\nvar RE_POSIX = reDirname( 'posix' );\nvar dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reDirname( 'win32' );\ndir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reDirname.REGEXP":"var RE = reDirname.REGEXP\n","reDirname.REGEXP_POSIX":"var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirname.REGEXP_WIN32":"var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reDirnamePosix":"var RE = reDirnamePosix();\nvar dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\ndir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\ndir = RE.exec( 'foo/file.pdf' )[ 1 ]\ndir = RE.exec( '/foo/bar/file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '.' )[ 1 ]\ndir = RE.exec( './' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnamePosix.REGEXP":"var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirnameWindows":"var RE = reDirnameWindows();\nvar dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\ndir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\ndir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\ndir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnameWindows.REGEXP":"var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n","reduce":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduce( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduce( arr, 0.0, f )\n","reduce2d":"var f = naryFunction( base.add, 2 );\nvar arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\nvar out = reduce2d( arr, [ 0, 0 ], f )\n","reduceAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\n","reduceAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 2000, 1500, 1000 ];\nf( arr, acc, done )\n","reduceRight":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduceRight( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduceRight( arr, 0.0, f )\n","reduceRightAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\n","reduceRightAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceRightAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 1000, 1500, 2000 ];\nf( arr, acc, done )\n","reEOL":"var RE_EOL = reEOL();\nvar bool = RE_EOL.test( '\\n' )\nbool = RE_EOL.test( '\\r\\n' )\nbool = RE_EOL.test( '\\\\r\\\\n' )\n","reEOL.REGEXP":"var bool = reEOL.REGEXP.test( 'abc' )\n","reEOL.REGEXP_CAPTURE":"var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n","reExtendedLengthPath":"var RE = reExtendedLengthPath();\nvar path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\nvar bool = RE.test( path )\npath = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\nbool = RE.test( path )\npath = 'C:\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '/c/foo/bar';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\n","reExtendedLengthPath.REGEXP":"var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n","reExtname":"var RE = reExtname()\nvar RE_POSIX = reExtname( 'posix' );\nvar ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reExtname( 'win32' );\next = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reExtname.REGEXP":"var RE = reExtname.REGEXP\n","reExtname.REGEXP_POSIX":"var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtname.REGEXP_WIN32":"var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reExtnamePosix":"var RE = reExtnamePosix();\nvar ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\next = RE.exec( './foo/bar/.gitignore' )[ 1 ]\next = RE.exec( 'foo/file.pdf' )[ 1 ]\next = RE.exec( '/foo/bar/file' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '.' )[ 1 ]\next = RE.exec( './' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnamePosix.REGEXP":"var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtnameWindows":"var RE = reExtnameWindows();\nvar ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\next = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\next = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\next = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\next = RE.exec( 'beep\\\\boop.' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnameWindows.REGEXP":"var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reFilename":"var RE = reFilename()\nvar RE_POSIX = reFilename( 'posix' );\nvar parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\nvar RE_WIN32 = reFilename( 'win32' );\nparts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reFilename.REGEXP":"var RE = reFilename.REGEXP\n","reFilename.REGEXP_POSIX":"var f = '/foo/bar/index.js';\nvar parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n","reFilename.REGEXP_WIN32":"var f = 'C:\\\\foo\\\\bar\\\\index.js';\nvar parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n","reFilenamePosix":"var RE = reFilenamePosix();\nvar parts = RE.exec( '/foo/bar/index.js' ).slice()\nparts = RE.exec( './foo/bar/.gitignore' ).slice()\nparts = RE.exec( 'foo/file.pdf' ).slice()\nparts = RE.exec( '/foo/bar/file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenamePosix.REGEXP":"var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n","reFilenameWindows":"var RE = reFilenameWindows();\nvar parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\nparts = RE.exec( 'foo\\\\file.pdf' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenameWindows.REGEXP":"var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n","reFromString":"var re = reFromString( '/beep/' )\nre = reFromString( '/beep' )\n","reFunctionName":"var RE_FUNCTION_NAME = reFunctionName();\nfunction beep() { return 'boop'; };\nvar name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\nname = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n","reFunctionName.REGEXP":"var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n","regexp2json":"var json = regexp2json( /ab+c/ )\n","reim":"var z = new Complex128( 5.0, 3.0 );\nvar out = reim( z )\n","reimf":"var z = new Complex64( 5.0, 3.0 );\nvar out = reimf( z )\n","rejectArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v === 2 ); };\nvar bar = rejectArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","removeFirst":"var out = removeFirst( 'beep' )\nout = removeFirst( 'Boop' )\nout = removeFirst( 'foo bar', 4 )\n","removeLast":"var out = removeLast( 'beep' )\nout = removeLast( 'Boop' )\nout = removeLast( 'foo bar', 4 )\n","removePunctuation":"var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\nvar out = removePunctuation( str )\nstr = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\nout = removePunctuation( str )\n","removeUTF8BOM":"var out = removeUTF8BOM( '\\ufeffbeep' )\n","removeWords":"var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\nout = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n","rename":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nrename( './beep/boop.txt', './beep/foo.txt', done );\n","rename.sync":"var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n","reNativeFunction":"var RE = reNativeFunction();\nvar bool = RE.test( Date.toString() )\nbool = RE.test( (function noop() {}).toString() )\n","reNativeFunction.REGEXP":"var bool = reNativeFunction.REGEXP.test( Date.toString() )\nbool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n","reorderArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reorderArguments( foo, [ 2, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","repeat":"var out = repeat( 'a', 5 )\nout = repeat( '', 100 )\nout = repeat( 'beep', 0 )\n","replace":"var out = replace( 'beep', 'e', 'o' )\nfunction replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nout = replace( str, /([^\\s]+)/gi, replacer )\nout = replace( 'beep', /e/, 'o' )\n","reRegExp":"var RE = reRegExp();\nvar bool = RE.test( '/^beep$/' )\nbool = RE.test( '/boop' )\nbool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\nbool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n","reRegExp.REGEXP":"var bool = reRegExp.REGEXP.test( '/^beep$/' )\nbool = reRegExp.REGEXP.test( '/boop' )\n","rescape":"var str = rescape( '[A-Z]*' )\n","reSemVer":"var RE_SEMVER = reSemVer()\nvar bool = RE_SEMVER.test( '1.0.0' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1' )\nbool = RE_SEMVER.test( 'abc' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n","reSemVer.REGEXP":"var bool = reSemVer.REGEXP.test( '1.0.0' )\nbool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n","resolveParentPath":"function onPath( error, path ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( path );\n }\n };\nresolveParentPath( 'package.json', onPath );\n","resolveParentPath.sync":"var out = resolveParentPath.sync( 'package.json' );\n","resolveParentPathBy":"function predicate( path, next ) {\n setTimeout( onTimeout, path );\n function onTimeout() {\n console.log( path );\n next( null, false );\n }\n };\nfunction onPath( error, path ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( path );\n }\n };\nresolveParentPathBy( 'package.json', predicate, onPath );\n","resolveParentPathBy.sync":"function predicate() { return false; };\nvar out = resolveParentPathBy.sync( 'package.json', predicate );\n","reUncPath":"var RE = reUncPath();\nvar path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = 'beep boop \\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server';\nbool = RE.test( path )\npath = '\\\\';\nbool = RE.test( path )\npath = '';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\nbool = RE.test( path )\npath = '//server/share';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\npath = 'foo/bar';\nbool = RE.test( path )\npath = './foo/bar';\nbool = RE.test( path )\npath = '/foo/../bar';\nbool = RE.test( path )\n","reUncPath.REGEXP":"var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = reUncPath.REGEXP.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = reUncPath.REGEXP.test( path )\n","reUtf16SurrogatePair":"var RE = reUtf16SurrogatePair();\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16SurrogatePair.REGEXP":"var RE = reUtf16SurrogatePair.REGEXP;\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16UnpairedSurrogate":"var RE = reUtf16UnpairedSurrogate();\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reUtf16UnpairedSurrogate.REGEXP":"var RE = reUtf16UnpairedSurrogate.REGEXP;\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reverseArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reverseArguments( foo );\nvar out = bar( 1, 2, 3 )\n","reverseString":"var out = reverseString( 'foo' )\nout = reverseString( 'abcdef' )\n","reviveBasePRNG":"var str = JSON.stringify( base.random.mt19937 );\nvar r = parseJSON( str, reviveBasePRNG )\n","reviveBuffer":"var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\nvar buf = parseJSON( str, reviveBuffer )\n","reviveComplex":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex )\n","reviveComplex64":"var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex64 )\n","reviveComplex128":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex128 )\n","reviveError":"var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\nvar err = JSON.parse( str, reviveError )\n","reviveRegExp":"var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\nvar v = parseJSON( str, reviveRegExp )\n","reviveTypedArray":"var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\nvar arr = parseJSON( str, reviveTypedArray )\n","reWhitespace":"var RE = reWhitespace();\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP":"var RE = reWhitespace.REGEXP;\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP_CAPTURE":"var RE = reWhitespace.REGEXP_CAPTURE;\nvar str = 'Duplicate capture';\nvar out = replace( str, RE, '$1$1' )\n","rpad":"var out = rpad( 'a', 5 )\nout = rpad( 'beep', 10, 'p' )\nout = rpad( 'beep', 12, 'boop' )\n","rtrim":"var out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","safeintmax":"var m = safeintmax( 'float16' )\nm = safeintmax( 'float32' )\n","safeintmin":"var m = safeintmin( 'float16' )\nm = safeintmin( 'float32' )\n","sample":"var out = sample( 'abc' )\nout = sample( [ 3, 6, 9 ] )\nvar bool = ( out.length === 3 )\nout = sample( [ 3, null, NaN, 'abc', function(){} ] )\nout = sample( [ 3, 6, 9 ], { 'size': 10 } )\nout = sample( [ 0, 1 ], { 'size': 20 } )\nout = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\nout = sample( [ 0, 1 ], { 'replace': false } )\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\nout = sample( x, { 'probs': probs } )\nout = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n","sample.factory":"var mysample = sample.factory({ 'seed': 232 } );\nvar out = mysample( 'abcdefg' )\nvar pool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\nout = mysample()\nout = mysample()\nvar opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\npool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, opts );\nout = mysample()\nout = mysample()\nout = mysample()\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'size': 10 })\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'replace': false })\nout = mysample()\n","SAVOY_STOPWORDS_FIN":"var list = SAVOY_STOPWORDS_FIN()\n","SAVOY_STOPWORDS_FR":"var list = SAVOY_STOPWORDS_FR()\n","SAVOY_STOPWORDS_GER":"var list = SAVOY_STOPWORDS_GER()\n","SAVOY_STOPWORDS_IT":"var list = SAVOY_STOPWORDS_IT()\n","SAVOY_STOPWORDS_POR":"var list = SAVOY_STOPWORDS_POR()\n","SAVOY_STOPWORDS_SP":"var list = SAVOY_STOPWORDS_SP()\n","SAVOY_STOPWORDS_SWE":"var list = SAVOY_STOPWORDS_SWE()\n","scalar2array":"var x = scalar2array( 1.0 )\n","scalar2ndarray":"var x = scalar2ndarray( 1.0 )\nvar sh = x.shape\nvar dt = x.dtype\nvar v = x.get()\n","sdot":"var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\nsdot( x, y )\n","SECONDS_IN_DAY":"var days = 3.14;\nvar secs = days * SECONDS_IN_DAY\n","SECONDS_IN_HOUR":"var hrs = 3.14;\nvar secs = hrs * SECONDS_IN_HOUR\n","SECONDS_IN_MINUTE":"var mins = 3.14;\nvar secs = mins * SECONDS_IN_MINUTE\n","SECONDS_IN_WEEK":"var wks = 3.14;\nvar secs = wks * SECONDS_IN_WEEK\n","secondsInMonth":"var num = secondsInMonth()\nnum = secondsInMonth( 2 )\nnum = secondsInMonth( 2, 2016 )\nnum = secondsInMonth( 2, 2017 )\nnum = secondsInMonth( 'feb', 2016 )\nnum = secondsInMonth( 'february', 2016 )\n","secondsInYear":"var num = secondsInYear()\nnum = secondsInYear( 2016 )\nnum = secondsInYear( 2017 )\n","seq2slice":"var s = new seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","setConfigurableReadOnly":"var obj = {};\nsetConfigurableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setConfigurableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetConfigurableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setConfigurableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setConfigurableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetConfigurableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setMemoizedConfigurableReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedConfigurableReadOnly( obj, 'foo', foo );\nobj.foo\n","setMemoizedReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedReadOnly( obj, 'foo', foo );\nobj.foo\n","setNonEnumerableProperty":"var obj = {};\nsetNonEnumerableProperty( obj, 'foo', 'bar' );\nobj.foo\nobjectKeys( obj )\n","setNonEnumerableReadOnly":"var obj = {};\nsetNonEnumerableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setNonEnumerableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setNonEnumerableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setNonEnumerableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setReadOnly":"var obj = {};\nsetReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","SharedArrayBuffer":"var buf = new SharedArrayBuffer( 5 )\n","SharedArrayBuffer.length":"SharedArrayBuffer.length\n","SharedArrayBuffer.prototype.byteLength":"var buf = new SharedArrayBuffer( 5 );\nbuf.byteLength\n","SharedArrayBuffer.prototype.slice":"var b1 = new SharedArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","shift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = shift( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = shift( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = shift( arr )\n","shuffle":"var data = [ 1, 2, 3 ];\nvar out = shuffle( data )\nout = shuffle( data, { 'copy': 'none' } );\nvar bool = ( data === out )\n","shuffle.factory":"var myshuffle = shuffle.factory();\nmyshuffle = shuffle.factory({ 'seed': 239 });\nvar arr = [ 0, 1, 2, 3, 4 ];\nvar out = myshuffle( arr )\nmyshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\narr = [ 1, 2, 3, 4, 5, 6 ];\nout = myshuffle( arr );\nvar bool = ( arr === out )\narr = [ 1, 2, 3, 4 ];\nout = myshuffle( arr, { 'copy': 'shallow' } );\nbool = ( arr === out )\n","sizeOf":"var s = sizeOf( 'int8' )\ns = sizeOf( 'uint32' )\n","Slice":"var s = new Slice();\ns = new Slice( 10 );\nvar s = new Slice( 2, 10 );\ns = new Slice( 2, 10, 1 );\n","Slice.prototype.start":"var s = new Slice( 10 );\ns.start\ns = new Slice( 2, 10 );\ns.start\n","Slice.prototype.stop":"var s = new Slice( 10 );\ns.stop\ns = new Slice( 2, 10 );\ns.stop\n","Slice.prototype.step":"var s = new Slice( 10 );\ns.step\ns = new Slice( 2, 10 );\ns.step\ns = new Slice( 2, 10, 1 );\ns.step\n","Slice.prototype.toString":"var s = new Slice( 10 );\ns.toString()\ns = new Slice( 2, 10, 1 );\ns.toString()\n","Slice.prototype.toJSON":"var s = new Slice( 10 );\ns.toJSON()\ns = new Slice( 2, 10, 1 );\ns.toJSON()\n","snakecase":"var out = snakecase( 'Hello World!' )\nout = snakecase( 'I am a tiny little teapot' )\n","some":"var arr = [ 0, 0, 1, 2, 3 ];\nvar bool = some( arr, 3 )\n","someBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, -3, 4, -1 ];\nvar bool = someBy( arr, 2, negative )\n","someByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\n","someByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, 2, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, 2, done )\n","someByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, -2, 3, 4 ];\nvar bool = someByRight( arr, 2, negative )\n","someByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\n","someByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, 2, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, 2, done )\n","SOTU":"var out = SOTU()\nvar opts = { 'name': 'Barack Obama' };\nout = SOTU( opts )\nopts = { 'party': [ 'Democratic', 'Federalist' ] };\nout = SOTU( opts )\nopts = { 'year': [ 2008, 2009, 2011 ] };\nout = SOTU( opts )\nopts = { 'range': [ 2008, 2016 ] }\nout = SOTU( opts )\n","SPACHE_REVISED":"var list = SPACHE_REVISED()\n","SPAM_ASSASSIN":"var data = SPAM_ASSASSIN()\n","SparklineBase":"var sparkline = new SparklineBase()\nvar data = [ 1, 2, 3 ];\nsparkline = new SparklineBase( data )\n","sparsearray2iterator":"var it = sparsearray2iterator( [ 1, , 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","sparsearray2iteratorRight":"var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\nvar v = it.next().value\nv = it.next().value\n","splitStream":"var s = splitStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = splitStream.factory( opts );\nvar s = createStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.objectMode":"var s = splitStream.objectMode();\ns.write( 'a\\nb\\c' );\ns.end();\n","SQRT_EPS":"SQRT_EPS\n","SQRT_HALF":"SQRT_HALF\n","SQRT_HALF_PI":"SQRT_HALF_PI\n","SQRT_PHI":"SQRT_PHI\n","SQRT_PI":"SQRT_PI\n","SQRT_THREE":"SQRT_THREE\n","SQRT_TWO":"SQRT_TWO\n","SQRT_TWO_PI":"SQRT_TWO_PI\n","SSA_US_BIRTHS_2000_2014":"var data = SSA_US_BIRTHS_2000_2014()\n","sswap":"var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\nsswap( x, y );\nx.data\ny.data\n","Stack":"var s = Stack();\ns.push( 'foo' ).push( 'bar' );\ns.length\ns.pop()\ns.length\ns.pop()\ns.length\n","standalone2pkg":"var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n","STANDARD_CARD_DECK":"var list = STANDARD_CARD_DECK()\n","startcase":"var out = startcase( 'beep boop' )\n","startsWith":"var bool = startsWith( 'Beep', 'Be' )\nbool = startsWith( 'Beep', 'ep' )\nbool = startsWith( 'Beep', 'ee', 1 )\nbool = startsWith( 'Beep', 'ee', -3 )\nbool = startsWith( 'Beep', '' )\n","STOPWORDS_EN":"var list = STOPWORDS_EN()\n","strided.abs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( 2, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2By":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.abs2By.ndarray":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -1.0, -2.0, -3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.absBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.absBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.absBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.add":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.add.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.cbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.cbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.ceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.deg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.deg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.dataTypes":"var out = strided.dataTypes()\n","strided.dispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1 );\ny\nf = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\ny\n","strided.dispatchBy":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\ny\nf = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\ny\n","strided.floor":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.floor.ndarray":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.inv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.inv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.mul":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.mul.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.ramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.rsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.rsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.sqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sub":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.sub.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.trunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.trunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","stridedarray2iterator":"var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\nvar v = it.next().value\nv = it.next().value\n","stridedArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","stridedArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = stridedArrayStream.factory( opts );\n","stridedArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","string2buffer":"var b = string2buffer( 'beep boop' )\nb = string2buffer( '7468697320697320612074c3a97374', 'hex' );\nb.toString()\n","sub2ind":"var d = [ 3, 3, 3 ];\nvar idx = sub2ind( d, 1, 2, 2 )\n","substringAfter":"var out = substringAfter( 'Hello World!', 'World' )\nout = substringAfter( 'Hello World!', 'Hello ' )\nout = substringAfter( 'Hello World!', 'l', 5 )\n","substringAfterLast":"var out = substringAfterLast( 'beep boop beep baz', 'beep' )\nout = substringAfterLast( 'Hello World!', 'Hello ' )\nout = substringAfterLast( 'Hello World!', 'o', 5 )\n","substringBefore":"var str = 'beep boop';\nvar out = substringBefore( str, ' ' )\nout = substringBefore( str, 'o' )\n","substringBeforeLast":"var str = 'Beep Boop Beep';\nvar out = substringBeforeLast( str, 'Beep' )\nout = substringBeforeLast( str, 'Boop' )\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n","Symbol":"var s = ( Symbol ) ? Symbol( 'beep' ) : null\n","tabulate":"var collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulate( collection )\n","tabulateBy":"function indicator( value ) { return value[ 0 ]; };\nvar collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulateBy( collection, indicator )\n","tabulateByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\n","tabulateByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = tabulateByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 750 ];\nf( arr, done )\n","thunk":"var fcn = thunk( base.add, 2, 3 );\nvar v = fcn()\nv = fcn()\n","tic":"var t = tic()\n","timeit":"var code = 'var x = Math.pow( Math.random(), 3 );';\ncode += 'if ( x !== x ) {';\ncode += 'throw new Error( \\'Something went wrong.\\' );';\ncode += '}';\nfunction done( error, results ) {\n if ( error ) {\n throw error;\n }\n console.dir( results );\n };\ntimeit( code, done )\n","tmpdir":"var dir = tmpdir()\n","toc":"var start = tic();\nvar delta = toc( start )\n","tokenize":"var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\nout = tokenize( 'Hello World!', true )\n","transformStream":"var s = transformStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = transformStream.factory( opts );\nfunction fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar s = createStream( fcn );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.objectMode":"var s = transformStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","transformStream.ctor":"function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar opts = { 'highWaterMark': 64, 'transform': fcn };\nvar customStream = transformStream.ctor( opts );\nvar s = customStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","trim":"var out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","truncate":"var str = 'beep boop';\nvar out = truncate( str, 5 )\nout = truncate( str, 5, '|' )\n","truncateMiddle":"var str = 'beep boop';\nvar out = truncateMiddle( str, 5 )\nout = truncateMiddle( str, 5, '|' )\n","trycatch":"function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n };\nvar z = trycatch( x, -1.0 )\n","trycatchAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n // process error...\n }\n console.log( result );\n };\ntrycatchAsync( x, 'boop', done )\n","tryFunction":"function fcn() { throw new Error( 'beep boop' ); };\nvar f = tryFunction( fcn );\nvar out = f();\nout.message\n","tryRequire":"var out = tryRequire( '_unknown_module_id_' )\n","trythen":"function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n };\nfunction y() {\n return -1.0;\n };\nvar z = trythen( x, y )\n","trythenAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ntrythenAsync( x, y, done )\n","ttest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ttest( x )\nrnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\nx = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n y[ i ] = rnorm();\n }\nout = ttest( x, y )\nvar table = out.print()\narr = [ 2, 4, 3, 1, 0 ];\nout = ttest( arr, { 'alpha': 0.01 } );\ntable = out.print()\nvar arr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest( arr, { 'alternative': 'greater' } );\ntable = out.print()\n","ttest2":"var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\nvar y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\nvar out = ttest2( x, y )\nvar table = out.print()\nout = ttest2( x, y, { 'alpha': 0.1 } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'greater' } );\ntable = out.print()\nx = [ 2, 3, 1, 4 ];\ny = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\nout = ttest2( x, y, { 'variance': 'equal' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 3.0 );\n }\ny = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 1.0, 3.0 );\n }\nout = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n","TWO_PI":"TWO_PI\n","typedarray":"var arr = typedarray()\narr = typedarray( 'float32' )\nvar arr = typedarray( 5 )\narr = typedarray( 5, 'int32' )\nvar arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = typedarray( buf, 0, 4, 'float32' )\n","typedarray2json":"var arr = new Float64Array( 2 );\narr[ 0 ] = 5.0;\narr[ 1 ] = 3.0;\nvar json = typedarray2json( arr )\n","typedarrayCtors":"var ctor = typedarrayCtors( 'float64' )\nctor = typedarrayCtors( 'float' )\n","typedarrayDataTypes":"var out = typedarrayDataTypes()\n","typedarraypool":"var arr = typedarraypool()\narr = typedarraypool( 'float32' )\nvar arr = typedarraypool( 5 )\narr = typedarraypool( 5, 'int32' )\nvar arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool( arr1, 'float32' )\n","typedarraypool.malloc":"var arr = typedarraypool.malloc()\narr = typedarraypool.malloc( 'float32' )\nvar arr = typedarraypool.malloc( 5 )\narr = typedarraypool.malloc( 5, 'int32' )\nvar arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\n","typedarraypool.calloc":"var arr = typedarraypool.calloc()\narr = typedarraypool.calloc( 'float32' )\nvar arr = typedarraypool.calloc( 5 )\narr = typedarraypool.calloc( 5, 'int32' )\n","typedarraypool.free":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr )\n","typedarraypool.clear":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\ntypedarraypool.clear()\n","typedarraypool.highWaterMark":"typedarraypool.highWaterMark\n","typedarraypool.nbytes":"var arr = typedarraypool( 5 )\ntypedarraypool.nbytes\n","typedarraypool.factory":"var pool = typedarraypool.factory();\nvar arr1 = pool( 3, 'float64' )\n","typemax":"var m = typemax( 'int8' )\nm = typemax( 'uint32' )\n","typemin":"var m = typemin( 'int8' )\nm = typemin( 'uint32' )\n","typeOf":"var t = typeOf( 'a' )\nt = typeOf( 5 )\nt = typeOf( NaN )\nt = typeOf( true )\nt = typeOf( false )\nt = typeOf( null )\nt = typeOf( undefined )\nt = typeOf( [] )\nt = typeOf( {} )\nt = typeOf( function noop() {} )\nt = typeOf( Symbol( 'beep' ) )\nt = typeOf( /.+/ )\nt = typeOf( new String( 'beep' ) )\nt = typeOf( new Number( 5 ) )\nt = typeOf( new Boolean( false ) )\nt = typeOf( new Array() )\nt = typeOf( new Object() )\nt = typeOf( new Int8Array( 10 ) )\nt = typeOf( new Uint8Array( 10 ) )\nt = typeOf( new Uint8ClampedArray( 10 ) )\nt = typeOf( new Int16Array( 10 ) )\nt = typeOf( new Uint16Array( 10 ) )\nt = typeOf( new Int32Array( 10 ) )\nt = typeOf( new Uint32Array( 10 ) )\nt = typeOf( new Float32Array( 10 ) )\nt = typeOf( new Float64Array( 10 ) )\nt = typeOf( new ArrayBuffer( 10 ) )\nt = typeOf( new Date() )\nt = typeOf( new RegExp( '.+' ) )\nt = typeOf( new Map() )\nt = typeOf( new Set() )\nt = typeOf( new WeakMap() )\nt = typeOf( new WeakSet() )\nt = typeOf( new Error( 'beep' ) )\nt = typeOf( new TypeError( 'beep' ) )\nt = typeOf( new SyntaxError( 'beep' ) )\nt = typeOf( new ReferenceError( 'beep' ) )\nt = typeOf( new URIError( 'beep' ) )\nt = typeOf( new RangeError( 'beep' ) )\nt = typeOf( new EvalError( 'beep' ) )\nt = typeOf( Math )\nt = typeOf( JSON )\nfunction beep() { return arguments; };\nt = typeOf( beep() )\nt = typeOf( new Buffer( 10 ) )\nfunction Person() { return this };\nt = typeOf( new Person() )\nvar Foo = function () { return this; };\nt = typeOf( new Foo() )\n","UINT8_MAX":"UINT8_MAX\n","UINT8_NUM_BYTES":"UINT8_NUM_BYTES\n","Uint8Array":"var arr = new Uint8Array()\nvar arr = new Uint8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8Array( buf, 0, 4 )\n","Uint8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n","Uint8Array.of":"var arr = Uint8Array.of( 1, 2 )\n","Uint8Array.BYTES_PER_ELEMENT":"Uint8Array.BYTES_PER_ELEMENT\n","Uint8Array.name":"Uint8Array.name\n","Uint8Array.prototype.buffer":"var arr = new Uint8Array( 5 );\narr.buffer\n","Uint8Array.prototype.byteLength":"var arr = new Uint8Array( 5 );\narr.byteLength\n","Uint8Array.prototype.byteOffset":"var arr = new Uint8Array( 5 );\narr.byteOffset\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8Array.prototype.length":"var arr = new Uint8Array( 5 );\narr.length\n","Uint8Array.prototype.copyWithin":"var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8Array.prototype.entries":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.every":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8Array.prototype.fill":"var arr = new Uint8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8Array.prototype.filter":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8Array.prototype.find":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8Array.prototype.findIndex":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8Array.prototype.forEach":"var arr = new Uint8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8Array.prototype.includes":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8Array.prototype.indexOf":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8Array.prototype.join":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8Array.prototype.keys":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.lastIndexOf":"var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8Array.prototype.map":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn );\n","Uint8Array.prototype.reduce":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8Array.prototype.reduceRight":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8Array.prototype.reverse":"var arr = new Uint8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8Array.prototype.set":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8Array.prototype.slice":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8Array.prototype.some":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8Array.prototype.sort":"var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8Array.prototype.subarray":"var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8Array.prototype.toLocaleString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8Array.prototype.toString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint8Array.prototype.values":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray":"var arr = new Uint8ClampedArray()\nvar arr = new Uint8ClampedArray( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8ClampedArray( buf, 0, 4 )\n","Uint8ClampedArray.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n","Uint8ClampedArray.of":"var arr = Uint8ClampedArray.of( 1, 2 )\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"Uint8ClampedArray.BYTES_PER_ELEMENT\n","Uint8ClampedArray.name":"Uint8ClampedArray.name\n","Uint8ClampedArray.prototype.buffer":"var arr = new Uint8ClampedArray( 5 );\narr.buffer\n","Uint8ClampedArray.prototype.byteLength":"var arr = new Uint8ClampedArray( 5 );\narr.byteLength\n","Uint8ClampedArray.prototype.byteOffset":"var arr = new Uint8ClampedArray( 5 );\narr.byteOffset\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8ClampedArray( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8ClampedArray.prototype.length":"var arr = new Uint8ClampedArray( 5 );\narr.length\n","Uint8ClampedArray.prototype.copyWithin":"var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8ClampedArray.prototype.entries":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.every":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8ClampedArray.prototype.fill":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8ClampedArray.prototype.filter":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8ClampedArray.prototype.find":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8ClampedArray.prototype.findIndex":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8ClampedArray.prototype.forEach":"var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8ClampedArray.prototype.includes":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8ClampedArray.prototype.indexOf":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8ClampedArray.prototype.join":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8ClampedArray.prototype.keys":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.lastIndexOf":"var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8ClampedArray.prototype.map":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn );\n","Uint8ClampedArray.prototype.reduce":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8ClampedArray.prototype.reduceRight":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8ClampedArray.prototype.reverse":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8ClampedArray.prototype.set":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8ClampedArray.prototype.slice":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8ClampedArray.prototype.some":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8ClampedArray.prototype.sort":"var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8ClampedArray.prototype.subarray":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8ClampedArray.prototype.toLocaleString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8ClampedArray.prototype.toString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toString()\n","Uint8ClampedArray.prototype.values":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","UINT16_MAX":"UINT16_MAX\n","UINT16_NUM_BYTES":"UINT16_NUM_BYTES\n","Uint16Array":"var arr = new Uint16Array()\nvar arr = new Uint16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Uint16Array( buf, 0, 4 )\n","Uint16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n","Uint16Array.of":"var arr = Uint16Array.of( 1, 2 )\n","Uint16Array.BYTES_PER_ELEMENT":"Uint16Array.BYTES_PER_ELEMENT\n","Uint16Array.name":"Uint16Array.name\n","Uint16Array.prototype.buffer":"var arr = new Uint16Array( 5 );\narr.buffer\n","Uint16Array.prototype.byteLength":"var arr = new Uint16Array( 5 );\narr.byteLength\n","Uint16Array.prototype.byteOffset":"var arr = new Uint16Array( 5 );\narr.byteOffset\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint16Array.prototype.length":"var arr = new Uint16Array( 5 );\narr.length\n","Uint16Array.prototype.copyWithin":"var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint16Array.prototype.entries":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.every":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint16Array.prototype.fill":"var arr = new Uint16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint16Array.prototype.filter":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint16Array.prototype.find":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint16Array.prototype.findIndex":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint16Array.prototype.forEach":"var arr = new Uint16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint16Array.prototype.includes":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint16Array.prototype.indexOf":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint16Array.prototype.join":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint16Array.prototype.keys":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.lastIndexOf":"var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint16Array.prototype.map":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn );\n","Uint16Array.prototype.reduce":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint16Array.prototype.reduceRight":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint16Array.prototype.reverse":"var arr = new Uint16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint16Array.prototype.set":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint16Array.prototype.slice":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint16Array.prototype.some":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint16Array.prototype.sort":"var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint16Array.prototype.subarray":"var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint16Array.prototype.toLocaleString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint16Array.prototype.toString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint16Array.prototype.values":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","UINT32_MAX":"UINT32_MAX\n","UINT32_NUM_BYTES":"UINT32_NUM_BYTES\n","Uint32Array":"var arr = new Uint32Array()\nvar arr = new Uint32Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Uint32Array( buf, 0, 4 )\n","Uint32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n","Uint32Array.of":"var arr = Uint32Array.of( 1, 2 )\n","Uint32Array.BYTES_PER_ELEMENT":"Uint32Array.BYTES_PER_ELEMENT\n","Uint32Array.name":"Uint32Array.name\n","Uint32Array.prototype.buffer":"var arr = new Uint32Array( 5 );\narr.buffer\n","Uint32Array.prototype.byteLength":"var arr = new Uint32Array( 5 );\narr.byteLength\n","Uint32Array.prototype.byteOffset":"var arr = new Uint32Array( 5 );\narr.byteOffset\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint32Array.prototype.length":"var arr = new Uint32Array( 5 );\narr.length\n","Uint32Array.prototype.copyWithin":"var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint32Array.prototype.entries":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.every":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint32Array.prototype.fill":"var arr = new Uint32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint32Array.prototype.filter":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint32Array.prototype.find":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint32Array.prototype.findIndex":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint32Array.prototype.forEach":"var arr = new Uint32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint32Array.prototype.includes":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint32Array.prototype.indexOf":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint32Array.prototype.join":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint32Array.prototype.keys":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.lastIndexOf":"var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint32Array.prototype.map":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn );\n","Uint32Array.prototype.reduce":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint32Array.prototype.reduceRight":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint32Array.prototype.reverse":"var arr = new Uint32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint32Array.prototype.set":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint32Array.prototype.slice":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint32Array.prototype.some":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint32Array.prototype.sort":"var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint32Array.prototype.subarray":"var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint32Array.prototype.toLocaleString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint32Array.prototype.toString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint32Array.prototype.values":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","umask":"var mask = umask()\nmask = umask( { 'symbolic': true } )\n","uncapitalize":"var out = uncapitalize( 'Beep' )\nout = uncapitalize( 'bOOp' )\n","uncapitalizeKeys":"var obj = { 'AA': 1, 'BB': 2 };\nvar out = uncapitalizeKeys( obj )\n","uncurry":"function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n };\nvar fcn = uncurry( addX );\nvar sum = fcn( 2, 3 )\nfunction add( x ) {\n return function add( y ) {\n return x + y;\n };\n };\nfcn = uncurry( add, 2 );\nsum = fcn( 9 )\nfunction addX( x ) {\n this.x = x;\n return addY;\n };\nfunction addY( y ) {\n return this.x + y;\n };\nfcn = uncurry( addX, {} );\nsum = fcn( 2, 3 )\n","uncurryRight":"function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n };\nvar fcn = uncurryRight( addX );\nvar sum = fcn( 3, 2 )\nfunction add( y ) {\n return function add( x ) {\n return x + y;\n };\n };\nfcn = uncurryRight( add, 2 );\nsum = fcn( 9 )\nfunction addY( y ) {\n this.y = y;\n return addX;\n };\nfunction addX( x ) {\n return x + this.y;\n };\nfcn = uncurryRight( addY, {} );\nsum = fcn( 3, 2 )\n","UNICODE_MAX":"UNICODE_MAX\n","UNICODE_MAX_BMP":"UNICODE_MAX_BMP\n","UnicodeColumnChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeColumnChartSparkline( data );\nchart.render()\n","UnicodeLineChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeLineChartSparkline( data );\nchart.render()\n","UnicodeSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeSparkline( data );\nchart.render()\nchart.type = 'line';\nchart.render()\n","UnicodeTristateChartSparkline":"var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\nvar chart = new UnicodeTristateChartSparkline( data );\nchart.render()\n","UnicodeUpDownChartSparkline":"var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\nvar chart = new UnicodeUpDownChartSparkline( data );\nchart.render()\n","UnicodeWinLossChartSparkline":"var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\nvar chart = new UnicodeWinLossChartSparkline( data );\nchart.render()\n","unlink":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nunlink( './beep/boop.txt', done );\n","unlink.sync":"var out = unlink.sync( './beep/boop.txt' );\n","unshift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = unshift( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = unshift( arr, 3.0, 4.0 )\narr = { 'length': 1, '0': 1.0 };\narr = unshift( arr, 2.0, 3.0 )\n","until":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nuntil( predicate, beep )\n","untilAsync":"function predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nuntilAsync( predicate, fcn, done )\n","untilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nuntilEach( arr, predicate, logger )\n","untilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nuntilEachRight( arr, predicate, logger )\n","unzip":"var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nvar out = unzip( arr )\narr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nout = unzip( arr, [ 0, 2 ] )\n","uppercase":"var out = uppercase( 'bEEp' )\n","uppercaseKeys":"var obj = { 'a': 1, 'b': 2 };\nvar out = uppercaseKeys( obj )\n","US_STATES_ABBR":"var list = US_STATES_ABBR()\n","US_STATES_CAPITALS":"var list = US_STATES_CAPITALS()\n","US_STATES_CAPITALS_NAMES":"var out = US_STATES_CAPITALS_NAMES()\n","US_STATES_NAMES":"var list = US_STATES_NAMES()\n","US_STATES_NAMES_CAPITALS":"var out = US_STATES_NAMES_CAPITALS()\n","utf16ToUTF8Array":"var str = '☃';\nvar out = utf16ToUTF8Array( str )\n","vartest":"var x = [ 610, 610, 550, 590, 565, 570 ];\nvar y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\nvar out = vartest( x, y )\nvar table = out.print()\n","waterfall":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nwaterfall( fcns, done );\n","waterfall.factory":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nvar waterfall = waterfall.factory( fcns, done );\nwaterfall();\nwaterfall();\nwaterfall();\n","whileAsync":"function predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nwhileAsync( predicate, fcn, done )\n","whileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nwhileEach( arr, predicate, logger )\n","whileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nwhileEachRight( arr, predicate, logger )\n","whilst":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nwhilst( predicate, beep )\n","wilcoxon":"var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\nvar out = wilcoxon( x )\nrunif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\nvar x = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = runif();\n y[ i ] = runif();\n }\nout = wilcoxon( x, y )\nvar table = out.print()\nout = wilcoxon( arr, { 'alpha': 0.01 });\ntable = out.print()\nout = wilcoxon( arr, { 'mu': 10 })\nout = wilcoxon( arr, { 'alternative': 'less' });\ntable = out.print()\nout = wilcoxon( arr, { 'alternative': 'greater' });\ntable = out.print()\n","writableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = writableProperties( obj )\n","writablePropertiesIn":"var props = writablePropertiesIn( [] )\n","writablePropertyNames":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNames( obj )\n","writablePropertyNamesIn":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNamesIn( obj )\n","writablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbols( obj )\n","writablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbolsIn( obj )\n","writeFile":"function onWrite( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nwriteFile( './beep/boop.txt', 'beep boop', onWrite );\n","writeFile.sync":"var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n","zip":"var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\nvar opts = { 'trunc': false };\nout = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n","ztest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ztest( x, 2.0 )\narr = [ 2, 4, 3, 1, 0 ];\nout = ztest( arr, 2.0, { 'alpha': 0.01 } );\ntable = out.print()\nvar arr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'alternative': 'less' } )\nout = ztest( arr, 1.0, { 'alternative': 'greater' } )\n","ztest2":"var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\nvar y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\nvar out = ztest2( x, y, 2.0, 2.0 )\nvar table = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 1.0 );\n }\ny = new Array( 100 );\n for ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 0.0, 2.0 );\n }\nout = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n"} \ No newline at end of file +{"abs":"var y = abs( -1.0 )\nvar x = new Float64Array( [ -1.0, -2.0 ] );\ny = abs( x )\nx = [ -1.0, -2.0 ];\ny = abs( x )\nx = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\ny = abs( x )\ny.get( 0, 1 )\n","abs.assign":"var x = new Float64Array( [ -1.0, -2.0 ] );\nvar y = new Float64Array( x.length );\nvar out = abs.assign( x, y )\nvar bool = ( out === y )\nx = [ -1.0, -2.0 ];\ny = [ 0.0, 0.0 ];\nout = abs.assign( x, y )\nbool = ( out === y )\nx = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\ny = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\nout = abs.assign( x, y )\nout.get( 0, 1 )\nbool = ( out === y )\n","acartesianPower":"var x = [ 1, 2 ];\nvar out = acartesianPower( x, 2 )\n","acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = acartesianProduct( x1, x2 )\n","acartesianSquare":"var out = acartesianSquare( [ 1, 2 ] )\n","acronym":"var out = acronym( 'the quick brown fox' )\nout = acronym( 'Hard-boiled eggs' )\n","aempty":"var arr = aempty( 2 )\narr = aempty( 2, 'float32' )\n","aemptyLike":"var x = new Float64Array( 2 );\nvar arr = aemptyLike( x )\narr = aemptyLike( x, 'float32' )\n","AFINN_96":"var list = AFINN_96()\n","AFINN_111":"var list = AFINN_111()\n","afull":"var arr = afull( 2, 1.0 )\narr = afull( 2, 1.0, 'float32' )\n","afullLike":"var x = new Float64Array( 2 );\nvar y = afullLike( x, 1.0 )\ny = afullLike( x, 1.0, 'float32' )\n","alias2pkg":"var v = alias2pkg( 'base.sin' )\n","alias2related":"var v = alias2related( 'base.sin' )\n","alias2standalone":"var v = alias2standalone( 'base.sin' )\n","aliases":"var o = aliases()\no = aliases( '@stdlib/math/base/special' )\n","allocUnsafe":"var buf = allocUnsafe( 100 )\n","amskfilter":"var x = [ 1, 2, 3, 4 ];\nvar y = amskfilter( x, [ 0, 1, 0, 1 ] )\n","amskreject":"var x = [ 1, 2, 3, 4 ];\nvar y = amskreject( x, [ 0, 1, 0, 1 ] )\n","anans":"var arr = anans( 2 )\narr = anans( 2, 'float32' )\n","anansLike":"var x = new Float64Array( 2 );\nvar y = anansLike( x )\ny = anansLike( x, 'float32' )\n","anova1":"var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\nvar f = [\n 'control', 'treatA', 'treatB', 'treatC', 'control',\n 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ];\nvar out = anova1( x, f )\n","ANSCOMBES_QUARTET":"var d = ANSCOMBES_QUARTET()\n","any":"var arr = [ 0, 0, 0, 0, 1 ];\nvar bool = any( arr )\n","anyBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4, -1 ];\nvar bool = anyBy( arr, negative )\n","anyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\n","anyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","anyByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, 2, 3, 4 ];\nvar bool = anyByRight( arr, negative )\n","anyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\n","anyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","aones":"var arr = aones( 2 )\narr = aones( 2, 'float32' )\n","aonesLike":"var x = new Float64Array( 2 );\nvar y = aonesLike( x )\ny = aonesLike( x, 'float32' )\n","aoneTo":"var arr = aoneTo( 2 )\narr = aoneTo( 2, 'float32' )\n","aoneToLike":"var arr = aoneToLike( [ 0, 0 ] )\narr = aoneToLike( [ 0, 0 ], 'float32' )\n","APERY":"APERY\n","append":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = append( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = append( arr, [ 3.0, 4.0 ] )\narr = { 'length': 0 };\narr = append( arr, [ 1.0, 2.0 ] )\n","ARCH":"ARCH\n","argumentFunction":"var argn = argumentFunction( 1 );\nvar v = argn( 3.14, -3.14, 0.0 )\nv = argn( -1.0, -0.0, 1.0 )\nv = argn( 'beep', 'boop', 'bop' )\nv = argn( 'beep' )\n","ARGV":"var execPath = ARGV[ 0 ]\n","array":"var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","array2buffer":"var buf = array2buffer( [ 1, 2, 3, 4 ] )\n","array2fancy":"var y = array2fancy( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.factory":"var f = array2fancy.factory();\nvar y = f( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.idx":"var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n","array2iterator":"var it = array2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","array2iteratorRight":"var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","ArrayBuffer":"var buf = new ArrayBuffer( 5 )\n","ArrayBuffer.length":"ArrayBuffer.length\n","ArrayBuffer.isView":"var arr = new Float64Array( 10 );\nArrayBuffer.isView( arr )\n","ArrayBuffer.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nbuf.byteLength\n","ArrayBuffer.prototype.slice":"var b1 = new ArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","arraybuffer2buffer":"var ab = new ArrayBuffer( 10 )\nvar buf = arraybuffer2buffer( ab )\nvar len = buf.length\nbuf = arraybuffer2buffer( ab, 2, 6 )\nlen = buf.length\n","arrayCtors":"var ctor = arrayCtors( 'float64' )\nctor = arrayCtors( 'float' )\n","arrayDataType":"var arr = new Float64Array( 10 );\nvar dt = arrayDataType( arr )\ndt = arrayDataType( 'beep' )\n","arrayDataTypes":"var out = arrayDataTypes()\nout = arrayDataTypes( 'floating_point' )\nout = arrayDataTypes( 'floating_point_and_generic' )\n","ArrayIndex":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n","ArrayIndex.free":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n// ...\nArrayIndex.free( idx.id )\n","ArrayIndex.get":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.get( idx.id )\n","ArrayIndex.prototype.data":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.data\n","ArrayIndex.prototype.dtype":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.dtype\n","ArrayIndex.prototype.id":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.id\n","ArrayIndex.prototype.isCached":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.isCached\n","ArrayIndex.prototype.type":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.type\n","ArrayIndex.prototype.toString":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toString()\n","ArrayIndex.prototype.toJSON":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toJSON()\n","arrayMinDataType":"var dt = arrayMinDataType( 3.141592653589793 )\ndt = arrayMinDataType( 3 )\ndt = arrayMinDataType( -3 )\ndt = arrayMinDataType( '-3' )\n","arrayMostlySafeCasts":"var out = arrayMostlySafeCasts( 'float32' )\n","arrayNextDataType":"var out = arrayNextDataType( 'float32' )\n","arrayPromotionRules":"var out = arrayPromotionRules( 'float32', 'int32' )\n","arraySafeCasts":"var out = arraySafeCasts( 'float32' )\n","arraySameKindCasts":"var out = arraySameKindCasts( 'float32' )\n","arrayShape":"var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n","arrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = arrayStream( [ 1, 2, 3 ] );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","arrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = arrayStream.factory( opts );\n","arrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = arrayStream.objectMode( [ 1, 2, 3 ] );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","arrayview2iterator":"var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","arrayview2iteratorRight":"var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","aslice":"var out = aslice( [ 1, 2, 3, 4 ] )\nout = aslice( [ 1, 2, 3, 4 ], 1 )\nout = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n","AsyncIteratorSymbol":"var s = AsyncIteratorSymbol\n","atake":"var x = [ 1, 2, 3, 4 ];\nvar y = atake( x, [ 1, 3 ] )\n","azeros":"var arr = azeros( 2 )\narr = azeros( 2, 'float32' )\n","azerosLike":"var x = new Float64Array( 2 );\nvar y = azerosLike( x )\ny = azerosLike( x, 'float32' )\n","azeroTo":"var arr = azeroTo( 2 )\narr = azeroTo( 2, 'float32' )\n","azeroToLike":"var arr = azeroToLike( [ 0, 0 ] )\narr = azeroToLike( [ 0, 0 ], 'float32' )\n","bartlettTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = bartlettTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = bartlettTest( arr, { 'groups': groups } )\n","base.abs":"var y = base.abs( -1.0 )\ny = base.abs( 2.0 )\ny = base.abs( 0.0 )\ny = base.abs( -0.0 )\ny = base.abs( NaN )\n","base.abs2":"var y = base.abs2( -1.0 )\ny = base.abs2( 2.0 )\ny = base.abs2( 0.0 )\ny = base.abs2( -0.0 )\ny = base.abs2( NaN )\n","base.abs2f":"var y = base.abs2f( -1.0 )\ny = base.abs2f( 2.0 )\ny = base.abs2f( 0.0 )\ny = base.abs2f( -0.0 )\ny = base.abs2f( NaN )\n","base.absdiff":"var d = base.absdiff( 2.0, 5.0 )\nd = base.absdiff( -1.0, 3.14 )\nd = base.absdiff( 10.1, -2.05 )\nd = base.absdiff( -0.0, 0.0 )\nd = base.absdiff( NaN, 5.0 )\nd = base.absdiff( PINF, NINF )\nd = base.absdiff( PINF, PINF )\n","base.absf":"var y = base.absf( -1.0 )\ny = base.absf( 2.0 )\ny = base.absf( 0.0 )\ny = base.absf( -0.0 )\ny = base.absf( NaN )\n","base.acos":"var y = base.acos( 1.0 )\ny = base.acos( 0.707 )\ny = base.acos( NaN )\n","base.acosh":"var y = base.acosh( 1.0 )\ny = base.acosh( 2.0 )\ny = base.acosh( NaN )\n","base.acot":"var y = base.acot( 2.0 )\ny = base.acot( 0.0 )\ny = base.acot( 0.5 )\ny = base.acot( 1.0 )\ny = base.acot( NaN )\n","base.acoth":"var y = base.acoth( 2.0 )\ny = base.acoth( 0.0 )\ny = base.acoth( 0.5 )\ny = base.acoth( 1.0 )\ny = base.acoth( NaN )\n","base.acovercos":"var y = base.acovercos( -1.5 )\ny = base.acovercos( -0.0 )\n","base.acoversin":"var y = base.acoversin( 1.5 )\ny = base.acoversin( 0.0 )\n","base.acsc":"var y = base.acsc( 1.0 )\ny = base.acsc( PI )\ny = base.acsc( -PI )\ny = base.acsc( NaN )\n","base.acsch":"var y = base.acsch( 0.0 )\ny = base.acsch( -1.0 )\ny = base.acsch( NaN )\n","base.add":"var v = base.add( -1.0, 5.0 )\nv = base.add( 2.0, 5.0 )\nv = base.add( 0.0, 5.0 )\nv = base.add( -0.0, 0.0 )\nv = base.add( NaN, NaN )\n","base.add3":"var v = base.add3( -1.0, 5.0, 2.0 )\nv = base.add3( 2.0, 5.0, 2.0 )\nv = base.add3( 0.0, 5.0, 2.0 )\nv = base.add3( -0.0, 0.0, -0.0 )\nv = base.add3( NaN, NaN, NaN )\n","base.add4":"var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\nv = base.add4( 2.0, 5.0, 2.0, -3.0 )\nv = base.add4( 0.0, 5.0, 2.0, -3.0 )\nv = base.add4( -0.0, 0.0, -0.0, -0.0 )\nv = base.add4( NaN, NaN, NaN, NaN )\n","base.add5":"var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\nv = base.add5( NaN, NaN, NaN, NaN, NaN )\n","base.addf":"var v = base.addf( -1.0, 5.0 )\nv = base.addf( 2.0, 5.0 )\nv = base.addf( 0.0, 5.0 )\nv = base.addf( -0.0, 0.0 )\nv = base.addf( NaN, NaN )\n","base.ahavercos":"var y = base.ahavercos( 0.5 )\ny = base.ahavercos( 0.0 )\n","base.ahaversin":"var y = base.ahaversin( 0.5 )\ny = base.ahaversin( 0.0 )\n","base.asec":"var y = base.asec( 1.0 )\ny = base.asec( 2.0 )\ny = base.asec( NaN )\n","base.asech":"var y = base.asech( 1.0 )\ny = base.asech( 0.5 )\ny = base.asech( NaN )\n","base.asin":"var y = base.asin( 0.0 )\ny = base.asin( -PI/6.0 )\ny = base.asin( NaN )\n","base.asinh":"var y = base.asinh( 0.0 )\ny = base.asinh( 2.0 )\ny = base.asinh( -2.0 )\ny = base.asinh( NaN )\ny = base.asinh( NINF )\ny = base.asinh( PINF )\n","base.atan":"var y = base.atan( 0.0 )\ny = base.atan( -PI/2.0 )\ny = base.atan( PI/2.0 )\ny = base.atan( NaN )\n","base.atan2":"var v = base.atan2( 2.0, 2.0 )\nv = base.atan2( 6.0, 2.0 )\nv = base.atan2( -1.0, -1.0 )\nv = base.atan2( 3.0, 0.0 )\nv = base.atan2( -2.0, 0.0 )\nv = base.atan2( 0.0, 0.0 )\nv = base.atan2( 3.0, NaN )\nv = base.atan2( NaN, 2.0 )\n","base.atanh":"var y = base.atanh( 0.0 )\ny = base.atanh( 0.9 )\ny = base.atanh( 1.0 )\ny = base.atanh( -1.0 )\ny = base.atanh( NaN )\n","base.avercos":"var y = base.avercos( -1.5 )\ny = base.avercos( -0.0 )\n","base.aversin":"var y = base.aversin( 1.5 )\ny = base.aversin( 0.0 )\n","base.bernoulli":"var y = base.bernoulli( 0 )\ny = base.bernoulli( 1 )\ny = base.bernoulli( 2 )\ny = base.bernoulli( 3 )\ny = base.bernoulli( 4 )\ny = base.bernoulli( 5 )\ny = base.bernoulli( 20 )\ny = base.bernoulli( 260 )\ny = base.bernoulli( 262 )\ny = base.bernoulli( NaN )\n","base.besselj0":"var y = base.besselj0( 0.0 )\ny = base.besselj0( 1.0 )\ny = base.besselj0( PINF )\ny = base.besselj0( NINF )\ny = base.besselj0( NaN )\n","base.besselj1":"var y = base.besselj1( 0.0 )\ny = base.besselj1( 1.0 )\ny = base.besselj1( PINF )\ny = base.besselj1( NINF )\ny = base.besselj1( NaN )\n","base.bessely0":"var y = base.bessely0( 0.0 )\ny = base.bessely0( 1.0 )\ny = base.bessely0( -1.0 )\ny = base.bessely0( PINF )\ny = base.bessely0( NINF )\ny = base.bessely0( NaN )\n","base.bessely1":"var y = base.bessely1( 0.0 )\ny = base.bessely1( 1.0 )\ny = base.bessely1( -1.0 )\ny = base.bessely1( PINF )\ny = base.bessely1( NINF )\ny = base.bessely1( NaN )\n","base.beta":"var v = base.beta( 0.0, 0.5 )\nv = base.beta( 1.0, 1.0 )\nv = base.beta( -1.0, 2.0 )\nv = base.beta( 5.0, 0.2 )\nv = base.beta( 4.0, 1.0 )\nv = base.beta( NaN, 2.0 )\n","base.betainc":"var y = base.betainc( 0.5, 2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, 2.0, false )\ny = base.betainc( 0.2, 1.0, 2.0 )\ny = base.betainc( 0.2, 1.0, 2.0, true, true )\ny = base.betainc( NaN, 1.0, 1.0 )\ny = base.betainc( 0.8, NaN, 1.0 )\ny = base.betainc( 0.8, 1.0, NaN )\ny = base.betainc( 1.5, 1.0, 1.0 )\ny = base.betainc( -0.5, 1.0, 1.0 )\ny = base.betainc( 0.5, -2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, -2.0 )\n","base.betaincinv":"var y = base.betaincinv( 0.2, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0, true )\ny = base.betaincinv( 0.4, 1.0, 6.0 )\ny = base.betaincinv( 0.8, 1.0, 6.0 )\ny = base.betaincinv( NaN, 1.0, 1.0 )\ny = base.betaincinv( 0.5, NaN, 1.0 )\ny = base.betaincinv( 0.5, 1.0, NaN )\ny = base.betaincinv( 1.2, 1.0, 1.0 )\ny = base.betaincinv( -0.5, 1.0, 1.0 )\ny = base.betaincinv( 0.5, -2.0, 2.0 )\ny = base.betaincinv( 0.5, 0.0, 2.0 )\ny = base.betaincinv( 0.5, 2.0, -2.0 )\ny = base.betaincinv( 0.5, 2.0, 0.0 )\n","base.betaln":"var v = base.betaln( 0.0, 0.0 )\nv = base.betaln( 1.0, 1.0 )\nv = base.betaln( -1.0, 2.0 )\nv = base.betaln( 5.0, 0.2 )\nv = base.betaln( 4.0, 1.0 )\nv = base.betaln( NaN, 2.0 )\n","base.binet":"var y = base.binet( 0.0 )\ny = base.binet( 1.0 )\ny = base.binet( 2.0 )\ny = base.binet( 3.0 )\ny = base.binet( 4.0 )\ny = base.binet( 5.0 )\ny = base.binet( NaN )\n","base.binomcoef":"var v = base.binomcoef( 8, 2 )\nv = base.binomcoef( 0, 0 )\nv = base.binomcoef( -4, 2 )\nv = base.binomcoef( 5, 3 )\nv = base.binomcoef( NaN, 3 )\nv = base.binomcoef( 5, NaN )\nv = base.binomcoef( NaN, NaN )\n","base.binomcoefln":"var v = base.binomcoefln( 8, 2 )\nv = base.binomcoefln( 0, 0 )\nv = base.binomcoefln( -4, 2 )\nv = base.binomcoefln( 88, 3 )\nv = base.binomcoefln( NaN, 3 )\nv = base.binomcoefln( 5, NaN )\nv = base.binomcoefln( NaN, NaN )\n","base.boxcox":"var v = base.boxcox( 1.0, 2.5 )\nv = base.boxcox( 4.0, 2.5 )\nv = base.boxcox( 10.0, 2.5 )\nv = base.boxcox( 2.0, 0.0 )\nv = base.boxcox( -1.0, 2.5 )\nv = base.boxcox( 0.0, -1.0 )\n","base.boxcox1p":"var v = base.boxcox1p( 1.0, 2.5 )\nv = base.boxcox1p( 4.0, 2.5 )\nv = base.boxcox1p( 10.0, 2.5 )\nv = base.boxcox1p( 2.0, 0.0 )\nv = base.boxcox1p( -1.0, 2.5 )\nv = base.boxcox1p( 0.0, -1.0 )\nv = base.boxcox1p( -1.0, -1.0 )\n","base.boxcox1pinv":"var v = base.boxcox1pinv( 1.0, 2.5 )\nv = base.boxcox1pinv( 4.0, 2.5 )\nv = base.boxcox1pinv( 10.0, 2.5 )\nv = base.boxcox1pinv( 2.0, 0.0 )\nv = base.boxcox1pinv( -1.0, 2.5 )\nv = base.boxcox1pinv( 0.0, -1.0 )\nv = base.boxcox1pinv( 1.0, NaN )\nv = base.boxcox1pinv( NaN, 3.1 )\n","base.boxcoxinv":"var v = base.boxcoxinv( 1.0, 2.5 )\nv = base.boxcoxinv( 4.0, 2.5 )\nv = base.boxcoxinv( 10.0, 2.5 )\nv = base.boxcoxinv( 2.0, 0.0 )\nv = base.boxcoxinv( -1.0, 2.5 )\nv = base.boxcoxinv( 0.0, -1.0 )\nv = base.boxcoxinv( 1.0, NaN )\nv = base.boxcoxinv( NaN, 3.1 )\n","base.cabs":"var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n","base.cabs2":"var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n","base.cabs2f":"var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n","base.cabsf":"var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n","base.cadd":"var z = new Complex128( 5.0, 3.0 )\nvar out = base.cadd( z, z )\nvar re = real( out )\nvar im = imag( out )\n","base.caddf":"var z = new Complex64( 5.0, 3.0 )\nvar out = base.caddf( z, z )\nvar re = realf( out )\nvar im = imagf( out )\n","base.cbrt":"var y = base.cbrt( 64.0 )\ny = base.cbrt( 27.0 )\ny = base.cbrt( 0.0 )\ny = base.cbrt( -0.0 )\ny = base.cbrt( -9.0 )\ny = base.cbrt( NaN )\n","base.cbrtf":"var y = base.cbrtf( 64.0 )\ny = base.cbrtf( 27.0 )\ny = base.cbrtf( 0.0 )\ny = base.cbrtf( -0.0 )\ny = base.cbrtf( -9.0 )\ny = base.cbrtf( NaN )\n","base.cceil":"var v = base.cceil( new Complex128( -1.5, 2.5 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.cceilf":"var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.cceiln":"var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\nvar re = real( out )\nvar im = imag( out )\n","base.ccis":"var y = base.ccis( new Complex128( 0.0, 0.0 ) )\nvar re = real( y )\nvar im = imag( y )\ny = base.ccis( new Complex128( 1.0, 0.0 ) )\nre = real( y )\nim = imag( y )\n","base.cdiv":"var z1 = new Complex128( -13.0, -1.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar y = base.cdiv( z1, z2 )\nvar re = real( y )\nvar im = imag( y )\n","base.ceil":"var y = base.ceil( 3.14 )\ny = base.ceil( -4.2 )\ny = base.ceil( -4.6 )\ny = base.ceil( 9.5 )\ny = base.ceil( -0.0 )\n","base.ceil2":"var y = base.ceil2( 3.14 )\ny = base.ceil2( -4.2 )\ny = base.ceil2( -4.6 )\ny = base.ceil2( 9.5 )\ny = base.ceil2( 13.0 )\ny = base.ceil2( -13.0 )\ny = base.ceil2( -0.0 )\n","base.ceil10":"var y = base.ceil10( 3.14 )\ny = base.ceil10( -4.2 )\ny = base.ceil10( -4.6 )\ny = base.ceil10( 9.5 )\ny = base.ceil10( 13.0 )\ny = base.ceil10( -13.0 )\ny = base.ceil10( -0.0 )\n","base.ceilb":"var y = base.ceilb( 3.14159, -4, 10 )\ny = base.ceilb( 3.14159, 0, 2 )\ny = base.ceilb( 5.0, 1, 2 )\n","base.ceilf":"var y = base.ceilf( 3.14 )\ny = base.ceilf( -4.2 )\ny = base.ceilf( -4.6 )\ny = base.ceilf( 9.5 )\ny = base.ceilf( -0.0 )\n","base.ceiln":"var y = base.ceiln( 3.14159, -2 )\ny = base.ceiln( 3.14159, 0 )\ny = base.ceiln( 12368.0, 3 )\n","base.ceilsd":"var y = base.ceilsd( 3.14159, 5 )\ny = base.ceilsd( 3.14159, 1 )\ny = base.ceilsd( 12368.0, 2 )\ny = base.ceilsd( 0.0313, 2, 2 )\n","base.cexp":"var y = base.cexp( new Complex128( 0.0, 0.0 ) )\nvar re = real( y )\nvar im = imag( y )\ny = base.cexp( new Complex128( 0.0, 1.0 ) )\nre = real( y )\nim = imag( y )\n","base.cflipsign":"var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\nvar re = real( v )\nvar im = imag( v )\n","base.cflipsignf":"var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\nvar re = real( v )\nvar im = imag( v )\n","base.cfloor":"var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.cfloorn":"var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\nvar re = real( v )\nvar im = imag( v )\n","base.cidentity":"var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\nvar re = real( v )\nvar img = imag( v )\n","base.cidentityf":"var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\nvar re = real( v )\nvar img = imag( v )\n","base.cinv":"var v = base.cinv( new Complex128( 2.0, 4.0 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.clamp":"var y = base.clamp( 3.14, 0.0, 5.0 )\ny = base.clamp( -3.14, 0.0, 5.0 )\ny = base.clamp( 3.14, 0.0, 3.0 )\ny = base.clamp( -0.0, 0.0, 5.0 )\ny = base.clamp( 0.0, -3.14, -0.0 )\ny = base.clamp( NaN, 0.0, 5.0 )\n","base.clampf":"var y = base.clampf( 3.14, 0.0, 5.0 )\ny = base.clampf( -3.14, 0.0, 5.0 )\ny = base.clampf( 3.14, 0.0, 3.0 )\ny = base.clampf( -0.0, 0.0, 5.0 )\ny = base.clampf( 0.0, -3.14, -0.0 )\ny = base.clampf( NaN, 0.0, 5.0 )\n","base.cmul":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.cmul( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.cmulf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.cmulf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.cneg":"var z = new Complex128( -4.2, 5.5 )\nvar v = base.cneg( z )\nvar re = real( v )\nvar im = imag( v )\n","base.cnegf":"var z = new Complex64( -4.0, 5.0 )\nvar v = base.cnegf( z )\nvar re = realf( v )\nvar im = imagf( v )\n","base.continuedFraction":"function closure() {\nvar i = 0;\nreturn function() {\n i += 1;\n return [ i, i ];\n};\n };\nvar gen = closure();\nvar out = base.continuedFraction( gen )\nfunction* generator() {\n var i = 0;\n while ( true ) {\n i += 1;\n yield [ i, i ];\n }\n };\ngen = generator();\nout = base.continuedFraction( gen )\nout = base.continuedFraction( generator(), { 'keep': true } )\nout = base.continuedFraction( generator(), { 'maxIter': 10 } )\nout = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n","base.copysign":"var z = base.copysign( -3.14, 10.0 )\nz = base.copysign( 3.14, -1.0 )\nz = base.copysign( 1.0, -0.0 )\nz = base.copysign( -3.14, -0.0 )\nz = base.copysign( -0.0, 1.0 )\n","base.copysignf":"var z = base.copysignf( -3.0, 10.0 )\nz = base.copysignf( 3.0, -1.0 )\nz = base.copysignf( 1.0, -0.0 )\nz = base.copysignf( -3.0, -0.0 )\nz = base.copysignf( -0.0, 1.0 )\n","base.cos":"var y = base.cos( 0.0 )\ny = base.cos( PI/4.0 )\ny = base.cos( -PI/6.0 )\ny = base.cos( NaN )\n","base.cosh":"var y = base.cosh( 0.0 )\ny = base.cosh( 2.0 )\ny = base.cosh( -2.0 )\ny = base.cosh( NaN )\n","base.cosm1":"var y = base.cosm1( 0.0 )\ny = base.cosm1( PI/4.0 )\ny = base.cosm1( -PI/6.0 )\ny = base.cosm1( NaN )\n","base.cospi":"var y = base.cospi( 0.0 )\ny = base.cospi( 0.5 )\ny = base.cospi( 0.1 )\ny = base.cospi( NaN )\n","base.cot":"var y = base.cot( 0.0 )\ny = base.cot( -PI/4.0 )\ny = base.cot( PI/4.0 )\ny = base.cot( NaN )\n","base.coth":"var y = base.coth( 0.0 )\ny = base.coth( -0.0 )\ny = base.coth( 2.0 )\ny = base.coth( -2.0 )\ny = base.coth( +Infinity )\ny = base.coth( -Infinity )\ny = base.coth( NaN )\n","base.covercos":"var y = base.covercos( 3.14 )\ny = base.covercos( -4.2 )\ny = base.covercos( -4.6 )\ny = base.covercos( 9.5 )\ny = base.covercos( -0.0 )\n","base.coversin":"var y = base.coversin( 3.14 )\ny = base.coversin( -4.2 )\ny = base.coversin( -4.6 )\ny = base.coversin( 9.5 )\ny = base.coversin( -0.0 )\n","base.cphase":"var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n","base.cpolar":"var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n","base.cpolar.assign":"var out = new Float64Array( 2 );\nvar v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\nvar bool = ( v === out )\n","base.cround":"var v = base.cround( new Complex128( 5.5, 3.3 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.croundn":"var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\nvar re = real( v )\nvar im = imag( v )\n","base.csch":"var y = base.csch( +0.0 )\nvar y = base.csch( -0.0 )\nvar y = base.csch( +Infinity )\nvar y = base.csch( -Infinity )\ny = base.csch( 2.0 )\ny = base.csch( -2.0 )\ny = base.csch( NaN )\n","base.csignum":"var v = base.csignum( new Complex128( -4.2, 5.5 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.csub":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.csub( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.csubf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.csubf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.deg2rad":"var r = base.deg2rad( 90.0 )\nr = base.deg2rad( -45.0 )\nr = base.deg2rad( NaN )\n","base.deg2radf":"var r = base.deg2radf( 90.0 )\nr = base.deg2radf( -45.0 )\nr = base.deg2radf( NaN )\n","base.digamma":"var y = base.digamma( -2.5 )\ny = base.digamma( 1.0 )\ny = base.digamma( 10.0 )\ny = base.digamma( NaN )\ny = base.digamma( -1.0 )\n","base.diracDelta":"var y = base.diracDelta( 3.14 )\ny = base.diracDelta( 0.0 )\n","base.div":"var v = base.div( -1.0, 5.0 )\nv = base.div( 2.0, 5.0 )\nv = base.div( 0.0, 5.0 )\nv = base.div( -0.0, 5.0 )\nv = base.div( NaN, NaN )\n","base.divf":"var v = base.divf( -1.0, 5.0 )\nv = base.divf( 2.0, 5.0 )\nv = base.divf( 0.0, 5.0 )\nv = base.divf( -0.0, 5.0 )\nv = base.divf( NaN, NaN )\n","base.dists.arcsine.Arcsine":"var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\narcsine.a\narcsine.b\narcsine.entropy\narcsine.kurtosis\narcsine.mean\narcsine.median\narcsine.mode\narcsine.skewness\narcsine.stdev\narcsine.variance\narcsine.cdf( 0.8 )\narcsine.logcdf( 0.8 )\narcsine.logpdf( 0.4 )\narcsine.pdf( 0.8 )\narcsine.quantile( 0.8 )\n","base.dists.arcsine.cdf":"var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n","base.dists.arcsine.cdf.factory":"var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.arcsine.entropy":"var v = base.dists.arcsine.entropy( 0.0, 1.0 )\nv = base.dists.arcsine.entropy( 4.0, 12.0 )\nv = base.dists.arcsine.entropy( 2.0, 8.0 )\n","base.dists.arcsine.kurtosis":"var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\nv = base.dists.arcsine.kurtosis( 4.0, 12.0 )\nv = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n","base.dists.arcsine.logcdf":"var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.arcsine.logcdf.factory":"var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.arcsine.logpdf":"var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.logpdf.factory":"var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 7.0 )\ny = mylogPDF( 5.0 )\n","base.dists.arcsine.mean":"var v = base.dists.arcsine.mean( 0.0, 1.0 )\nv = base.dists.arcsine.mean( 4.0, 12.0 )\nv = base.dists.arcsine.mean( 2.0, 8.0 )\n","base.dists.arcsine.median":"var v = base.dists.arcsine.median( 0.0, 1.0 )\nv = base.dists.arcsine.median( 4.0, 12.0 )\nv = base.dists.arcsine.median( 2.0, 8.0 )\n","base.dists.arcsine.mode":"var v = base.dists.arcsine.mode( 0.0, 1.0 )\nv = base.dists.arcsine.mode( 4.0, 12.0 )\nv = base.dists.arcsine.mode( 2.0, 8.0 )\n","base.dists.arcsine.pdf":"var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.pdf.factory":"var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.arcsine.quantile":"var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\ny = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n","base.dists.arcsine.quantile.factory":"var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.arcsine.skewness":"var v = base.dists.arcsine.skewness( 0.0, 1.0 )\nv = base.dists.arcsine.skewness( 4.0, 12.0 )\nv = base.dists.arcsine.skewness( 2.0, 8.0 )\n","base.dists.arcsine.stdev":"var v = base.dists.arcsine.stdev( 0.0, 1.0 )\nv = base.dists.arcsine.stdev( 4.0, 12.0 )\nv = base.dists.arcsine.stdev( 2.0, 8.0 )\n","base.dists.arcsine.variance":"var v = base.dists.arcsine.variance( 0.0, 1.0 )\nv = base.dists.arcsine.variance( 4.0, 12.0 )\nv = base.dists.arcsine.variance( 2.0, 8.0 )\n","base.dists.bernoulli.Bernoulli":"var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\nbernoulli.p\nbernoulli.entropy\nbernoulli.kurtosis\nbernoulli.mean\nbernoulli.median\nbernoulli.skewness\nbernoulli.stdev\nbernoulli.variance\nbernoulli.cdf( 0.5 )\nbernoulli.mgf( 3.0 )\nbernoulli.pmf( 0.0 )\nbernoulli.quantile( 0.7 )\n","base.dists.bernoulli.cdf":"var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\ny = base.dists.bernoulli.cdf( 0.8, 0.1 )\ny = base.dists.bernoulli.cdf( -1.0, 0.4 )\ny = base.dists.bernoulli.cdf( 1.5, 0.4 )\ny = base.dists.bernoulli.cdf( NaN, 0.5 )\ny = base.dists.bernoulli.cdf( 0.0, NaN )\ny = base.dists.bernoulli.cdf( 2.0, 1.4 )\n","base.dists.bernoulli.cdf.factory":"var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 0.7 )\n","base.dists.bernoulli.entropy":"var v = base.dists.bernoulli.entropy( 0.1 )\nv = base.dists.bernoulli.entropy( 0.5 )\n","base.dists.bernoulli.kurtosis":"var v = base.dists.bernoulli.kurtosis( 0.1 )\nv = base.dists.bernoulli.kurtosis( 0.5 )\n","base.dists.bernoulli.mean":"var v = base.dists.bernoulli.mean( 0.1 )\nv = base.dists.bernoulli.mean( 0.5 )\n","base.dists.bernoulli.median":"var v = base.dists.bernoulli.median( 0.1 )\nv = base.dists.bernoulli.median( 0.8 )\n","base.dists.bernoulli.mgf":"var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\ny = base.dists.bernoulli.mgf( 0.4, 0.5 )\ny = base.dists.bernoulli.mgf( NaN, 0.0 )\ny = base.dists.bernoulli.mgf( 0.0, NaN )\ny = base.dists.bernoulli.mgf( -2.0, -1.0 )\ny = base.dists.bernoulli.mgf( 0.2, 2.0 )\n","base.dists.bernoulli.mgf.factory":"var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.bernoulli.mode":"var v = base.dists.bernoulli.mode( 0.1 )\nv = base.dists.bernoulli.mode( 0.8 )\n","base.dists.bernoulli.pmf":"var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\ny = base.dists.bernoulli.pmf( 0.0, 0.7 )\ny = base.dists.bernoulli.pmf( -1.0, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, NaN )\ny = base.dists.bernoulli.pmf( NaN, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, 1.5 )\n","base.dists.bernoulli.pmf.factory":"var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\nvar y = mypmf( 1.0 )\ny = mypmf( 0.0 )\n","base.dists.bernoulli.quantile":"var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\ny = base.dists.bernoulli.quantile( 0.5, 0.4 )\ny = base.dists.bernoulli.quantile( 0.9, 0.1 )\ny = base.dists.bernoulli.quantile( -0.2, 0.1 )\ny = base.dists.bernoulli.quantile( NaN, 0.8 )\ny = base.dists.bernoulli.quantile( 0.4, NaN )\ny = base.dists.bernoulli.quantile( 0.5, -1.0 )\ny = base.dists.bernoulli.quantile( 0.5, 1.5 )\n","base.dists.bernoulli.quantile.factory":"var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.bernoulli.skewness":"var v = base.dists.bernoulli.skewness( 0.1 )\nv = base.dists.bernoulli.skewness( 0.5 )\n","base.dists.bernoulli.stdev":"var v = base.dists.bernoulli.stdev( 0.1 )\nv = base.dists.bernoulli.stdev( 0.5 )\n","base.dists.bernoulli.variance":"var v = base.dists.bernoulli.variance( 0.1 )\nv = base.dists.bernoulli.variance( 0.5 )\n","base.dists.beta.Beta":"var beta = base.dists.beta.Beta( 1.0, 1.0 );\nbeta.alpha\nbeta.beta\nbeta.entropy\nbeta.kurtosis\nbeta.mean\nbeta.median\nbeta.mode\nbeta.skewness\nbeta.stdev\nbeta.variance\nbeta.cdf( 0.8 )\nbeta.logcdf( 0.8 )\nbeta.logpdf( 1.0 )\nbeta.mgf( 3.14 )\nbeta.pdf( 1.0 )\nbeta.quantile( 0.8 )\n","base.dists.beta.cdf":"var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.cdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.cdf( 0.0, 1.0, NaN )\n","base.dists.beta.cdf.factory":"var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.beta.entropy":"var v = base.dists.beta.entropy( 1.0, 1.0 )\nv = base.dists.beta.entropy( 4.0, 12.0 )\nv = base.dists.beta.entropy( 8.0, 2.0 )\nv = base.dists.beta.entropy( 1.0, -0.1 )\nv = base.dists.beta.entropy( -0.1, 1.0 )\nv = base.dists.beta.entropy( 2.0, NaN )\nv = base.dists.beta.entropy( NaN, 2.0 )\n","base.dists.beta.kurtosis":"var v = base.dists.beta.kurtosis( 1.0, 1.0 )\nv = base.dists.beta.kurtosis( 4.0, 12.0 )\nv = base.dists.beta.kurtosis( 8.0, 2.0 )\nv = base.dists.beta.kurtosis( 1.0, -0.1 )\nv = base.dists.beta.kurtosis( -0.1, 1.0 )\nv = base.dists.beta.kurtosis( 2.0, NaN )\nv = base.dists.beta.kurtosis( NaN, 2.0 )\n","base.dists.beta.logcdf":"var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n","base.dists.beta.logcdf.factory":"var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.beta.logpdf":"var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n","base.dists.beta.logpdf.factory":"var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.beta.mean":"var v = base.dists.beta.mean( 1.0, 1.0 )\nv = base.dists.beta.mean( 4.0, 12.0 )\nv = base.dists.beta.mean( 8.0, 2.0 )\n","base.dists.beta.median":"var v = base.dists.beta.median( 1.0, 1.0 )\nv = base.dists.beta.median( 4.0, 12.0 )\nv = base.dists.beta.median( 8.0, 2.0 )\nv = base.dists.beta.median( 1.0, -0.1 )\nv = base.dists.beta.median( -0.1, 1.0 )\nv = base.dists.beta.median( 2.0, NaN )\nv = base.dists.beta.median( NaN, 2.0 )\n","base.dists.beta.mgf":"var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\ny = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\ny = base.dists.beta.mgf( NaN, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.0, NaN, 1.0 )\ny = base.dists.beta.mgf( 0.0, 1.0, NaN )\ny = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n","base.dists.beta.mgf.factory":"var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.3 )\n","base.dists.beta.mode":"var v = base.dists.beta.mode( 4.0, 12.0 )\nv = base.dists.beta.mode( 8.0, 2.0 )\nv = base.dists.beta.mode( 1.0, 1.0 )\n","base.dists.beta.pdf":"var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.pdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.pdf( 0.5, 1.0, NaN )\n","base.dists.beta.pdf.factory":"var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.beta.quantile":"var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.beta.quantile( NaN, 1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, NaN, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, NaN )\ny = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n","base.dists.beta.quantile.factory":"var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\ny = myquantile( 0.8 )\ny = myquantile( 0.4 )\n","base.dists.beta.skewness":"var v = base.dists.beta.skewness( 1.0, 1.0 )\nv = base.dists.beta.skewness( 4.0, 12.0 )\nv = base.dists.beta.skewness( 8.0, 2.0 )\nv = base.dists.beta.skewness( 1.0, -0.1 )\nv = base.dists.beta.skewness( -0.1, 1.0 )\nv = base.dists.beta.skewness( 2.0, NaN )\nv = base.dists.beta.skewness( NaN, 2.0 )\n","base.dists.beta.stdev":"var v = base.dists.beta.stdev( 1.0, 1.0 )\nv = base.dists.beta.stdev( 4.0, 12.0 )\nv = base.dists.beta.stdev( 8.0, 2.0 )\nv = base.dists.beta.stdev( 1.0, -0.1 )\nv = base.dists.beta.stdev( -0.1, 1.0 )\nv = base.dists.beta.stdev( 2.0, NaN )\nv = base.dists.beta.stdev( NaN, 2.0 )\n","base.dists.beta.variance":"var v = base.dists.beta.variance( 1.0, 1.0 )\nv = base.dists.beta.variance( 4.0, 12.0 )\nv = base.dists.beta.variance( 8.0, 2.0 )\nv = base.dists.beta.variance( 1.0, -0.1 )\nv = base.dists.beta.variance( -0.1, 1.0 )\nv = base.dists.beta.variance( 2.0, NaN )\nv = base.dists.beta.variance( NaN, 2.0 )\n","base.dists.betaprime.BetaPrime":"var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\nbetaprime.alpha\nbetaprime.beta\nbetaprime.kurtosis\nbetaprime.mean\nbetaprime.mode\nbetaprime.skewness\nbetaprime.stdev\nbetaprime.variance\nbetaprime.cdf( 0.8 )\nbetaprime.logcdf( 0.8 )\nbetaprime.logpdf( 1.0 )\nbetaprime.pdf( 1.0 )\nbetaprime.quantile( 0.8 )\n","base.dists.betaprime.cdf":"var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.cdf.factory":"var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.betaprime.kurtosis":"var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 4.0, 12.0 )\nv = base.dists.betaprime.kurtosis( 8.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 1.0, 2.8 )\nv = base.dists.betaprime.kurtosis( 1.0, -0.1 )\nv = base.dists.betaprime.kurtosis( -0.1, 5.0 )\nv = base.dists.betaprime.kurtosis( 2.0, NaN )\nv = base.dists.betaprime.kurtosis( NaN, 6.0 )\n","base.dists.betaprime.logcdf":"var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.logcdf.factory":"var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.betaprime.logpdf":"var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.logpdf.factory":"var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.betaprime.mean":"var v = base.dists.betaprime.mean( 1.0, 2.0 )\nv = base.dists.betaprime.mean( 4.0, 12.0 )\nv = base.dists.betaprime.mean( 8.0, 2.0 )\n","base.dists.betaprime.mode":"var v = base.dists.betaprime.mode( 1.0, 2.0 )\nv = base.dists.betaprime.mode( 4.0, 12.0 )\nv = base.dists.betaprime.mode( 8.0, 2.0 )\n","base.dists.betaprime.pdf":"var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.pdf.factory":"var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.betaprime.quantile":"var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\ny = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n","base.dists.betaprime.quantile.factory":"var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\ny = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.betaprime.skewness":"var v = base.dists.betaprime.skewness( 2.0, 4.0 )\nv = base.dists.betaprime.skewness( 4.0, 12.0 )\nv = base.dists.betaprime.skewness( 8.0, 4.0 )\nv = base.dists.betaprime.skewness( 1.0, 2.8 )\nv = base.dists.betaprime.skewness( 1.0, -0.1 )\nv = base.dists.betaprime.skewness( -0.1, 4.0 )\nv = base.dists.betaprime.skewness( 2.0, NaN )\nv = base.dists.betaprime.skewness( NaN, 4.0 )\n","base.dists.betaprime.stdev":"var v = base.dists.betaprime.stdev( 1.0, 2.5 )\nv = base.dists.betaprime.stdev( 4.0, 12.0 )\nv = base.dists.betaprime.stdev( 8.0, 2.5 )\nv = base.dists.betaprime.stdev( 8.0, 1.0 )\nv = base.dists.betaprime.stdev( 1.0, -0.1 )\nv = base.dists.betaprime.stdev( -0.1, 3.0 )\nv = base.dists.betaprime.stdev( 2.0, NaN )\nv = base.dists.betaprime.stdev( NaN, 3.0 )\n","base.dists.betaprime.variance":"var v = base.dists.betaprime.variance( 1.0, 2.5 )\nv = base.dists.betaprime.variance( 4.0, 12.0 )\nv = base.dists.betaprime.variance( 8.0, 2.5 )\nv = base.dists.betaprime.variance( 8.0, 1.0 )\nv = base.dists.betaprime.variance( 1.0, -0.1 )\nv = base.dists.betaprime.variance( -0.1, 3.0 )\nv = base.dists.betaprime.variance( 2.0, NaN )\nv = base.dists.betaprime.variance( NaN, 3.0 )\n","base.dists.binomial.Binomial":"var binomial = base.dists.binomial.Binomial( 8, 0.5 );\nbinomial.n\nbinomial.p\nbinomial.kurtosis\nbinomial.mean\nbinomial.median\nbinomial.mode\nbinomial.skewness\nbinomial.stdev\nbinomial.variance\nbinomial.cdf( 2.9 )\nbinomial.logpmf( 3.0 )\nbinomial.mgf( 0.2 )\nbinomial.pmf( 3.0 )\nbinomial.quantile( 0.8 )\n","base.dists.binomial.cdf":"var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 21.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 5.0, 10, 0.4 )\ny = base.dists.binomial.cdf( 0.0, 10, 0.4 )\ny = base.dists.binomial.cdf( NaN, 20, 0.5 )\ny = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.cdf( 0.0, 20, NaN )\ny = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n","base.dists.binomial.cdf.factory":"var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.binomial.entropy":"var v = base.dists.binomial.entropy( 100, 0.1 )\nv = base.dists.binomial.entropy( 20, 0.5 )\nv = base.dists.binomial.entropy( 10.3, 0.5 )\nv = base.dists.binomial.entropy( 20, 1.1 )\nv = base.dists.binomial.entropy( 20, NaN )\n","base.dists.binomial.kurtosis":"var v = base.dists.binomial.kurtosis( 100, 0.1 )\nv = base.dists.binomial.kurtosis( 20, 0.5 )\nv = base.dists.binomial.kurtosis( 10.3, 0.5 )\nv = base.dists.binomial.kurtosis( 20, 1.1 )\nv = base.dists.binomial.kurtosis( 20, NaN )\n","base.dists.binomial.logpmf":"var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( NaN, 20, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, 20, NaN )\ny = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n","base.dists.binomial.logpmf.factory":"var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 5.0 )\n","base.dists.binomial.mean":"var v = base.dists.binomial.mean( 100, 0.1 )\nv = base.dists.binomial.mean( 20, 0.5 )\nv = base.dists.binomial.mean( 10.3, 0.5 )\nv = base.dists.binomial.mean( 20, 1.1 )\nv = base.dists.binomial.mean( 20, NaN )\n","base.dists.binomial.median":"var v = base.dists.binomial.median( 100, 0.1 )\nv = base.dists.binomial.median( 20, 0.5 )\nv = base.dists.binomial.median( 10.3, 0.5 )\nv = base.dists.binomial.median( 20, 1.1 )\nv = base.dists.binomial.median( 20, NaN )\n","base.dists.binomial.mgf":"var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\ny = base.dists.binomial.mgf( 5.0, 20, 0.2 )\ny = base.dists.binomial.mgf( 0.9, 10, 0.4 )\ny = base.dists.binomial.mgf( 0.0, 10, 0.4 )\ny = base.dists.binomial.mgf( NaN, 20, 0.5 )\ny = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.mgf( 0.0, 20, NaN )\ny = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.mgf( 2.0, 20, -1.0 )\ny = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n","base.dists.binomial.mgf.factory":"var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\nvar y = myMGF( 0.3 )\n","base.dists.binomial.mode":"var v = base.dists.binomial.mode( 100, 0.1 )\nv = base.dists.binomial.mode( 20, 0.5 )\nv = base.dists.binomial.mode( 10.3, 0.5 )\nv = base.dists.binomial.mode( 20, 1.1 )\nv = base.dists.binomial.mode( 20, NaN )\n","base.dists.binomial.pmf":"var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.pmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.pmf( NaN, 20, 0.5 )\ny = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.pmf( 0.0, 20, NaN )\ny = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n","base.dists.binomial.pmf.factory":"var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 5.0 )\n","base.dists.binomial.quantile":"var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.8, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.5, 10, 0.4 )\ny = base.dists.binomial.quantile( 0.0, 10, 0.4 )\ny = base.dists.binomial.quantile( 1.0, 10, 0.4 )\ny = base.dists.binomial.quantile( NaN, 20, 0.5 )\ny = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\ny = base.dists.binomial.quantile( 0.2, 20, NaN )\ny = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\ny = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.binomial.quantile( 0.5, 20, -1.0 )\ny = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n","base.dists.binomial.quantile.factory":"var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\nvar y = myquantile( 0.1 )\ny = myquantile( 0.9 )\n","base.dists.binomial.skewness":"var v = base.dists.binomial.skewness( 100, 0.1 )\nv = base.dists.binomial.skewness( 20, 0.5 )\nv = base.dists.binomial.skewness( 10.3, 0.5 )\nv = base.dists.binomial.skewness( 20, 1.1 )\nv = base.dists.binomial.skewness( 20, NaN )\n","base.dists.binomial.stdev":"var v = base.dists.binomial.stdev( 100, 0.1 )\nv = base.dists.binomial.stdev( 20, 0.5 )\nv = base.dists.binomial.stdev( 10.3, 0.5 )\nv = base.dists.binomial.stdev( 20, 1.1 )\nv = base.dists.binomial.stdev( 20, NaN )\n","base.dists.binomial.variance":"var v = base.dists.binomial.variance( 100, 0.1 )\nv = base.dists.binomial.variance( 20, 0.5 )\nv = base.dists.binomial.variance( 10.3, 0.5 )\nv = base.dists.binomial.variance( 20, 1.1 )\nv = base.dists.binomial.variance( 20, NaN )\n","base.dists.cauchy.Cauchy":"var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\ncauchy.x0\ncauchy.gamma\ncauchy.entropy\ncauchy.median\ncauchy.mode\ncauchy.cdf( 0.8 )\ncauchy.logcdf( 1.0 )\ncauchy.logpdf( 1.0 )\ncauchy.pdf( 1.0 )\ncauchy.quantile( 0.8 )\n","base.dists.cauchy.cdf":"var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.cdf.factory":"var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\nvar y = myCDF( 1.0 )\n","base.dists.cauchy.entropy":"var v = base.dists.cauchy.entropy( 10.0, 7.0 )\nv = base.dists.cauchy.entropy( 22.0, 0.5 )\nv = base.dists.cauchy.entropy( 10.3, -0.5 )\n","base.dists.cauchy.logcdf":"var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.logcdf.factory":"var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\nvar y = mylogCDF( 1.0 )\n","base.dists.cauchy.logpdf":"var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.logpdf.factory":"var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.cauchy.median":"var v = base.dists.cauchy.median( 10.0, 5.0 )\nv = base.dists.cauchy.median( 7.0, 0.5 )\nv = base.dists.cauchy.median( 10.3, -0.5 )\n","base.dists.cauchy.mode":"var v = base.dists.cauchy.mode( 10.0, 5.0 )\nv = base.dists.cauchy.mode( 7.0, 0.5 )\nv = base.dists.cauchy.mode( 10.3, -0.5 )\n","base.dists.cauchy.pdf":"var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.pdf.factory":"var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.cauchy.quantile":"var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\ny = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\ny = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\ny = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\ny = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cauchy.quantile.factory":"var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.chi.cdf":"var y = base.dists.chi.cdf( 2.0, 3.0 )\ny = base.dists.chi.cdf( 1.0, 0.5 )\ny = base.dists.chi.cdf( -1.0, 4.0 )\ny = base.dists.chi.cdf( NaN, 1.0 )\ny = base.dists.chi.cdf( 0.0, NaN )\ny = base.dists.chi.cdf( 2.0, -1.0 )\ny = base.dists.chi.cdf( 2.0, 0.0 )\ny = base.dists.chi.cdf( -2.0, 0.0 )\ny = base.dists.chi.cdf( 0.0, 0.0 )\n","base.dists.chi.cdf.factory":"var mycdf = base.dists.chi.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chi.Chi":"var chi = base.dists.chi.Chi( 6.0 );\nchi.k\nchi.entropy\nchi.kurtosis\nchi.mean\nchi.mode\nchi.skewness\nchi.stdev\nchi.variance\nchi.cdf( 1.0 )\nchi.logpdf( 1.5 )\nchi.pdf( 1.5 )\nchi.quantile( 0.5 )\n","base.dists.chi.entropy":"var v = base.dists.chi.entropy( 11.0 )\nv = base.dists.chi.entropy( 1.5 )\n","base.dists.chi.kurtosis":"var v = base.dists.chi.kurtosis( 9.0 )\nv = base.dists.chi.kurtosis( 1.5 )\n","base.dists.chi.logpdf":"var y = base.dists.chi.logpdf( 0.3, 4.0 )\ny = base.dists.chi.logpdf( 0.7, 0.7 )\ny = base.dists.chi.logpdf( -1.0, 0.5 )\ny = base.dists.chi.logpdf( 0.0, NaN )\ny = base.dists.chi.logpdf( NaN, 2.0 )\ny = base.dists.chi.logpdf( 2.0, -1.0 )\ny = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.logpdf.factory":"var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\nvar y = mylogPDF( 3.0 )\n","base.dists.chi.mean":"var v = base.dists.chi.mean( 11.0 )\nv = base.dists.chi.mean( 4.5 )\n","base.dists.chi.mode":"var v = base.dists.chi.mode( 11.0 )\nv = base.dists.chi.mode( 1.5 )\n","base.dists.chi.pdf":"var y = base.dists.chi.pdf( 0.3, 4.0 )\ny = base.dists.chi.pdf( 0.7, 0.7 )\ny = base.dists.chi.pdf( -1.0, 0.5 )\ny = base.dists.chi.pdf( 0.0, NaN )\ny = base.dists.chi.pdf( NaN, 2.0 )\ny = base.dists.chi.pdf( 2.0, -1.0 )\ny = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.pdf.factory":"var myPDF = base.dists.chi.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chi.quantile":"var y = base.dists.chi.quantile( 0.8, 1.0 )\ny = base.dists.chi.quantile( 0.5, 4.0 )\ny = base.dists.chi.quantile( 0.8, 0.1 )\ny = base.dists.chi.quantile( -0.2, 0.5 )\ny = base.dists.chi.quantile( 1.1, 0.5 )\ny = base.dists.chi.quantile( NaN, 1.0 )\ny = base.dists.chi.quantile( 0.0, NaN )\ny = base.dists.chi.quantile( 0.5, -1.0 )\ny = base.dists.chi.quantile( 0.3, 0.0 )\ny = base.dists.chi.quantile( 0.9, 0.0 )\n","base.dists.chi.quantile.factory":"var myquantile = base.dists.chi.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chi.skewness":"var v = base.dists.chi.skewness( 11.0 )\nv = base.dists.chi.skewness( 1.5 )\n","base.dists.chi.stdev":"var v = base.dists.chi.stdev( 11.0 )\nv = base.dists.chi.stdev( 1.5 )\n","base.dists.chi.variance":"var v = base.dists.chi.variance( 11.0 )\nv = base.dists.chi.variance( 1.5 )\n","base.dists.chisquare.cdf":"var y = base.dists.chisquare.cdf( 2.0, 3.0 )\ny = base.dists.chisquare.cdf( 1.0, 0.5 )\ny = base.dists.chisquare.cdf( -1.0, 4.0 )\ny = base.dists.chisquare.cdf( NaN, 1.0 )\ny = base.dists.chisquare.cdf( 0.0, NaN )\ny = base.dists.chisquare.cdf( 2.0, -1.0 )\ny = base.dists.chisquare.cdf( 2.0, 0.0 )\ny = base.dists.chisquare.cdf( -2.0, 0.0 )\ny = base.dists.chisquare.cdf( 0.0, 0.0 )\n","base.dists.chisquare.cdf.factory":"var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chisquare.ChiSquare":"var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\nchisquare.k\nchisquare.entropy\nchisquare.kurtosis\nchisquare.mean\nchisquare.median\nchisquare.mode\nchisquare.skewness\nchisquare.stdev\nchisquare.variance\nchisquare.cdf( 3.0 )\nchisquare.mgf( 0.2 )\nchisquare.pdf( 1.5 )\nchisquare.quantile( 0.5 )\n","base.dists.chisquare.entropy":"var v = base.dists.chisquare.entropy( 11.0 )\nv = base.dists.chisquare.entropy( 1.5 )\n","base.dists.chisquare.kurtosis":"var v = base.dists.chisquare.kurtosis( 9.0 )\nv = base.dists.chisquare.kurtosis( 1.5 )\n","base.dists.chisquare.logpdf":"var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\ny = base.dists.chisquare.logpdf( 0.7, 0.7 )\ny = base.dists.chisquare.logpdf( -1.0, 0.5 )\ny = base.dists.chisquare.logpdf( 0.0, NaN )\ny = base.dists.chisquare.logpdf( NaN, 2.0 )\ny = base.dists.chisquare.logpdf( 2.0, -1.0 )\ny = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.logpdf.factory":"var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\nvar y = myLogPDF( 3.0 )\n","base.dists.chisquare.mean":"var v = base.dists.chisquare.mean( 11.0 )\nv = base.dists.chisquare.mean( 4.5 )\n","base.dists.chisquare.median":"var k = base.dists.chisquare.median( 9.0 )\nk = base.dists.chisquare.median( 2.0 )\n","base.dists.chisquare.mgf":"var y = base.dists.chisquare.mgf( 0.4, 2 )\ny = base.dists.chisquare.mgf( -1.0, 5.0 )\ny = base.dists.chisquare.mgf( 0.0, 10.0 )\n","base.dists.chisquare.mgf.factory":"var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\nvar y = mymgf( 0.2 )\ny = mymgf( 0.4 )\n","base.dists.chisquare.mode":"var v = base.dists.chisquare.mode( 11.0 )\nv = base.dists.chisquare.mode( 1.5 )\n","base.dists.chisquare.pdf":"var y = base.dists.chisquare.pdf( 0.3, 4.0 )\ny = base.dists.chisquare.pdf( 0.7, 0.7 )\ny = base.dists.chisquare.pdf( -1.0, 0.5 )\ny = base.dists.chisquare.pdf( 0.0, NaN )\ny = base.dists.chisquare.pdf( NaN, 2.0 )\ny = base.dists.chisquare.pdf( 2.0, -1.0 )\ny = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.pdf.factory":"var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chisquare.quantile":"var y = base.dists.chisquare.quantile( 0.8, 1.0 )\ny = base.dists.chisquare.quantile( 0.5, 4.0 )\ny = base.dists.chisquare.quantile( 0.8, 0.1 )\ny = base.dists.chisquare.quantile( -0.2, 0.5 )\ny = base.dists.chisquare.quantile( 1.1, 0.5 )\ny = base.dists.chisquare.quantile( NaN, 1.0 )\ny = base.dists.chisquare.quantile( 0.0, NaN )\ny = base.dists.chisquare.quantile( 0.5, -1.0 )\ny = base.dists.chisquare.quantile( 0.3, 0.0 )\ny = base.dists.chisquare.quantile( 0.9, 0.0 )\n","base.dists.chisquare.quantile.factory":"var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chisquare.skewness":"var v = base.dists.chisquare.skewness( 11.0 )\nv = base.dists.chisquare.skewness( 1.5 )\n","base.dists.chisquare.stdev":"var v = base.dists.chisquare.stdev( 11.0 )\nv = base.dists.chisquare.stdev( 1.5 )\n","base.dists.chisquare.variance":"var v = base.dists.chisquare.variance( 11.0 )\nv = base.dists.chisquare.variance( 1.5 )\n","base.dists.cosine.cdf":"var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.cdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.cdf.factory":"var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\nvar y = mycdf( 1.9 )\n","base.dists.cosine.Cosine":"var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\ncosine.mu\ncosine.s\ncosine.kurtosis\ncosine.mean\ncosine.median\ncosine.mode\ncosine.skewness\ncosine.stdev\ncosine.variance\ncosine.cdf( 0.5 )\ncosine.logcdf( 0.5 )\ncosine.logpdf( -1.0 )\ncosine.mgf( 0.2 )\ncosine.pdf( -2.0 )\ncosine.quantile( 0.9 )\n","base.dists.cosine.kurtosis":"var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\ny = base.dists.cosine.kurtosis( 4.0, 2.0 )\ny = base.dists.cosine.kurtosis( NaN, 1.0 )\ny = base.dists.cosine.kurtosis( 0.0, NaN )\ny = base.dists.cosine.kurtosis( 0.0, 0.0 )\n","base.dists.cosine.logcdf":"var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.logcdf.factory":"var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\nvar y = mylogcdf( 1.9 )\n","base.dists.cosine.logpdf":"var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\ny = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.logpdf.factory":"var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\n","base.dists.cosine.mean":"var y = base.dists.cosine.mean( 0.0, 1.0 )\ny = base.dists.cosine.mean( 4.0, 2.0 )\ny = base.dists.cosine.mean( NaN, 1.0 )\ny = base.dists.cosine.mean( 0.0, NaN )\ny = base.dists.cosine.mean( 0.0, 0.0 )\n","base.dists.cosine.median":"var y = base.dists.cosine.median( 0.0, 1.0 )\ny = base.dists.cosine.median( 4.0, 2.0 )\ny = base.dists.cosine.median( NaN, 1.0 )\ny = base.dists.cosine.median( 0.0, NaN )\ny = base.dists.cosine.median( 0.0, 0.0 )\n","base.dists.cosine.mgf":"var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.mgf( 0.5, 0.0, NaN )\ny = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\ny = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n","base.dists.cosine.mgf.factory":"var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\nvar y = mymgf( 1.9 )\n","base.dists.cosine.mode":"var y = base.dists.cosine.mode( 0.0, 1.0 )\ny = base.dists.cosine.mode( 4.0, 2.0 )\ny = base.dists.cosine.mode( NaN, 1.0 )\ny = base.dists.cosine.mode( 0.0, NaN )\ny = base.dists.cosine.mode( 0.0, 0.0 )\n","base.dists.cosine.pdf":"var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\ny = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.pdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.pdf.factory":"var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\nvar y = myPDF( 2.0 )\n","base.dists.cosine.quantile":"var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cosine.quantile( 0.0, 0.0, NaN )\ny = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cosine.quantile.factory":"var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.3 )\n","base.dists.cosine.skewness":"var y = base.dists.cosine.skewness( 0.0, 1.0 )\ny = base.dists.cosine.skewness( 4.0, 2.0 )\ny = base.dists.cosine.skewness( NaN, 1.0 )\ny = base.dists.cosine.skewness( 0.0, NaN )\ny = base.dists.cosine.skewness( 0.0, 0.0 )\n","base.dists.cosine.stdev":"var y = base.dists.cosine.stdev( 0.0, 1.0 )\ny = base.dists.cosine.stdev( 4.0, 2.0 )\ny = base.dists.cosine.stdev( NaN, 1.0 )\ny = base.dists.cosine.stdev( 0.0, NaN )\ny = base.dists.cosine.stdev( 0.0, 0.0 )\n","base.dists.cosine.variance":"var y = base.dists.cosine.variance( 0.0, 1.0 )\ny = base.dists.cosine.variance( 4.0, 2.0 )\ny = base.dists.cosine.variance( NaN, 1.0 )\ny = base.dists.cosine.variance( 0.0, NaN )\ny = base.dists.cosine.variance( 0.0, 0.0 )\n","base.dists.degenerate.cdf":"var y = base.dists.degenerate.cdf( 2.0, 3.0 )\ny = base.dists.degenerate.cdf( 4.0, 3.0 )\ny = base.dists.degenerate.cdf( 3.0, 3.0 )\ny = base.dists.degenerate.cdf( NaN, 0.0 )\ny = base.dists.degenerate.cdf( 0.0, NaN )\n","base.dists.degenerate.cdf.factory":"var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 6.0 )\n","base.dists.degenerate.Degenerate":"var degenerate = base.dists.degenerate.Degenerate( 2.0 );\ndegenerate.mu\ndegenerate.entropy\ndegenerate.mean\ndegenerate.mode\ndegenerate.median\ndegenerate.stdev\ndegenerate.variance\ndegenerate.cdf( 0.5 )\ndegenerate.logcdf( 2.5 )\ndegenerate.logpdf( 0.5 )\ndegenerate.logpmf( 2.5 )\ndegenerate.mgf( 0.2 )\ndegenerate.pdf( 2.0 )\ndegenerate.pmf( 2.0 )\ndegenerate.quantile( 0.7 )\n","base.dists.degenerate.entropy":"var v = base.dists.degenerate.entropy( 20.0 )\nv = base.dists.degenerate.entropy( -10.0 )\n","base.dists.degenerate.logcdf":"var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\ny = base.dists.degenerate.logcdf( 4.0, 3.0 )\ny = base.dists.degenerate.logcdf( 3.0, 3.0 )\ny = base.dists.degenerate.logcdf( NaN, 0.0 )\ny = base.dists.degenerate.logcdf( 0.0, NaN )\n","base.dists.degenerate.logcdf.factory":"var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 6.0 )\n","base.dists.degenerate.logpdf":"var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\ny = base.dists.degenerate.logpdf( 3.0, 3.0 )\ny = base.dists.degenerate.logpdf( NaN, 0.0 )\ny = base.dists.degenerate.logpdf( 0.0, NaN )\n","base.dists.degenerate.logpdf.factory":"var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.degenerate.logpmf":"var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\ny = base.dists.degenerate.logpmf( 3.0, 3.0 )\ny = base.dists.degenerate.logpmf( NaN, 0.0 )\ny = base.dists.degenerate.logpmf( 0.0, NaN )\n","base.dists.degenerate.logpmf.factory":"var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\nvar y = mylogPMF( 10.0 )\n","base.dists.degenerate.mean":"var v = base.dists.degenerate.mean( 20.0 )\nv = base.dists.degenerate.mean( -10.0 )\n","base.dists.degenerate.median":"var v = base.dists.degenerate.median( 20.0 )\nv = base.dists.degenerate.median( -10.0 )\n","base.dists.degenerate.mgf":"var y = base.dists.degenerate.mgf( 1.0, 1.0 )\ny = base.dists.degenerate.mgf( 2.0, 3.0 )\ny = base.dists.degenerate.mgf( NaN, 0.0 )\ny = base.dists.degenerate.mgf( 0.0, NaN )\n","base.dists.degenerate.mgf.factory":"var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\nvar y = myMGF( 0.1 )\n","base.dists.degenerate.mode":"var v = base.dists.degenerate.mode( 20.0 )\nv = base.dists.degenerate.mode( -10.0 )\n","base.dists.degenerate.pdf":"var y = base.dists.degenerate.pdf( 2.0, 3.0 )\ny = base.dists.degenerate.pdf( 3.0, 3.0 )\ny = base.dists.degenerate.pdf( NaN, 0.0 )\ny = base.dists.degenerate.pdf( 0.0, NaN )\n","base.dists.degenerate.pdf.factory":"var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\nvar y = myPDF( 10.0 )\n","base.dists.degenerate.pmf":"var y = base.dists.degenerate.pmf( 2.0, 3.0 )\ny = base.dists.degenerate.pmf( 3.0, 3.0 )\ny = base.dists.degenerate.pmf( NaN, 0.0 )\ny = base.dists.degenerate.pmf( 0.0, NaN )\n","base.dists.degenerate.pmf.factory":"var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\nvar y = myPMF( 10.0 )\n","base.dists.degenerate.quantile":"var y = base.dists.degenerate.quantile( 0.5, 2.0 )\ny = base.dists.degenerate.quantile( 0.9, 4.0 )\ny = base.dists.degenerate.quantile( 1.1, 0.0 )\ny = base.dists.degenerate.quantile( -0.2, 0.0 )\ny = base.dists.degenerate.quantile( NaN, 0.0 )\ny = base.dists.degenerate.quantile( 0.0, NaN )\n","base.dists.degenerate.quantile.factory":"var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.degenerate.stdev":"var v = base.dists.degenerate.stdev( 20.0 )\nv = base.dists.degenerate.stdev( -10.0 )\n","base.dists.degenerate.variance":"var v = base.dists.degenerate.variance( 20.0 )\nv = base.dists.degenerate.variance( -10.0 )\n","base.dists.discreteUniform.cdf":"var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.cdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n","base.dists.discreteUniform.cdf.factory":"var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.discreteUniform.DiscreteUniform":"var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\ndiscreteUniform.a\ndiscreteUniform.b\ndiscreteUniform.entropy\ndiscreteUniform.kurtosis\ndiscreteUniform.mean\ndiscreteUniform.median\ndiscreteUniform.skewness\ndiscreteUniform.stdev\ndiscreteUniform.variance\ndiscreteUniform.cdf( 0.8 )\ndiscreteUniform.logcdf( 0.5 )\ndiscreteUniform.logpmf( 1.0 )\ndiscreteUniform.mgf( 0.8 )\ndiscreteUniform.pmf( 0.0 )\ndiscreteUniform.quantile( 0.8 )\n","base.dists.discreteUniform.kurtosis":"var v = base.dists.discreteUniform.kurtosis( 0, 1 )\nv = base.dists.discreteUniform.kurtosis( 4, 12 )\nv = base.dists.discreteUniform.kurtosis( -4, 8 )\n","base.dists.discreteUniform.logcdf":"var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n","base.dists.discreteUniform.logcdf.factory":"var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\nvar y = myLogCDF( 0.5 )\ny = myLogCDF( 8.0 )\n","base.dists.discreteUniform.logpmf":"var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.logpmf.factory":"var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\nvar y = myLogPMF( 7.0 )\ny = myLogPMF( 5.0 )\n","base.dists.discreteUniform.mean":"var v = base.dists.discreteUniform.mean( -2, 2 )\nv = base.dists.discreteUniform.mean( 4, 12 )\nv = base.dists.discreteUniform.mean( 2, 8 )\n","base.dists.discreteUniform.median":"var v = base.dists.discreteUniform.median( -2, 2 )\nv = base.dists.discreteUniform.median( 4, 12 )\nv = base.dists.discreteUniform.median( 2, 8 )\n","base.dists.discreteUniform.mgf":"var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\ny = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\ny = base.dists.discreteUniform.mgf( NaN, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n","base.dists.discreteUniform.mgf.factory":"var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.discreteUniform.pmf":"var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.pmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.pmf.factory":"var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\nvar y = myPMF( 7.0 )\ny = myPMF( 5.0 )\n","base.dists.discreteUniform.quantile":"var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\ny = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\ny = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\ny = base.dists.discreteUniform.quantile( NaN, -2, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\ny = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n","base.dists.discreteUniform.quantile.factory":"var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\nvar y = myQuantile( 0.8 )\n","base.dists.discreteUniform.skewness":"var v = base.dists.discreteUniform.skewness( -2, 2 )\nv = base.dists.discreteUniform.skewness( 4, 12 )\nv = base.dists.discreteUniform.skewness( 2, 8 )\n","base.dists.discreteUniform.stdev":"var v = base.dists.discreteUniform.stdev( 0, 1 )\nv = base.dists.discreteUniform.stdev( 4, 12 )\nv = base.dists.discreteUniform.stdev( 2, 8 )\n","base.dists.discreteUniform.variance":"var v = base.dists.discreteUniform.variance( 0, 1 )\nv = base.dists.discreteUniform.variance( 4, 12 )\nv = base.dists.discreteUniform.variance( 2, 8 )\n","base.dists.erlang.cdf":"var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 3, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\ny = base.dists.erlang.cdf( -1.0, 2, 2.0 )\ny = base.dists.erlang.cdf( PINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NaN, 0, 1.0 )\ny = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.cdf( 0.0, 0, NaN )\ny = base.dists.erlang.cdf( 2.0, -1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n","base.dists.erlang.cdf.factory":"var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\nvar y = mycdf( 6.0 )\ny = mycdf( 2.0 )\n","base.dists.erlang.entropy":"var v = base.dists.erlang.entropy( 1, 1.0 )\nv = base.dists.erlang.entropy( 4, 12.0 )\nv = base.dists.erlang.entropy( 8, 2.0 )\n","base.dists.erlang.Erlang":"var erlang = base.dists.erlang.Erlang( 6, 5.0 );\nerlang.k\nerlang.lambda\nerlang.entropy\nerlang.kurtosis\nerlang.mean\nerlang.mode\nerlang.skewness\nerlang.stdev\nerlang.variance\nerlang.cdf( 3.0 )\nerlang.logpdf( 3.0 )\nerlang.mgf( -0.5 )\nerlang.pdf( 3.0 )\nerlang.quantile( 0.8 )\n","base.dists.erlang.kurtosis":"var v = base.dists.erlang.kurtosis( 1, 1.0 )\nv = base.dists.erlang.kurtosis( 4, 12.0 )\nv = base.dists.erlang.kurtosis( 8, 2.0 )\n","base.dists.erlang.logpdf":"var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.logpdf( NaN, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, 1, NaN )\ny = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n","base.dists.erlang.logpdf.factory":"var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\ny = myLogPDF( 7.0 )\n","base.dists.erlang.mean":"var v = base.dists.erlang.mean( 1, 1.0 )\nv = base.dists.erlang.mean( 4, 12.0 )\nv = base.dists.erlang.mean( 8, 2.0 )\n","base.dists.erlang.mgf":"var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\ny = base.dists.erlang.mgf( 2.0, 2, 3.0 )\ny = base.dists.erlang.mgf( -1.0, 2, 2.0 )\ny = base.dists.erlang.mgf( NaN, 1, 1.0 )\ny = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.mgf( 0.0, 1, NaN )\ny = base.dists.erlang.mgf( 0.2, -2, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 1, 0.0 )\ny = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n","base.dists.erlang.mgf.factory":"var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\nvar y = myMGF( 0.2 )\ny = myMGF( -0.5 )\n","base.dists.erlang.mode":"var v = base.dists.erlang.mode( 1, 1.0 )\nv = base.dists.erlang.mode( 4, 12.0 )\nv = base.dists.erlang.mode( 8, 2.0 )\n","base.dists.erlang.pdf":"var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.pdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.pdf( NaN, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.pdf( 0.0, 1, NaN )\ny = base.dists.erlang.pdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n","base.dists.erlang.pdf.factory":"var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\ny = myPDF( 7.0 )\n","base.dists.erlang.quantile":"var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 4, 2.0 )\ny = base.dists.erlang.quantile( 1.1, 1, 1.0 )\ny = base.dists.erlang.quantile( -0.2, 1, 1.0 )\ny = base.dists.erlang.quantile( NaN, 1, 1.0 )\ny = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\ny = base.dists.erlang.quantile( 0.0, 1, NaN )\ny = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\ny = base.dists.erlang.quantile( 0.5, -1, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n","base.dists.erlang.quantile.factory":"var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.erlang.skewness":"var v = base.dists.erlang.skewness( 1, 1.0 )\nv = base.dists.erlang.skewness( 4, 12.0 )\nv = base.dists.erlang.skewness( 8, 2.0 )\n","base.dists.erlang.stdev":"var v = base.dists.erlang.stdev( 1, 1.0 )\nv = base.dists.erlang.stdev( 4, 12.0 )\nv = base.dists.erlang.stdev( 8, 2.0 )\n","base.dists.erlang.variance":"var v = base.dists.erlang.variance( 1, 1.0 )\nv = base.dists.erlang.variance( 4, 12.0 )\nv = base.dists.erlang.variance( 8, 2.0 )\n","base.dists.exponential.cdf":"var y = base.dists.exponential.cdf( 2.0, 0.1 )\ny = base.dists.exponential.cdf( 1.0, 2.0 )\ny = base.dists.exponential.cdf( -1.0, 4.0 )\ny = base.dists.exponential.cdf( NaN, 1.0 )\ny = base.dists.exponential.cdf( 0.0, NaN )\ny = base.dists.exponential.cdf( 2.0, -1.0 )\n","base.dists.exponential.cdf.factory":"var myCDF = base.dists.exponential.cdf.factory( 0.5 );\nvar y = myCDF( 3.0 )\n","base.dists.exponential.entropy":"var v = base.dists.exponential.entropy( 11.0 )\nv = base.dists.exponential.entropy( 4.5 )\n","base.dists.exponential.Exponential":"var exponential = base.dists.exponential.Exponential( 6.0 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0.3, 4.0 )\ny = base.dists.exponential.logpdf( 2.0, 0.7 )\ny = base.dists.exponential.logpdf( -1.0, 0.5 )\ny = base.dists.exponential.logpdf( 0, NaN )\ny = base.dists.exponential.logpdf( NaN, 2.0 )\ny = base.dists.exponential.logpdf( 2.0, -1.0 )\n","base.dists.exponential.logpdf.factory":"var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\nvar y = mylogpdf( 3.0 )\n","base.dists.exponential.mean":"var v = base.dists.exponential.mean( 11.0 )\nv = base.dists.exponential.mean( 4.5 )\n","base.dists.exponential.median":"var v = base.dists.exponential.median( 11.0 )\nv = base.dists.exponential.median( 4.5 )\n","base.dists.exponential.mgf":"var v = base.dists.exponential.mgf( 2.0, 3.0 )\nv = base.dists.exponential.mgf( 0.4, 1.2 )\nv = base.dists.exponential.mgf( 0.8, 1.6 )\nv = base.dists.exponential.mgf( 4.0, 3.0 )\nv = base.dists.exponential.mgf( NaN, 3.0 )\nv = base.dists.exponential.mgf( 2.0, NaN )\n","base.dists.exponential.mgf.factory":"var myMGF = base.dists.exponential.mgf.factory( 4.0 );\nvar y = myMGF( 3.0 )\ny = myMGF( 0.5 )\n","base.dists.exponential.mode":"var v = base.dists.exponential.mode( 11.0 )\nv = base.dists.exponential.mode( 4.5 )\n","base.dists.exponential.pdf":"var y = base.dists.exponential.pdf( 0.3, 4.0 )\ny = base.dists.exponential.pdf( 2.0, 0.7 )\ny = base.dists.exponential.pdf( -1.0, 0.5 )\ny = base.dists.exponential.pdf( 0, NaN )\ny = base.dists.exponential.pdf( NaN, 2.0 )\ny = base.dists.exponential.pdf( 2.0, -1.0 )\n","base.dists.exponential.pdf.factory":"var myPDF = base.dists.exponential.pdf.factory( 0.5 );\nvar y = myPDF( 3.0 )\n","base.dists.exponential.quantile":"var y = base.dists.exponential.quantile( 0.8, 1.0 )\ny = base.dists.exponential.quantile( 0.5, 4.0 )\ny = base.dists.exponential.quantile( 0.5, 0.1 )\ny = base.dists.exponential.quantile( -0.2, 0.1 )\ny = base.dists.exponential.quantile( NaN, 1.0 )\ny = base.dists.exponential.quantile( 0.0, NaN )\ny = base.dists.exponential.quantile( 0.5, -1.0 )\n","base.dists.exponential.quantile.factory":"var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.exponential.skewness":"var v = base.dists.exponential.skewness( 11.0 )\nv = base.dists.exponential.skewness( 4.5 )\n","base.dists.exponential.stdev":"var v = base.dists.exponential.stdev( 9.0 )\nv = base.dists.exponential.stdev( 1.0 )\n","base.dists.exponential.variance":"var v = base.dists.exponential.variance( 9.0 )\nv = base.dists.exponential.variance( 1.0 )\n","base.dists.f.cdf":"var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\nvar y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\nvar y = base.dists.f.cdf( PINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NaN, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 0.0, NaN, 1.0 )\nvar y = base.dists.f.cdf( 0.0, 1.0, NaN )\nvar y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\nvar y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n","base.dists.f.cdf.factory":"var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 8.0 )\n","base.dists.f.entropy":"var v = base.dists.f.entropy( 3.0, 7.0 )\nv = base.dists.f.entropy( 4.0, 12.0 )\nv = base.dists.f.entropy( 8.0, 2.0 )\n","base.dists.f.F":"var f = base.dists.f.F( 6.0, 9.0 );\nf.d1\nf.d2\nf.entropy\nf.kurtosis\nf.mean\nf.mode\nf.skewness\nf.stdev\nf.variance\nf.cdf( 3.0 )\nf.pdf( 2.5 )\nf.quantile( 0.8 )\n","base.dists.f.kurtosis":"var v = base.dists.f.kurtosis( 3.0, 9.0 )\nv = base.dists.f.kurtosis( 4.0, 12.0 )\nv = base.dists.f.kurtosis( 8.0, 9.0 )\n","base.dists.f.mean":"var v = base.dists.f.mean( 3.0, 5.0 )\nv = base.dists.f.mean( 4.0, 12.0 )\nv = base.dists.f.mean( 8.0, 4.0 )\n","base.dists.f.mode":"var v = base.dists.f.mode( 3.0, 5.0 )\nv = base.dists.f.mode( 4.0, 12.0 )\nv = base.dists.f.mode( 8.0, 4.0 )\n","base.dists.f.pdf":"var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.f.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.f.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.f.pdf( NaN, 1.0, 1.0 )\ny = base.dists.f.pdf( 0.0, NaN, 1.0 )\ny = base.dists.f.pdf( 0.0, 1.0, NaN )\ny = base.dists.f.pdf( 2.0, 1.0, -1.0 )\ny = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n","base.dists.f.pdf.factory":"var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 2.0 )\n","base.dists.f.quantile":"var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.f.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.f.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.f.quantile( NaN, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, NaN, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, NaN )\ny = base.dists.f.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n","base.dists.f.quantile.factory":"var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.f.skewness":"var v = base.dists.f.skewness( 3.0, 7.0 )\nv = base.dists.f.skewness( 4.0, 12.0 )\nv = base.dists.f.skewness( 8.0, 7.0 )\n","base.dists.f.stdev":"var v = base.dists.f.stdev( 3.0, 5.0 )\nv = base.dists.f.stdev( 4.0, 12.0 )\nv = base.dists.f.stdev( 8.0, 5.0 )\n","base.dists.f.variance":"var v = base.dists.f.variance( 3.0, 5.0 )\nv = base.dists.f.variance( 4.0, 12.0 )\nv = base.dists.f.variance( 8.0, 5.0 )\n","base.dists.frechet.cdf":"var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.cdf.factory":"var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 7.0 )\n","base.dists.frechet.entropy":"var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\ny = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\ny = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\ny = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n","base.dists.frechet.Frechet":"var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\nfrechet.alpha\nfrechet.s\nfrechet.m\nfrechet.entropy\nfrechet.kurtosis\nfrechet.mean\nfrechet.median\nfrechet.mode\nfrechet.skewness\nfrechet.stdev\nfrechet.variance\nfrechet.cdf( 0.8 )\nfrechet.logcdf( 0.8 )\nfrechet.logpdf( 0.8 )\nfrechet.pdf( 0.8 )\nfrechet.quantile( 0.8 )\n","base.dists.frechet.kurtosis":"var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\nvar y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\ny = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\ny = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n","base.dists.frechet.logcdf":"var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.logcdf.factory":"var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 7.0 )\n","base.dists.frechet.logpdf":"var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\ny = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\ny = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\ny = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\ny = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n","base.dists.frechet.logpdf.factory":"var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\nvar y = mylogPDF( 10.0 )\ny = mylogPDF( 2.0 )\n","base.dists.frechet.mean":"var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mean( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mean( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mean( 1.0, 1.0, NaN )\n","base.dists.frechet.median":"var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.median( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.median( NaN, 1.0, 0.0 )\ny = base.dists.frechet.median( 1.0, NaN, 0.0 )\ny = base.dists.frechet.median( 1.0, 1.0, NaN )\n","base.dists.frechet.mode":"var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mode( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mode( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mode( 1.0, 1.0, NaN )\n","base.dists.frechet.pdf":"var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, NaN )\ny = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n","base.dists.frechet.pdf.factory":"var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.frechet.quantile":"var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\ny = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\ny = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\ny = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\ny = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.quantile.factory":"var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.2 )\n","base.dists.frechet.skewness":"var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\ny = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\ny = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n","base.dists.frechet.stdev":"var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\ny = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\ny = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n","base.dists.frechet.variance":"var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.variance( NaN, 1.0, 0.0 )\ny = base.dists.frechet.variance( 1.0, NaN, 0.0 )\ny = base.dists.frechet.variance( 1.0, 1.0, NaN )\n","base.dists.gamma.cdf":"var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.cdf.factory":"var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 6.0 )\ny = myCDF( 2.0 )\n","base.dists.gamma.entropy":"var v = base.dists.gamma.entropy( 1.0, 1.0 )\nv = base.dists.gamma.entropy( 4.0, 12.0 )\nv = base.dists.gamma.entropy( 8.0, 2.0 )\n","base.dists.gamma.Gamma":"var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\ngamma.alpha\ngamma.beta\ngamma.entropy\ngamma.kurtosis\ngamma.mean\ngamma.mode\ngamma.skewness\ngamma.stdev\ngamma.variance\ngamma.cdf( 0.8 )\ngamma.logcdf( 0.8 )\ngamma.logpdf( 1.0 )\ngamma.mgf( -0.5 )\ngamma.pdf( 1.0 )\ngamma.quantile( 0.8 )\n","base.dists.gamma.kurtosis":"var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\nv = base.dists.gamma.kurtosis( 4.0, 12.0 )\nv = base.dists.gamma.kurtosis( 8.0, 2.0 )\n","base.dists.gamma.logcdf":"var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.logcdf.factory":"var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\nvar y = mylogCDF( 2.0 )\n","base.dists.gamma.logpdf":"var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.logpdf.factory":"var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.gamma.mean":"var v = base.dists.gamma.mean( 1.0, 1.0 )\nv = base.dists.gamma.mean( 4.0, 12.0 )\nv = base.dists.gamma.mean( 8.0, 2.0 )\n","base.dists.gamma.mgf":"var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\ny = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\ny = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.mgf( 0.0, 1.0, NaN )\ny = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\ny = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.mgf.factory":"var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.gamma.mode":"var v = base.dists.gamma.mode( 1.0, 1.0 )\nv = base.dists.gamma.mode( 4.0, 12.0 )\nv = base.dists.gamma.mode( 8.0, 2.0 )\n","base.dists.gamma.pdf":"var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.pdf.factory":"var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 2.0 )\n","base.dists.gamma.quantile":"var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gamma.quantile( 0.0, 1.0, NaN )\ny = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\ny = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\ny = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n","base.dists.gamma.quantile.factory":"var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.gamma.skewness":"var v = base.dists.gamma.skewness( 1.0, 1.0 )\nv = base.dists.gamma.skewness( 4.0, 12.0 )\nv = base.dists.gamma.skewness( 8.0, 2.0 )\n","base.dists.gamma.stdev":"var v = base.dists.gamma.stdev( 1.0, 1.0 )\nv = base.dists.gamma.stdev( 4.0, 12.0 )\nv = base.dists.gamma.stdev( 8.0, 2.0 )\n","base.dists.gamma.variance":"var v = base.dists.gamma.variance( 1.0, 1.0 )\nv = base.dists.gamma.variance( 4.0, 12.0 )\nv = base.dists.gamma.variance( 8.0, 2.0 )\n","base.dists.geometric.cdf":"var y = base.dists.geometric.cdf( 2.0, 0.5 )\ny = base.dists.geometric.cdf( 2.0, 0.1 )\ny = base.dists.geometric.cdf( -1.0, 4.0 )\ny = base.dists.geometric.cdf( NaN, 0.5 )\ny = base.dists.geometric.cdf( 0.0, NaN )\ny = base.dists.geometric.cdf( 2.0, 1.4 )\n","base.dists.geometric.cdf.factory":"var mycdf = base.dists.geometric.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.geometric.entropy":"var v = base.dists.geometric.entropy( 0.1 )\nv = base.dists.geometric.entropy( 0.5 )\n","base.dists.geometric.Geometric":"var geometric = base.dists.geometric.Geometric( 0.6 );\ngeometric.p\ngeometric.entropy\ngeometric.kurtosis\ngeometric.mean\ngeometric.median\ngeometric.mode\ngeometric.skewness\ngeometric.stdev\ngeometric.variance\ngeometric.cdf( 3.0 )\ngeometric.logcdf( 3.0 )\ngeometric.logpmf( 4.0 )\ngeometric.mgf( 0.5 )\ngeometric.pmf( 2.0 )\ngeometric.quantile( 0.7 )\n","base.dists.geometric.kurtosis":"var v = base.dists.geometric.kurtosis( 0.1 )\nv = base.dists.geometric.kurtosis( 0.5 )\n","base.dists.geometric.logcdf":"var y = base.dists.geometric.logcdf( 2.0, 0.5 )\ny = base.dists.geometric.logcdf( 2.0, 0.1 )\ny = base.dists.geometric.logcdf( -1.0, 4.0 )\ny = base.dists.geometric.logcdf( NaN, 0.5 )\ny = base.dists.geometric.logcdf( 0.0, NaN )\ny = base.dists.geometric.logcdf( 2.0, 1.4 )\n","base.dists.geometric.logcdf.factory":"var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 1.0 )\n","base.dists.geometric.logpmf":"var y = base.dists.geometric.logpmf( 4.0, 0.3 )\ny = base.dists.geometric.logpmf( 2.0, 0.7 )\ny = base.dists.geometric.logpmf( -1.0, 0.5 )\ny = base.dists.geometric.logpmf( 0.0, NaN )\ny = base.dists.geometric.logpmf( NaN, 0.5 )\ny = base.dists.geometric.logpmf( 2.0, 1.5 )\n","base.dists.geometric.logpmf.factory":"var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.geometric.mean":"var v = base.dists.geometric.mean( 0.1 )\nv = base.dists.geometric.mean( 0.5 )\n","base.dists.geometric.median":"var v = base.dists.geometric.median( 0.1 )\nv = base.dists.geometric.median( 0.5 )\n","base.dists.geometric.mgf":"var y = base.dists.geometric.mgf( 0.2, 0.5 )\ny = base.dists.geometric.mgf( 0.4, 0.5 )\ny = base.dists.geometric.mgf( 0.8, 0.5 )\ny = base.dists.geometric.mgf( NaN, 0.0 )\ny = base.dists.geometric.mgf( 0.0, NaN )\ny = base.dists.geometric.mgf( -2.0, -1.0 )\ny = base.dists.geometric.mgf( 0.2, 2.0 )\n","base.dists.geometric.mgf.factory":"var mymgf = base.dists.geometric.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.geometric.mode":"var v = base.dists.geometric.mode( 0.1 )\nv = base.dists.geometric.mode( 0.5 )\n","base.dists.geometric.pmf":"var y = base.dists.geometric.pmf( 4.0, 0.3 )\ny = base.dists.geometric.pmf( 2.0, 0.7 )\ny = base.dists.geometric.pmf( -1.0, 0.5 )\ny = base.dists.geometric.pmf( 0.0, NaN )\ny = base.dists.geometric.pmf( NaN, 0.5 )\ny = base.dists.geometric.pmf( 2.0, 1.5 )\n","base.dists.geometric.pmf.factory":"var mypmf = base.dists.geometric.pmf.factory( 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.geometric.quantile":"var y = base.dists.geometric.quantile( 0.8, 0.4 )\ny = base.dists.geometric.quantile( 0.5, 0.4 )\ny = base.dists.geometric.quantile( 0.9, 0.1 )\ny = base.dists.geometric.quantile( -0.2, 0.1 )\ny = base.dists.geometric.quantile( NaN, 0.8 )\ny = base.dists.geometric.quantile( 0.4, NaN )\ny = base.dists.geometric.quantile( 0.5, -1.0 )\ny = base.dists.geometric.quantile( 0.5, 1.5 )\n","base.dists.geometric.quantile.factory":"var myquantile = base.dists.geometric.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.geometric.skewness":"var v = base.dists.geometric.skewness( 0.1 )\nv = base.dists.geometric.skewness( 0.5 )\n","base.dists.geometric.stdev":"var v = base.dists.geometric.stdev( 0.1 )\nv = base.dists.geometric.stdev( 0.5 )\n","base.dists.geometric.variance":"var v = base.dists.geometric.variance( 0.1 )\nv = base.dists.geometric.variance( 0.5 )\n","base.dists.gumbel.cdf":"var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.cdf.factory":"var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.gumbel.entropy":"var y = base.dists.gumbel.entropy( 0.0, 1.0 )\ny = base.dists.gumbel.entropy( 4.0, 2.0 )\ny = base.dists.gumbel.entropy( NaN, 1.0 )\ny = base.dists.gumbel.entropy( 0.0, NaN )\ny = base.dists.gumbel.entropy( 0.0, 0.0 )\n","base.dists.gumbel.Gumbel":"var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\ngumbel.mu\ngumbel.beta\ngumbel.entropy\ngumbel.kurtosis\ngumbel.mean\ngumbel.median\ngumbel.mode\ngumbel.skewness\ngumbel.stdev\ngumbel.variance\ngumbel.cdf( 0.8 )\ngumbel.logcdf( 0.8 )\ngumbel.logpdf( 1.0 )\ngumbel.mgf( 0.2 )\ngumbel.pdf( 1.0 )\ngumbel.quantile( 0.8 )\n","base.dists.gumbel.kurtosis":"var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\ny = base.dists.gumbel.kurtosis( 4.0, 2.0 )\ny = base.dists.gumbel.kurtosis( NaN, 1.0 )\ny = base.dists.gumbel.kurtosis( 0.0, NaN )\ny = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n","base.dists.gumbel.logcdf":"var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.logcdf.factory":"var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\nvar y = myLCDF( 10.0 )\ny = myLCDF( 2.0 )\n","base.dists.gumbel.logpdf":"var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.logpdf.factory":"var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\ny = mylogpdf( 12.0 )\n","base.dists.gumbel.mean":"var y = base.dists.gumbel.mean( 0.0, 1.0 )\ny = base.dists.gumbel.mean( 4.0, 2.0 )\ny = base.dists.gumbel.mean( NaN, 1.0 )\ny = base.dists.gumbel.mean( 0.0, NaN )\ny = base.dists.gumbel.mean( 0.0, 0.0 )\n","base.dists.gumbel.median":"var y = base.dists.gumbel.median( 0.0, 1.0 )\ny = base.dists.gumbel.median( 4.0, 2.0 )\ny = base.dists.gumbel.median( NaN, 1.0 )\ny = base.dists.gumbel.median( 0.0, NaN )\ny = base.dists.gumbel.median( 0.0, 0.0 )\n","base.dists.gumbel.mgf":"var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.mgf.factory":"var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\nvar y = myMGF( -1.5 )\ny = myMGF( -1.0 )\n","base.dists.gumbel.mode":"var y = base.dists.gumbel.mode( 0.0, 1.0 )\ny = base.dists.gumbel.mode( 4.0, 2.0 )\ny = base.dists.gumbel.mode( NaN, 1.0 )\ny = base.dists.gumbel.mode( 0.0, NaN )\ny = base.dists.gumbel.mode( 0.0, 0.0 )\n","base.dists.gumbel.pdf":"var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.pdf.factory":"var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 12.0 )\n","base.dists.gumbel.quantile":"var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\ny = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\ny = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n","base.dists.gumbel.quantile.factory":"var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.7 )\n","base.dists.gumbel.skewness":"var y = base.dists.gumbel.skewness( 0.0, 1.0 )\ny = base.dists.gumbel.skewness( 4.0, 2.0 )\ny = base.dists.gumbel.skewness( NaN, 1.0 )\ny = base.dists.gumbel.skewness( 0.0, NaN )\ny = base.dists.gumbel.skewness( 0.0, 0.0 )\n","base.dists.gumbel.stdev":"var y = base.dists.gumbel.stdev( 0.0, 1.0 )\ny = base.dists.gumbel.stdev( 4.0, 2.0 )\ny = base.dists.gumbel.stdev( NaN, 1.0 )\ny = base.dists.gumbel.stdev( 0.0, NaN )\ny = base.dists.gumbel.stdev( 0.0, 0.0 )\n","base.dists.gumbel.variance":"var y = base.dists.gumbel.variance( 0.0, 1.0 )\ny = base.dists.gumbel.variance( 4.0, 2.0 )\ny = base.dists.gumbel.variance( NaN, 1.0 )\ny = base.dists.gumbel.variance( 0.0, NaN )\ny = base.dists.gumbel.variance( 0.0, 0.0 )\n","base.dists.hypergeometric.cdf":"var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\ny = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.cdf.factory":"var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\nvar y = myCDF( 4.0 )\ny = myCDF( 1.0 )\n","base.dists.hypergeometric.Hypergeometric":"var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\nhypergeometric.N\nhypergeometric.K\nhypergeometric.n\nhypergeometric.kurtosis\nhypergeometric.mean\nhypergeometric.mode\nhypergeometric.skewness\nhypergeometric.stdev\nhypergeometric.variance\nhypergeometric.cdf( 2.9 )\nhypergeometric.logpmf( 10 )\nhypergeometric.pmf( 10 )\nhypergeometric.quantile( 0.8 )\n","base.dists.hypergeometric.kurtosis":"var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\nv = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\nv = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\nv = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n","base.dists.hypergeometric.logpmf":"var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.logpmf.factory":"var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\nvar y = mylogPMF( 4.0 )\ny = mylogPMF( 1.0 )\n","base.dists.hypergeometric.mean":"var v = base.dists.hypergeometric.mean( 16, 11, 4 )\nv = base.dists.hypergeometric.mean( 2, 1, 1 )\nv = base.dists.hypergeometric.mean( 10, 5, 12 )\nv = base.dists.hypergeometric.mean( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mean( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mean( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mean( NaN, 10, 4 )\nv = base.dists.hypergeometric.mean( 20, NaN, 4 )\nv = base.dists.hypergeometric.mean( 20, 10, NaN )\n","base.dists.hypergeometric.mode":"var v = base.dists.hypergeometric.mode( 16, 11, 4 )\nv = base.dists.hypergeometric.mode( 2, 1, 1 )\nv = base.dists.hypergeometric.mode( 10, 5, 12 )\nv = base.dists.hypergeometric.mode( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mode( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mode( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mode( NaN, 10, 4 )\nv = base.dists.hypergeometric.mode( 20, NaN, 4 )\nv = base.dists.hypergeometric.mode( 20, 10, NaN )\n","base.dists.hypergeometric.pmf":"var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.pmf.factory":"var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\nvar y = myPMF( 4.0 )\ny = myPMF( 1.0 )\n","base.dists.hypergeometric.quantile":"var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\ny = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\ny = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n","base.dists.hypergeometric.quantile.factory":"var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.hypergeometric.skewness":"var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\nv = base.dists.hypergeometric.skewness( 4, 2, 2 )\nv = base.dists.hypergeometric.skewness( 10, 5, 12 )\nv = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\nv = base.dists.hypergeometric.skewness( NaN, 10, 4 )\nv = base.dists.hypergeometric.skewness( 20, NaN, 4 )\nv = base.dists.hypergeometric.skewness( 20, 10, NaN )\n","base.dists.hypergeometric.stdev":"var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\nv = base.dists.hypergeometric.stdev( 2, 1, 1 )\nv = base.dists.hypergeometric.stdev( 10, 5, 12 )\nv = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\nv = base.dists.hypergeometric.stdev( NaN, 10, 4 )\nv = base.dists.hypergeometric.stdev( 20, NaN, 4 )\nv = base.dists.hypergeometric.stdev( 20, 10, NaN )\n","base.dists.hypergeometric.variance":"var v = base.dists.hypergeometric.variance( 16, 11, 4 )\nv = base.dists.hypergeometric.variance( 2, 1, 1 )\nv = base.dists.hypergeometric.variance( 10, 5, 12 )\nv = base.dists.hypergeometric.variance( 10.3, 10, 4 )\nv = base.dists.hypergeometric.variance( 10, 5.5, 4 )\nv = base.dists.hypergeometric.variance( 10, 5, 4.5 )\nv = base.dists.hypergeometric.variance( NaN, 10, 4 )\nv = base.dists.hypergeometric.variance( 20, NaN, 4 )\nv = base.dists.hypergeometric.variance( 20, 10, NaN )\n","base.dists.invgamma.cdf":"var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.cdf.factory":"var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 0.5 )\ny = myCDF( 2.0 )\n","base.dists.invgamma.entropy":"var v = base.dists.invgamma.entropy( 1.0, 1.0 )\nv = base.dists.invgamma.entropy( 4.0, 12.0 )\nv = base.dists.invgamma.entropy( 8.0, 2.0 )\n","base.dists.invgamma.InvGamma":"var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\ninvgamma.alpha\ninvgamma.beta\ninvgamma.entropy\ninvgamma.kurtosis\ninvgamma.mean\ninvgamma.mode\ninvgamma.skewness\ninvgamma.stdev\ninvgamma.variance\ninvgamma.cdf( 0.8 )\ninvgamma.pdf( 1.0 )\ninvgamma.logpdf( 1.0 )\ninvgamma.quantile( 0.8 )\n","base.dists.invgamma.kurtosis":"var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\nv = base.dists.invgamma.kurtosis( 6.0, 12.0 )\nv = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n","base.dists.invgamma.logpdf":"var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.logpdf.factory":"var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.invgamma.mean":"var v = base.dists.invgamma.mean( 4.0, 12.0 )\nv = base.dists.invgamma.mean( 8.0, 2.0 )\n","base.dists.invgamma.mode":"var v = base.dists.invgamma.mode( 1.0, 1.0 )\nv = base.dists.invgamma.mode( 4.0, 12.0 )\nv = base.dists.invgamma.mode( 8.0, 2.0 )\n","base.dists.invgamma.pdf":"var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.pdf.factory":"var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 2.0 )\n","base.dists.invgamma.quantile":"var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\ny = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n","base.dists.invgamma.quantile.factory":"var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.invgamma.skewness":"var v = base.dists.invgamma.skewness( 4.0, 12.0 )\nv = base.dists.invgamma.skewness( 8.0, 2.0 )\n","base.dists.invgamma.stdev":"var v = base.dists.invgamma.stdev( 5.0, 7.0 )\nv = base.dists.invgamma.stdev( 4.0, 12.0 )\nv = base.dists.invgamma.stdev( 8.0, 2.0 )\n","base.dists.invgamma.variance":"var v = base.dists.invgamma.variance( 5.0, 7.0 )\nv = base.dists.invgamma.variance( 4.0, 12.0 )\nv = base.dists.invgamma.variance( 8.0, 2.0 )\n","base.dists.kumaraswamy.cdf":"var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.cdf.factory":"var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.kumaraswamy.Kumaraswamy":"var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\nkumaraswamy.a\nkumaraswamy.b\nkumaraswamy.kurtosis\nkumaraswamy.mean\nkumaraswamy.mode\nkumaraswamy.skewness\nkumaraswamy.stdev\nkumaraswamy.variance\nkumaraswamy.cdf( 0.8 )\nkumaraswamy.pdf( 1.0 )\nkumaraswamy.quantile( 0.8 )\n","base.dists.kumaraswamy.kurtosis":"var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\nv = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\nv = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n","base.dists.kumaraswamy.logcdf":"var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logcdf.factory":"var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.kumaraswamy.logpdf":"var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logpdf.factory":"var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.kumaraswamy.mean":"var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mean( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n","base.dists.kumaraswamy.median":"var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\nv = base.dists.kumaraswamy.median( 4.0, 12.0 )\nv = base.dists.kumaraswamy.median( 16.0, 8.0 )\n","base.dists.kumaraswamy.mode":"var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mode( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n","base.dists.kumaraswamy.pdf":"var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.pdf.factory":"var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.kumaraswamy.quantile":"var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.quantile.factory":"var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.3 )\n","base.dists.kumaraswamy.skewness":"var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\nv = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\nv = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n","base.dists.kumaraswamy.stdev":"var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\nv = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\nv = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n","base.dists.kumaraswamy.variance":"var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\nv = base.dists.kumaraswamy.variance( 4.0, 12.0 )\nv = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n","base.dists.laplace.cdf":"var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 2, NaN, 1.0 )\ny = base.dists.laplace.cdf( 2.0, 0.0, NaN )\ny = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.cdf.factory":"var myCDF = base.dists.laplace.cdf.factory( 2.0, 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base.dists.logistic.pdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.pdf( 0.0, 0.0, NaN )\ny = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n","base.dists.logistic.pdf.factory":"var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.logistic.quantile":"var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\ny = base.dists.logistic.quantile( 0.0, 0.0, NaN )\ny = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n","base.dists.logistic.quantile.factory":"var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.logistic.skewness":"var y = 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NaN, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.cdf.factory":"var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 4.0 )\n","base.dists.lognormal.entropy":"var y = base.dists.lognormal.entropy( 0.0, 1.0 )\ny = base.dists.lognormal.entropy( 5.0, 2.0 )\ny = base.dists.lognormal.entropy( NaN, 1.0 )\ny = base.dists.lognormal.entropy( 0.0, NaN )\ny = base.dists.lognormal.entropy( 0.0, 0.0 )\n","base.dists.lognormal.kurtosis":"var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\ny = base.dists.lognormal.kurtosis( 5.0, 2.0 )\ny = base.dists.lognormal.kurtosis( NaN, 1.0 )\ny = base.dists.lognormal.kurtosis( 0.0, NaN )\ny = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n","base.dists.lognormal.LogNormal":"var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 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0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.logpdf.factory":"var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\nvar y = mylogPDF( 10.0 )\ny = mylogPDF( 2.0 )\n","base.dists.lognormal.mean":"var y = base.dists.lognormal.mean( 0.0, 1.0 )\ny = base.dists.lognormal.mean( 4.0, 2.0 )\ny = base.dists.lognormal.mean( NaN, 1.0 )\ny = base.dists.lognormal.mean( 0.0, NaN )\ny = base.dists.lognormal.mean( 0.0, 0.0 )\n","base.dists.lognormal.median":"var y = base.dists.lognormal.median( 0.0, 1.0 )\ny = base.dists.lognormal.median( 5.0, 2.0 )\ny = base.dists.lognormal.median( NaN, 1.0 )\ny = base.dists.lognormal.median( 0.0, NaN )\ny = base.dists.lognormal.median( 0.0, 0.0 )\n","base.dists.lognormal.mode":"var y = base.dists.lognormal.mode( 0.0, 1.0 )\ny = base.dists.lognormal.mode( 5.0, 2.0 )\ny = base.dists.lognormal.mode( NaN, 1.0 )\ny = base.dists.lognormal.mode( 0.0, NaN )\ny = base.dists.lognormal.mode( 0.0, 0.0 )\n","base.dists.lognormal.pdf":"var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.pdf.factory":"var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.lognormal.quantile":"var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\ny = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n","base.dists.lognormal.quantile.factory":"var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.lognormal.skewness":"var y = base.dists.lognormal.skewness( 0.0, 1.0 )\ny = base.dists.lognormal.skewness( 5.0, 2.0 )\ny = base.dists.lognormal.skewness( NaN, 1.0 )\ny = base.dists.lognormal.skewness( 0.0, NaN )\ny = base.dists.lognormal.skewness( 0.0, 0.0 )\n","base.dists.lognormal.stdev":"var y = base.dists.lognormal.stdev( 0.0, 1.0 )\ny = base.dists.lognormal.stdev( 4.0, 2.0 )\ny = base.dists.lognormal.stdev( NaN, 1.0 )\ny = base.dists.lognormal.stdev( 0.0, NaN )\ny = base.dists.lognormal.stdev( 0.0, 0.0 )\n","base.dists.lognormal.variance":"var y = base.dists.lognormal.variance( 0.0, 1.0 )\ny = base.dists.lognormal.variance( 4.0, 2.0 )\ny = base.dists.lognormal.variance( NaN, 1.0 )\ny = base.dists.lognormal.variance( 0.0, NaN )\ny = base.dists.lognormal.variance( 0.0, 0.0 )\n","base.dists.negativeBinomial.cdf":"var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n","base.dists.negativeBinomial.cdf.factory":"var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\nvar y = myCDF( 3.0 )\ny = myCDF( 11.0 )\n","base.dists.negativeBinomial.kurtosis":"var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\nv = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n","base.dists.negativeBinomial.logpmf":"var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.logpmf.factory":"var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\nvar y = mylogPMF( 3.0 )\ny = mylogPMF( 5.0 )\n","base.dists.negativeBinomial.mean":"var v = base.dists.negativeBinomial.mean( 100, 0.2 )\nv = base.dists.negativeBinomial.mean( 20, 0.5 )\n","base.dists.negativeBinomial.mgf":"var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\ny = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\ny = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n","base.dists.negativeBinomial.mgf.factory":"var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\nvar y = myMGF( 0.2 )\ny = myMGF( 0.4 )\n","base.dists.negativeBinomial.mode":"var v = base.dists.negativeBinomial.mode( 100, 0.2 )\nv = base.dists.negativeBinomial.mode( 20, 0.5 )\n","base.dists.negativeBinomial.NegativeBinomial":"var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\nnbinomial.r\nnbinomial.p\nnbinomial.kurtosis\nnbinomial.mean\nnbinomial.mode\nnbinomial.skewness\nnbinomial.stdev\nnbinomial.variance\nnbinomial.cdf( 2.9 )\nnbinomial.logpmf( 3.0 )\nnbinomial.mgf( 0.2 )\nnbinomial.pmf( 3.0 )\nnbinomial.quantile( 0.8 )\n","base.dists.negativeBinomial.pmf":"var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.pmf.factory":"var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\nvar y = myPMF( 3.0 )\ny = myPMF( 5.0 )\n","base.dists.negativeBinomial.quantile":"var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\ny = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\ny = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\ny = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n","base.dists.negativeBinomial.quantile.factory":"var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\nvar y = myQuantile( 0.1 )\ny = myQuantile( 0.9 )\n","base.dists.negativeBinomial.skewness":"var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\nv = base.dists.negativeBinomial.skewness( 20, 0.5 )\n","base.dists.negativeBinomial.stdev":"var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\nv = base.dists.negativeBinomial.stdev( 20, 0.5 )\n","base.dists.negativeBinomial.variance":"var v = base.dists.negativeBinomial.variance( 100, 0.2 )\nv = base.dists.negativeBinomial.variance( 20, 0.5 )\n","base.dists.normal.cdf":"var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\ny = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.cdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.cdf( 0.0, 0.0, NaN )\ny = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n","base.dists.normal.cdf.factory":"var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 10.0 )\n","base.dists.normal.entropy":"var y = base.dists.normal.entropy( 0.0, 1.0 )\ny = base.dists.normal.entropy( 4.0, 3.0 )\ny = base.dists.normal.entropy( NaN, 1.0 )\ny = base.dists.normal.entropy( 0.0, NaN )\ny = base.dists.normal.entropy( 0.0, 0.0 )\n","base.dists.normal.kurtosis":"var y = base.dists.normal.kurtosis( 0.0, 1.0 )\ny = base.dists.normal.kurtosis( 4.0, 3.0 )\ny = base.dists.normal.kurtosis( NaN, 1.0 )\ny = base.dists.normal.kurtosis( 0.0, NaN )\ny = base.dists.normal.kurtosis( 0.0, 0.0 )\n","base.dists.normal.logcdf":"var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logcdf.factory":"var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.normal.logpdf":"var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logpdf.factory":"var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\nvar y = myLogPDF( 10.0 )\n","base.dists.normal.mean":"var y = base.dists.normal.mean( 0.0, 1.0 )\ny = base.dists.normal.mean( 4.0, 2.0 )\ny = base.dists.normal.mean( NaN, 1.0 )\ny = base.dists.normal.mean( 0.0, NaN )\ny = base.dists.normal.mean( 0.0, 0.0 )\n","base.dists.normal.median":"var y = base.dists.normal.median( 0.0, 1.0 )\ny = base.dists.normal.median( 4.0, 2.0 )\ny = base.dists.normal.median( NaN, 1.0 )\ny = base.dists.normal.median( 0.0, NaN )\ny = base.dists.normal.median( 0.0, 0.0 )\n","base.dists.normal.mgf":"var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.mgf( NaN, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, NaN, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, NaN )\ny = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n","base.dists.normal.mgf.factory":"var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.normal.mode":"var y = base.dists.normal.mode( 0.0, 1.0 )\ny = base.dists.normal.mode( 4.0, 2.0 )\ny = base.dists.normal.mode( NaN, 1.0 )\ny = base.dists.normal.mode( 0.0, NaN )\ny = base.dists.normal.mode( 0.0, 0.0 )\n","base.dists.normal.Normal":"var normal = base.dists.normal.Normal( -2.0, 3.0 );\nnormal.mu\nnormal.sigma\nnormal.entropy\nnormal.kurtosis\nnormal.mean\nnormal.median\nnormal.mode\nnormal.skewness\nnormal.stdev\nnormal.variance\nnormal.cdf( 0.8 )\nnormal.logcdf( 0.8 )\nnormal.logpdf( 2.0 )\nnormal.mgf( 0.2 )\nnormal.pdf( 2.0 )\nnormal.quantile( 0.9 )\n","base.dists.normal.pdf":"var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.pdf( 0.0, 0.0, NaN )\ny = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.pdf.factory":"var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.normal.quantile":"var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.normal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.normal.quantile( 0.0, 0.0, NaN )\ny = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\ny = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n","base.dists.normal.quantile.factory":"var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.normal.skewness":"var y = base.dists.normal.skewness( 0.0, 1.0 )\ny = base.dists.normal.skewness( 4.0, 3.0 )\ny = base.dists.normal.skewness( NaN, 1.0 )\ny = base.dists.normal.skewness( 0.0, NaN )\ny = base.dists.normal.skewness( 0.0, 0.0 )\n","base.dists.normal.stdev":"var y = base.dists.normal.stdev( 0.0, 1.0 )\ny = base.dists.normal.stdev( 4.0, 3.0 )\ny = base.dists.normal.stdev( NaN, 1.0 )\ny = base.dists.normal.stdev( 0.0, NaN )\ny = base.dists.normal.stdev( 0.0, 0.0 )\n","base.dists.normal.variance":"var y = base.dists.normal.variance( 0.0, 1.0 )\ny = base.dists.normal.variance( 4.0, 3.0 )\ny = base.dists.normal.variance( NaN, 1.0 )\ny = base.dists.normal.variance( 0.0, NaN )\ny = base.dists.normal.variance( 0.0, 0.0 )\n","base.dists.pareto1.cdf":"var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.cdf.factory":"var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 2.5 )\n","base.dists.pareto1.entropy":"var v = base.dists.pareto1.entropy( 0.8, 1.0 )\nv = base.dists.pareto1.entropy( 4.0, 12.0 )\nv = base.dists.pareto1.entropy( 8.0, 2.0 )\n","base.dists.pareto1.kurtosis":"var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\nv = base.dists.pareto1.kurtosis( 4.5, 12.0 )\nv = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n","base.dists.pareto1.logcdf":"var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.logcdf.factory":"var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\nvar y = mylogCDF( 3.0 )\ny = mylogCDF( 2.5 )\n","base.dists.pareto1.logpdf":"var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.logpdf.factory":"var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\nvar y = mylogPDF( 0.8 )\ny = mylogPDF( 2.0 )\n","base.dists.pareto1.mean":"var v = base.dists.pareto1.mean( 0.8, 1.0 )\nv = base.dists.pareto1.mean( 4.0, 12.0 )\nv = base.dists.pareto1.mean( 8.0, 2.0 )\n","base.dists.pareto1.median":"var v = base.dists.pareto1.median( 0.8, 1.0 )\nv = base.dists.pareto1.median( 4.0, 12.0 )\nv = base.dists.pareto1.median( 8.0, 2.0 )\n","base.dists.pareto1.mode":"var v = base.dists.pareto1.mode( 0.8, 1.0 )\nv = base.dists.pareto1.mode( 4.0, 12.0 )\nv = base.dists.pareto1.mode( 8.0, 2.0 )\n","base.dists.pareto1.Pareto1":"var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\npareto1.alpha\npareto1.beta\npareto1.entropy\npareto1.kurtosis\npareto1.mean\npareto1.median\npareto1.mode\npareto1.skewness\npareto1.variance\npareto1.cdf( 7.0 )\npareto1.logcdf( 7.0 )\npareto1.logpdf( 5.0 )\npareto1.pdf( 5.0 )\npareto1.quantile( 0.8 )\n","base.dists.pareto1.pdf":"var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.pdf.factory":"var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\nvar y = myPDF( 0.8 )\ny = myPDF( 2.0 )\n","base.dists.pareto1.quantile":"var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\ny = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n","base.dists.pareto1.quantile.factory":"var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.8 )\n","base.dists.pareto1.skewness":"var v = base.dists.pareto1.skewness( 3.5, 1.0 )\nv = base.dists.pareto1.skewness( 4.0, 12.0 )\nv = base.dists.pareto1.skewness( 8.0, 2.0 )\n","base.dists.pareto1.stdev":"var v = base.dists.pareto1.stdev( 0.8, 1.0 )\nv = base.dists.pareto1.stdev( 4.0, 12.0 )\nv = base.dists.pareto1.stdev( 8.0, 2.0 )\n","base.dists.pareto1.variance":"var v = base.dists.pareto1.variance( 0.8, 1.0 )\nv = base.dists.pareto1.variance( 4.0, 12.0 )\nv = base.dists.pareto1.variance( 8.0, 2.0 )\n","base.dists.poisson.cdf":"var y = base.dists.poisson.cdf( 2.0, 0.5 )\ny = base.dists.poisson.cdf( 2.0, 10.0 )\ny = base.dists.poisson.cdf( -1.0, 4.0 )\ny = base.dists.poisson.cdf( NaN, 1.0 )\ny = base.dists.poisson.cdf( 0.0, NaN )\ny = base.dists.poisson.cdf( 2.0, -1.0 )\ny = base.dists.poisson.cdf( -2.0, 0.0 )\ny = base.dists.poisson.cdf( 0.0, 0.0 )\ny = base.dists.poisson.cdf( 10.0, 0.0 )\n","base.dists.poisson.cdf.factory":"var mycdf = base.dists.poisson.cdf.factory( 5.0 );\nvar y = mycdf( 3.0 )\ny = mycdf( 8.0 )\n","base.dists.poisson.entropy":"var v = base.dists.poisson.entropy( 11.0 )\nv = base.dists.poisson.entropy( 4.5 )\n","base.dists.poisson.kurtosis":"var v = base.dists.poisson.kurtosis( 11.0 )\nv = base.dists.poisson.kurtosis( 4.5 )\n","base.dists.poisson.logpmf":"var y = base.dists.poisson.logpmf( 4.0, 3.0 )\ny = base.dists.poisson.logpmf( 1.0, 3.0 )\ny = base.dists.poisson.logpmf( -1.0, 2.0 )\ny = base.dists.poisson.logpmf( 0.0, NaN )\ny = base.dists.poisson.logpmf( NaN, 0.5 )\ny = base.dists.poisson.logpmf( 2.0, -0.5 )\ny = base.dists.poisson.logpmf( 2.0, 0.0 )\ny = base.dists.poisson.logpmf( 0.0, 0.0 )\n","base.dists.poisson.logpmf.factory":"var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.poisson.mean":"var v = base.dists.poisson.mean( 11.0 )\nv = base.dists.poisson.mean( 4.5 )\n","base.dists.poisson.median":"var v = base.dists.poisson.median( 11.0 )\nv = base.dists.poisson.median( 4.5 )\n","base.dists.poisson.mgf":"var y = base.dists.poisson.mgf( 1.0, 1.5 )\ny = base.dists.poisson.mgf( 0.5, 0.5 )\ny = base.dists.poisson.mgf( NaN, 0.5 )\ny = base.dists.poisson.mgf( 0.0, NaN )\ny = base.dists.poisson.mgf( -2.0, -1.0 )\n","base.dists.poisson.mgf.factory":"var myMGF = base.dists.poisson.mgf.factory( 2.0 );\nvar y = myMGF( 0.1 )\n","base.dists.poisson.mode":"var v = base.dists.poisson.mode( 11.0 )\nv = base.dists.poisson.mode( 4.5 )\n","base.dists.poisson.pmf":"var y = base.dists.poisson.pmf( 4.0, 3.0 )\ny = base.dists.poisson.pmf( 1.0, 3.0 )\ny = base.dists.poisson.pmf( -1.0, 2.0 )\ny = base.dists.poisson.pmf( 0.0, NaN )\ny = base.dists.poisson.pmf( NaN, 0.5 )\ny = base.dists.poisson.pmf( 2.0, -0.5 )\ny = base.dists.poisson.pmf( 2.0, 0.0 )\ny = base.dists.poisson.pmf( 0.0, 0.0 )\n","base.dists.poisson.pmf.factory":"var mypmf = base.dists.poisson.pmf.factory( 1.0 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.poisson.Poisson":"var poisson = base.dists.poisson.Poisson( 6.0 );\npoisson.lambda\npoisson.entropy\npoisson.kurtosis\npoisson.mean\npoisson.median\npoisson.mode\npoisson.skewness\npoisson.stdev\npoisson.variance\npoisson.cdf( 4.0 )\npoisson.logpmf( 2.0 )\npoisson.mgf( 0.5 )\npoisson.pmf( 2.0 )\npoisson.quantile( 0.5 )\n","base.dists.poisson.quantile":"var y = base.dists.poisson.quantile( 0.5, 2.0 )\ny = base.dists.poisson.quantile( 0.9, 4.0 )\ny = base.dists.poisson.quantile( 0.1, 200.0 )\ny = base.dists.poisson.quantile( 1.1, 0.0 )\ny = base.dists.poisson.quantile( -0.2, 0.0 )\ny = base.dists.poisson.quantile( NaN, 0.5 )\ny = base.dists.poisson.quantile( 0.0, NaN )\ny = base.dists.poisson.quantile( 2.0, -1.0 )\ny = base.dists.poisson.quantile( 0.1, 0.0 )\ny = base.dists.poisson.quantile( 0.9, 0.0 )\n","base.dists.poisson.quantile.factory":"var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.poisson.skewness":"var v = base.dists.poisson.skewness( 11.0 )\nv = base.dists.poisson.skewness( 4.5 )\n","base.dists.poisson.stdev":"var v = base.dists.poisson.stdev( 11.0 )\nv = base.dists.poisson.stdev( 4.5 )\n","base.dists.poisson.variance":"var v = base.dists.poisson.variance( 11.0 )\nv = base.dists.poisson.variance( 4.5 )\n","base.dists.rayleigh.cdf":"var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\ny = base.dists.rayleigh.cdf( 1.0, 2.0 )\ny = base.dists.rayleigh.cdf( -1.0, 4.0 )\ny = base.dists.rayleigh.cdf( NaN, 1.0 )\ny = base.dists.rayleigh.cdf( 0.0, NaN )\ny = base.dists.rayleigh.cdf( 2.0, -1.0 )\ny = base.dists.rayleigh.cdf( -2.0, 0.0 )\ny = base.dists.rayleigh.cdf( 0.0, 0.0 )\ny = base.dists.rayleigh.cdf( 2.0, 0.0 )\n","base.dists.rayleigh.cdf.factory":"var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 0.5 )\n","base.dists.rayleigh.entropy":"var v = base.dists.rayleigh.entropy( 11.0 )\nv = base.dists.rayleigh.entropy( 4.5 )\n","base.dists.rayleigh.kurtosis":"var v = base.dists.rayleigh.kurtosis( 11.0 )\nv = base.dists.rayleigh.kurtosis( 4.5 )\n","base.dists.rayleigh.logcdf":"var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\ny = base.dists.rayleigh.logcdf( 1.0, 2.0 )\ny = base.dists.rayleigh.logcdf( -1.0, 4.0 )\ny = base.dists.rayleigh.logcdf( NaN, 1.0 )\ny = base.dists.rayleigh.logcdf( 0.0, NaN )\ny = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n","base.dists.rayleigh.logcdf.factory":"var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\nvar y = mylogcdf( 1.0 )\ny = mylogcdf( 0.5 )\n","base.dists.rayleigh.logpdf":"var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\ny = base.dists.rayleigh.logpdf( 2.0, 0.8 )\ny = base.dists.rayleigh.logpdf( -1.0, 0.5 )\ny = base.dists.rayleigh.logpdf( 0.0, NaN )\ny = base.dists.rayleigh.logpdf( NaN, 2.0 )\ny = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n","base.dists.rayleigh.logpdf.factory":"var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\nvar y = mylogpdf( 6.0 )\ny = mylogpdf( 4.0 )\n","base.dists.rayleigh.mean":"var v = base.dists.rayleigh.mean( 11.0 )\nv = base.dists.rayleigh.mean( 4.5 )\n","base.dists.rayleigh.median":"var v = base.dists.rayleigh.median( 11.0 )\nv = base.dists.rayleigh.median( 4.5 )\n","base.dists.rayleigh.mgf":"var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\ny = base.dists.rayleigh.mgf( 1.0, 2.0 )\ny = base.dists.rayleigh.mgf( -1.0, 4.0 )\ny = base.dists.rayleigh.mgf( NaN, 1.0 )\ny = base.dists.rayleigh.mgf( 0.0, NaN )\ny = base.dists.rayleigh.mgf( 0.5, -1.0 )\n","base.dists.rayleigh.mgf.factory":"var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.rayleigh.mode":"var v = base.dists.rayleigh.mode( 11.0 )\nv = base.dists.rayleigh.mode( 4.5 )\n","base.dists.rayleigh.pdf":"var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.8 )\ny = base.dists.rayleigh.pdf( -1.0, 0.5 )\ny = base.dists.rayleigh.pdf( 0.0, NaN )\ny = base.dists.rayleigh.pdf( NaN, 2.0 )\ny = base.dists.rayleigh.pdf( 2.0, -1.0 )\ny = base.dists.rayleigh.pdf( -2.0, 0.0 )\ny = base.dists.rayleigh.pdf( 0.0, 0.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.0 )\n","base.dists.rayleigh.pdf.factory":"var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\nvar y = myPDF( 6.0 )\ny = myPDF( 4.0 )\n","base.dists.rayleigh.quantile":"var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\ny = base.dists.rayleigh.quantile( 0.5, 4.0 )\ny = base.dists.rayleigh.quantile( 1.1, 1.0 )\ny = base.dists.rayleigh.quantile( -0.2, 1.0 )\ny = base.dists.rayleigh.quantile( NaN, 1.0 )\ny = base.dists.rayleigh.quantile( 0.0, NaN )\ny = base.dists.rayleigh.quantile( 0.5, -1.0 )\n","base.dists.rayleigh.quantile.factory":"var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.rayleigh.Rayleigh":"var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\nrayleigh.sigma\nrayleigh.entropy\nrayleigh.kurtosis\nrayleigh.mean\nrayleigh.median\nrayleigh.mode\nrayleigh.skewness\nrayleigh.stdev\nrayleigh.variance\nrayleigh.cdf( 1.0 )\nrayleigh.logcdf( 1.0 )\nrayleigh.logpdf( 1.5 )\nrayleigh.mgf( -0.5 )\nrayleigh.pdf( 1.5 )\nrayleigh.quantile( 0.5 )\n","base.dists.rayleigh.skewness":"var v = base.dists.rayleigh.skewness( 11.0 )\nv = base.dists.rayleigh.skewness( 4.5 )\n","base.dists.rayleigh.stdev":"var v = base.dists.rayleigh.stdev( 9.0 )\nv = base.dists.rayleigh.stdev( 4.5 )\n","base.dists.rayleigh.variance":"var v = base.dists.rayleigh.variance( 9.0 )\nv = base.dists.rayleigh.variance( 4.5 )\n","base.dists.signrank.cdf":"var y = base.dists.signrank.cdf( 3, 7 )\ny = base.dists.signrank.cdf( 1.8, 3 )\ny = base.dists.signrank.cdf( -1.0, 40 )\ny = base.dists.signrank.cdf( NaN, 10 )\ny = base.dists.signrank.cdf( 0.0, NaN )\n","base.dists.signrank.cdf.factory":"var myCDF = base.dists.signrank.cdf.factory( 8 );\nvar y = myCDF( 5.7 )\ny = myCDF( 2.2 )\n","base.dists.signrank.pdf":"var y = base.dists.signrank.pdf( 3, 7 )\ny = base.dists.signrank.pdf( 1.8, 3 )\ny = base.dists.signrank.pdf( -1.0, 40 )\ny = base.dists.signrank.pdf( NaN, 10 )\ny = base.dists.signrank.pdf( 0.0, NaN )\n","base.dists.signrank.pdf.factory":"var myPDF = base.dists.signrank.pdf.factory( 8 );\nvar y = myPDF( 6.0 )\ny = myPDF( 2.0 )\n","base.dists.signrank.quantile":"var y = base.dists.signrank.quantile( 0.8, 5 )\ny = base.dists.signrank.quantile( 0.5, 4 )\ny = base.dists.signrank.quantile( 1.1, 5 )\ny = base.dists.signrank.quantile( -0.2, 5 )\ny = base.dists.signrank.quantile( NaN, 5 )\ny = base.dists.signrank.quantile( 0.0, NaN )\n","base.dists.signrank.quantile.factory":"var myQuantile = base.dists.signrank.quantile.factory( 8 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.t.cdf":"var y = base.dists.t.cdf( 2.0, 0.1 )\ny = base.dists.t.cdf( 1.0, 2.0 )\ny = base.dists.t.cdf( -1.0, 4.0 )\ny = base.dists.t.cdf( NaN, 1.0 )\ny = base.dists.t.cdf( 0.0, NaN )\ny = base.dists.t.cdf( 2.0, -1.0 )\n","base.dists.t.cdf.factory":"var mycdf = base.dists.t.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.t.entropy":"var v = base.dists.t.entropy( 11.0 )\nv = base.dists.t.entropy( 4.5 )\n","base.dists.t.kurtosis":"var v = base.dists.t.kurtosis( 11.0 )\nv = base.dists.t.kurtosis( 4.5 )\n","base.dists.t.mean":"var v = base.dists.t.mean( 11.0 )\nv = base.dists.t.mean( 4.5 )\n","base.dists.t.median":"var v = base.dists.t.median( 11.0 )\nv = base.dists.t.median( 4.5 )\n","base.dists.t.mode":"var v = base.dists.t.mode( 11.0 )\nv = base.dists.t.mode( 4.5 )\n","base.dists.t.pdf":"var y = base.dists.t.pdf( 0.3, 4.0 )\ny = base.dists.t.pdf( 2.0, 0.7 )\ny = base.dists.t.pdf( -1.0, 0.5 )\ny = base.dists.t.pdf( 0.0, NaN )\ny = base.dists.t.pdf( NaN, 2.0 )\ny = base.dists.t.pdf( 2.0, -1.0 )\n","base.dists.t.pdf.factory":"var myPDF = base.dists.t.pdf.factory( 3.0 );\nvar y = myPDF( 1.0 )\n","base.dists.t.quantile":"var y = base.dists.t.quantile( 0.8, 1.0 )\ny = base.dists.t.quantile( 0.1, 1.0 )\ny = base.dists.t.quantile( 0.5, 0.1 )\ny = base.dists.t.quantile( -0.2, 0.1 )\ny = base.dists.t.quantile( NaN, 1.0 )\ny = base.dists.t.quantile( 0.0, NaN )\ny = base.dists.t.quantile( 0.5, -1.0 )\n","base.dists.t.quantile.factory":"var myQuantile = base.dists.t.quantile.factory( 4.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.t.skewness":"var v = base.dists.t.skewness( 11.0 )\nv = base.dists.t.skewness( 4.5 )\n","base.dists.t.stdev":"var v = base.dists.t.stdev( 9.0 )\nv = base.dists.t.stdev( 4.5 )\n","base.dists.t.T":"var t = base.dists.t.T( 6.0 );\nt.v\nt.entropy\nt.kurtosis\nt.mean\nt.median\nt.mode\nt.skewness\nt.stdev\nt.variance\nt.cdf( 1.0 )\nt.logcdf( 1.0 )\nt.logpdf( 1.5 )\nt.pdf( 1.5 )\nt.quantile( 0.8 )\n","base.dists.t.variance":"var v = base.dists.t.variance( 9.0 )\nv = base.dists.t.variance( 4.5 )\n","base.dists.triangular.cdf":"var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.cdf.factory":"var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.triangular.entropy":"var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n","base.dists.triangular.kurtosis":"var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n","base.dists.triangular.logcdf":"var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.logcdf.factory":"var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.triangular.logpdf":"var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.logpdf.factory":"var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\nvar y = mylogpdf( 2.0 )\ny = mylogpdf( 12.0 )\n","base.dists.triangular.mean":"var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n","base.dists.triangular.median":"var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.median( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n","base.dists.triangular.mgf":"var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n","base.dists.triangular.mgf.factory":"var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\nvar y = mymgf( -1.0 )\ny = mymgf( 2.0 )\n","base.dists.triangular.mode":"var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n","base.dists.triangular.pdf":"var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.pdf.factory":"var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\nvar y = mypdf( 2.0 )\ny = mypdf( 12.0 )\n","base.dists.triangular.quantile":"var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\ny = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n","base.dists.triangular.quantile.factory":"var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\n","base.dists.triangular.skewness":"var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n","base.dists.triangular.stdev":"var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n","base.dists.triangular.Triangular":"var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\ntriangular.a\ntriangular.b\ntriangular.c\ntriangular.entropy\ntriangular.kurtosis\ntriangular.mean\ntriangular.median\ntriangular.mode\ntriangular.skewness\ntriangular.stdev\ntriangular.variance\ntriangular.cdf( 0.8 )\ntriangular.logcdf( 0.8 )\ntriangular.logpdf( 0.8 )\ntriangular.mgf( 0.8 )\ntriangular.pdf( 0.8 )\ntriangular.quantile( 0.8 )\n","base.dists.triangular.variance":"var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n","base.dists.uniform.cdf":"var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.cdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.cdf.factory":"var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.uniform.entropy":"var v = base.dists.uniform.entropy( 0.0, 1.0 )\nv = base.dists.uniform.entropy( 4.0, 12.0 )\nv = base.dists.uniform.entropy( 2.0, 8.0 )\n","base.dists.uniform.kurtosis":"var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\nv = base.dists.uniform.kurtosis( 4.0, 12.0 )\nv = base.dists.uniform.kurtosis( 2.0, 8.0 )\n","base.dists.uniform.logcdf":"var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.logcdf.factory":"var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.uniform.logpdf":"var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.logpdf.factory":"var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 7.0 )\ny = mylogPDF( 5.0 )\n","base.dists.uniform.mean":"var v = base.dists.uniform.mean( 0.0, 1.0 )\nv = base.dists.uniform.mean( 4.0, 12.0 )\nv = base.dists.uniform.mean( 2.0, 8.0 )\n","base.dists.uniform.median":"var v = base.dists.uniform.median( 0.0, 1.0 )\nv = base.dists.uniform.median( 4.0, 12.0 )\nv = base.dists.uniform.median( 2.0, 8.0 )\n","base.dists.uniform.mgf":"var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\ny = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\ny = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n","base.dists.uniform.mgf.factory":"var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.uniform.pdf":"var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.pdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.pdf.factory":"var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.uniform.quantile":"var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\ny = base.dists.uniform.quantile( 0.0, 0.0, NaN )\ny = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n","base.dists.uniform.quantile.factory":"var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.uniform.skewness":"var v = base.dists.uniform.skewness( 0.0, 1.0 )\nv = base.dists.uniform.skewness( 4.0, 12.0 )\nv = base.dists.uniform.skewness( 2.0, 8.0 )\n","base.dists.uniform.stdev":"var v = base.dists.uniform.stdev( 0.0, 1.0 )\nv = base.dists.uniform.stdev( 4.0, 12.0 )\nv = base.dists.uniform.stdev( 2.0, 8.0 )\n","base.dists.uniform.Uniform":"var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\nuniform.a\nuniform.b\nuniform.entropy\nuniform.kurtosis\nuniform.mean\nuniform.median\nuniform.skewness\nuniform.stdev\nuniform.variance\nuniform.cdf( 0.8 )\nuniform.logcdf( 0.5 )\nuniform.logpdf( 1.0 )\nuniform.mgf( 0.8 )\nuniform.pdf( 0.8 )\nuniform.quantile( 0.8 )\n","base.dists.uniform.variance":"var v = base.dists.uniform.variance( 0.0, 1.0 )\nv = base.dists.uniform.variance( 4.0, 12.0 )\nv = base.dists.uniform.variance( 2.0, 8.0 )\n","base.dists.weibull.cdf":"var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.cdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.cdf.factory":"var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\nvar y = myCDF( 12.0 )\n","base.dists.weibull.entropy":"var v = base.dists.weibull.entropy( 1.0, 1.0 )\nv = base.dists.weibull.entropy( 4.0, 12.0 )\nv = base.dists.weibull.entropy( 8.0, 2.0 )\n","base.dists.weibull.kurtosis":"var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\nv = base.dists.weibull.kurtosis( 4.0, 12.0 )\nv = base.dists.weibull.kurtosis( 8.0, 2.0 )\n","base.dists.weibull.logcdf":"var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logcdf.factory":"var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\nvar y = mylogcdf( 12.0 )\n","base.dists.weibull.logpdf":"var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logpdf.factory":"var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\ny = mylofpdf( 7.0 )\n","base.dists.weibull.mean":"var v = base.dists.weibull.mean( 1.0, 1.0 )\nv = base.dists.weibull.mean( 4.0, 12.0 )\nv = base.dists.weibull.mean( 8.0, 2.0 )\n","base.dists.weibull.median":"var v = base.dists.weibull.median( 1.0, 1.0 )\nv = base.dists.weibull.median( 4.0, 12.0 )\nv = base.dists.weibull.median( 8.0, 2.0 )\n","base.dists.weibull.mgf":"var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\ny = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\ny = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\ny = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.mgf( 0.0, 1.0, NaN )\ny = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\ny = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n","base.dists.weibull.mgf.factory":"var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.08 )\n","base.dists.weibull.mode":"var v = base.dists.weibull.mode( 1.0, 1.0 )\nv = base.dists.weibull.mode( 4.0, 12.0 )\nv = base.dists.weibull.mode( 8.0, 2.0 )\n","base.dists.weibull.pdf":"var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.pdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.pdf.factory":"var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\nvar y = myPDF( 7.0 )\n","base.dists.weibull.quantile":"var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\ny = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\ny = base.dists.weibull.quantile( 0.0, 0.0, NaN )\ny = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n","base.dists.weibull.quantile.factory":"var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.weibull.skewness":"var v = base.dists.weibull.skewness( 1.0, 1.0 )\nv = base.dists.weibull.skewness( 4.0, 12.0 )\nv = base.dists.weibull.skewness( 8.0, 2.0 )\n","base.dists.weibull.stdev":"var v = base.dists.weibull.stdev( 1.0, 1.0 )\nv = base.dists.weibull.stdev( 4.0, 12.0 )\nv = base.dists.weibull.stdev( 8.0, 2.0 )\n","base.dists.weibull.variance":"var v = base.dists.weibull.variance( 1.0, 1.0 )\nv = base.dists.weibull.variance( 4.0, 12.0 )\nv = base.dists.weibull.variance( 8.0, 2.0 )\n","base.dists.weibull.Weibull":"var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\nweibull.k\nweibull.lambda\nweibull.entropy\nweibull.kurtosis\nweibull.mean\nweibull.median\nweibull.mode\nweibull.skewness\nweibull.stdev\nweibull.variance\nweibull.cdf( 3.0 )\nweibull.logcdf( 3.0 )\nweibull.logpdf( 1.0 )\nweibull.mgf( -0.5 )\nweibull.pdf( 3.0 )\nweibull.quantile( 0.8 )\n","base.ellipe":"var y = base.ellipe( 0.5 )\ny = base.ellipe( -1.0 )\ny = base.ellipe( 2.0 )\ny = base.ellipe( PINF )\ny = base.ellipe( NINF )\ny = base.ellipe( NaN )\n","base.ellipj":"var v = base.ellipj( 0.3, 0.5 )\nv = base.ellipj( 0.0, 0.0 )\nv = base.ellipj( Infinity, 1.0 )\nv = base.ellipj( 0.0, -2.0)\nv = base.ellipj( NaN, NaN )\n","base.ellipj.assign":"var out = new Float64Array( 4 );\nvar v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.ellipj.sn":"var v = base.ellipj.sn( 0.3, 0.5 )\n","base.ellipj.cn":"var v = base.ellipj.cn( 0.3, 0.5 )\n","base.ellipj.dn":"var v = base.ellipj.dn( 0.3, 0.5 )\n","base.ellipj.am":"var v = base.ellipj.am( 0.3, 0.5 )\n","base.ellipk":"var y = base.ellipk( 0.5 )\ny = base.ellipk( -1.0 )\ny = base.ellipk( 2.0 )\ny = base.ellipk( PINF )\ny = base.ellipk( NINF )\ny = base.ellipk( NaN )\n","base.epsdiff":"var d = base.epsdiff( 12.15, 12.149999999999999 )\nd = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\nfunction scale( x, y ) { return ( x > y ) ? y : x; };\nd = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n","base.erf":"var y = base.erf( 2.0 )\ny = base.erf( -1.0 )\ny = base.erf( -0.0 )\ny = base.erf( NaN )\n","base.erfc":"var y = base.erfc( 2.0 )\ny = base.erfc( -1.0 )\ny = base.erfc( 0.0 )\ny = base.erfc( PINF )\ny = base.erfc( NINF )\ny = base.erfc( NaN )\n","base.erfcinv":"var y = base.erfcinv( 0.5 )\ny = base.erfcinv( 0.8 )\ny = base.erfcinv( 0.0 )\ny = base.erfcinv( 2.0 )\ny = base.erfcinv( NaN )\n","base.erfcx":"var y = base.erfcx( 1.0 )\ny = base.erfcx( -1.0 )\ny = base.erfcx( 0.0 )\ny = base.erfcx( NaN )\n","base.erfinv":"var y = base.erfinv( 0.5 )\ny = base.erfinv( 0.8 )\ny = base.erfinv( 0.0 )\ny = base.erfinv( -0.0 )\ny = base.erfinv( -1.0 )\ny = base.erfinv( 1.0 )\ny = base.erfinv( NaN )\n","base.eta":"var y = base.eta( 0.0 )\ny = base.eta( -1.0 )\ny = base.eta( 1.0 )\ny = base.eta( 3.14 )\ny = base.eta( NaN )\n","base.evalpoly":"var arr = [ 3.0, 2.0, 1.0 ];\nvar v = base.evalpoly( arr, 10.0 )\n","base.evalpoly.factory":"var polyval = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\nvar v = polyval( 10.0 )\nv = polyval( 5.0 )\n","base.evalrational":"var P = [ -6.0, -5.0, 4.0, 2.0 ];\nvar Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\nvar v = base.evalrational( P, Q, 6.0 )\n","base.evalrational.factory":"var P = [ 20.0, 8.0, 3.0 ];\nvar Q = [ 10.0, 9.0, 1.0 ];\nvar rational = base.evalrational.factory( P, Q );\nvar v = rational( 10.0 )\nv = rational( 2.0 )\n","base.exp":"var y = base.exp( 4.0 )\ny = base.exp( -9.0 )\ny = base.exp( 0.0 )\ny = base.exp( NaN )\n","base.exp2":"var y = base.exp2( 3.0 )\ny = base.exp2( -9.0 )\ny = base.exp2( 0.0 )\ny = base.exp2( NaN )\n","base.exp10":"var y = base.exp10( 3.0 )\ny = base.exp10( -9.0 )\ny = base.exp10( 0.0 )\ny = base.exp10( NaN )\n","base.expit":"var y = base.expit( 0.0 )\ny = base.expit( 1.0 )\ny = base.expit( -1.0 )\ny = base.expit( Infinity )\ny = base.expit( NaN )\n","base.expm1":"var y = base.expm1( 0.2 )\ny = base.expm1( -9.0 )\ny = base.expm1( 0.0 )\ny = base.expm1( NaN )\n","base.expm1rel":"var y = base.expm1rel( 0.0 )\ny = base.expm1rel( 1.0 )\ny = base.expm1rel( -1.0 )\ny = base.expm1rel( NaN )\n","base.exponent":"var exponent = base.exponent( 3.14e-307 )\nexponent = base.exponent( -3.14 )\nexponent = base.exponent( 0.0 )\nexponent = base.exponent( NaN )\n","base.exponentf":"var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\nexponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\nexponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\nexponent = base.exponentf( 0.0 )\nexponent = base.exponentf( NaN )\n","base.factorial":"var y = base.factorial( 3.0 )\ny = base.factorial( -1.5 )\ny = base.factorial( -0.5 )\ny = base.factorial( 0.5 )\ny = base.factorial( -10.0 )\ny = base.factorial( 171.0 )\ny = base.factorial( NaN )\n","base.factorial2":"var y = base.factorial2( 3 )\ny = base.factorial2( 5 )\ny = base.factorial2( 6 )\ny = base.factorial2( 301 )\ny = base.factorial2( NaN )\n","base.factorialln":"var y = base.factorialln( 3.0 )\ny = base.factorialln( 2.4 )\ny = base.factorialln( -1.0 )\ny = base.factorialln( -1.5 )\ny = base.factorialln( NaN )\n","base.fallingFactorial":"var v = base.fallingFactorial( 0.9, 5 )\nv = base.fallingFactorial( -9.0, 3 )\nv = base.fallingFactorial( 0.0, 2 )\nv = base.fallingFactorial( 3.0, -2 )\n","base.fibonacci":"var y = base.fibonacci( 0 )\ny = base.fibonacci( 1 )\ny = base.fibonacci( 2 )\ny = base.fibonacci( 3 )\ny = base.fibonacci( 4 )\ny = base.fibonacci( 79 )\ny = base.fibonacci( NaN )\n","base.fibonacciIndex":"var n = base.fibonacciIndex( 2 )\nn = base.fibonacciIndex( 3 )\nn = base.fibonacciIndex( 5 )\nn = base.fibonacciIndex( NaN )\nn = base.fibonacciIndex( 1 )\n","base.fibpoly":"var v = base.fibpoly( 5, 2.0 )\n","base.fibpoly.factory":"var polyval = base.fibpoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.firstCodePoint":"var out = base.firstCodePoint( 'beep', 1 )\nout = base.firstCodePoint( 'Boop', 1 )\nout = base.firstCodePoint( 'foo bar', 5 )\n","base.firstCodeUnit":"var out = base.firstCodeUnit( 'beep', 1 )\nout = base.firstCodeUnit( 'Boop', 1 )\nout = base.firstCodeUnit( 'foo bar', 5 )\n","base.firstGraphemeCluster":"var out = base.firstGraphemeCluster( 'beep', 1 )\nout = base.firstGraphemeCluster( 'Boop', 1 )\nout = base.firstGraphemeCluster( 'foo bar', 5 )\n","base.flipsign":"var z = base.flipsign( -3.0, 10.0 )\nz = base.flipsign( -3.0, -1.0 )\nz = base.flipsign( 1.0, -0.0 )\nz = base.flipsign( -3.0, -0.0 )\nz = base.flipsign( -0.0, 1.0 )\nz = base.flipsign( 0.0, -1.0 )\n","base.flipsignf":"var z = base.flipsignf( -3.0, 10.0 )\nz = base.flipsignf( -3.0, -1.0 )\nz = base.flipsignf( 1.0, -0.0 )\nz = base.flipsignf( -3.0, -0.0 )\nz = base.flipsignf( -0.0, 1.0 )\nz = base.flipsignf( 0.0, -1.0 )\n","base.float32ToInt32":"var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\ny = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( NaN ) )\ny = base.float32ToInt32( FLOAT32_PINF )\ny = base.float32ToInt32( FLOAT32_NINF )\n","base.float32ToUint32":"var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\ny = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( NaN ) )\ny = base.float32ToUint32( FLOAT32_PINF )\ny = base.float32ToUint32( FLOAT32_NINF )\n","base.float64ToFloat32":"var y = base.float64ToFloat32( 1.337 )\n","base.float64ToInt32":"var y = base.float64ToInt32( 4294967295.0 )\ny = base.float64ToInt32( 3.14 )\ny = base.float64ToInt32( -3.14 )\ny = base.float64ToInt32( NaN )\ny = base.float64ToInt32( PINF )\ny = base.float64ToInt32( NINF )\n","base.float64ToInt64Bytes":"var y = base.float64ToInt64Bytes( 4294967297.0 )\n","base.float64ToInt64Bytes.assign":"var out = new Uint8Array( 16 );\nvar y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n","base.float64ToUint32":"var y = base.float64ToUint32( 4294967297.0 )\ny = base.float64ToUint32( 3.14 )\ny = base.float64ToUint32( -3.14 )\ny = base.float64ToUint32( NaN )\ny = base.float64ToUint32( PINF )\ny = base.float64ToUint32( NINF )\n","base.floor":"var y = base.floor( 3.14 )\ny = base.floor( -4.2 )\ny = base.floor( -4.6 )\ny = base.floor( 9.5 )\ny = base.floor( -0.0 )\n","base.floor2":"var y = base.floor2( 3.14 )\ny = base.floor2( -4.2 )\ny = base.floor2( -4.6 )\ny = base.floor2( 9.5 )\ny = base.floor2( 13.0 )\ny = base.floor2( -13.0 )\ny = base.floor2( -0.0 )\n","base.floor10":"var y = base.floor10( 3.14 )\ny = base.floor10( -4.2 )\ny = base.floor10( -4.6 )\ny = base.floor10( 9.5 )\ny = base.floor10( 13.0 )\ny = base.floor10( -13.0 )\ny = base.floor10( -0.0 )\n","base.floorb":"var y = base.floorb( 3.14159, -4, 10 )\ny = base.floorb( 3.14159, 0, 2 )\ny = base.floorb( 5.0, 1, 2 )\n","base.floorf":"var y = base.floorf( 3.14 )\ny = base.floorf( -4.2 )\ny = base.floorf( -4.6 )\ny = base.floorf( 9.5 )\ny = base.floorf( -0.0 )\n","base.floorn":"var y = base.floorn( 3.14159, -4 )\ny = base.floorn( 3.14159, 0 )\ny = base.floorn( 12368.0, 3 )\n","base.floorsd":"var y = base.floorsd( 3.14159, 5 )\ny = base.floorsd( 3.14159, 1 )\ny = base.floorsd( 12368.0, 2 )\ny = base.floorsd( 0.0313, 2, 2 )\n","base.forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachChar( 'hello world!', fcn );\nn\n","base.forEachCodePoint":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePoint( 'hello world!', fcn );\nn\n","base.forEachGraphemeCluster":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachGraphemeCluster( 'hello world!', fcn );\nn\n","base.fresnel":"var y = base.fresnel( 0.0 )\ny = base.fresnel( 1.0 )\ny = base.fresnel( PINF )\ny = base.fresnel( NINF )\ny = base.fresnel( NaN )\n","base.fresnel.assign":"var out = new Float64Array( 2 );\nvar v = base.fresnel.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.fresnelc":"var y = base.fresnelc( 0.0 )\ny = base.fresnelc( 1.0 )\ny = base.fresnelc( PINF )\ny = base.fresnelc( NINF )\ny = base.fresnelc( NaN )\n","base.fresnels":"var y = base.fresnels( 0.0 )\ny = base.fresnels( 1.0 )\ny = base.fresnels( PINF )\ny = base.fresnels( NINF )\ny = base.fresnels( NaN )\n","base.frexp":"var out = base.frexp( 4.0 )\nout = base.frexp( 0.0 )\nout = base.frexp( -0.0 )\nout = base.frexp( NaN )\nout = base.frexp( PINF )\nout = base.frexp( NINF )\n","base.frexp.assign":"var out = new Float64Array( 2 );\nvar y = base.frexp.assign( 4.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.fromBinaryString":"var bstr;\nbstr = '0100000000010000000000000000000000000000000000000000000000000000';\nvar val = base.fromBinaryString( bstr )\nbstr = '0100000000001001001000011111101101010100010001000010110100011000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111100001110011001111001110000101111010111100100010100000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000001100011010011';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000001';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111111000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\n","base.fromBinaryStringf":"var bstr = '01000000100000000000000000000000';\nvar val = base.fromBinaryStringf( bstr )\nbstr = '01000000010010010000111111011011';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111011011000011101000110011';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000010110';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000001';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111110000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\n","base.fromBinaryStringUint8":"var bstr = '01010101';\nvar val = base.fromBinaryStringUint8( bstr )\nbstr = '00000000';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '00000010';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '11111111';\nval = base.fromBinaryStringUint8( bstr )\n","base.fromBinaryStringUint16":"var bstr = '0101010101010101';\nvar val = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000000';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000010';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '1111111111111111';\nval = base.fromBinaryStringUint16( bstr )\n","base.fromBinaryStringUint32":"var bstr = '01010101010101010101010101010101';\nvar val = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000010';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '11111111111111111111111111111111';\nval = base.fromBinaryStringUint32( bstr )\n","base.fromInt64Bytes":"var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\nvar y = base.fromInt64Bytes( bytes, 1, 0 )\n","base.fromWordf":"var word = 1068180177; // => 0 01111111 01010110010001011010001\nvar f32 = base.fromWordf( word ) // when printed, promoted to float64\n","base.fromWords":"var v = base.fromWords( 1774486211, 2479577218 )\nv = base.fromWords( 3221823995, 1413754136 )\nv = base.fromWords( 0, 0 )\nv = base.fromWords( 2147483648, 0 )\nv = base.fromWords( 2146959360, 0 )\nv = base.fromWords( 2146435072, 0 )\nv = base.fromWords( 4293918720, 0 )\n","base.gamma":"var y = base.gamma( 4.0 )\ny = base.gamma( -1.5 )\ny = base.gamma( -0.5 )\ny = base.gamma( 0.5 )\ny = base.gamma( 0.0 )\ny = base.gamma( -0.0 )\ny = base.gamma( NaN )\n","base.gamma1pm1":"var y = base.gamma1pm1( 0.2 )\ny = base.gamma1pm1( -6.7 )\ny = base.gamma1pm1( 0.0 )\ny = base.gamma1pm1( NaN )\n","base.gammaDeltaRatio":"var y = base.gammaDeltaRatio( 2.0, 3.0 )\ny = base.gammaDeltaRatio( 4.0, 0.5 )\ny = base.gammaDeltaRatio( 100.0, 0.0 )\ny = base.gammaDeltaRatio( NaN, 3.0 )\ny = base.gammaDeltaRatio( 5.0, NaN )\ny = base.gammaDeltaRatio( NaN, NaN )\n","base.gammainc":"var y = base.gammainc( 6.0, 2.0 )\ny = base.gammainc( 1.0, 2.0, true, true )\ny = base.gammainc( 7.0, 5.0 )\ny = base.gammainc( 7.0, 5.0, false )\ny = base.gammainc( NaN, 2.0 )\ny = base.gammainc( 6.0, NaN )\n","base.gammaincinv":"var y = base.gammaincinv( 0.5, 2.0 )\ny = base.gammaincinv( 0.1, 10.0 )\ny = base.gammaincinv( 0.75, 3.0 )\ny = base.gammaincinv( 0.75, 3.0, true )\ny = base.gammaincinv( 0.75, NaN )\ny = base.gammaincinv( NaN, 3.0 )\n","base.gammaLanczosSum":"var y = base.gammaLanczosSum( 4.0 )\ny = base.gammaLanczosSum( -1.5 )\ny = base.gammaLanczosSum( -0.5 )\ny = base.gammaLanczosSum( 0.5 )\ny = base.gammaLanczosSum( 0.0 )\ny = base.gammaLanczosSum( NaN )\n","base.gammaLanczosSumExpGScaled":"var y = base.gammaLanczosSumExpGScaled( 4.0 )\ny = base.gammaLanczosSumExpGScaled( -1.5 )\ny = base.gammaLanczosSumExpGScaled( -0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.0 )\ny = base.gammaLanczosSumExpGScaled( NaN )\n","base.gammaln":"var y = base.gammaln( 1.0 )\ny = base.gammaln( 2.0 )\ny = base.gammaln( 4.0 )\ny = base.gammaln( -0.5 )\ny = base.gammaln( 0.5 )\ny = base.gammaln( 0.0 )\ny = base.gammaln( NaN )\n","base.gcd":"var v = base.gcd( 48, 18 )\n","base.getHighWord":"var w = base.getHighWord( 3.14e201 )\n","base.getLowWord":"var w = base.getLowWord( 3.14e201 )\n","base.hacovercos":"var y = base.hacovercos( 3.14 )\ny = base.hacovercos( -4.2 )\ny = base.hacovercos( -4.6 )\ny = base.hacovercos( 9.5 )\ny = base.hacovercos( -0.0 )\n","base.hacoversin":"var y = base.hacoversin( 3.14 )\ny = base.hacoversin( -4.2 )\ny = base.hacoversin( -4.6 )\ny = base.hacoversin( 9.5 )\ny = base.hacoversin( -0.0 )\n","base.havercos":"var y = base.havercos( 3.14 )\ny = base.havercos( -4.2 )\ny = base.havercos( -4.6 )\ny = base.havercos( 9.5 )\ny = base.havercos( -0.0 )\n","base.haversin":"var y = base.haversin( 3.14 )\ny = base.haversin( -4.2 )\ny = base.haversin( -4.6 )\ny = base.haversin( 9.5 )\ny = base.haversin( -0.0 )\n","base.heaviside":"var y = base.heaviside( 3.14 )\ny = base.heaviside( -3.14 )\ny = base.heaviside( 0.0 )\ny = base.heaviside( 0.0, 'half-maximum' )\ny = base.heaviside( 0.0, 'left-continuous' )\ny = base.heaviside( 0.0, 'right-continuous' )\n","base.hermitepoly":"var y = base.hermitepoly( 1, 0.5 )\ny = base.hermitepoly( -1, 0.5 )\ny = base.hermitepoly( 0, 0.5 )\ny = base.hermitepoly( 2, 0.5 )\n","base.hermitepoly.factory":"var polyval = base.hermitepoly.factory( 2 );\nvar v = polyval( 0.5 )\n","base.hypot":"var h = base.hypot( -5.0, 12.0 )\nh = base.hypot( NaN, 12.0 )\nh = base.hypot( -0.0, -0.0 )\n","base.hypotf":"var h = base.hypotf( -5.0, 12.0 )\nh = base.hypotf( NaN, 12.0 )\nh = base.hypotf( -0.0, -0.0 )\n","base.identity":"var y = base.identity( -1.0 )\ny = base.identity( 2.0 )\ny = base.identity( 0.0 )\ny = base.identity( -0.0 )\ny = base.identity( NaN )\n","base.identityf":"var y = base.identityf( -1.0 )\ny = base.identityf( 2.0 )\ny = base.identityf( 0.0 )\ny = base.identityf( -0.0 )\ny = base.identityf( NaN )\n","base.imul":"var v = base.imul( -10|0, 4|0 )\n","base.imuldw":"var v = base.imuldw( 1, 10 )\n","base.imuldw.assign":"var out = [ 0, 0 ];\nvar v = base.imuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.int32ToUint32":"var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\ny = base.int32ToUint32( base.float64ToInt32( 3 ) )\n","base.inv":"var y = base.inv( -1.0 )\ny = base.inv( 2.0 )\ny = base.inv( 0.0 )\ny = base.inv( -0.0 )\ny = base.inv( NaN )\n","base.invf":"var y = base.invf( -1.0 )\ny = base.invf( 2.0 )\ny = base.invf( 0.0 )\ny = base.invf( -0.0 )\ny = base.invf( NaN )\n","base.isComposite":"var bool = base.isComposite( 10.0 )\nbool = base.isComposite( 11.0 )\n","base.isCoprime":"var bool = base.isCoprime( 14.0, 15.0 )\nbool = base.isCoprime( 14.0, 21.0 )\n","base.isEven":"var bool = base.isEven( 5.0 )\nbool = base.isEven( -2.0 )\nbool = base.isEven( 0.0 )\nbool = base.isEven( NaN )\n","base.isEvenInt32":"var bool = base.isEvenInt32( 5 )\nbool = base.isEvenInt32( -2 )\nbool = base.isEvenInt32( 0 )\n","base.isFinite":"var bool = base.isFinite( 5.0 )\nbool = base.isFinite( -2.0e64 )\nbool = base.isFinite( PINF )\nbool = base.isFinite( NINF )\n","base.isFinitef":"var bool = base.isFinitef( 5.0 )\nbool = base.isFinitef( -1.0e38 )\nbool = base.isFinitef( FLOAT32_PINF )\nbool = base.isFinitef( FLOAT32_NINF )\n","base.isInfinite":"var bool = base.isInfinite( PINF )\nbool = base.isInfinite( NINF )\nbool = base.isInfinite( 5.0 )\nbool = base.isInfinite( NaN )\n","base.isInfinitef":"var bool = base.isInfinitef( FLOAT32_PINF )\nbool = base.isInfinitef( FLOAT32_NINF )\nbool = base.isInfinitef( 5.0 )\nbool = base.isInfinitef( NaN )\n","base.isInteger":"var bool = base.isInteger( 1.0 )\nbool = base.isInteger( 3.14 )\n","base.isnan":"var bool = base.isnan( NaN )\nbool = base.isnan( 7.0 )\n","base.isnanf":"var bool = base.isnanf( NaN )\nbool = base.isnanf( 7.0 )\n","base.isNegativeInteger":"var bool = base.isNegativeInteger( -1.0 )\nbool = base.isNegativeInteger( 0.0 )\nbool = base.isNegativeInteger( 10.0 )\n","base.isNegativeZero":"var bool = base.isNegativeZero( -0.0 )\nbool = base.isNegativeZero( 0.0 )\n","base.isNegativeZerof":"var bool = base.isNegativeZerof( -0.0 )\nbool = base.isNegativeZerof( 0.0 )\n","base.isNonNegativeInteger":"var bool = base.isNonNegativeInteger( 1.0 )\nbool = base.isNonNegativeInteger( 0.0 )\nbool = base.isNonNegativeInteger( -10.0 )\n","base.isNonPositiveInteger":"var bool = base.isNonPositiveInteger( -1.0 )\nbool = base.isNonPositiveInteger( 0.0 )\nbool = base.isNonPositiveInteger( 10.0 )\n","base.isOdd":"var bool = base.isOdd( 5.0 )\nbool = base.isOdd( -2.0 )\nbool = base.isOdd( 0.0 )\nbool = base.isOdd( NaN )\n","base.isOddInt32":"var bool = base.isOddInt32( 5 )\nbool = base.isOddInt32( -2 )\nbool = base.isOddInt32( 0 )\n","base.isPositiveInteger":"var bool = base.isPositiveInteger( 1.0 )\nbool = base.isPositiveInteger( 0.0 )\nbool = base.isPositiveInteger( -10.0 )\n","base.isPositiveZero":"var bool = base.isPositiveZero( 0.0 )\nbool = base.isPositiveZero( -0.0 )\n","base.isPositiveZerof":"var bool = base.isPositiveZerof( 0.0 )\nbool = base.isPositiveZerof( -0.0 )\n","base.isPow2Uint32":"var bool = base.isPow2Uint32( 2 )\nbool = base.isPow2Uint32( 5 )\n","base.isPrime":"var bool = base.isPrime( 11.0 )\nbool = base.isPrime( 3.14 )\n","base.isProbability":"var bool = base.isProbability( 0.5 )\nbool = base.isProbability( 3.14 )\nbool = base.isProbability( NaN )\n","base.isSafeInteger":"var bool = base.isSafeInteger( 1.0 )\nbool = base.isSafeInteger( 2.0e200 )\nbool = base.isSafeInteger( 3.14 )\n","base.kernelBetainc":"var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\nout = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n","base.kernelBetainc.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\nvar bool = ( v === out )\n","base.kernelBetaincinv":"var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\ny = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n","base.kernelCos":"var out = base.kernelCos( 0.0, 0.0 )\nout = base.kernelCos( PI/6.0, 0.0 )\nout = base.kernelCos( 0.785, -1.144e-17 )\nout = base.kernelCos( NaN )\n","base.kernelSin":"var y = base.kernelSin( 0.0, 0.0 )\ny = base.kernelSin( PI/6.0, 0.0 )\ny = base.kernelSin( 0.619, 9.279e-18 )\ny = base.kernelSin( NaN, 0.0 )\ny = base.kernelSin( 2.0, NaN )\ny = base.kernelSin( NaN, NaN )\n","base.kernelTan":"var out = base.kernelTan( PI/4.0, 0.0, 1 )\nout = base.kernelTan( PI/4.0, 0.0, -1 )\nout = base.kernelTan( PI/6.0, 0.0, 1 )\nout = base.kernelTan( 0.664, 5.288e-17, 1 )\nout = base.kernelTan( NaN, 0.0, 1 )\nout = base.kernelTan( 3.0, NaN, 1 )\nout = base.kernelTan( 3.0, 0.0, NaN )\n","base.kroneckerDelta":"var y = base.kroneckerDelta( 3.14, 0.0 )\ny = base.kroneckerDelta( 3.14, 3.14 )\n","base.kroneckerDeltaf":"var y = base.kroneckerDeltaf( 3.14, 0.0 )\ny = base.kroneckerDeltaf( 3.14, 3.14 )\n","base.labs":"var v = base.labs( -1|0 )\nv = base.labs( 2|0 )\nv = base.labs( 0|0 )\n","base.lcm":"var v = base.lcm( 21, 6 )\n","base.ldexp":"var x = base.ldexp( 0.5, 3 )\nx = base.ldexp( 4.0, -2 )\nx = base.ldexp( 0.0, 20 )\nx = base.ldexp( -0.0, 39 )\nx = base.ldexp( NaN, -101 )\nx = base.ldexp( PINF, 11 )\nx = base.ldexp( NINF, -118 )\n","base.ln":"var y = base.ln( 4.0 )\ny = base.ln( 0.0 )\ny = base.ln( PINF )\ny = base.ln( NaN )\ny = base.ln( -4.0 )\n","base.log":"var y = base.log( 100.0, 10.0 )\ny = base.log( 16.0, 2.0 )\ny = base.log( 5.0, 1.0 )\ny = base.log( NaN, 2.0 )\ny = base.log( 1.0, NaN )\ny = base.log( -4.0, 2.0 )\ny = base.log( 4.0, -2.0 )\n","base.log1mexp":"var y = base.log1mexp( -10.0 )\ny = base.log1mexp( 0.0 )\ny = base.log1mexp( 5.0 )\ny = base.log1mexp( 10.0 )\ny = base.log1mexp( NaN )\n","base.log1p":"var y = base.log1p( 4.0 )\ny = base.log1p( -1.0 )\ny = base.log1p( 0.0 )\ny = base.log1p( -0.0 )\ny = base.log1p( -2.0 )\ny = base.log1p( NaN )\n","base.log1pexp":"var y = base.log1pexp( -10.0 )\ny = base.log1pexp( 0.0 )\ny = base.log1pexp( 5.0 )\ny = base.log1pexp( 34.0 )\ny = base.log1pexp( NaN )\n","base.log1pmx":"base.log1pmx( 1.1 )\nbase.log1pmx( 0.99 )\nbase.log1pmx( -0.99 )\nbase.log1pmx( -1.1 )\nbase.log1pmx( NaN )\n","base.log2":"var y = base.log2( 4.0 )\ny = base.log2( 8.0 )\ny = base.log2( 0.0 )\ny = base.log2( PINF )\ny = base.log2( NaN )\ny = base.log2( -4.0 )\n","base.log10":"var y = base.log10( 100.0 )\ny = base.log10( 8.0 )\ny = base.log10( 0.0 )\ny = base.log10( PINF )\ny = base.log10( NaN )\ny = base.log10( -4.0 )\n","base.logaddexp":"var v = base.logaddexp( 90.0, 90.0 )\nv = base.logaddexp( -20.0, 90.0 )\nv = base.logaddexp( 0.0, -100.0 )\nv = base.logaddexp( NaN, NaN )\n","base.logit":"var y = base.logit( 0.2 )\ny = base.logit( 0.9 )\ny = base.logit( -4.0 )\ny = base.logit( 1.5 )\ny = base.logit( NaN )\n","base.lucas":"var y = base.lucas( 0 )\ny = base.lucas( 1 )\ny = base.lucas( 2 )\ny = base.lucas( 3 )\ny = base.lucas( 4 )\ny = base.lucas( 77 )\ny = base.lucas( NaN )\n","base.lucaspoly":"var v = base.lucaspoly( 5, 2.0 )\n","base.lucaspoly.factory":"var polyval = base.lucaspoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.max":"var v = base.max( 3.14, 4.2 )\nv = base.max( 3.14, NaN )\nv = base.max( +0.0, -0.0 )\n","base.maxabs":"var v = base.maxabs( 3.14, -4.2 )\nv = base.maxabs( 3.14, NaN )\nv = base.maxabs( +0.0, -0.0 )\n","base.maxn":"var v = base.maxn( 3.14, 4.2 )\nv = base.maxn( 5.9, 3.14, 4.2 )\nv = base.maxn( 3.14, NaN )\nv = base.maxn( +0.0, -0.0 )\n","base.min":"var v = base.min( 3.14, 4.2 )\nv = base.min( 3.14, NaN )\nv = base.min( +0.0, -0.0 )\n","base.minabs":"var v = base.minabs( 3.14, -4.2 )\nv = base.minabs( 3.14, NaN )\nv = base.minabs( +0.0, -0.0 )\n","base.minmax":"var v = base.minmax( 3.14, 4.2 )\nv = base.minmax( 3.14, NaN )\nv = base.minmax( +0.0, -0.0 )\n","base.minmax.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabs":"var v = base.minmaxabs( 3.14, 4.2 )\nv = base.minmaxabs( -5.9, 3.14)\nv = base.minmaxabs( 3.14, NaN )\nv = base.minmaxabs( +0.0, -0.0 )\n","base.minmaxabs.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minn":"var v = base.minn( 3.14, 4.2 )\nv = base.minn( 5.9, 3.14, 4.2 )\nv = base.minn( 3.14, NaN )\nv = base.minn( +0.0, -0.0 )\n","base.modf":"var parts = base.modf( 3.14 )\nparts = base.modf( 3.14 )\nparts = base.modf( +0.0 )\nparts = base.modf( -0.0 )\nparts = base.modf( PINF )\nparts = base.modf( NINF )\nparts = base.modf( NaN )\n","base.modf.assign":"var out = new Float64Array( 2 );\nvar parts = base.modf.assign( 3.14, out, 1, 0 )\nvar bool = ( parts === out )\n","base.mul":"var v = base.mul( -1.0, 5.0 )\nv = base.mul( 2.0, 5.0 )\nv = base.mul( 0.0, 5.0 )\nv = base.mul( -0.0, 0.0 )\nv = base.mul( NaN, NaN )\n","base.mulf":"var v = base.mulf( -1.0, 5.0 )\nv = base.mulf( 2.0, 5.0 )\nv = base.mulf( 0.0, 5.0 )\nv = base.mulf( -0.0, 0.0 )\nv = base.mulf( NaN, NaN )\n","base.ndarray":"var b = [ 1, 2, 3, 4 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40 );\narr.get( 1, 1 )\narr.iset( 3, 99 );\narr.get( 1, 1 )\n","base.ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","base.ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","base.ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","base.ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","base.ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","base.ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","base.ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","base.ndarray.prototype.order: string":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","base.ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","base.ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","base.ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","base.ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","base.ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","base.ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","base.ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","base.ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","base.ndarrayUnary":"var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dtype = 'float64';\nvar shape = [ 2, 2 ];\nvar sx = [ 2, 1 ];\nvar sy = [ 2, 1 ];\nvar ox = 0;\nvar oy = 0;\nvar order = 'row-major';\nvar x = ndarray( dtype, xbuf, shape, sx, ox, order );\nvar y = ndarray( dtype, ybuf, shape, sy, oy, order );\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\nx = {\n 'dtype': dtype,\n 'data': xbuf,\n 'shape': shape,\n 'strides': sx,\n 'offset': ox,\n 'order': order\n };\ny = {\n 'dtype': dtype,\n 'data': ybuf,\n 'shape': shape,\n 'strides': sy,\n 'offset': oy,\n 'order': order\n };\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\n","base.ndzeros":"var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = arr.shape\nvar dt = arr.dtype\n","base.ndzerosLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = base.ndzerosLike( x )\nsh = y.shape\ndt = y.dtype\n","base.negafibonacci":"var y = base.negafibonacci( 0 )\ny = base.negafibonacci( -1 )\ny = base.negafibonacci( -2 )\ny = base.negafibonacci( -3 )\ny = base.negafibonacci( -4 )\ny = base.negafibonacci( -79 )\ny = base.negafibonacci( -80 )\ny = base.negafibonacci( NaN )\n","base.negalucas":"var y = base.negalucas( 0 )\ny = base.negalucas( -1 )\ny = base.negalucas( -2 )\ny = base.negalucas( -3 )\ny = base.negalucas( -4 )\ny = base.negalucas( -77 )\ny = base.negalucas( -78 )\ny = base.negalucas( NaN )\n","base.nonfibonacci":"var v = base.nonfibonacci( 1 )\nv = base.nonfibonacci( 2 )\nv = base.nonfibonacci( 3 )\nv = base.nonfibonacci( NaN )\n","base.normalize":"var out = base.normalize( 3.14e-319 )\nvar y = out[ 0 ];\nvar exponent = out[ 1 ];\nvar bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\nout = base.normalize( 0.0 )\nout = base.normalize( PINF )\nout = base.normalize( NINF )\nout = base.normalize( NaN )\n","base.normalize.assign":"var out = new Float64Array( 2 )\nvar v = base.normalize.assign( 3.14e-319, out, 1, 0 )\nvar bool = ( v === out )\n","base.normalizef":"var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\nvar y = out[ 0 ];\nvar exp = out[ 1 ];\nvar bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\nout = base.normalizef( FLOAT32_PINF )\nout = base.normalizef( FLOAT32_NINF )\nout = base.normalizef( NaN )\n","base.normalizef.assign":"out = new Float32Array( 2 );\nvar v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\nbool = ( v === out )\n","base.normhermitepoly":"var y = base.normhermitepoly( 1, 0.5 )\ny = base.normhermitepoly( -1, 0.5 )\ny = base.normhermitepoly( 0, 0.5 )\ny = base.normhermitepoly( 2, 0.5 )\n","base.normhermitepoly.factory":"var polyval = base.normhermitepoly.factory( 2 );\nvar v = polyval( 0.5 )\n","base.pdiff":"var v = base.pdiff( 5.9, 3.14 )\nv = base.pdiff( 3.14, 4.2 )\nv = base.pdiff( 3.14, NaN )\nv = base.pdiff( -0.0, +0.0 )\n","base.pdifff":"var v = base.pdifff( 5.9, 3.15 )\nv = base.pdifff( 3.14, 4.2 )\nv = base.pdifff( 3.14, NaN )\nv = base.pdifff( -0.0, +0.0 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base.random.arcsine.byteLength;\n","base.random.arcsine.toJSON":"var o = base.random.arcsine.toJSON()\n","base.random.bernoulli":"var r = base.random.bernoulli( 0.8 );\n","base.random.bernoulli.factory":"var rand = base.random.bernoulli.factory();\nvar r = rand( 0.3 );\nr = rand( 0.59 );\nrand = base.random.bernoulli.factory( 0.3 );\nr = rand();\nr = rand();\n","base.random.bernoulli.NAME":"var str = base.random.bernoulli.NAME\n","base.random.bernoulli.PRNG":"var prng = base.random.bernoulli.PRNG;\n","base.random.bernoulli.seed":"var seed = base.random.bernoulli.seed;\n","base.random.bernoulli.seedLength":"var len = base.random.bernoulli.seedLength;\n","base.random.bernoulli.state":"var r = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nvar state = base.random.bernoulli.state\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nbase.random.bernoulli.state = state;\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\n","base.random.bernoulli.stateLength":"var len = base.random.bernoulli.stateLength;\n","base.random.bernoulli.byteLength":"var sz = base.random.bernoulli.byteLength;\n","base.random.bernoulli.toJSON":"var o = base.random.bernoulli.toJSON()\n","base.random.beta":"var r = base.random.beta( 2.0, 5.0 );\n","base.random.beta.factory":"var rand = base.random.beta.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.beta.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.beta.NAME":"var str = base.random.beta.NAME\n","base.random.beta.PRNG":"var prng = base.random.beta.PRNG;\n","base.random.beta.seed":"var seed = base.random.beta.seed;\n","base.random.beta.seedLength":"var len = base.random.beta.seedLength;\n","base.random.beta.state":"var r = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nvar state = base.random.beta.state\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nbase.random.beta.state = state;\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\n","base.random.beta.stateLength":"var len = base.random.beta.stateLength;\n","base.random.beta.byteLength":"var sz = base.random.beta.byteLength;\n","base.random.beta.toJSON":"var o = base.random.beta.toJSON()\n","base.random.betaprime":"var r = base.random.betaprime( 2.0, 5.0 );\n","base.random.betaprime.factory":"var rand = base.random.betaprime.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.betaprime.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.betaprime.NAME":"var str = base.random.betaprime.NAME\n","base.random.betaprime.PRNG":"var prng = base.random.betaprime.PRNG;\n","base.random.betaprime.seed":"var seed = base.random.betaprime.seed;\n","base.random.betaprime.seedLength":"var len = base.random.betaprime.seedLength;\n","base.random.betaprime.state":"var r = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nvar state = base.random.betaprime.state\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nbase.random.betaprime.state = state;\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\n","base.random.betaprime.stateLength":"var len = base.random.betaprime.stateLength;\n","base.random.betaprime.byteLength":"var sz = base.random.betaprime.byteLength;\n","base.random.betaprime.toJSON":"var o = base.random.betaprime.toJSON()\n","base.random.binomial":"var r = base.random.binomial( 20, 0.8 );\n","base.random.binomial.factory":"var rand = base.random.binomial.factory();\nvar r = rand( 20, 0.3 );\nr = rand( 10, 0.77 );\nrand = base.random.binomial.factory( 10, 0.8 );\nr = rand();\nr = rand();\n","base.random.binomial.NAME":"var str = base.random.binomial.NAME\n","base.random.binomial.PRNG":"var prng = base.random.binomial.PRNG;\n","base.random.binomial.seed":"var seed = base.random.binomial.seed;\n","base.random.binomial.seedLength":"var len = base.random.binomial.seedLength;\n","base.random.binomial.state":"var r = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nvar state = base.random.binomial.state\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nbase.random.binomial.state = state;\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\n","base.random.binomial.stateLength":"var len = base.random.binomial.stateLength;\n","base.random.binomial.byteLength":"var sz = base.random.binomial.byteLength;\n","base.random.binomial.toJSON":"var o = base.random.binomial.toJSON()\n","base.random.boxMuller":"var r = base.random.boxMuller();\n","base.random.boxMuller.factory":"var rand = base.random.boxMuller.factory();\nr = rand();\nr = rand();\n","base.random.boxMuller.NAME":"var str = base.random.boxMuller.NAME\n","base.random.boxMuller.PRNG":"var prng = base.random.boxMuller.PRNG;\n","base.random.boxMuller.seed":"var seed = base.random.boxMuller.seed;\n","base.random.boxMuller.seedLength":"var len = base.random.boxMuller.seedLength;\n","base.random.boxMuller.state":"var r = base.random.boxMuller()\nr = base.random.boxMuller()\nr = base.random.boxMuller()\nvar state = base.random.boxMuller.state\nr = base.random.boxMuller()\nr = base.random.boxMuller()\nbase.random.boxMuller.state = state;\nr = base.random.boxMuller()\nr = base.random.boxMuller()\n","base.random.boxMuller.stateLength":"var len = base.random.boxMuller.stateLength;\n","base.random.boxMuller.byteLength":"var sz = base.random.boxMuller.byteLength;\n","base.random.boxMuller.toJSON":"var o = base.random.boxMuller.toJSON()\n","base.random.cauchy":"var r = base.random.cauchy( 2.0, 5.0 );\n","base.random.cauchy.factory":"var rand = base.random.cauchy.factory();\nvar r = rand( 0.0, 1.5 );\nr = rand( -2.0, 2.0 );\nrand = base.random.cauchy.factory( 0.0, 1.5 );\nr = rand();\nr = rand();\n","base.random.cauchy.NAME":"var str = base.random.cauchy.NAME\n","base.random.cauchy.PRNG":"var prng = base.random.cauchy.PRNG;\n","base.random.cauchy.seed":"var seed = base.random.cauchy.seed;\n","base.random.cauchy.seedLength":"var len = base.random.cauchy.seedLength;\n","base.random.cauchy.state":"var r = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\nvar state = base.random.cauchy.state\nr = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\nbase.random.cauchy.state = state;\nr = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\n","base.random.cauchy.stateLength":"var len = base.random.cauchy.stateLength;\n","base.random.cauchy.byteLength":"var sz = base.random.cauchy.byteLength;\n","base.random.cauchy.toJSON":"var o = base.random.cauchy.toJSON()\n","base.random.chi":"var r = base.random.chi( 2 );\n","base.random.chi.factory":"var rand = base.random.chi.factory();\nvar r = rand( 5 );\nr = rand( 3.14 );\nrand = base.random.chi.factory( 3 );\nr = rand();\nr = rand();\n","base.random.chi.NAME":"var str = base.random.chi.NAME\n","base.random.chi.PRNG":"var prng = base.random.chi.PRNG;\n","base.random.chi.seed":"var seed = base.random.chi.seed;\n","base.random.chi.seedLength":"var len = base.random.chi.seedLength;\n","base.random.chi.state":"var r = base.random.chi( 2 )\nr = base.random.chi( 2 )\nr = base.random.chi( 2 )\nvar state = base.random.chi.state\nr = base.random.chi( 2 )\nr = base.random.chi( 2 )\nbase.random.chi.state = state;\nr = base.random.chi( 2 )\nr = base.random.chi( 2 )\n","base.random.chi.stateLength":"var len = base.random.chi.stateLength;\n","base.random.chi.byteLength":"var sz = base.random.chi.byteLength;\n","base.random.chi.toJSON":"var o = base.random.chi.toJSON()\n","base.random.chisquare":"var r = base.random.chisquare( 2 );\n","base.random.chisquare.factory":"var rand = base.random.chisquare.factory();\nvar r = rand( 5 );\nr = rand( 3.14 );\nrand = base.random.chisquare.factory( 3 );\nr = rand();\nr = rand();\n","base.random.chisquare.NAME":"var str = base.random.chisquare.NAME\n","base.random.chisquare.PRNG":"var prng = base.random.chisquare.PRNG;\n","base.random.chisquare.seed":"var seed = base.random.chisquare.seed;\n","base.random.chisquare.seedLength":"var len = base.random.chisquare.seedLength;\n","base.random.chisquare.state":"var r = base.random.chisquare( 2 )\nr = base.random.chisquare( 2 )\nr = base.random.chisquare( 2 )\nvar state = base.random.chisquare.state\nr = base.random.chisquare( 2 )\nr = base.random.chisquare( 2 )\nbase.random.chisquare.state = state;\nr = base.random.chisquare( 2 )\nr = base.random.chisquare( 2 )\n","base.random.chisquare.stateLength":"var len = base.random.chisquare.stateLength;\n","base.random.chisquare.byteLength":"var sz = base.random.chisquare.byteLength;\n","base.random.chisquare.toJSON":"var o = base.random.chisquare.toJSON()\n","base.random.cosine":"var r = base.random.cosine( 2.0, 5.0 );\n","base.random.cosine.factory":"var rand = base.random.cosine.factory();\nvar r = rand( 0.1, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.cosine.factory( 0.1, 1.5 );\nr = rand();\nr = rand();\n","base.random.cosine.NAME":"var str = base.random.cosine.NAME\n","base.random.cosine.PRNG":"var prng = base.random.cosine.PRNG;\n","base.random.cosine.seed":"var seed = base.random.cosine.seed;\n","base.random.cosine.seedLength":"var len = base.random.cosine.seedLength;\n","base.random.cosine.state":"var r = base.random.cosine( 2.0, 5.0 )\nr = base.random.cosine( 2.0, 5.0 )\nr = base.random.cosine( 2.0, 5.0 )\nvar state = base.random.cosine.state\nr = base.random.cosine( 2.0, 5.0 )\nr = base.random.cosine( 2.0, 5.0 )\nbase.random.cosine.state = state;\nr = base.random.cosine( 2.0, 5.0 )\nr = base.random.cosine( 2.0, 5.0 )\n","base.random.cosine.stateLength":"var len = base.random.cosine.stateLength;\n","base.random.cosine.byteLength":"var sz = base.random.cosine.byteLength;\n","base.random.cosine.toJSON":"var o = base.random.cosine.toJSON()\n","base.random.discreteUniform":"var r = base.random.discreteUniform( 2, 50 );\n","base.random.discreteUniform.factory":"var rand = base.random.discreteUniform.factory();\nvar r = rand( 0, 10 );\nr = rand( -20, 20 );\nrand = base.random.discreteUniform.factory( 0, 10 );\nr = rand();\nr = rand();\n","base.random.discreteUniform.NAME":"var str = base.random.discreteUniform.NAME\n","base.random.discreteUniform.PRNG":"var prng = base.random.discreteUniform.PRNG;\n","base.random.discreteUniform.seed":"var seed = base.random.discreteUniform.seed;\n","base.random.discreteUniform.seedLength":"var len = base.random.discreteUniform.seedLength;\n","base.random.discreteUniform.state":"var r = base.random.discreteUniform( 2, 50 )\nr = base.random.discreteUniform( 2, 50 )\nr = base.random.discreteUniform( 2, 50 )\nvar state = base.random.discreteUniform.state\nr = base.random.discreteUniform( 2, 50 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base.random.improvedZiggurat.factory();\nr = rand();\nr = rand();\n","base.random.improvedZiggurat.NAME":"var str = base.random.improvedZiggurat.NAME\n","base.random.improvedZiggurat.PRNG":"var prng = base.random.improvedZiggurat.PRNG;\n","base.random.improvedZiggurat.seed":"var seed = base.random.improvedZiggurat.seed;\n","base.random.improvedZiggurat.seedLength":"var len = base.random.improvedZiggurat.seedLength;\n","base.random.improvedZiggurat.state":"var r = base.random.improvedZiggurat()\nr = base.random.improvedZiggurat()\nr = base.random.improvedZiggurat()\nvar state = base.random.improvedZiggurat.state\nr = base.random.improvedZiggurat()\nr = base.random.improvedZiggurat()\nbase.random.improvedZiggurat.state = state;\nr = base.random.improvedZiggurat()\nr = base.random.improvedZiggurat()\n","base.random.improvedZiggurat.stateLength":"var len = base.random.improvedZiggurat.stateLength;\n","base.random.improvedZiggurat.byteLength":"var sz = 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);\nr = rand();\nr = rand();\n","base.random.levy.NAME":"var str = base.random.levy.NAME\n","base.random.levy.PRNG":"var prng = base.random.levy.PRNG;\n","base.random.levy.seed":"var seed = base.random.levy.seed;\n","base.random.levy.seedLength":"var len = base.random.levy.seedLength;\n","base.random.levy.state":"var r = base.random.levy( 2.0, 5.0 )\nr = base.random.levy( 2.0, 5.0 )\nr = base.random.levy( 2.0, 5.0 )\nvar state = base.random.levy.state\nr = base.random.levy( 2.0, 5.0 )\nr = base.random.levy( 2.0, 5.0 )\nbase.random.levy.state = state;\nr = base.random.levy( 2.0, 5.0 )\nr = base.random.levy( 2.0, 5.0 )\n","base.random.levy.stateLength":"var len = base.random.levy.stateLength;\n","base.random.levy.byteLength":"var sz = base.random.levy.byteLength;\n","base.random.levy.toJSON":"var o = base.random.levy.toJSON()\n","base.random.logistic":"var r = base.random.logistic( 2.0, 5.0 );\n","base.random.logistic.factory":"var rand = base.random.logistic.factory();\nvar r = rand( 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)\n","base.random.lognormal.stateLength":"var len = base.random.lognormal.stateLength;\n","base.random.lognormal.byteLength":"var sz = base.random.lognormal.byteLength;\n","base.random.lognormal.toJSON":"var o = base.random.lognormal.toJSON()\n","base.random.minstd":"var r = base.random.minstd();\n","base.random.minstd.normalized":"var r = base.random.minstd.normalized();\n","base.random.minstd.factory":"var rand = base.random.minstd.factory();\nr = rand();\nr = rand();\nrand = base.random.minstd.factory( { 'seed': 1234 } );\nr = rand()\n","base.random.minstd.NAME":"var str = base.random.minstd.NAME\n","base.random.minstd.MIN":"var v = base.random.minstd.MIN\n","base.random.minstd.MAX":"var v = base.random.minstd.MAX\n","base.random.minstd.seed":"var seed = base.random.minstd.seed;\n","base.random.minstd.seedLength":"var len = base.random.minstd.seedLength;\n","base.random.minstd.state":"var r = base.random.minstd()\nr = base.random.minstd()\nr = base.random.minstd()\nvar state = 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base.random.randi.factory({ 'name': 'minstd' });\nr = randi();\nr = randi();\n","base.random.randi.NAME":"var str = base.random.randi.NAME\n","base.random.randi.PRNG":"var prng = base.random.randi.PRNG;\n","base.random.randi.MIN":"var v = base.random.randi.MIN;\n","base.random.randi.MAX":"var v = base.random.randi.MAX;\n","base.random.randi.seed":"var seed = base.random.randi.seed;\n","base.random.randi.seedLength":"var len = base.random.randi.seedLength;\n","base.random.randi.state":"var r = base.random.randi()\nr = base.random.randi()\nr = base.random.randi()\nvar state = base.random.randi.state;\nr = base.random.randi()\nr = base.random.randi()\nbase.random.randi.state = state;\nr = base.random.randi()\nr = base.random.randi()\n","base.random.randi.stateLength":"var len = base.random.randi.stateLength;\n","base.random.randi.byteLength":"var sz = base.random.randi.byteLength;\n","base.random.randi.toJSON":"var o = base.random.randi.toJSON()\n","base.random.randn":"var r = base.random.randn();\n","base.random.randn.factory":"var rand = base.random.randn.factory();\nvar r = rand();\nr = rand();\nvar rand = base.random.randn.factory({ 'name': 'box-muller' });\nr = rand();\nr = rand();\n","base.random.randn.NAME":"var str = base.random.randn.NAME\n","base.random.randn.PRNG":"var prng = base.random.randn.PRNG;\n","base.random.randn.seed":"var seed = base.random.randn.seed;\n","base.random.randn.seedLength":"var len = base.random.randn.seedLength;\n","base.random.randn.state":"var r = base.random.randn()\nr = base.random.randn()\nr = base.random.randn()\nvar state = base.random.randn.state;\nr = base.random.randn()\nr = base.random.randn()\nbase.random.randn.state = state;\nr = base.random.randn()\nr = base.random.randn()\n","base.random.randn.stateLength":"var len = base.random.randn.stateLength;\n","base.random.randn.byteLength":"var sz = base.random.randn.byteLength;\n","base.random.randn.toJSON":"var o = 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base.random.randu.stateLength;\n","base.random.randu.byteLength":"var sz = base.random.randu.byteLength;\n","base.random.randu.toJSON":"var o = base.random.randu.toJSON()\n","base.random.rayleigh":"var r = base.random.rayleigh( 2.5 );\n","base.random.rayleigh.factory":"var rand = base.random.rayleigh.factory();\nvar r = rand( 5.0 );\nr = rand( 10.0 );\nrand = base.random.rayleigh.factory( 5.0 );\nr = rand();\nr = rand();\n","base.random.rayleigh.NAME":"var str = base.random.rayleigh.NAME\n","base.random.rayleigh.PRNG":"var prng = base.random.rayleigh.PRNG;\n","base.random.rayleigh.seed":"var seed = base.random.rayleigh.seed;\n","base.random.rayleigh.seedLength":"var len = base.random.rayleigh.seedLength;\n","base.random.rayleigh.state":"var r = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nvar state = base.random.rayleigh.state\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nbase.random.rayleigh.state = state;\nr = 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)\nr = base.random.t( 10.0 )\n","base.random.t.stateLength":"var len = base.random.t.stateLength;\n","base.random.t.byteLength":"var sz = base.random.t.byteLength;\n","base.random.t.toJSON":"var o = base.random.t.toJSON()\n","base.random.triangular":"var r = base.random.triangular( 2.0, 5.0, 3.33 );\n","base.random.triangular.factory":"var rand = base.random.triangular.factory();\nvar r = rand( 0.0, 1.0, 0.5 );\nr = rand( -2.0, 2.0, 1.0 );\nrand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\nr = rand();\nr = rand();\n","base.random.triangular.NAME":"var str = base.random.triangular.NAME\n","base.random.triangular.PRNG":"var prng = base.random.triangular.PRNG;\n","base.random.triangular.seed":"var seed = base.random.triangular.seed;\n","base.random.triangular.seedLength":"var len = base.random.triangular.seedLength;\n","base.random.triangular.state":"var r = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 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rand();\n","base.random.weibull.NAME":"var str = base.random.weibull.NAME\n","base.random.weibull.PRNG":"var prng = base.random.weibull.PRNG;\n","base.random.weibull.seed":"var seed = base.random.weibull.seed;\n","base.random.weibull.seedLength":"var len = base.random.weibull.seedLength;\n","base.random.weibull.state":"var r = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nvar state = base.random.weibull.state\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nbase.random.weibull.state = state;\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\n","base.random.weibull.stateLength":"var len = base.random.weibull.stateLength;\n","base.random.weibull.byteLength":"var sz = base.random.weibull.byteLength;\n","base.random.weibull.toJSON":"var o = base.random.weibull.toJSON()\n","base.reldiff":"var d = base.reldiff( 2.0, 5.0 )\nd = base.reldiff( -1.0, 3.14 )\nd = base.reldiff( -2.0, 5.0, 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)\n","base.sici.assign":"var out = new Float64Array( 2 );\nvar y = base.sici.assign( 3.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.signbit":"var bool = base.signbit( 4.0 )\nbool = base.signbit( -9.14e-34 )\nbool = base.signbit( 0.0 )\nbool = base.signbit( -0.0 )\n","base.signbitf":"var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\nbool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\nbool = base.signbitf( 0.0 )\nbool = base.signbitf( -0.0 )\n","base.significandf":"var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\ns = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\ns = base.significandf( base.float64ToFloat32( -3.14 ) )\ns = base.significandf( 0.0 )\ns = base.significandf( NaN )\n","base.signum":"var sign = base.signum( -5.0 )\nsign = base.signum( 5.0 )\nsign = base.signum( -0.0 )\nsign = base.signum( 0.0 )\nsign = base.signum( NaN )\n","base.signumf":"var sign = base.signumf( -5.0 )\nsign = base.signumf( 5.0 )\nsign = base.signumf( -0.0 )\nsign = base.signumf( 0.0 )\nsign = base.signumf( NaN )\n","base.sin":"var y = base.sin( 0.0 )\ny = base.sin( PI/2.0 )\ny = base.sin( -PI/6.0 )\ny = base.sin( NaN )\n","base.sinc":"var y = base.sinc( 0.5 )\ny = base.sinc( -1.2 )\ny = base.sinc( 0.0 )\ny = base.sinc( NaN )\n","base.sincos":"var y = base.sincos( 0.0 )\ny = base.sincos( PI/2.0 )\ny = base.sincos( -PI/6.0 )\ny = base.sincos( NaN )\nvar out = new Float64Array( 2 );\nvar v = base.sincos.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sincospi":"var y = base.sincospi( 0.0 )\ny = base.sincospi( 0.5 )\ny = base.sincospi( 0.1 )\ny = base.sincospi( NaN )\n","base.sincospi.assign":"var out = new Float64Array( 2 );\nvar v = base.sincospi.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sinh":"var y = base.sinh( 0.0 )\ny = base.sinh( 2.0 )\ny = base.sinh( -2.0 )\ny = base.sinh( NaN )\n","base.sinpi":"var y = base.sinpi( 0.0 )\ny = base.sinpi( 0.5 )\ny = base.sinpi( 0.9 )\ny = base.sinpi( NaN )\n","base.spence":"var y = base.spence( 3.0 )\ny = base.spence( 0.0 )\ny = base.spence( -9.0 )\ny = base.spence( NaN )\n","base.sqrt":"var y = base.sqrt( 4.0 )\ny = base.sqrt( 9.0 )\ny = base.sqrt( 0.0 )\ny = base.sqrt( -4.0 )\ny = base.sqrt( NaN )\n","base.sqrt1pm1":"var y = base.sqrt1pm1( 3.0 )\ny = base.sqrt1pm1( 0.5 )\ny = base.sqrt1pm1( 0.02 )\ny = base.sqrt1pm1( -0.5 )\ny = base.sqrt1pm1( -1.1 )\ny = base.sqrt1pm1( NaN )\n","base.sqrtf":"var y = base.sqrtf( 4.0 )\ny = base.sqrtf( 9.0 )\ny = base.sqrtf( 0.0 )\ny = base.sqrtf( -4.0 )\ny = base.sqrtf( NaN )\n","base.sqrtpi":"var y = base.sqrtpi( 4.0 )\ny = base.sqrtpi( 10.0 )\ny = base.sqrtpi( 0.0 )\ny = base.sqrtpi( -4.0 )\ny = base.sqrtpi( NaN )\n","base.strided.binary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary( [ x, y, z ], shape, strides, f );\nz\n","base.strided.binary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\nz\n","base.strided.binaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n","base.strided.binarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\nvar t = {\n 'default': base.add,\n 'complex64': base.caddf,\n 'complex128': base.cadd\n };\nvar out = base.strided.binarySignatureCallbacks( t, sigs )\n","base.strided.ccopy":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy( x.length, x, 1, y, 1 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imag( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy( 2, x, -2, y, 1 );\nz = y.get( 0 );\nre = realf( z )\nim = imag( z )\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.ccopy( 2, x1, -2, y1, 1 );\nz = y0.get( 2 );\nre = realf( z )\nim = imag( z )\n","base.strided.ccopy.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imag( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\nz = y.get( y.length-1 );\nre = realf( z )\nim = imag( z )\n","base.strided.cmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap( x.length, x, 1, y, 1, base.cidentityf );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\ny = new Complex64Array( x.length );\nbase.strided.cmap( 2, x, 2, y, -1, base.cidentityf );\nv = y.get( 0 )\nre = real( v )\nim = imag( v )\nvar x0 = new Complex64Array( xbuf );\nvar y0 = new Complex64Array( x0.length );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf );\nv = y1.get( 0 )\nre = real( v )\nim = imag( v )\n","base.strided.cmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\nx = new Complex64Array( xbuf );\ny = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\nv = y.get( y.length-1 )\nre = real( v )\nim = imag( v )\n","base.strided.cswap":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap( x.length, x, 1, y, 1 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap( 2, x, -2, y, 1 );\nz = y.get( 0 );\nre = realf( z )\nim = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cswap( 2, x1, -2, y1, 1 );\nz = y0.get( 2 );\nre = realf( z )\nim = imagf( z )\nz = x0.get( 1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cswap.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\nz = y.get( y.length-1 );\nre = realf( z )\nim = imagf( z )\nz = x.get( 1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cumax":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumax( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumax( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumax.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumaxabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumaxabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumaxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumin":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumin( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumin( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumin.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cuminabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cuminabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cuminabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.cuminabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs2":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs2.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dapx":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nvar alpha = 5.0;\nbase.strided.dapx( x.length, alpha, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.dapx( N, alpha, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nalpha = 5.0;\nstride = 2;\nbase.strided.dapx( N, alpha, x1, stride )\nx0\n","base.strided.dapx.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nvar alpha = 5.0;\nbase.strided.dapx.ndarray( x.length, alpha, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.dapx.ndarray( N, alpha, x, stride, 1 )\n","base.strided.dapxsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dapxsum( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dapxsum( N, 5.0, x1, stride )\n","base.strided.dapxsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dapxsum.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dapxsumkbn( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dapxsumkbn( N, 5.0, x1, stride )\n","base.strided.dapxsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dapxsumkbn2( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dapxsumkbn2( N, 5.0, x1, stride )\n","base.strided.dapxsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.dapxsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dapxsumors( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dapxsumors( N, 5.0, x1, stride )\n","base.strided.dapxsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dapxsumors.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.dapxsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dapxsumpw( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dapxsumpw( N, 5.0, x1, stride )\n","base.strided.dapxsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.dasum":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum( x.length, x, 1 )\ns = base.strided.dasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.dasum( 3, x1, 2 )\n","base.strided.dasum.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.dasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dasumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dasumpw( N, x1, stride )\n","base.strided.dasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dasumpw.ndarray( N, x, 2, 1 )\n","base.strided.daxpy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.daxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.daxpy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.dceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcopy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dcopy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumax( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcumax( N, x1, 2, y1, 1 )\ny0\n","base.strided.dcumax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcumaxabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.dcumaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumin( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcumin( N, x1, 2, y1, 1 )\ny0\n","base.strided.dcumin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcuminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcuminabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcuminabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.dcuminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcusumkbn( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcusumkbn( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcusumkbn2( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcusumkbn2( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcusumors( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcusumors( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcusumpw( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcusumpw( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ddeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.ddeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddot":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.ddot( 3, x1, -2, y1, 1 )\n","base.strided.ddot.ndarray":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dfill":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.dfill.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dfloor":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.dfloor.ndarray":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.dinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( x.length, x, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( 2, x, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap( 2, x1, -2, y1, 1, base.identity )\ny0\n","base.strided.dmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n","base.strided.dmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\nz0\n","base.strided.dmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n","base.strided.dmax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmax( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmax( N, x1, stride )\n","base.strided.dmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmax.ndarray( N, x, 2, 1 )\n","base.strided.dmaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmaxabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmaxabs( N, x1, stride )\n","base.strided.dmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmaxabs.ndarray( N, x, 2, 1 )\n","base.strided.dmaxabssorted":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmaxabssorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmaxabssorted( N, x1, stride )\n","base.strided.dmaxabssorted.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmaxabssorted.ndarray( N, x, 2, 1 )\n","base.strided.dmaxsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmaxsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmaxsorted( N, x1, stride )\n","base.strided.dmaxsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmaxsorted.ndarray( N, x, 2, 1 )\n","base.strided.dmean":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmean( N, x1, stride )\n","base.strided.dmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmean.ndarray( N, x, 2, 1 )\n","base.strided.dmeankbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeankbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeankbn( N, x1, stride )\n","base.strided.dmeankbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeankbn.ndarray( N, x, 2, 1 )\n","base.strided.dmeankbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeankbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeankbn2( N, x1, stride )\n","base.strided.dmeankbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n","base.strided.dmeanli":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanli( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanli( N, x1, stride )\n","base.strided.dmeanli.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanli.ndarray( N, x, 2, 1 )\n","base.strided.dmeanlipw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanlipw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanlipw( N, x1, stride )\n","base.strided.dmeanlipw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n","base.strided.dmeanors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanors( N, x1, stride )\n","base.strided.dmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dmeanpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanpn( N, x1, stride )\n","base.strided.dmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dmeanpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanpw( N, x1, stride )\n","base.strided.dmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanpw.ndarray( N, x, 2, 1 )\n","base.strided.dmeanstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanstdev( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanstdevpn( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvar":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanvar( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanvar.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvarpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanvarpn( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanvarpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanwd( N, x1, stride )\n","base.strided.dmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dmediansorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmediansorted( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dmediansorted( N, x1, 2 )\n","base.strided.dmediansorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmediansorted.ndarray( N, x, 2, 1 )\n","base.strided.dmidrange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmidrange( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmidrange( N, x1, stride )\n","base.strided.dmidrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmidrange.ndarray( N, x, 2, 1 )\n","base.strided.dmin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmin( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmin( N, x1, stride )\n","base.strided.dmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmin.ndarray( N, x, 2, 1 )\n","base.strided.dminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dminabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dminabs( N, x1, stride )\n","base.strided.dminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dminabs.ndarray( N, x, 2, 1 )\n","base.strided.dminsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dminsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dminsorted( N, x1, stride )\n","base.strided.dminsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dminsorted.ndarray( N, x, 2, 1 )\n","base.strided.dmskabs":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskabs2":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskdeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskdeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskfloor":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskfloor.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.dmskmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.dmskmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\nz0\n","base.strided.dmskmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n","base.strided.dmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dmskmax( N, x1, 2, mask1, 2 )\n","base.strided.dmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dmskmin( N, x1, 2, mask1, 2 )\n","base.strided.dmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dmskrange( N, x1, 2, mask1, 2 )\n","base.strided.dmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskrsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskrsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsksqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsksqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsktrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsktrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dnanasum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanasum( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanasum( N, x1, stride )\n","base.strided.dnanasum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanasum.ndarray( N, x, 2, 1 )\n","base.strided.dnanasumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanasumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanasumors( N, x1, stride )\n","base.strided.dnanasumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanasumors.ndarray( N, x, 2, 1 )\n","base.strided.dnanmax":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmax( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmax( N, x1, stride )\n","base.strided.dnanmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmax.ndarray( N, x, 2, 1 )\n","base.strided.dnanmaxabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmaxabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmaxabs( N, x1, stride )\n","base.strided.dnanmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmaxabs.ndarray( N, x, 2, 1 )\n","base.strided.dnanmean":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmean( N, x1, stride )\n","base.strided.dnanmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmean.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanors( N, x1, stride )\n","base.strided.dnanmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanpn( N, x1, stride )\n","base.strided.dnanmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanpw( N, x1, stride )\n","base.strided.dnanmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanwd( N, x1, stride )\n","base.strided.dnanmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dnanmin":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmin( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmin( N, x1, stride )\n","base.strided.dnanmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmin.ndarray( N, x, 2, 1 )\n","base.strided.dnanminabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanminabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanminabs( N, x1, stride )\n","base.strided.dnanminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanminabs.ndarray( N, x, 2, 1 )\n","base.strided.dnanmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnannsum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnannsum( N, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( N, x1, 2, out, 1 )\n","base.strided.dnannsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( N, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnannsumkbn( N, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( N, x1, 2, out, 1 )\n","base.strided.dnannsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnannsumkbn2( N, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( N, x1, 2, out, 1 )\n","base.strided.dnannsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( N, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnannsumors( N, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( N, x1, 2, out, 1 )\n","base.strided.dnannsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( N, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnannsumpw( N, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( N, x1, 2, out, 1 )\n","base.strided.dnannsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( N, x, 2, 1, out, 1, 0 )\n","base.strided.dnanrange":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanrange( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanrange( N, x1, stride )\n","base.strided.dnanrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanrange.ndarray( N, x, 2, 1 )\n","base.strided.dnanstdev":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdev( N, 1, x1, stride )\n","base.strided.dnanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevch":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevch( N, 1, x1, stride )\n","base.strided.dnanstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevpn( N, 1, x1, stride )\n","base.strided.dnanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevtk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevtk( N, 1, x1, stride )\n","base.strided.dnanstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevwd( N, 1, x1, stride )\n","base.strided.dnanstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevyc":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevyc( N, 1, x1, stride )\n","base.strided.dnanstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnansum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansum( 4, x1, 2 )\n","base.strided.dnansum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnansumkbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnansumkbn( N, x1, stride )\n","base.strided.dnansumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnansumkbn.ndarray( N, x, 2, 1 )\n","base.strided.dnansumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnansumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnansumkbn2( N, x1, stride )\n","base.strided.dnansumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnansumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.dnansumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnansumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnansumors( N, x1, stride )\n","base.strided.dnansumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnansumors.ndarray( N, x, 2, 1 )\n","base.strided.dnansumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnansumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnansumpw( N, x1, stride )\n","base.strided.dnansumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnansumpw.ndarray( N, x, 2, 1 )\n","base.strided.dnanvariance":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariance( N, 1, x1, stride )\n","base.strided.dnanvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancech":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancech( N, 1, x1, stride )\n","base.strided.dnanvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancepn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancepn( N, 1, x1, stride )\n","base.strided.dnanvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancetk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancetk( N, 1, x1, stride )\n","base.strided.dnanvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancewd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancewd( N, 1, x1, stride )\n","base.strided.dnanvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvarianceyc( N, 1, x1, stride )\n","base.strided.dnanvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnrm2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnrm2( 3, x1, 2 )\n","base.strided.dnrm2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.dramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.dramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.drange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.drange( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.drange( N, x1, stride )\n","base.strided.drange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.drange.ndarray( N, x, 2, 1 )\n","base.strided.drev":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.drev( 3, x1, 2 )\nx0\n","base.strided.drev.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.drev.ndarray( 3, x, 2, 1 )\n","base.strided.drsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.drsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.drsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsapxsum( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsapxsum( N, 5.0, x1, stride )\n","base.strided.dsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsapxsum.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.dsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsapxsumpw( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsapxsumpw( N, 5.0, x1, stride )\n","base.strided.dsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.dscal":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.dscal.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\ndot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n","base.strided.dsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dsem":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsem( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsem( N, 1, x1, stride )\n","base.strided.dsem.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsem.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemch( N, 1, x1, stride )\n","base.strided.dsemch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsempn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsempn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsempn( N, 1, x1, stride )\n","base.strided.dsempn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemtk( N, 1, x1, stride )\n","base.strided.dsemtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemwd( N, 1, x1, stride )\n","base.strided.dsemwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemyc( N, 1, x1, stride )\n","base.strided.dsemyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmean( N, x1, stride )\n","base.strided.dsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmean.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanors( N, x1, stride )\n","base.strided.dsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanpn( N, x1, stride )\n","base.strided.dsmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanpw( N, x1, stride )\n","base.strided.dsmeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanwd( N, x1, stride )\n","base.strided.dsmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmean( N, x1, stride )\n","base.strided.dsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmean.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanors( N, x1, stride )\n","base.strided.dsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanpn( N, x1, stride )\n","base.strided.dsnanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanwd( N, x1, stride )\n","base.strided.dsnanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dsnannsumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors( x.length, x, 1, out, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnannsumors( N, x, 2, out, 1 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( N, x1, 2, out, 1 )\n","base.strided.dsnannsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( N, x, 2, 1, out, 1, 0 )\n","base.strided.dsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnansum( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnansum( N, x1, stride )\n","base.strided.dsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnansum.ndarray( N, x, 2, 1 )\n","base.strided.dsnansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnansumors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnansumors( N, x1, stride )\n","base.strided.dsnansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnansumors.ndarray( N, x, 2, 1 )\n","base.strided.dsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnansumpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnansumpw( N, x1, stride )\n","base.strided.dsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnansumpw.ndarray( N, x, 2, 1 )\n","base.strided.dsort2hp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2hp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2ins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2ins( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2ins( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2ins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2sh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2sh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsorthp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsorthp( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsorthp( N, 1, x1, 2 )\nx0\n","base.strided.dsorthp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsortins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortins( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsortins( N, 1, x1, 2 )\nx0\n","base.strided.dsortins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsortsh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsortsh( N, 1, x1, 2 )\nx0\n","base.strided.dsortsh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssum( 3, x1, 2 )\n","base.strided.dssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssum.ndarray(3, x, 2, 1 )\n","base.strided.dssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dssumors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dssumors( N, x1, stride )\n","base.strided.dssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dssumors.ndarray( N, x, 2, 1 )\n","base.strided.dssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dssumpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dssumpw( N, x1, stride )\n","base.strided.dssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dssumpw.ndarray( N, x, 2, 1 )\n","base.strided.dstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdev( N, 1, x1, stride )\n","base.strided.dstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevch( N, 1, x1, stride )\n","base.strided.dstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevpn( N, 1, x1, stride )\n","base.strided.dstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevtk( N, 1, x1, stride )\n","base.strided.dstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevwd( N, 1, x1, stride )\n","base.strided.dstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevyc( N, 1, x1, stride )\n","base.strided.dstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsum( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsum( N, x1, stride )\n","base.strided.dsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsum.ndarray( N, x, 2, 1 )\n","base.strided.dsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsumkbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsumkbn( N, x1, stride )\n","base.strided.dsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsumkbn.ndarray( N, x, 2, 1 )\n","base.strided.dsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsumkbn2( N, x1, stride )\n","base.strided.dsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.dsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsumors( N, x1, stride )\n","base.strided.dsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsumors.ndarray( N, x, 2, 1 )\n","base.strided.dsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsumpw( N, x1, stride )\n","base.strided.dsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsumpw.ndarray( N, x, 2, 1 )\n","base.strided.dsvariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsvariance( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsvariance( N, 1, x1, stride )\n","base.strided.dsvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsvariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsvariancepn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsvariancepn( N, 1, x1, stride )\n","base.strided.dsvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dswap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dswap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dtrunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.dtrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dvariance":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariance( N, 1, x1, stride )\n","base.strided.dvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancech":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancech( N, 1, x1, stride )\n","base.strided.dvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancepn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancepn( N, 1, x1, stride )\n","base.strided.dvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancetk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancetk( N, 1, x1, stride )\n","base.strided.dvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancewd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancewd( N, 1, x1, stride )\n","base.strided.dvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvarianceyc( N, 1, x1, stride )\n","base.strided.dvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvarm":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarm( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarm( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarm.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.dvarmpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmpn( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarmpn( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarmpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.dvarmtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmtk( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarmtk( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarmtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.gapx":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gapx( x.length, alpha, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.gapx( N, alpha, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nalpha = 5.0;\nstride = 2;\nbase.strided.gapx( N, alpha, x1, stride )\nx0\n","base.strided.gapx.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n","base.strided.gapxsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsum( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsum( N, 5.0, x1, stride )\n","base.strided.gapxsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumkbn( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumkbn( N, 5.0, x1, stride )\n","base.strided.gapxsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumkbn2( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumkbn2( N, 5.0, x1, stride )\n","base.strided.gapxsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumors( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumors( N, 5.0, x1, stride )\n","base.strided.gapxsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumpw( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumpw( N, 5.0, x1, stride )\n","base.strided.gapxsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gasum":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum( x.length, x, 1 )\ns = base.strided.gasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.gasum( 3, x1, 2 )\n","base.strided.gasum.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\ns = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.gasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gasumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gasumpw( N, x1, stride )\n","base.strided.gasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.gasumpw.ndarray( N, x, 2, 1 )\n","base.strided.gaxpy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.gaxpy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcopy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gcopy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusum":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusum( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusum( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumkbn( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn2( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumkbn2( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumors":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumors( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumors( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumpw":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumpw( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumpw( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gdot":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.gdot( 3, x1, -2, y1, 1 )\n","base.strided.gdot.ndarray":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nout = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.gfill":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfill( N, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gfill( N, 5.0, x1, 2 )\nx0\n","base.strided.gfill.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gfillBy":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy( x.length, x, 1, fill )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfillBy( N, x, 2, fill )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gfillBy( N, x1, 2, fill )\nx0\n","base.strided.gfillBy.ndarray":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n","base.strided.gnannsumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( x.length, x, 1, out, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nout = [ 0.0, 0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnannsumkbn( N, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( N, x1, 2, out, 1 )\n","base.strided.gnannsumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n","base.strided.gnansum":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansum( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansum( N, x1, stride )\n","base.strided.gnansum.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansum.ndarray( N, x, 2, 1 )\n","base.strided.gnansumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumkbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumkbn( N, x1, stride )\n","base.strided.gnansumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n","base.strided.gnansumkbn2":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumkbn2( N, x1, stride )\n","base.strided.gnansumkbn2.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.gnansumors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumors( N, x1, stride )\n","base.strided.gnansumors.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumors.ndarray( N, x, 2, 1 )\n","base.strided.gnansumpw":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumpw( N, x1, stride )\n","base.strided.gnansumpw.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumpw.ndarray( N, x, 2, 1 )\n","base.strided.gnrm2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnrm2( 3, x1, 2 )\n","base.strided.gnrm2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.grev":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev( x.length, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.grev( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.grev( N, x1, 2 )\nx0\n","base.strided.grev.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.grev.ndarray( N, x, 2, 1 )\n","base.strided.gscal":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gscal( x.length, alpha, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.gscal.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gsort2hp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2hp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2ins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2ins( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2ins( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2ins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2sh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2sh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsorthp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsorthp( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsorthp( N, 1, x1, 2 )\nx0\n","base.strided.gsorthp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsortins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortins( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsortins( N, 1, x1, 2 )\nx0\n","base.strided.gsortins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsortsh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortsh( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsortsh( N, 1, x1, 2 )\nx0\n","base.strided.gsortsh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsum( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsum( N, x1, stride )\n","base.strided.gsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsum.ndarray( N, x, 2, 1 )\n","base.strided.gsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumkbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumkbn( N, x1, stride )\n","base.strided.gsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumkbn.ndarray( N, x, 2, 1 )\n","base.strided.gsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumkbn2( N, x1, stride )\n","base.strided.gsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.gsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumors( N, x1, stride )\n","base.strided.gsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumors.ndarray( N, x, 2, 1 )\n","base.strided.gsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumpw( N, x1, stride )\n","base.strided.gsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumpw.ndarray( N, x, 2, 1 )\n","base.strided.gswap":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gswap.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.mapBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\ny0\n","base.strided.mapBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n","base.strided.mapBy2":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\nz0\n","base.strided.mapBy2.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 1.0, 1.0, 2.0, 2.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n","base.strided.max":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.max( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.max( N, x1, stride )\n","base.strided.max.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.max.ndarray( N, x, 2, 1 )\n","base.strided.maxabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.maxabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.maxabs( N, x1, stride )\n","base.strided.maxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxabs.ndarray( N, x, 2, 1 )\n","base.strided.maxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.maxBy( N, x1, 2, accessor )\n","base.strided.maxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.maxsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.maxsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.maxsorted( N, x1, stride )\n","base.strided.maxsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxsorted.ndarray( N, x, 2, 1 )\n","base.strided.mean":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.mean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.mean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.mean( N, x1, stride )\n","base.strided.mean.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.mean.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mean.ndarray( N, x, 2, 1 )\n","base.strided.meankbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meankbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meankbn( N, x1, stride )\n","base.strided.meankbn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meankbn.ndarray( N, x, 2, 1 )\n","base.strided.meankbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meankbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meankbn2( N, x1, stride )\n","base.strided.meankbn2.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meankbn2.ndarray( N, x, 2, 1 )\n","base.strided.meanors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanors( N, x1, stride )\n","base.strided.meanors.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanors.ndarray( N, x, 2, 1 )\n","base.strided.meanpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanpn( N, x1, stride )\n","base.strided.meanpn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanpn.ndarray( N, x, 2, 1 )\n","base.strided.meanpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanpw( N, x1, stride )\n","base.strided.meanpw.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanpw.ndarray( N, x, 2, 1 )\n","base.strided.meanwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanwd( N, x1, stride )\n","base.strided.meanwd.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanwd.ndarray( N, x, 2, 1 )\n","base.strided.mediansorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mediansorted( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mediansorted( N, x1, 2 )\n","base.strided.mediansorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mediansorted.ndarray( N, x, 2, 1 )\n","base.strided.min":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.min( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.min( N, x1, stride )\n","base.strided.min.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.min.ndarray( N, x, 2, 1 )\n","base.strided.minabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.minabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.minabs( N, x1, stride )\n","base.strided.minabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minabs.ndarray( N, x, 2, 1 )\n","base.strided.minBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.minBy( N, x1, 2, accessor )\n","base.strided.minBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.minsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.minsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.minsorted( N, x1, stride )\n","base.strided.minsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minsorted.ndarray( N, x, 2, 1 )\n","base.strided.mskmax":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskmax( N, x1, 2, mask1, 2 )\n","base.strided.mskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskmin":"var x = [ 1.0, -2.0, -4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskmin( N, x1, 2, mask1, 2 )\n","base.strided.mskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskrange":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskrange( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskrange( N, x1, 2, mask1, 2 )\n","base.strided.mskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskunary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nbase.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\ny\n","base.strided.mskunary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nbase.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.mskunaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.mskunaryDtypeSignatures( dt, dt )\n","base.strided.mskunarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.mskunarySignatureCallbacks( t, sigs )\n","base.strided.nanmax":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmax( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmax( N, x1, stride )\n","base.strided.nanmax.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmax.ndarray( N, x, 2, 1 )\n","base.strided.nanmaxabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmaxabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmaxabs( N, x1, stride )\n","base.strided.nanmaxabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n","base.strided.nanmaxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmaxBy( N, x1, 2, accessor )\n","base.strided.nanmaxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanmean":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmean( N, x1, stride )\n","base.strided.nanmean.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmean.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanors( N, x1, stride )\n","base.strided.nanmeanors.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanpn( N, x1, stride )\n","base.strided.nanmeanpn.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanwd( N, x1, stride )\n","base.strided.nanmeanwd.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.nanmin":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmin( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmin( N, x1, stride )\n","base.strided.nanmin.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmin.ndarray( N, x, 2, 1 )\n","base.strided.nanminabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanminabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanminabs( N, x1, stride )\n","base.strided.nanminabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminabs.ndarray( N, x, 2, 1 )\n","base.strided.nanminBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanminBy( N, x1, 2, accessor )\n","base.strided.nanminBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanmskmax":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.nanmskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskmin":"var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.nanmskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskrange":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskrange( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.nanmskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanrange":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanrange( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanrange( N, x1, stride )\n","base.strided.nanrange.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrange.ndarray( N, x, 2, 1 )\n","base.strided.nanrangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanrangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrangeBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanrangeBy( N, x1, 2, accessor )\n","base.strided.nanrangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanstdev":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdev( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdev( N, 1, x1, 2 )\n","base.strided.nanstdev.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevch":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevch( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevch( N, 1, x1, 2 )\n","base.strided.nanstdevch.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevpn( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevpn( N, 1, x1, 2 )\n","base.strided.nanstdevpn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevtk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevtk( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevtk( N, 1, x1, 2 )\n","base.strided.nanstdevtk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevwd( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevwd( N, 1, x1, 2 )\n","base.strided.nanstdevwd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevyc( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevyc( N, 1, x1, 2 )\n","base.strided.nanstdevyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariance":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariance( N, 1, x1, stride )\n","base.strided.nanvariance.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancech":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancech( N, 1, x1, stride )\n","base.strided.nanvariancech.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancepn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancepn( N, 1, x1, stride )\n","base.strided.nanvariancepn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancetk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancetk( N, 1, x1, stride )\n","base.strided.nanvariancetk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancewd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancewd( N, 1, x1, stride )\n","base.strided.nanvariancewd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvarianceyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvarianceyc( N, 1, x1, stride )\n","base.strided.nanvarianceyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.nullary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary( [ x ], shape, strides, fcn );\nx\n","base.strided.nullary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1 ];\nvar offsets = [ 0 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\nx\n","base.strided.quaternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\nu\n","base.strided.quaternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\nu\n","base.strided.quinary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\nv\n","base.strided.quinary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\nv\n","base.strided.range":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.range( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.range( N, x1, stride )\n","base.strided.range.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.range.ndarray( N, x, 2, 1 )\n","base.strided.rangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.rangeBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.rangeBy( N, x1, 2, accessor )\n","base.strided.rangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.sabs":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sabs2":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs2.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sapx":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nvar alpha = 5.0;\nbase.strided.sapx( x.length, alpha, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.sapx( N, alpha, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nalpha = 5.0;\nstride = 2;\nbase.strided.sapx( N, alpha, x1, stride )\nx0\n","base.strided.sapx.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nvar alpha = 5.0;\nbase.strided.sapx.ndarray( x.length, alpha, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.sapx.ndarray( N, alpha, x, stride, 1 )\n","base.strided.sapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sapxsum( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sapxsum( N, 5.0, x1, stride )\n","base.strided.sapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sapxsum.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sapxsumkbn( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sapxsumkbn( N, 5.0, x1, stride )\n","base.strided.sapxsumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sapxsumkbn2( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sapxsumkbn2( N, 5.0, x1, stride )\n","base.strided.sapxsumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.sapxsumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sapxsumors( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sapxsumors( N, 5.0, x1, stride )\n","base.strided.sapxsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.sapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sapxsumpw( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sapxsumpw( N, 5.0, x1, stride )\n","base.strided.sapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.sasum":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum( x.length, x, 1 )\ns = base.strided.sasum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.sasum( 3, x1, 2 )\n","base.strided.sasum.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.sasumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sasumpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sasumpw( N, x1, stride )\n","base.strided.sasumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sasumpw.ndarray( N, x, 2, 1 )\n","base.strided.saxpy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.saxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.saxpy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.scbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.scbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.sceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scopy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.scopy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumax( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scumax( N, x1, 2, y1, 1 )\ny0\n","base.strided.scumax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scumaxabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.scumaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumin( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scumin( N, x1, 2, y1, 1 )\ny0\n","base.strided.scumin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scuminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scuminabs( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scuminabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.scuminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scusum( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusum( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scusumkbn( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumkbn( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scusumkbn2( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumkbn2( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scusumors( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumors( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scusumpw( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumpw( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sdeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.sdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdot( 3, x1, -2, y1, 1 )\n","base.strided.sdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsapxsum( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsapxsum( N, 5.0, x1, stride )\n","base.strided.sdsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsapxsum.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.sdsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsapxsumpw( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsapxsumpw( N, 5.0, x1, stride )\n","base.strided.sdsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.sdsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n","base.strided.sdsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsmean( N, x1, stride )\n","base.strided.sdsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsmean.ndarray( N, x, 2, 1 )\n","base.strided.sdsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsmeanors( N, x1, stride )\n","base.strided.sdsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n","base.strided.sdsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmean( N, x1, stride )\n","base.strided.sdsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n","base.strided.sdsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmeanors( N, x1, stride )\n","base.strided.sdsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.sdsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnansum( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnansum( N, x1, stride )\n","base.strided.sdsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnansum.ndarray( N, x, 2, 1 )\n","base.strided.sdsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnansumpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnansumpw( N, x1, stride )\n","base.strided.sdsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnansumpw.ndarray( N, x, 2, 1 )\n","base.strided.sdssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdssum( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdssum( N, x1, stride )\n","base.strided.sdssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdssum.ndarray( N, x, 2, 1 )\n","base.strided.sdssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdssumpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdssumpw( N, x1, stride )\n","base.strided.sdssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdssumpw.ndarray( N, x, 2, 1 )\n","base.strided.sfill":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sfill( N, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.sfill( N, 5.0, x1, 2 )\nx0\n","base.strided.sfill.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sfill.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.sfloor":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.sfloor.ndarray":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.sinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.smap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( x.length, x, 1, y, 1, base.identityf )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( 2, x, 2, y, -1, base.identityf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap( 2, x1, -2, y1, 1, base.identityf )\ny0\n","base.strided.smap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n","base.strided.smap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\nz0\n","base.strided.smap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n","base.strided.smax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smax( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smax( N, x1, stride )\n","base.strided.smax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smax.ndarray( N, x, 2, 1 )\n","base.strided.smaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smaxabs( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smaxabs( N, x1, stride )\n","base.strided.smaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smaxabs.ndarray( N, x, 2, 1 )\n","base.strided.smaxabssorted":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smaxabssorted( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smaxabssorted( N, x1, stride )\n","base.strided.smaxabssorted.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smaxabssorted.ndarray( N, x, 2, 1 )\n","base.strided.smaxsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smaxsorted( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smaxsorted( N, x1, stride )\n","base.strided.smaxsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smaxsorted.ndarray( N, x, 2, 1 )\n","base.strided.smean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smean( N, x1, stride )\n","base.strided.smean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smean.ndarray( N, x, 2, 1 )\n","base.strided.smeankbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeankbn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeankbn( N, x1, stride )\n","base.strided.smeankbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeankbn.ndarray( N, x, 2, 1 )\n","base.strided.smeankbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeankbn2( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeankbn2( N, x1, stride )\n","base.strided.smeankbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeankbn2.ndarray( N, x, 2, 1 )\n","base.strided.smeanli":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanli( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanli( N, x1, stride )\n","base.strided.smeanli.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanli.ndarray( N, x, 2, 1 )\n","base.strided.smeanlipw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanlipw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanlipw( N, x1, stride )\n","base.strided.smeanlipw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanlipw.ndarray( N, x, 2, 1 )\n","base.strided.smeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanors( N, x1, stride )\n","base.strided.smeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanors.ndarray( N, x, 2, 1 )\n","base.strided.smeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanpn( N, x1, stride )\n","base.strided.smeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanpn.ndarray( N, x, 2, 1 )\n","base.strided.smeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanpw( N, x1, stride )\n","base.strided.smeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanpw.ndarray( N, x, 2, 1 )\n","base.strided.smeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanwd( N, x1, stride )\n","base.strided.smeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanwd.ndarray( N, x, 2, 1 )\n","base.strided.smediansorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smediansorted( N, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smediansorted( N, x1, 2 )\n","base.strided.smediansorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smediansorted.ndarray( N, x, 2, 1 )\n","base.strided.smidrange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smidrange( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smidrange( N, x1, stride )\n","base.strided.smidrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smidrange.ndarray( N, x, 2, 1 )\n","base.strided.smin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smin( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smin( N, x1, stride )\n","base.strided.smin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smin.ndarray( N, x, 2, 1 )\n","base.strided.sminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sminabs( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sminabs( N, x1, stride )\n","base.strided.sminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sminabs.ndarray( N, x, 2, 1 )\n","base.strided.sminsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sminsorted( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sminsorted( N, x1, stride )\n","base.strided.sminsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sminsorted.ndarray( N, x, 2, 1 )\n","base.strided.smskabs":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskabs2":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs2.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskcbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskcbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskfloor":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskfloor.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskmap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.smskmap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.smskmap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\nz0\n","base.strided.smskmap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n","base.strided.smskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmax( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smskmax( N, x1, 2, mask1, 2 )\n","base.strided.smskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.smskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmin( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smskmin( N, x1, 2, mask1, 2 )\n","base.strided.smskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.smskramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskrange( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smskrange( N, x1, 2, mask1, 2 )\n","base.strided.smskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.smskrsqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskrsqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsksqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsksqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsktrunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsktrunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.snanmax":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmax( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmax( N, x1, stride )\n","base.strided.snanmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmax.ndarray( N, x, 2, 1 )\n","base.strided.snanmaxabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmaxabs( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmaxabs( N, x1, stride )\n","base.strided.snanmaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmaxabs.ndarray( N, x, 2, 1 )\n","base.strided.snanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmean( N, x1, stride )\n","base.strided.snanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmean.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanors( N, x1, stride )\n","base.strided.snanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanpn( N, x1, stride )\n","base.strided.snanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanwd( N, x1, stride )\n","base.strided.snanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.snanmin":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmin( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmin( N, x1, stride )\n","base.strided.snanmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmin.ndarray( N, x, 2, 1 )\n","base.strided.snanminabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanminabs( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanminabs( N, x1, stride )\n","base.strided.snanminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanminabs.ndarray( N, x, 2, 1 )\n","base.strided.snanmskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.snanmskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.snanmskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.snanmskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanrange":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanrange( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanrange( N, x1, stride )\n","base.strided.snanrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanrange.ndarray( N, x, 2, 1 )\n","base.strided.snanstdev":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdev( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdev( N, 1, x1, stride )\n","base.strided.snanstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevch":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevch( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevch( N, 1, x1, stride )\n","base.strided.snanstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevpn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevpn( N, 1, x1, stride )\n","base.strided.snanstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevtk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevtk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevtk( N, 1, x1, stride )\n","base.strided.snanstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevwd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevwd( N, 1, x1, stride )\n","base.strided.snanstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevyc( N, 1, x1, stride )\n","base.strided.snanstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snansum( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snansum( N, x1, stride )\n","base.strided.snansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snansum.ndarray( N, x, 2, 1 )\n","base.strided.snansumkbn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snansumkbn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snansumkbn( N, x1, stride )\n","base.strided.snansumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snansumkbn.ndarray( N, x, 2, 1 )\n","base.strided.snansumkbn2":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snansumkbn2( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snansumkbn2( N, x1, stride )\n","base.strided.snansumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snansumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.snansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snansumors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snansumors( N, x1, stride )\n","base.strided.snansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snansumors.ndarray( N, x, 2, 1 )\n","base.strided.snansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snansumpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snansumpw( N, x1, stride )\n","base.strided.snansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snansumpw.ndarray( N, x, 2, 1 )\n","base.strided.snanvariance":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariance( N, 1, x1, 2 )\n","base.strided.snanvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancech":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancech( N, 1, x1, 2 )\n","base.strided.snanvariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancepn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancepn( N, 1, x1, 2 )\n","base.strided.snanvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancetk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancetk( N, 1, x1, 2 )\n","base.strided.snanvariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancewd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancewd( N, 1, x1, 2 )\n","base.strided.snanvariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvarianceyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x1, 2 )\n","base.strided.snanvarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snrm2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.snrm2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snrm2( 3, x1, 2 )\n","base.strided.snrm2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.snrm2.ndarray( 3, x, 2, 1 )\n","base.strided.sramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.sramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.srange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.srange( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.srange( N, x1, stride )\n","base.strided.srange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.srange.ndarray( N, x, 2, 1 )\n","base.strided.srev":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srev( 3, x1, 2 )\nx0\n","base.strided.srev.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.srev.ndarray( 3, x, 2, 1 )\n","base.strided.srsqrt":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.srsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.srsqrt.ndarray":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sscal":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.sscal.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.ssort2hp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2hp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2ins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssort2ins( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssort2ins( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2ins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2sh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2sh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssorthp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssorthp( N, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssorthp( N, 1, x1, 2 )\nx0\n","base.strided.ssorthp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssorthp.ndarray( N, 1, x, 2, 1 )\n","base.strided.ssortins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssortins( N, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssortins( N, 1, x1, 2 )\nx0\n","base.strided.ssortins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssortins.ndarray( N, 1, x, 2, 1 )\n","base.strided.ssortsh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssortsh( N, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssortsh( N, 1, x1, 2 )\nx0\n","base.strided.ssortsh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.ssqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.ssqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sstdev":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdev( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdev( N, 1, x1, stride )\n","base.strided.sstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevch":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevch( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevch( N, 1, x1, stride )\n","base.strided.sstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevpn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevpn( N, 1, x1, stride )\n","base.strided.sstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevtk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevtk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevtk( N, 1, x1, stride )\n","base.strided.sstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevwd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevwd( N, 1, x1, stride )\n","base.strided.sstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevyc( N, 1, x1, stride )\n","base.strided.sstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.ssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.ssum( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.ssum( N, x1, stride )\n","base.strided.ssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssum.ndarray( N, x, 2, 1 )\n","base.strided.ssumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn( 3, x1, 2 )\n","base.strided.ssumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.ssumkbn2( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.ssumkbn2( N, x1, stride )\n","base.strided.ssumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.ssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumors( 3, x1, 2 )\n","base.strided.ssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumors.ndarray( 3, x, 2, 1 )\n","base.strided.ssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumpw( 3, x1, 2 )\n","base.strided.ssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sswap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.sswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.sswap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.stdev":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdev( N, 1, x1, stride )\n","base.strided.stdev.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevch":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevch( N, 1, x1, stride )\n","base.strided.stdevch.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevpn( N, 1, x1, stride )\n","base.strided.stdevpn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevtk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevtk( N, 1, x1, stride )\n","base.strided.stdevtk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevwd( N, 1, x1, stride )\n","base.strided.stdevwd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevyc( N, 1, x1, stride )\n","base.strided.stdevyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.strunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.strunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.strunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.svariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariance( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariance( N, 1, x1, stride )\n","base.strided.svariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancech":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancech( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancech( N, 1, x1, stride )\n","base.strided.svariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancepn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancepn( N, 1, x1, stride )\n","base.strided.svariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancetk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancetk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancetk( N, 1, x1, stride )\n","base.strided.svariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancewd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancewd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancewd( N, 1, x1, stride )\n","base.strided.svariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.svarianceyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svarianceyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svarianceyc( N, 1, x1, stride )\n","base.strided.svarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.ternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary( [ x, y, z, w ], shape, strides, f );\nw\n","base.strided.ternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\nw\n","base.strided.unary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nbase.strided.unary( [ x, y ], shape, strides, base.abs );\ny\n","base.strided.unary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar offsets = [ 0, 0 ];\nbase.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.unaryBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nsh = [ 2 ];\nst = [ -2, 1 ];\nbase.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\ny1\ny0\n","base.strided.unaryBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nvar o = [ 0, 0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\no = [ 1, y.length-1 ];\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\n","base.strided.unaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.unaryDtypeSignatures( dt, dt )\n","base.strided.unarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.unaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.unarySignatureCallbacks( t, sigs )\n","base.strided.variance":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variance( N, 1, x1, stride )\n","base.strided.variance.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variance.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancech":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancech( N, 1, x1, stride )\n","base.strided.variancech.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancepn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancepn( N, 1, x1, stride )\n","base.strided.variancepn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancetk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancetk( N, 1, x1, stride )\n","base.strided.variancetk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancewd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancewd( N, 1, x1, stride )\n","base.strided.variancewd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.varianceyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.varianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.varianceyc( N, 1, x1, stride )\n","base.strided.varianceyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.zmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap( x.length, x, 1, y, 1, base.cidentity );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\ny = new Complex128Array( x.length );\nbase.strided.zmap( 2, x, 2, y, -1, base.cidentity );\nv = y.get( 0 )\nre = real( v )\nim = imag( v )\nvar x0 = new Complex128Array( xbuf );\nvar y0 = new Complex128Array( x0.length );\nvar x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.zmap( 2, x1, -2, y1, 1, base.cidentity );\nv = y1.get( 0 )\nre = real( v )\nim = imag( v )\n","base.strided.zmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\nx = new Complex128Array( xbuf );\ny = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\nv = y.get( y.length-1 )\nre = real( v )\nim = imag( v )\n","base.sub":"var v = base.sub( -1.0, 5.0 )\nv = base.sub( 2.0, 5.0 )\nv = base.sub( 0.0, 5.0 )\nv = base.sub( -0.0, 0.0 )\nv = base.sub( NaN, NaN )\n","base.subf":"var v = base.subf( -1.0, 5.0 )\nv = base.subf( 2.0, 5.0 )\nv = base.subf( 0.0, 5.0 )\nv = base.subf( -0.0, 0.0 )\nv = base.subf( NaN, NaN )\n","base.sumSeries":"function* geometricSeriesGenerator( x ) {\n var exponent = 0;\n while ( true ) {\n yield Math.pow( x, exponent );\n exponent += 1;\n }\n };\nvar gen = geometricSeriesGenerator( 0.9 );\nvar out = base.sumSeries( gen )\nfunction geometricSeriesClosure( x ) {\n var exponent = -1;\n return function() {\n exponent += 1;\n return Math.pow( x, exponent );\n };\n };\ngen = geometricSeriesClosure( 0.9 );\nout = base.sumSeries( gen )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n","base.tan":"var y = base.tan( 0.0 )\ny = base.tan( -PI/4.0 )\ny = base.tan( PI/4.0 )\ny = base.tan( NaN )\n","base.tanh":"var y = base.tanh( 0.0 )\nvar y = base.tanh( -0.0 )\ny = base.tanh( 2.0 )\ny = base.tanh( -2.0 )\ny = base.tanh( NaN )\n","base.toBinaryString":"var str = base.toBinaryString( 4.0 )\nstr = base.toBinaryString( PI )\nstr = base.toBinaryString( -1.0e308 )\nstr = base.toBinaryString( -3.14e-320 )\nstr = base.toBinaryString( 5.0e-324 )\nstr = base.toBinaryString( 0.0 )\nstr = base.toBinaryString( -0.0 )\nstr = base.toBinaryString( NaN )\nstr = base.toBinaryString( PINF )\nstr = base.toBinaryString( NINF )\n","base.toBinaryStringf":"var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( PI ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\nstr = base.toBinaryStringf( 0.0 )\nstr = base.toBinaryStringf( -0.0 )\nstr = base.toBinaryStringf( NaN )\nstr = base.toBinaryStringf( FLOAT32_PINF )\nstr = base.toBinaryStringf( FLOAT32_NINF )\n","base.toBinaryStringUint8":"var a = new Uint8Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint8( a[ 0 ] )\nstr = base.toBinaryStringUint8( a[ 1 ] )\nstr = base.toBinaryStringUint8( a[ 2 ] )\n","base.toBinaryStringUint16":"var a = new Uint16Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint16( a[ 0 ] )\nstr = base.toBinaryStringUint16( a[ 1 ] )\nstr = base.toBinaryStringUint16( a[ 2 ] )\n","base.toBinaryStringUint32":"var a = new Uint32Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint32( a[ 0 ] )\nstr = base.toBinaryStringUint32( a[ 1 ] )\nstr = base.toBinaryStringUint32( a[ 2 ] )\n","base.toWordf":"var f32 = base.float64ToFloat32( 1.337 )\nvar w = base.toWordf( f32 )\n","base.toWords":"var w = base.toWords( 3.14e201 )\n","base.toWords.assign":"var out = new Uint32Array( 2 );\nvar w = base.toWords.assign( 3.14e201, out, 1, 0 )\nvar bool = ( w === out )\n","base.transpose":"var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nvar sh = x.shape\nvar y = base.transpose( x )\nsh = y.shape\nvar bool = ( x.data === y.data )\nbool = ( x.get( 0, 1 ) === y.get( 1, 0 ) )\n","base.tribonacci":"var y = base.tribonacci( 0 )\ny = base.tribonacci( 1 )\ny = base.tribonacci( 2 )\ny = base.tribonacci( 3 )\ny = base.tribonacci( 4 )\ny = base.tribonacci( 64 )\ny = base.tribonacci( NaN )\n","base.trigamma":"var y = base.trigamma( -2.5 )\ny = base.trigamma( 1.0 )\ny = base.trigamma( 10.0 )\ny = base.trigamma( NaN )\ny = base.trigamma( -1.0 )\n","base.trunc":"var y = base.trunc( 3.14 )\ny = base.trunc( -4.2 )\ny = base.trunc( -4.6 )\ny = base.trunc( 9.5 )\ny = base.trunc( -0.0 )\n","base.trunc2":"var y = base.trunc2( 3.14 )\ny = base.trunc2( -4.2 )\ny = base.trunc2( -4.6 )\ny = base.trunc2( 9.5 )\ny = base.trunc2( 13.0 )\ny = base.trunc2( -13.0 )\ny = base.trunc2( -0.0 )\n","base.trunc10":"var y = base.trunc10( 3.14 )\ny = base.trunc10( -4.2 )\ny = base.trunc10( -4.6 )\ny = base.trunc10( 9.5 )\ny = base.trunc10( 13.0 )\ny = base.trunc10( -13.0 )\ny = base.trunc10( -0.0 )\n","base.truncb":"var y = base.truncb( 3.14159, -4, 10 )\ny = base.truncb( 3.14159, 0, 2 )\ny = base.truncb( 5.0, 1, 2 )\n","base.truncf":"var y = base.truncf( 3.14 )\ny = base.truncf( -4.2 )\ny = base.truncf( -4.6 )\ny = base.truncf( 9.5 )\ny = base.truncf( -0.0 )\n","base.truncn":"var y = base.truncn( 3.14159, -4 )\ny = base.truncn( 3.14159, 0 )\ny = base.truncn( 12368.0, 3 )\n","base.truncsd":"var y = base.truncsd( 3.14159, 5 )\ny = base.truncsd( 3.14159, 1 )\ny = base.truncsd( 12368.0, 2 )\ny = base.truncsd( 0.0313, 2, 2 )\n","base.umul":"var v = base.umul( 10>>>0, 4>>>0 )\n","base.umuldw":"var v = base.umuldw( 1, 10 )\n","base.umuldw.assign":"var out = [ 0, 0 ];\nvar v = base.umuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.uint32ToInt32":"var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\ny = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n","base.vercos":"var y = base.vercos( 3.14 )\ny = base.vercos( -4.2 )\ny = base.vercos( -4.6 )\ny = base.vercos( 9.5 )\ny = base.vercos( -0.0 )\n","base.versin":"var y = base.versin( 3.14 )\ny = base.versin( -4.2 )\ny = base.versin( -4.6 )\ny = base.versin( 9.5 )\ny = base.versin( -0.0 )\n","base.wrap":"var y = base.wrap( 3.14, 0.0, 5.0 )\ny = base.wrap( -3.14, 0.0, 5.0 )\ny = base.wrap( 3.14, 0.0, 3.0 )\ny = base.wrap( -0.0, 0.0, 5.0 )\ny = base.wrap( 0.0, -3.14, -0.0 )\ny = base.wrap( NaN, 0.0, 5.0 )\n","base.xlog1py":"var out = base.xlog1py( 3.0, 2.0 )\nout = base.xlog1py( 1.5, 5.9 )\nout = base.xlog1py( 0.9, 1.0 )\nout = base.xlog1py( 1.0, 0.0 )\nout = base.xlog1py( 0.0, -2.0 )\nout = base.xlog1py( 1.5, NaN )\nout = base.xlog1py( 0.0, NaN )\nout = base.xlog1py( NaN, 2.3 )\n","base.xlogy":"var out = base.xlogy( 3.0, 2.0 )\nout = base.xlogy( 1.5, 5.9 )\nout = base.xlogy( 0.9, 1.0 )\nout = base.xlogy( 0.0, -2.0 )\nout = base.xlogy( 1.5, NaN )\nout = base.xlogy( 0.0, NaN )\nout = base.xlogy( NaN, 2.3 )\n","base.zeta":"var y = base.zeta( 1.1 )\ny = base.zeta( -4.0 )\ny = base.zeta( 70.0 )\ny = base.zeta( 0.5 )\ny = base.zeta( NaN )\ny = base.zeta( 1.0 )\n","BERNDT_CPS_WAGES_1985":"var data = BERNDT_CPS_WAGES_1985()\n","bifurcate":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar f = [ true, true, false, true ];\nvar out = bifurcate( collection, f )\nf = [ 1, 1, 0, 1 ];\nout = bifurcate( collection, f )\nf = [ true, true, false, true ];\nvar opts = { 'returns': 'indices' };\nout = bifurcate( collection, opts, f )\nopts = { 'returns': '*' };\nout = bifurcate( collection, opts, f )\n","bifurcateBy":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = bifurcateBy( collection, predicate )\nvar opts = { 'returns': 'indices' };\nout = bifurcateBy( collection, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateBy( collection, opts, predicate )\n","bifurcateByAsync":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, predicate, done )\nvar opts = { 'returns': 'indices' };\nbifurcateByAsync( arr, opts, predicate, done )\nopts = { 'returns': '*' };\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\n","bifurcateByAsync.factory":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = bifurcateByAsync.factory( opts, predicate );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","bifurcateIn":"function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nfunction predicate( v ) { return v[ 0 ] === 'b'; };\nvar out = bifurcateIn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateIn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateIn( obj, opts, predicate )\n","bifurcateOwn":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = bifurcateOwn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateOwn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateOwn( obj, opts, predicate )\n","BigInt":"var v = ( BigInt ) ? BigInt( '1' ) : null\n","binomialTest":"var out = binomialTest( 682, 925 )\nout = binomialTest( [ 682, 925 - 682 ] )\nout = binomialTest( 21, 40, {\n 'p': 0.4,\n 'alternative': 'greater'\n })\n","Boolean":"var b = new Boolean( null )\nb = Boolean( null )\nb = Boolean( [] )\n","Boolean.prototype.toString":"var b = new Boolean( true )\nb.toString()\n","Boolean.prototype.valueOf":"var b = new Boolean( true )\nb.valueOf()\n","broadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = broadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","broadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = broadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","Buffer":"var b = new Buffer( 4 )\nvar b1 = new Buffer( [ 1, 2, 3, 4 ] );\nvar b2 = new Buffer( b1 )\nvar b = new Buffer( [ 1, 2, 3, 4 ] )\nvar b = new Buffer( 'beep boop' )\n","buffer2json":"var buf = new allocUnsafe( 2 );\nbuf[ 0 ] = 1;\nbuf[ 1 ] = 2;\nvar json = buffer2json( buf )\n","BYTE_ORDER":"BYTE_ORDER\n","camelcase":"var out = camelcase( 'Hello World!' )\nout = camelcase( 'beep boop' )\n","capitalize":"var out = capitalize( 'beep' )\nout = capitalize( 'Boop' )\n","capitalizeKeys":"var obj = { 'aa': 1, 'bb': 2 };\nvar out = capitalizeKeys( obj )\n","CATALAN":"CATALAN\n","CBRT_EPS":"CBRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"var data = CDC_NCHS_US_BIRTHS_1969_1988()\n","CDC_NCHS_US_BIRTHS_1994_2003":"var data = CDC_NCHS_US_BIRTHS_1994_2003()\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n","chdir":"var err = chdir( '/path/to/current/working/directory' )\n","chi2gof":"var x = [ 89, 37, 30, 28, 2 ];\nvar p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nvar out = chi2gof( x, p );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.01 };\nout = chi2gof( x, p, opts );\nout.toString()\nx = [ 89, 37, 30, 28, 2 ];\np = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nopts = { 'simulate': true, 'iterations': 1000 };\nout = chi2gof( x, p, opts );\nout.toString()\nvar lambda = 3.0;\nvar rpois = base.random.poisson.factory( lambda );\nvar len = 400;\nx = [];\nfor ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\nvar freqs = new Int32Array( len );\nfor ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\nout = chi2gof( freqs, 'poisson', lambda );\nout.toString()\n","chi2test":"var x = [ [ 20, 30 ], [ 30, 20 ] ];\nvar out = chi2test( x );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.1 };\nout = chi2test( x, opts );\no = out.toJSON()\nout.toString()\nopts = { 'correct': false };\nout = chi2test( x, opts );\nout.toString()\n","circarray2iterator":"var it = circarray2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","circularArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","circularArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = circularArrayStream.factory( opts );\n","circularArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","CircularBuffer":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.length\nb.count\nb.push( 'boop' )\n","CircularBuffer.prototype.clear":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.count\nb.clear();\nb.count\n","CircularBuffer.prototype.count":"var b = CircularBuffer( 3 );\nb.count\nb.push( 'foo' );\nb.count\nb.push( 'bar' );\nb.count\n","CircularBuffer.prototype.full":"var b = CircularBuffer( 3 );\nb.full\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.full\n","CircularBuffer.prototype.iterator":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar it = b.iterator( b.length );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","CircularBuffer.prototype.length":"var b = CircularBuffer( [ 0, 0, 0 ] );\nvar len = b.length\n","CircularBuffer.prototype.push":"var b = CircularBuffer( 3 );\nb.push( 'foo' )\nb.push( 'bar' )\nb.push( 'beep' )\nb.push( 'boop' )\n","CircularBuffer.prototype.toArray":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar vals = b.toArray()\n","CircularBuffer.prototype.toJSON":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar o = b.toJSON()\n","close":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nvar fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close( fd, done ); };\n","close.sync":"var fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","CMUDICT":"var data = CMUDICT();\nvar dict = data.dict\nvar phones = data.phones\nvar symbols = data.symbols\nvar vp = data.vp\n","codePointAt":"var out = codePointAt( 'last man standing', 4 )\nout = codePointAt( 'presidential election', 8, true )\nout = codePointAt( 'अनुच्छेद', 2 )\nout = codePointAt( '🌷', 1, true )\n","commonKeys":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeys( obj1, obj2 )\n","commonKeysIn":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeysIn( obj1, obj2 )\n","complex":"var z = complex( 5.0, 3.0, 'float64' )\nz = complex( 5.0, 3.0, 'float32' )\n","Complex64":"var z = new Complex64( 5.0, 3.0 )\nz.re\nz.im\n","COMPLEX64_NAN":"COMPLEX64_NAN\n","COMPLEX64_NUM_BYTES":"COMPLEX64_NUM_BYTES\n","COMPLEX64_ZERO":"COMPLEX64_ZERO\n","Complex128":"var z = new Complex128( 5.0, 3.0 )\nz.re\nz.im\n","COMPLEX128_NAN":"COMPLEX128_NAN\n","COMPLEX128_NUM_BYTES":"COMPLEX128_NUM_BYTES\n","COMPLEX128_ZERO":"COMPLEX128_ZERO\n","complexarray":"var arr = complexarray()\narr = complexarray( 'complex64' )\nvar arr = complexarray( 5 )\narr = complexarray( 5, 'complex64' )\nvar arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\nvar arr2 = complexarray( arr1, 'complex64' )\nvar arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\nvar arr2 = complexarray( arr1, 'complex64' )\nvar buf = new ArrayBuffer( 64 );\nvar arr = complexarray( buf, 0, 8, 'complex64' )\n","complexarrayCtors":"var ctor = complexarrayCtors( 'complex64' )\nctor = complexarrayCtors( 'float32' )\n","complexarrayDataTypes":"var out = complexarrayDataTypes()\n","complexCtors":"var ctor = complexCtors( 'complex128' )\nctor = complexCtors( 'complex' )\n","complexDataType":"var v = new Complex128( 1.0, 2.0 );\nvar dt = complexDataType( v )\ndt = complexDataType( 'beep' )\n","complexDataTypes":"var out = complexDataTypes()\n","complexPromotionRules":"var out = complexPromotionRules( 'complex128', 'complex64' )\n","compose":"function a( x ) {\nreturn 2 * x;\n }\nfunction b( x ) {\nreturn x + 3;\n }\nfunction c( x ) {\nreturn x / 5;\n }\nvar f = compose( c, b, a );\nvar z = f( 6 )\n","composeAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x/5 );\n}\n };\nvar f = composeAsync( c, b, a );\nfunction done( error, result ) {\nif ( error ) {\n throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","configdir":"var dir = configdir()\ndir = configdir( 'appname/config' )\n","conj":"var z = new Complex128( 5.0, 3.0 );\nz.toString()\nvar v = conj( z );\nv.toString()\n","conjf":"var z = new Complex64( 5.0, 3.0 );\nz.toString()\nvar v = conjf( z );\nv.toString()\n","constantcase":"var out = constantcase( 'Hello World!' )\nout = constantcase( 'I am a tiny little teapot' )\n","constantFunction":"var fcn = constantFunction( 3.14 );\nvar v = fcn()\nv = fcn()\nv = fcn()\n","constantStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream( 'beep', opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","constantStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = constantStream.factory( opts );\n","constantStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream.objectMode( 3.14, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","constructorName":"var v = constructorName( 'a' )\nv = constructorName( {} )\nv = constructorName( true )\n","contains":"var bool = contains( 'Hello World', 'World' )\nbool = contains( 'Hello World', 'world' )\nbool = contains( [ 1, 2, 3, 4 ], 2 )\nbool = contains( [ NaN, 2, 3, 4 ], NaN )\nbool = contains( 'Hello World', 'Hello', 6 )\nbool = contains( [ true, NaN, false ], true, 1 )\n","convertArray":"var arr = [ 1.0, 2.0, 3.0, 4.0 ];\nvar out = convertArray( arr, 'float32' )\n","convertArraySame":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = new Float32Array( 0 );\nvar out = convertArraySame( x, y )\n","convertPath":"var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\nout = convertPath( '/c/foo/bar/beep.c', 'mixed' )\nout = convertPath( '/c/foo/bar/beep.c', 'posix' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n","copy":"var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nvar out = copy( value )\nvar bool = ( value[ 0 ].c === out[ 0 ].c )\nvalue = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nout = copy( value, 1 );\nbool = ( value[ 0 ] === out[ 0 ] )\nbool = ( value[ 0 ].c === out[ 0 ].c )\n","copyBuffer":"var b1 = array2buffer( [ 1, 2, 3, 4 ] );\nvar b2 = copyBuffer( b1 )\n","countBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = countBy( collection, indicator )\n","countByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\n","countByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = countByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 500 ];\nf( arr, done )\n","currentYear":"var y = currentYear()\n","curry":"function add( x, y ) { return x + y; };\nvar f = curry( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curry( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curry( obj.greet, obj );\nvar str = f( 'Hello' )( 'there' )\n","curryRight":"function add( x, y ) { return x + y; };\nvar f = curryRight( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curryRight( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curryRight( obj.greet, obj );\nvar str = f( 'there' )( 'Hello' )\n","cwd":"var dir = cwd()\n","DALE_CHALL_NEW":"var list = DALE_CHALL_NEW()\n","datasets":"var out = datasets( 'MONTH_NAMES_EN' )\nvar opts = { 'data': 'cities' };\nout = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n","DataView":"var buf = new ArrayBuffer( 5 )\nvar dv = new DataView( buf )\n","DataView.prototype.buffer":"var buf1 = new ArrayBuffer( 5 );\nvar dv = new DataView( buf1 );\nvar buf2 = dv.buffer\nvar b = ( buf1 === buf2 )\n","DataView.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf );\ndv.byteLength\n","DataView.prototype.byteOffset":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf, 2 );\ndv.byteLength\ndv.byteOffset\n","datespace":"var stop = '2014-12-02T07:00:54.973Z';\nvar start = new Date( stop ) - 60000;\nvar arr = datespace( start, stop, 6 )\nvar opts = { 'round': 'ceil' };\narr = datespace( 1417503655000, 1417503655001, 3, opts )\n","dayOfQuarter":"var day = dayOfQuarter()\nday = dayOfQuarter( new Date() )\nday = dayOfQuarter( 12, 31, 2017 )\nday = dayOfQuarter( 'dec', 31, 2017 )\nday = dayOfQuarter( 'december', 31, 2017 )\n","dayOfYear":"var day = dayOfYear()\nday = dayOfYear( new Date() )\nday = dayOfYear( 12, 31, 2016 )\nday = dayOfYear( 'dec', 31, 2016 )\nday = dayOfYear( 'december', 31, 2016 )\n","daysInMonth":"var num = daysInMonth()\nnum = daysInMonth( 2 )\nnum = daysInMonth( 2, 2016 )\nnum = daysInMonth( 2, 2017 )\nnum = daysInMonth( 'feb', 2016 )\nnum = daysInMonth( 'february', 2016 )\n","daysInYear":"var num = daysInYear()\nnum = daysInYear( 2016 )\nnum = daysInYear( 2017 )\n","ddot":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\nddot( x, y )\n","debugSinkStream":"var s = debugSinkStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugSinkStream.factory( opts );\n","debugSinkStream.objectMode":"var s = debugSinkStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","debugStream":"var s = debugStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugStream.factory( opts );\n","debugStream.objectMode":"var s = debugStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","decorateAfter":"function f( v ) { return -v; };\nvar fcn = decorateAfter( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","decorateAfter.factory":"function f( v ) { return -v; };\nvar fcn = decorateAfter.factory( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","deepEqual":"var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\nbool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\nbool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n","deepGet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a.b.c' )\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n","deepGet.factory":"var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = dget( obj )\n","deepHasOwnProp":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepHasOwnProp( obj, 'a.b.c' )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasOwnProp.factory":"var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = has( obj )\n","deepHasProp":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar obj = { 'a': new Foo() };\nvar bool = deepHasProp( obj, 'a.b.c' )\nbool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasProp.factory":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': new Foo() };\nvar bool = has( obj )\n","deepPluck":"var arr = [\n { 'a': { 'b': { 'c': 1 } } },\n { 'a': { 'b': { 'c': 2 } } }\n ];\nvar out = deepPluck( arr, 'a.b.c' )\narr = [\n { 'a': [ 0, 1, 2 ] },\n { 'a': [ 3, 4, 5 ] }\n ];\nout = deepPluck( arr, [ 'a', 1 ] )\n","deepSet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepSet( obj, 'a.b.c', 'beep' )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\nobj\nbool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\nobj\n","deepSet.factory":"var dset = deepSet.factory( 'a/b/c', {\n 'create': true,\n 'sep': '/'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = dset( obj, 'beep' )\nobj\n","defineMemoizedProperty":"var obj = {};\nfunction foo() {\n return 'bar';\n };\ndefineMemoizedProperty( obj, 'foo', {\n 'configurable': false,\n 'enumerable': true,\n 'writable': false,\n 'value': foo\n });\nobj.foo\n","defineProperties":"var obj = {};\ndefineProperties( obj, {\n 'foo': {\n 'value': 'bar',\n 'writable': false,\n 'configurable': false,\n 'enumerable': true\n },\n 'baz': {\n 'value': 13\n }\n });\nobj.foo\nobj.baz\n","defineProperty":"var obj = {};\ndefineProperty( obj, 'foo', {\n 'value': 'bar',\n 'enumerable': true,\n 'writable': false\n });\nobj.foo = 'boop';\nobj\n","dirname":"var dir = dirname( './foo/bar/index.js' )\n","dotcase":"var out = dotcase( 'Hello World!' )\nout = dotcase( 'beep boop' )\n","DoublyLinkedList":"var list = DoublyLinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","doUntil":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoUntil( beep, predicate )\n","doUntilAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ndoUntilAsync( fcn, predicate, done )\n","doUntilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoUntilEach( arr, logger, predicate )\n","doUntilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoUntilEachRight( arr, logger, predicate )\n","doWhile":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoWhile( beep, predicate )\n","doWhileAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ndoWhileAsync( fcn, predicate, done )\n","doWhileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoWhileEach( arr, logger, predicate )\n","doWhileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoWhileEachRight( arr, logger, predicate )\n","dswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ndswap( x, y );\nx.data\ny.data\n","E":"E\n","EMOJI":"var data = EMOJI()\n","EMOJI_CODE_PICTO":"var out = EMOJI_CODE_PICTO()\n","EMOJI_PICTO_CODE":"var out = EMOJI_PICTO_CODE()\n","emptyStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = emptyStream();\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","emptyStream.factory":"var opts = { 'objectMode': true };\nvar createStream = emptyStream.factory( opts );\n","emptyStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = emptyStream.objectMode();\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","endsWith":"var bool = endsWith( 'beep', 'ep' )\nbool = endsWith( 'Beep', 'op' )\nbool = endsWith( 'Beep', 'ee', 3 )\nbool = endsWith( 'Beep', 'ee', -1 )\nbool = endsWith( 'beep', '' )\n","enumerableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = enumerableProperties( obj )\n","enumerablePropertiesIn":"var props = enumerablePropertiesIn( [] )\n","enumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbols( obj )\n","enumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbolsIn( obj )\n","ENV":"var user = ENV.USER\n","EPS":"EPS\n","error2json":"var err = new Error( 'beep' );\nvar json = error2json( err )\n","EULERGAMMA":"EULERGAMMA\n","every":"var arr = [ 1, 1, 1, 1, 1 ];\nvar bool = every( arr )\n","everyBy":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyBy( arr, positive )\n","everyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\n","everyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","everyByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyByRight( arr, positive )\n","everyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\n","everyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","evil":"var v = evil( '5*4*3*2*1' )\n","EXEC_PATH":"EXEC_PATH\n","exists":"function done( error, bool ) { console.log( bool ); };\nexists( './beep/boop', done );\n","exists.sync":"var bool = exists.sync( './beep/boop' )\n","expandAcronyms":"var str = 'LOL, this is fun. I am ROFL.';\nvar out = expandAcronyms( str )\nstr = 'brb, I need to check my mail. thx!';\nout = expandAcronyms( str )\n","expandContractions":"var str = 'I won\\'t be able to get y\\'all out of this one.';\nvar out = expandContractions( str )\nstr = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\nout = expandContractions( str )\n","extname":"var ext = extname( 'index.js' )\n","FancyArray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","FancyArray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","FancyArray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","FancyArray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","FancyArray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","FancyArray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","FancyArray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","FancyArray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","FancyArray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","FancyArray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","FancyArray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","FancyArray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","FancyArray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","FancyArray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","FancyArray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","FancyArray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","fastmath.abs":"var v = fastmath.abs( -1.0 )\nv = fastmath.abs( 2.0 )\nv = fastmath.abs( 0.0 )\nv = fastmath.abs( -0.0 )\nv = fastmath.abs( NaN )\n","fastmath.acosh":"var v = fastmath.acosh( 1.0 )\nv = fastmath.acosh( 2.0 )\nv = fastmath.acosh( NaN )\nv = fastmath.acosh( 1.0e308 )\n","fastmath.ampbm":"var h = fastmath.ampbm( 5.0, 12.0 )\n","fastmath.ampbm.factory":"var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n","fastmath.asinh":"var v = fastmath.asinh( 0.0 )\nv = fastmath.asinh( 2.0 )\nv = fastmath.asinh( -2.0 )\nv = fastmath.asinh( NaN )\nv = fastmath.asinh( 1.0e200 )\nv = fastmath.asinh( 1.0e-50 )\n","fastmath.atanh":"var v = fastmath.atanh( 0.0 )\nv = fastmath.atanh( 0.9 )\nv = fastmath.atanh( 1.0 )\nv = fastmath.atanh( -1.0 )\nv = fastmath.atanh( NaN )\nv = fastmath.atanh( 1.0e-17 )\n","fastmath.hypot":"var h = fastmath.hypot( -5.0, 12.0 )\nh = fastmath.hypot( 1.0e154, 1.0e154 )\nh = fastmath.hypot( 1e-200, 1.0e-200 )\n","fastmath.log2Uint32":"var v = fastmath.log2Uint32( 4 >>> 0 )\nv = fastmath.log2Uint32( 8 >>> 0 )\nv = fastmath.log2Uint32( 9 >>> 0 )\n","fastmath.max":"var v = fastmath.max( 3.14, 4.2 )\nv = fastmath.max( 3.14, NaN )\nv = fastmath.max( NaN, 3.14 )\nv = fastmath.max( -0.0, +0.0 )\nv = fastmath.max( +0.0, -0.0 )\n","fastmath.min":"var v = fastmath.min( 3.14, 4.2 )\nv = fastmath.min( 3.14, NaN )\nv = fastmath.min( NaN, 3.14 )\nv = fastmath.min( -0.0, +0.0 )\nv = fastmath.min( +0.0, -0.0 )\n","fastmath.powint":"var v = fastmath.powint( 2.0, 3 )\nv = fastmath.powint( 3.14, 0 )\nv = fastmath.powint( 2.0, -2 )\nv = fastmath.powint( 0.0, 0 )\nv = fastmath.powint( -3.14, 1 )\nv = fastmath.powint( NaN, 0 )\n","fastmath.sqrtUint32":"var v = fastmath.sqrtUint32( 9 >>> 0 )\nv = fastmath.sqrtUint32( 2 >>> 0 )\nv = fastmath.sqrtUint32( 3 >>> 0 )\nv = fastmath.sqrtUint32( 0 >>> 0 )\n","FEMALE_FIRST_NAMES_EN":"var list = FEMALE_FIRST_NAMES_EN()\n","FIFO":"var q = FIFO();\nq.push( 'foo' ).push( 'bar' );\nq.length\nq.pop()\nq.length\nq.pop()\nq.length\n","filledarray":"var arr = filledarray()\narr = filledarray( 'float32' )\nvar arr = filledarray( 1.0, 5 )\narr = filledarray( 1, 5, 'int32' )\nvar arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n","filledarrayBy":"var arr = filledarrayBy()\narr = filledarrayBy( 'float32' )\nfunction clbk() { return 1.0; };\nvar arr = filledarrayBy( 5, clbk )\narr = filledarrayBy( 5, 'int32', clbk )\nvar arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n","filterArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v !== 2 ); };\nvar bar = filterArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","find":"var data = [ 30, 20, 50, 60, 10 ];\nfunction condition( val ) { return val > 20; };\nvar vals = find( data, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nvar opts = { 'k': 2, 'returns': 'values' };\nvals = find( data, opts, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nopts = { 'k': -2, 'returns': '*' };\nvals = find( data, opts, condition )\n","firstChar":"var out = firstChar( 'beep' )\nout = firstChar( 'Boop', 1 )\nout = firstChar( 'foo bar', 5 )\n","FIVETHIRTYEIGHT_FFQ":"var data = FIVETHIRTYEIGHT_FFQ()\n","flattenArray":"var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nvar out = flattenArray( arr )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2 } )\nvar bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2, 'copy': true } )\nbool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n","flattenArray.factory":"var flatten = flattenArray.factory( [ 2, 2 ], {\n 'copy': false\n });\nvar out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\nout = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n","flattenObject":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flattenObject( obj )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'depth': 1 } )\nvar bool = ( obj.a.b === out[ 'a.b' ] )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'delimiter': '-|-' } )\nobj = { 'a': { 'b': [ 1, 2, 3 ] } };\nout = flattenObject( obj, { 'flattenArrays': true } )\n","flattenObject.factory":"var flatten = flattenObject.factory({\n 'depth': 1,\n 'copy': true,\n 'delimiter': '|'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flatten( obj )\n","flignerTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = flignerTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = flignerTest( arr, { 'groups': groups } )\n","FLOAT_WORD_ORDER":"FLOAT_WORD_ORDER\n","FLOAT16_CBRT_EPS":"FLOAT16_CBRT_EPS\n","FLOAT16_EPS":"FLOAT16_EPS\n","FLOAT16_EXPONENT_BIAS":"FLOAT16_EXPONENT_BIAS\n","FLOAT16_MAX":"FLOAT16_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"FLOAT16_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"FLOAT16_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"FLOAT16_NINF\n","FLOAT16_NUM_BYTES":"FLOAT16_NUM_BYTES\n","FLOAT16_PINF":"FLOAT16_PINF\n","FLOAT16_PRECISION":"FLOAT16_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"FLOAT16_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"FLOAT16_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"FLOAT16_SQRT_EPS\n","FLOAT32_CBRT_EPS":"FLOAT32_CBRT_EPS\n","FLOAT32_EPS":"FLOAT32_EPS\n","FLOAT32_EXPONENT_BIAS":"FLOAT32_EXPONENT_BIAS\n","FLOAT32_MAX":"FLOAT32_MAX\n","FLOAT32_MAX_SAFE_INTEGER":"FLOAT32_MAX_SAFE_INTEGER\n","FLOAT32_MIN_SAFE_INTEGER":"FLOAT32_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"FLOAT32_NAN\n","FLOAT32_NINF":"FLOAT32_NINF\n","FLOAT32_NUM_BYTES":"FLOAT32_NUM_BYTES\n","FLOAT32_PINF":"FLOAT32_PINF\n","FLOAT32_PRECISION":"FLOAT32_PRECISION\n","FLOAT32_SMALLEST_NORMAL":"FLOAT32_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"FLOAT32_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"FLOAT32_SQRT_EPS\n","Float32Array":"var arr = new Float32Array()\nvar arr = new Float32Array( 5 )\nvar arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float32Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Float32Array( buf, 0, 4 )\n","Float32Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float32Array.of":"var arr = Float32Array.of( 2.0, -2.0 )\n","Float32Array.BYTES_PER_ELEMENT":"Float32Array.BYTES_PER_ELEMENT\n","Float32Array.name":"Float32Array.name\n","Float32Array.prototype.buffer":"var arr = new Float32Array( 5 );\narr.buffer\n","Float32Array.prototype.byteLength":"var arr = new Float32Array( 5 );\narr.byteLength\n","Float32Array.prototype.byteOffset":"var arr = new Float32Array( 5 );\narr.byteOffset\n","Float32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float32Array.prototype.length":"var arr = new Float32Array( 5 );\narr.length\n","Float32Array.prototype.copyWithin":"var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float32Array.prototype.entries":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.every":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float32Array.prototype.fill":"var arr = new Float32Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float32Array.prototype.filter":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float32Array.prototype.find":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float32Array.prototype.findIndex":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float32Array.prototype.forEach":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float32Array.prototype.includes":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float32Array.prototype.indexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float32Array.prototype.join":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float32Array.prototype.keys":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.lastIndexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float32Array.prototype.map":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn );\n","Float32Array.prototype.reduce":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float32Array.prototype.reduceRight":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float32Array.prototype.reverse":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float32Array.prototype.set":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float32Array.prototype.slice":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float32Array.prototype.some":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float32Array.prototype.sort":"var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float32Array.prototype.subarray":"var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float32Array.prototype.toLocaleString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float32Array.prototype.toString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float32Array.prototype.values":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","FLOAT64_EXPONENT_BIAS":"FLOAT64_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"FLOAT64_HIGH_WORD_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n","FLOAT64_MAX":"FLOAT64_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"FLOAT64_MAX_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"FLOAT64_MAX_SAFE_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MIN_BASE2_EXPONENT":"FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE10_EXPONENT":"FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"FLOAT64_MIN_LN\n","FLOAT64_MIN_SAFE_INTEGER":"FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"FLOAT64_NUM_BYTES\n","FLOAT64_PRECISION":"FLOAT64_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"FLOAT64_SMALLEST_NORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"FLOAT64_SMALLEST_SUBNORMAL\n","Float64Array":"var arr = new Float64Array()\nvar arr = new Float64Array( 5 )\nvar arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float64Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float64Array( arr1 )\nvar buf = new ArrayBuffer( 32 );\nvar arr = new Float64Array( buf, 0, 4 )\n","Float64Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float64Array.of":"var arr = Float64Array.of( 2.0, -2.0 )\n","Float64Array.BYTES_PER_ELEMENT":"Float64Array.BYTES_PER_ELEMENT\n","Float64Array.name":"Float64Array.name\n","Float64Array.prototype.buffer":"var arr = new Float64Array( 5 );\narr.buffer\n","Float64Array.prototype.byteLength":"var arr = new Float64Array( 5 );\narr.byteLength\n","Float64Array.prototype.byteOffset":"var arr = new Float64Array( 5 );\narr.byteOffset\n","Float64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float64Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float64Array.prototype.length":"var arr = new Float64Array( 5 );\narr.length\n","Float64Array.prototype.copyWithin":"var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float64Array.prototype.entries":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.every":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float64Array.prototype.fill":"var arr = new Float64Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float64Array.prototype.filter":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float64Array.prototype.find":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float64Array.prototype.findIndex":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float64Array.prototype.forEach":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float64Array.prototype.includes":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float64Array.prototype.indexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float64Array.prototype.join":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float64Array.prototype.keys":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.lastIndexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float64Array.prototype.map":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn );\n","Float64Array.prototype.reduce":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float64Array.prototype.reduceRight":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float64Array.prototype.reverse":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float64Array.prototype.set":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float64Array.prototype.slice":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float64Array.prototype.some":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float64Array.prototype.sort":"var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float64Array.prototype.subarray":"var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float64Array.prototype.toLocaleString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float64Array.prototype.toString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float64Array.prototype.values":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","forEach":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEach( arr, logger )\n","forEachAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\n","forEachAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nforEachChar( 'hello world!', fcn );\nn\n","forEachRight":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEachRight( arr, logger )\n","forEachRightAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\n","forEachRightAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachRightAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","forIn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nfunction Foo() { return this; };\nFoo.prototype.beep = 'boop';\nvar obj = new Foo();\nforIn( obj, logger )\n","forOwn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nforOwn( obj, logger )\n","FOURTH_PI":"FOURTH_PI\n","FOURTH_ROOT_EPS":"FOURTH_ROOT_EPS\n","FRB_SF_WAGE_RIGIDITY":"var data = FRB_SF_WAGE_RIGIDITY()\n","fromCodePoint":"var out = fromCodePoint( 9731 )\nout = fromCodePoint( [ 9731 ] )\nout = fromCodePoint( 97, 98, 99 )\nout = fromCodePoint( [ 97, 98, 99 ] )\n","Function":"var f = new Function( 'x', 'y', 'return x + y' );\nf( 1, 2 )\n","Function.prototype.apply":"var f = new Function( 'x', 'y', 'return x + y' );\nf.apply( null, [ 1, 2 ] )\n","Function.prototype.call":"var f = new Function( 'x', 'y', 'return x + y' );\nf.call( null, 1, 2 )\n","Function.prototype.bind":"var f = new Function( 'x', 'y', 'return x + y' );\nvar g = f.bind( null, 1 );\ng( 2 )\n","Function.prototype.toString":"var f = new Function( 'x', 'y', 'return x + y' );\nf.toString()\n","Function.prototype.length":"var f = new Function( 'x', 'y', 'return x + y' );\nf.length\n","Function.prototype.name":"var f = new Function( 'x', 'y', 'return x + y' );\nf.name\nvar f = new Function( 'x', 'y', 'return x + y' );\nf.name = 'add';\nf.name\n","Function.prototype.prototype":"var f = new Function( 'x', 'y', 'return x + y' );\nf.prototype\n","function2string":"function2string( base.erf )\n","functionName":"var v = functionName( String )\nv = functionName( function foo(){} )\nv = functionName( function(){} )\n","functionSequence":"function a( x ) { return 2 * x; };\nfunction b( x ) { return x + 3; };\nfunction c( x ) { return x / 5; };\nvar f = functionSequence( a, b, c );\nvar z = f( 6 )\n","functionSequenceAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x/5 );\n}\n };\nvar f = functionSequenceAsync( a, b, c );\nfunction done( error, result ) {\nif ( error ) {\n throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","GAMMA_LANCZOS_G":"GAMMA_LANCZOS_G\n","gdot":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngdot( x, y )\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngdot( x, y )\n","getegid":"var gid = getegid()\n","geteuid":"var uid = geteuid()\n","getgid":"var gid = getgid()\n","getGlobal":"var g = getGlobal()\n","getPrototypeOf":"var proto = getPrototypeOf( {} )\n","getuid":"var uid = getuid()\n","GLAISHER":"GLAISHER\n","graphemeClusters2iterator":"var it = graphemeClusters2iterator( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","graphemeClusters2iteratorRight":"var it = graphemeClusters2iteratorRight( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","group":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar groups = [ 'b', 'b', 'f', 'b' ];\nvar out = group( collection, groups )\ngroups = [ 1, 1, 2, 1 ];\nout = group( collection, groups )\ngroups = [ 'b', 'b', 'f', 'b' ];\nvar opts = { 'returns': 'indices' };\nout = group( collection, opts, groups )\nopts = { 'returns': '*' };\nout = group( collection, opts, groups )\n","groupBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = groupBy( collection, indicator )\nvar opts = { 'returns': 'indices' };\nout = groupBy( collection, opts, indicator )\nopts = { 'returns': '*' };\nout = groupBy( collection, opts, indicator )\n","groupByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, indicator, done )\nvar opts = { 'returns': 'indices' };\ngroupByAsync( arr, opts, indicator, done )\nopts = { 'returns': '*' };\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\n","groupByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = groupByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","groupIn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nfunction Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nvar out = groupIn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupIn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupIn( obj, opts, indicator )\n","groupOwn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = groupOwn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupOwn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupOwn( obj, opts, indicator )\n","gswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngswap( x, y );\nx.data\ny.data\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngswap( x, y );\nx\ny\n","HALF_LN2":"HALF_LN2\n","HALF_PI":"HALF_PI\n","HARRISON_BOSTON_HOUSE_PRICES":"var data = HARRISON_BOSTON_HOUSE_PRICES()\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n","hasArrayBufferSupport":"var bool = hasArrayBufferSupport()\n","hasAsyncAwaitSupport":"var bool = hasAsyncAwaitSupport()\n","hasAsyncIteratorSymbolSupport":"var bool = hasAsyncIteratorSymbolSupport()\n","hasBigInt64ArraySupport":"var bool = hasBigInt64ArraySupport()\n","hasBigIntSupport":"var bool = hasBigIntSupport()\n","hasBigUint64ArraySupport":"var bool = hasBigUint64ArraySupport()\n","hasClassSupport":"var bool = hasClassSupport()\n","hasDataViewSupport":"var bool = hasDataViewSupport()\n","hasDefinePropertiesSupport":"var bool = hasDefinePropertiesSupport()\n","hasDefinePropertySupport":"var bool = hasDefinePropertySupport()\n","hasFloat32ArraySupport":"var bool = hasFloat32ArraySupport()\n","hasFloat64ArraySupport":"var bool = hasFloat64ArraySupport()\n","hasFunctionNameSupport":"var bool = hasFunctionNameSupport()\n","hasGeneratorSupport":"var bool = hasGeneratorSupport()\n","hasGlobalThisSupport":"var bool = hasGlobalThisSupport()\n","hasInt8ArraySupport":"var bool = hasInt8ArraySupport()\n","hasInt16ArraySupport":"var bool = hasInt16ArraySupport()\n","hasInt32ArraySupport":"var bool = hasInt32ArraySupport()\n","hasIteratorSymbolSupport":"var bool = hasIteratorSymbolSupport()\n","hasMapSupport":"var bool = hasMapSupport()\n","hasNodeBufferSupport":"var bool = hasNodeBufferSupport()\n","hasOwnProp":"var beep = { 'boop': true };\nvar bool = hasOwnProp( beep, 'boop' )\nbool = hasOwnProp( beep, 'bop' )\n","hasProp":"var beep = { 'boop': true };\nvar bool = hasProp( beep, 'boop' )\nbool = hasProp( beep, 'toString' )\nbool = hasProp( beep, 'bop' )\n","hasProxySupport":"var bool = hasProxySupport()\n","hasSetSupport":"var bool = hasSetSupport()\n","hasSharedArrayBufferSupport":"var bool = hasSharedArrayBufferSupport()\n","hasSymbolSupport":"var bool = hasSymbolSupport()\n","hasToStringTagSupport":"var bool = hasToStringTagSupport()\n","hasUint8ArraySupport":"var bool = hasUint8ArraySupport()\n","hasUint8ClampedArraySupport":"var bool = hasUint8ClampedArraySupport()\n","hasUint16ArraySupport":"var bool = hasUint16ArraySupport()\n","hasUint32ArraySupport":"var bool = hasUint32ArraySupport()\n","hasUTF16SurrogatePairAt":"var out = hasUTF16SurrogatePairAt( '🌷', 0 )\nout = hasUTF16SurrogatePairAt( '🌷', 1 )\n","hasWeakMapSupport":"var bool = hasWeakMapSupport()\n","hasWeakSetSupport":"var bool = hasWeakSetSupport()\n","hasWebAssemblySupport":"var bool = hasWebAssemblySupport()\n","headercase":"var out = headercase( 'Hello World!' )\nout = headercase( 'beep boop' )\n","HERNDON_VENUS_SEMIDIAMETERS":"var d = HERNDON_VENUS_SEMIDIAMETERS()\n","homedir":"var home = homedir()\n","HOURS_IN_DAY":"var days = 3.14;\nvar hrs = days * HOURS_IN_DAY\n","HOURS_IN_WEEK":"var wks = 3.14;\nvar hrs = wks * HOURS_IN_WEEK\n","hoursInMonth":"var num = hoursInMonth()\nnum = hoursInMonth( 2 )\nnum = hoursInMonth( 2, 2016 )\nnum = hoursInMonth( 2, 2017 )\nnum = hoursInMonth( 'feb', 2016 )\nnum = hoursInMonth( 'february', 2016 )\n","hoursInYear":"var num = hoursInYear()\nnum = hoursInYear( 2016 )\nnum = hoursInYear( 2017 )\n","httpServer":"var createServer = httpServer()\nfunction onRequest( request, response ) {\nconsole.log( request.url );\nresponse.end( 'OK' );\n };\ncreateServer = httpServer( onRequest )\nvar opts = { 'port': 7331 };\ncreateServer = httpServer( opts )\n","identity":"var v = identity( 3.14 )\n","ifelse":"var z = ifelse( true, 1.0, -1.0 )\nz = ifelse( false, 1.0, -1.0 )\n","ifelseAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, true );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nifelseAsync( predicate, 'beep', 'boop', done )\n","ifthen":"function x() { return 1.0; };\nfunction y() { return -1.0; };\nvar z = ifthen( true, x, y )\nz = ifthen( false, x, y )\n","ifthenAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, false );\n }\n };\nfunction x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'beep' );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nifthenAsync( predicate, x, y, done )\n","imag":"var z = new Complex128( 5.0, 3.0 );\nvar im = imag( z )\n","imagf":"var z = new Complex64( 5.0, 3.0 );\nvar im = imagf( z )\n","IMG_ACANTHUS_MOLLIS":"var img = IMG_ACANTHUS_MOLLIS()\n","IMG_AIRPLANE_FROM_ABOVE":"var img = IMG_AIRPLANE_FROM_ABOVE()\n","IMG_ALLIUM_OREOPHILUM":"var img = IMG_ALLIUM_OREOPHILUM()\n","IMG_BLACK_CANYON":"var img = IMG_BLACK_CANYON()\n","IMG_DUST_BOWL_HOME":"var img = IMG_DUST_BOWL_HOME()\n","IMG_FRENCH_ALPINE_LANDSCAPE":"var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n","IMG_LOCOMOTION_HOUSE_CAT":"var img = IMG_LOCOMOTION_HOUSE_CAT()\n","IMG_LOCOMOTION_NUDE_MALE":"var img = IMG_LOCOMOTION_NUDE_MALE()\n","IMG_MARCH_PASTORAL":"var img = IMG_MARCH_PASTORAL()\n","IMG_NAGASAKI_BOATS":"var img = IMG_NAGASAKI_BOATS()\n","incrapcorr":"var accumulator = incrapcorr();\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator()\n","incrBinaryClassification":"var opts = {};\nopts.intercept = true;\nopts.lambda = 1.0e-5;\nvar acc = incrBinaryClassification( 3, opts );\nvar buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\nvar x = array( buf );\nvar coefs = acc( x, 1 )\nbuf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\nx = array( buf );\nvar yhat = acc.predict( x )\n","incrcount":"var accumulator = incrcount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrcovariance":"var accumulator = incrcovariance();\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator()\n","incrcovmat":"var accumulator = incrcovmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrcv":"var accumulator = incrcv();\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator()\n","increwmean":"var accumulator = increwmean( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","increwstdev":"var accumulator = increwstdev( 0.5 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","increwvariance":"var accumulator = increwvariance( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrgmean":"var accumulator = incrgmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrgrubbs":"var acc = incrgrubbs();\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrhmean":"var accumulator = incrhmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrkmeans":"var accumulator = incrkmeans( 5, 2 );\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v );\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v );\n","incrkurtosis":"var accumulator = incrkurtosis();\nvar v = accumulator( 2.0 )\nv = accumulator( 2.0 )\nv = accumulator( -4.0 )\nv = accumulator( -4.0 )\n","incrmaape":"var accumulator = incrmaape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmae":"var accumulator = incrmae();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmapcorr":"var accumulator = incrmapcorr( 3 );\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator( 3.0, -1.0 )\nar = accumulator( 5.0, -9.5 )\nar = accumulator()\n","incrmape":"var accumulator = incrmape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmax":"var accumulator = incrmax();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmaxabs":"var accumulator = incrmaxabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmcovariance":"var accumulator = incrmcovariance( 3 );\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator( 3.0, -1.0 )\nv = accumulator( 5.0, -9.5 )\nv = accumulator()\n","incrmcv":"var accumulator = incrmcv( 3 );\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator( 3.0 )\ncv = accumulator( 7.0 )\ncv = accumulator()\n","incrmda":"var accumulator = incrmda();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 4.0 )\nm = accumulator()\n","incrme":"var accumulator = incrme();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmean":"var accumulator = incrmean();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs":"var accumulator = incrmeanabs();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs2":"var accumulator = incrmeanabs2();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanstdev":"var accumulator = incrmeanstdev();\nvar ms = accumulator()\nms = accumulator( 2.0 )\nms = accumulator( -5.0 )\nms = accumulator( 3.0 )\nms = accumulator( 5.0 )\nms = accumulator()\n","incrmeanvar":"var accumulator = incrmeanvar();\nvar mv = accumulator()\nmv = accumulator( 2.0 )\nmv = accumulator( -5.0 )\nmv = accumulator( 3.0 )\nmv = accumulator( 5.0 )\nmv = accumulator()\n","incrmgmean":"var accumulator = incrmgmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmgrubbs":"var acc = incrmgrubbs( 20 );\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrmhmean":"var accumulator = incrmhmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmidrange":"var accumulator = incrmidrange();\nvar v = accumulator()\nv = accumulator( 3.14 )\nv = accumulator( -5.0 )\nv = accumulator( 10.1 )\nv = accumulator()\n","incrmin":"var accumulator = incrmin();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminabs":"var accumulator = incrminabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminmax":"var accumulator = incrminmax();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrminmaxabs":"var accumulator = incrminmaxabs();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmaape":"var accumulator = incrmmaape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmae":"var accumulator = incrmmae( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmape":"var accumulator = incrmmape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmax":"var accumulator = incrmmax( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmaxabs":"var accumulator = incrmmaxabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmda":"var accumulator = incrmmda( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 4.0, 5.0 )\nm = accumulator()\n","incrmme":"var accumulator = incrmme( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmean":"var accumulator = incrmmean( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs":"var accumulator = incrmmeanabs( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs2":"var accumulator = incrmmeanabs2( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmeanstdev":"var accumulator = incrmmeanstdev( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmeanvar":"var accumulator = incrmmeanvar( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmidrange":"var accumulator = incrmmidrange( 3 );\nvar mr = accumulator()\nmr = accumulator( 2.0 )\nmr = accumulator( -5.0 )\nmr = accumulator( 3.0 )\nmr = accumulator( 5.0 )\nmr = accumulator()\n","incrmmin":"var accumulator = incrmmin( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminabs":"var accumulator = incrmminabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminmax":"var accumulator = incrmminmax( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmminmaxabs":"var accumulator = incrmminmaxabs( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmpe":"var accumulator = incrmmpe( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmse":"var accumulator = incrmmse( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmpcorr":"var accumulator = incrmpcorr( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator( 3.0, -1.0 )\nr = accumulator( 5.0, -9.5 )\nr = accumulator()\n","incrmpcorr2":"var accumulator = incrmpcorr2( 3 );\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator( 3.0, -1.0 )\nr2 = accumulator( 5.0, -9.5 )\nr2 = accumulator()\n","incrmpcorrdist":"var accumulator = incrmpcorrdist( 3 );\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator( 3.0, -1.0 )\nd = accumulator( 5.0, -9.5 )\nd = accumulator()\n","incrmpe":"var accumulator = incrmpe();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmprod":"var accumulator = incrmprod( 3 );\nvar p = accumulator()\np = accumulator( 2.0 )\np = accumulator( -5.0 )\np = accumulator( 3.0 )\np = accumulator( 5.0 )\np = accumulator()\n","incrmrange":"var accumulator = incrmrange( 3 );\nvar r = accumulator()\nr = accumulator( 2.0 )\nr = accumulator( -5.0 )\nr = accumulator( 3.0 )\nr = accumulator( 5.0 )\nr = accumulator()\n","incrmrmse":"var accumulator = incrmrmse( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmrss":"var accumulator = incrmrss( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmse":"var accumulator = incrmse();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmstdev":"var accumulator = incrmstdev( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsum":"var accumulator = incrmsum( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsumabs":"var accumulator = incrmsumabs( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumabs2":"var accumulator = incrmsumabs2( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsummary":"var accumulator = incrmsummary( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumprod":"var accumulator = incrmsumprod( 3 );\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator( 3.0, -2.0 )\ns = accumulator( 5.0, 3.0 )\ns = accumulator()\n","incrmvariance":"var accumulator = incrmvariance( 3 );\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator( 3.0 )\ns2 = accumulator( 5.0 )\ns2 = accumulator()\n","incrmvmr":"var accumulator = incrmvmr( 3 );\nvar F = accumulator()\nF = accumulator( 2.0 )\nF = accumulator( 1.0 )\nF = accumulator( 3.0 )\nF = accumulator( 7.0 )\nF = accumulator()\n","incrnancount":"var accumulator = incrnancount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrnansum":"var accumulator = incrnansum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs":"var accumulator = incrnansumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs2":"var accumulator = incrnansumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrpcorr":"var accumulator = incrpcorr();\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator()\n","incrpcorr2":"var accumulator = incrpcorr2();\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator()\n","incrpcorrdist":"var accumulator = incrpcorrdist();\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator()\n","incrpcorrdistmat":"var accumulator = incrpcorrdistmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrpcorrmat":"var accumulator = incrpcorrmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrprod":"var accumulator = incrprod();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrrange":"var accumulator = incrrange();\nvar v = accumulator()\nv = accumulator( -2.0 )\nv = accumulator( 1.0 )\nv = accumulator( 3.0 )\nv = accumulator()\n","incrrmse":"var accumulator = incrrmse();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrrss":"var accumulator = incrrss();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrskewness":"var accumulator = incrskewness();\nvar v = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( -10.0 )\nv = accumulator()\n","incrspace":"var arr = incrspace( 0, 11, 2 )\n","incrstdev":"var accumulator = incrstdev();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsum":"var accumulator = incrsum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs":"var accumulator = incrsumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs2":"var accumulator = incrsumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsummary":"var accumulator = incrsummary();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumprod":"var accumulator = incrsumprod();\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator()\n","incrvariance":"var accumulator = incrvariance();\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator()\n","incrvmr":"var accumulator = incrvmr();\nvar D = accumulator()\nD = accumulator( 2.0 )\nD = accumulator( 1.0 )\nD = accumulator()\n","incrwmean":"var accumulator = incrwmean();\nvar mu = accumulator()\nmu = accumulator( 2.0, 1.0 )\nmu = accumulator( 2.0, 0.5 )\nmu = accumulator( 3.0, 1.5 )\nmu = accumulator()\n","ind2sub":"var d = [ 3, 3, 3 ];\nvar s = ind2sub( d, 17 )\n","ind2sub.assign":"var d = [ 3, 3, 3 ];\nvar out = [ 0, 0, 0 ];\nvar s = ind2sub.assign( d, 17, out )\nvar bool = ( s === out )\n","indexOf":"var arr = [ 4, 3, 2, 1 ];\nvar idx = indexOf( arr, 3 )\narr = [ 4, 3, 2, 1 ];\nidx = indexOf( arr, 5 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, 3 )\narr = [ 1, 2, 3, 4, 2, 5 ];\nidx = indexOf( arr, 2, 10 )\narr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\nidx = indexOf( arr, 2, -4 )\nidx = indexOf( arr, 2, -1 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, -10 )\nvar str = 'bebop';\nidx = indexOf( str, 'o' )\n","inherit":"function Foo() { return this; };\nFoo.prototype.beep = function beep() { return 'boop'; };\nfunction Bar() { Foo.call( this ); return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar v = bar.beep()\n","inheritedEnumerableProperties":"var props = inheritedEnumerableProperties( {} )\n","inheritedEnumerablePropertySymbols":"var symbols = inheritedEnumerablePropertySymbols( [] )\n","inheritedKeys":"var keys = inheritedKeys( {} )\n","inheritedNonEnumerableProperties":"var props = inheritedNonEnumerableProperties( {} )\n","inheritedNonEnumerablePropertyNames":"var keys = inheritedNonEnumerablePropertyNames( {} )\n","inheritedNonEnumerablePropertySymbols":"var symbols = inheritedNonEnumerablePropertySymbols( [] )\n","inheritedProperties":"var symbols = inheritedProperties( [] )\n","inheritedPropertyDescriptor":"var desc = inheritedPropertyDescriptor( {}, 'toString' )\n","inheritedPropertyDescriptors":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = inheritedPropertyDescriptors( obj )\n","inheritedPropertyNames":"var keys = inheritedPropertyNames( [] )\n","inheritedPropertySymbols":"var symbols = inheritedPropertySymbols( [] )\n","inheritedWritableProperties":"var props = inheritedWritableProperties( {} )\n","inheritedWritablePropertyNames":"var keys = inheritedWritablePropertyNames( {} )\n","inheritedWritablePropertySymbols":"var symbols = inheritedWritablePropertySymbols( [] )\n","inmap":"function foo( v, i ) { return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmap( arr, foo )\nvar bool = ( out === arr )\n","inmapAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\n","inmapAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","inmapRight":"function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmapRight( arr, foo )\nvar bool = ( out === arr )\n","inmapRightAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\n","inmapRightAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapRightAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","inspectSinkStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectSinkStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","inspectStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","instanceOf":"var bool = instanceOf( [], Array )\nbool = instanceOf( {}, Object )\nbool = instanceOf( null, Object )\n","INT8_MAX":"INT8_MAX\n","INT8_MIN":"INT8_MIN\n","INT8_NUM_BYTES":"INT8_NUM_BYTES\n","Int8Array":"var arr = new Int8Array()\nvar arr = new Int8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Int8Array( buf, 0, 4 )\n","Int8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int8Array.from( [ 1, 2 ], mapFcn )\n","Int8Array.of":"var arr = Int8Array.of( 1, 2 )\n","Int8Array.BYTES_PER_ELEMENT":"Int8Array.BYTES_PER_ELEMENT\n","Int8Array.name":"Int8Array.name\n","Int8Array.prototype.buffer":"var arr = new Int8Array( 5 );\narr.buffer\n","Int8Array.prototype.byteLength":"var arr = new Int8Array( 5 );\narr.byteLength\n","Int8Array.prototype.byteOffset":"var arr = new Int8Array( 5 );\narr.byteOffset\n","Int8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int8Array.prototype.length":"var arr = new Int8Array( 5 );\narr.length\n","Int8Array.prototype.copyWithin":"var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int8Array.prototype.entries":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.every":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int8Array.prototype.fill":"var arr = new Int8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int8Array.prototype.filter":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int8Array.prototype.find":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int8Array.prototype.findIndex":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int8Array.prototype.forEach":"var arr = new Int8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int8Array.prototype.includes":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int8Array.prototype.indexOf":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int8Array.prototype.join":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int8Array.prototype.keys":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.lastIndexOf":"var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int8Array.prototype.map":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn );\n","Int8Array.prototype.reduce":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int8Array.prototype.reduceRight":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int8Array.prototype.reverse":"var arr = new Int8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int8Array.prototype.set":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int8Array.prototype.slice":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int8Array.prototype.some":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int8Array.prototype.sort":"var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int8Array.prototype.subarray":"var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int8Array.prototype.toLocaleString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int8Array.prototype.toString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toString()\n","Int8Array.prototype.values":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","INT16_MAX":"INT16_MAX\n","INT16_MIN":"INT16_MIN\n","INT16_NUM_BYTES":"INT16_NUM_BYTES\n","Int16Array":"var arr = new Int16Array()\nvar arr = new Int16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Int16Array( buf, 0, 4 )\n","Int16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int16Array.from( [ 1, 2 ], mapFcn )\n","Int16Array.of":"var arr = Int16Array.of( 1, 2 )\n","Int16Array.BYTES_PER_ELEMENT":"Int16Array.BYTES_PER_ELEMENT\n","Int16Array.name":"Int16Array.name\n","Int16Array.prototype.buffer":"var arr = new Int16Array( 5 );\narr.buffer\n","Int16Array.prototype.byteLength":"var arr = new Int16Array( 5 );\narr.byteLength\n","Int16Array.prototype.byteOffset":"var arr = new Int16Array( 5 );\narr.byteOffset\n","Int16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int16Array.prototype.length":"var arr = new Int16Array( 5 );\narr.length\n","Int16Array.prototype.copyWithin":"var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int16Array.prototype.entries":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.every":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int16Array.prototype.fill":"var arr = new Int16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int16Array.prototype.filter":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int16Array.prototype.find":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int16Array.prototype.findIndex":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int16Array.prototype.forEach":"var arr = new Int16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int16Array.prototype.includes":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int16Array.prototype.indexOf":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int16Array.prototype.join":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int16Array.prototype.keys":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.lastIndexOf":"var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int16Array.prototype.map":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn );\n","Int16Array.prototype.reduce":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int16Array.prototype.reduceRight":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int16Array.prototype.reverse":"var arr = new Int16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int16Array.prototype.set":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int16Array.prototype.slice":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int16Array.prototype.some":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int16Array.prototype.sort":"var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int16Array.prototype.subarray":"var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int16Array.prototype.toLocaleString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int16Array.prototype.toString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toString()\n","Int16Array.prototype.values":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","INT32_MAX":"INT32_MAX\n","INT32_MIN":"INT32_MIN\n","INT32_NUM_BYTES":"INT32_NUM_BYTES\n","Int32Array":"var arr = new Int32Array()\nvar arr = new Int32Array( 5 )\nvar arr1 = new Int16Array( [ 5, 5, 5 ] );\nvar arr2 = new Int32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Int32Array( buf, 0, 4 )\n","Int32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int32Array.from( [ 1, 2 ], mapFcn )\n","Int32Array.of":"var arr = Int32Array.of( 1, 2 )\n","Int32Array.BYTES_PER_ELEMENT":"Int32Array.BYTES_PER_ELEMENT\n","Int32Array.name":"Int32Array.name\n","Int32Array.prototype.buffer":"var arr = new Int32Array( 5 );\narr.buffer\n","Int32Array.prototype.byteLength":"var arr = new Int32Array( 5 );\narr.byteLength\n","Int32Array.prototype.byteOffset":"var arr = new Int32Array( 5 );\narr.byteOffset\n","Int32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int32Array.prototype.length":"var arr = new Int32Array( 5 );\narr.length\n","Int32Array.prototype.copyWithin":"var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int32Array.prototype.entries":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.every":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int32Array.prototype.fill":"var arr = new Int32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int32Array.prototype.filter":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int32Array.prototype.find":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int32Array.prototype.findIndex":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int32Array.prototype.forEach":"var arr = new Int32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int32Array.prototype.includes":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int32Array.prototype.indexOf":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int32Array.prototype.join":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int32Array.prototype.keys":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.lastIndexOf":"var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int32Array.prototype.map":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn );\n","Int32Array.prototype.reduce":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int32Array.prototype.reduceRight":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int32Array.prototype.reverse":"var arr = new Int32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int32Array.prototype.set":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int32Array.prototype.slice":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int32Array.prototype.some":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int32Array.prototype.sort":"var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int32Array.prototype.subarray":"var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int32Array.prototype.toLocaleString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int32Array.prototype.toString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toString()\n","Int32Array.prototype.values":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","IS_BIG_ENDIAN":"IS_BIG_ENDIAN\n","IS_BROWSER":"IS_BROWSER\n","IS_DARWIN":"IS_DARWIN\n","IS_ELECTRON":"IS_ELECTRON\n","IS_ELECTRON_MAIN":"IS_ELECTRON_MAIN\n","IS_ELECTRON_RENDERER":"IS_ELECTRON_RENDERER\n","IS_LITTLE_ENDIAN":"IS_LITTLE_ENDIAN\n","IS_NODE":"IS_NODE\n","IS_WEB_WORKER":"IS_WEB_WORKER\n","IS_WINDOWS":"IS_WINDOWS\n","isAbsolutePath":"var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath( '/foo/bar/baz' )\n","isAbsolutePath.posix":"var bool = isAbsolutePath.posix( '/foo/bar/baz' )\nbool = isAbsolutePath.posix( 'foo/bar/baz' )\n","isAbsolutePath.win32":"var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n","isAccessorArray":"var bool = isAccessorArray( new Complex64Array( 10 ) )\nbool = isAccessorArray( [] )\nbool = isAccessorArray( { 'length': 0 } )\nbool = isAccessorArray( {} )\n","isAccessorProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorProperty( obj, 'boop' )\nbool = isAccessorProperty( obj, 'beep' )\n","isAccessorPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorPropertyIn( obj, 'boop' )\nbool = isAccessorPropertyIn( obj, 'beep' )\n","isAlphagram":"var out = isAlphagram( 'beep' )\nout = isAlphagram( 'zba' )\nout = isAlphagram( '' )\n","isAlphaNumeric":"var bool = isAlphaNumeric( 'abc0123456789' )\nbool = isAlphaNumeric( 'abcdef' )\nbool = isAlphaNumeric( '0xff' )\nbool = isAlphaNumeric( '' )\n","isAnagram":"var str1 = 'I am a weakish speller';\nvar str2 = 'William Shakespeare';\nvar bool = isAnagram( str1, str2 )\nbool = isAnagram( 'bat', 'tabba' )\n","isArguments":"function foo() { return arguments; };\nvar bool = isArguments( foo() )\nbool = isArguments( [] )\n","isArray":"var bool = isArray( [] )\nbool = isArray( {} )\n","isArrayArray":"var bool = isArrayArray( [ [], [] ] )\nbool = isArrayArray( [ {}, {} ] )\nbool = isArrayArray( [] )\n","isArrayBuffer":"var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\nbool = isArrayBuffer( [] )\n","isArrayBufferView":"var bool = isArrayBufferView( new Int8Array() )\nbool = isArrayBufferView( [] )\n","isArrayLength":"var bool = isArrayLength( 5 )\nbool = isArrayLength( 2.0e200 )\nbool = isArrayLength( -3.14 )\nbool = isArrayLength( null )\n","isArrayLike":"var bool = isArrayLike( [] )\nbool = isArrayLike( { 'length': 10 } )\nbool = isArrayLike( 'beep' )\nbool = isArrayLike( null )\n","isArrayLikeObject":"var bool = isArrayLikeObject( [] )\nbool = isArrayLikeObject( { 'length': 10 } )\nbool = isArrayLikeObject( 'beep' )\n","isASCII":"var str = 'beep boop';\nvar bool = isASCII( str )\nbool = isASCII( fromCodePoint( 130 ) )\n","isBetween":"var bool = isBetween( 3.14, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.0, 4.0 )\nbool = isBetween( 4.0, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.14, 4.0 )\nbool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\nbool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n","isBetweenArray":"var arr = [ 3.0, 3.14, 4.0 ];\nvar bool = isBetweenArray( arr, 3.0, 4.0 )\nbool = isBetweenArray( arr, 3.14, 4.0 )\nbool = isBetweenArray( arr, 3.0, 3.14 )\nbool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\nbool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n","isBigInt":"var bool = isBigInt( BigInt( '1' ) )\nbool = isBigInt( Object( BigInt( '1' ) ) )\nbool = isBigInt( {} )\nbool = isBigInt( null )\nbool = isBigInt( true )\n","isBigInt64Array":"var bool = isBigInt64Array( new BigInt64Array( 10 ) )\nbool = isBigInt64Array( [] )\n","isBigUint64Array":"var bool = isBigUint64Array( new BigUint64Array( 10 ) )\nbool = isBigUint64Array( [] )\n","isBinaryString":"var bool = isBinaryString( '1000101' )\nbool = isBinaryString( 'beep' )\nbool = isBinaryString( '' )\n","isBlankString":"var bool = isBlankString( ' ' )\nbool = isBlankString( 'beep' )\nbool = isBlankString( null )\n","isBoolean":"var bool = isBoolean( false )\nbool = isBoolean( new Boolean( false ) )\n","isBoolean.isPrimitive":"var bool = isBoolean.isPrimitive( true )\nbool = isBoolean.isPrimitive( false )\nbool = isBoolean.isPrimitive( new Boolean( true ) )\n","isBoolean.isObject":"var bool = isBoolean.isObject( true )\nbool = isBoolean.isObject( new Boolean( false ) )\n","isBooleanArray":"var bool = isBooleanArray( [ true, false, true ] )\nbool = isBooleanArray( [ true, 'abc', false ] )\n","isBooleanArray.primitives":"var bool = isBooleanArray.primitives( [ true, false ] )\nbool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n","isBooleanArray.objects":"var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\nbool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n","isBoxedPrimitive":"var bool = isBoxedPrimitive( new Boolean( false ) )\nbool = isBoxedPrimitive( true )\n","isBuffer":"var bool = isBuffer( new Buffer( 'beep' ) )\nbool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\nbool = isBuffer( {} )\nbool = isBuffer( [] )\n","isCapitalized":"var bool = isCapitalized( 'Hello' )\nbool = isCapitalized( 'world' )\n","isCentrosymmetricMatrix":"var buf = [ 2, 1, 1, 2 ];\nvar M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isCentrosymmetricMatrix( M )\nbool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isCentrosymmetricMatrix( 3.14 )\nbool = isCentrosymmetricMatrix( {} )\n","isCircular":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircular( obj )\nbool = isCircular( {} )\nbool = isCircular( null )\n","isCircularArray":"var arr = [ 1, 2, 3 ];\narr.push( arr );\nvar bool = isCircularArray( arr )\nbool = isCircularArray( [] )\nbool = isCircularArray( null )\n","isCircularPlainObject":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircularPlainObject( obj )\nbool = isCircularPlainObject( {} )\nbool = isCircularPlainObject( null )\n","isClass":"var bool = isClass( class Person {} )\nbool = isClass( function Person() {} )\nbool = isClass( {} )\nbool = isClass( null )\nbool = isClass( true )\n","isCollection":"var bool = isCollection( [] )\nbool = isCollection( { 'length': 0 } )\nbool = isCollection( {} )\n","isComplex":"var bool = isComplex( new Complex64( 2.0, 2.0 ) )\nbool = isComplex( new Complex128( 3.0, 1.0 ) )\nbool = isComplex( 3.14 )\nbool = isComplex( {} )\n","isComplex64":"var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\nbool = isComplex64( new Complex128( 3.0, 1.0 ) )\nbool = isComplex64( 3.14 )\nbool = isComplex64( {} )\n","isComplex64Array":"var bool = isComplex64Array( new Complex64Array( 10 ) )\nbool = isComplex64Array( [] )\n","isComplex64MatrixLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64MatrixLike( M )\nbool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64MatrixLike( 3.14 )\nbool = isComplex64MatrixLike( {} )\n","isComplex64ndarrayLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64ndarrayLike( M )\nbool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64ndarrayLike( 3.14 )\nbool = isComplex64ndarrayLike( {} )\n","isComplex64VectorLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64VectorLike( M )\nbool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64VectorLike( 3.14 )\nbool = isComplex64VectorLike( {} )\n","isComplex128":"var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\nbool = isComplex128( new Complex64( 2.0, 2.0 ) )\nbool = isComplex128( 3.14 )\nbool = isComplex128( {} )\n","isComplex128Array":"var bool = isComplex128Array( new Complex128Array( 10 ) )\nbool = isComplex128Array( [] )\n","isComplex128MatrixLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128MatrixLike( M )\nbool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128MatrixLike( 3.14 )\nbool = isComplex128MatrixLike( {} )\n","isComplex128ndarrayLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128ndarrayLike( M )\nbool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128ndarrayLike( 3.14 )\nbool = isComplex128ndarrayLike( {} )\n","isComplex128VectorLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128VectorLike( M )\nbool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128VectorLike( 3.14 )\nbool = isComplex128VectorLike( {} )\n","isComplexLike":"var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\nbool = isComplexLike( new Complex128( 3.0, 1.0 ) )\nbool = isComplexLike( 3.14 )\nbool = isComplexLike( {} )\n","isComplexTypedArray":"var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n","isComplexTypedArrayLike":"var bool = isComplexTypedArrayLike( new Complex128Array() )\nbool = isComplexTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4,\n'get': function get() {},\n'set': function set() {}\n })\n","isComposite":"var bool = isComposite( 4.0 )\nbool = isComposite( new Number( 4.0 ) )\nbool = isComposite( 3.14 )\nbool = isComposite( -4.0 )\nbool = isComposite( null )\n","isComposite.isPrimitive":"var bool = isComposite.isPrimitive( 4.0 )\nbool = isComposite.isPrimitive( new Number( 4.0 ) )\n","isComposite.isObject":"var bool = isComposite.isObject( 4.0 )\nbool = isComposite.isObject( new Number( 4.0 ) )\n","isConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurableProperty( obj, 'boop' )\nbool = isConfigurableProperty( obj, 'beep' )\n","isConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurablePropertyIn( obj, 'boop' )\nbool = isConfigurablePropertyIn( obj, 'beep' )\n","isCubeNumber":"var bool = isCubeNumber( 8.0 )\nbool = isCubeNumber( new Number( 8.0 ) )\nbool = isCubeNumber( 3.14 )\nbool = isCubeNumber( -5.0 )\nbool = isCubeNumber( null )\n","isCubeNumber.isPrimitive":"var bool = isCubeNumber.isPrimitive( 8.0 )\nbool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n","isCubeNumber.isObject":"var bool = isCubeNumber.isObject( 8.0 )\nbool = isCubeNumber.isObject( new Number( 8.0 ) )\n","isDataProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataProperty( obj, 'boop' )\nbool = isDataProperty( obj, 'beep' )\n","isDataPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataPropertyIn( obj, 'boop' )\nbool = isDataPropertyIn( obj, 'beep' )\n","isDataView":"var buf = new ArrayBuffer( 10 );\nvar bool = isDataView( new DataView( buf ) )\nbool = isDataView( [] )\n","isDateObject":"var bool = isDateObject( new Date() )\nbool = isDateObject( '2017-01-01' )\n","isDateObjectArray":"var bool = isDateObjectArray( [ new Date(), new Date() ] )\nbool = isDateObjectArray( [ {}, {} ] )\nbool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\nbool = isDateObjectArray( [] )\n","isDigitString":"var bool = isDigitString( '0123456789' )\nbool = isDigitString( 'abcdef' )\nbool = isDigitString( '0xff' )\nbool = isDigitString( '' )\n","isEmailAddress":"var bool = isEmailAddress( 'beep@boop.com' )\nbool = isEmailAddress( 'beep' )\nbool = isEmailAddress( null )\n","isEmptyArray":"var bool = isEmptyArray( [] )\nbool = isEmptyArray( [ 1, 2, 3 ] )\nbool = isEmptyArray( {} )\n","isEmptyArrayLikeObject":"var bool = isEmptyArrayLikeObject( [] )\nbool = isEmptyArrayLikeObject( { 'length': 0 } )\nbool = isEmptyArrayLikeObject( '' )\n","isEmptyCollection":"var bool = isEmptyCollection( [] )\nbool = isEmptyCollection( { 'length': 0 } )\nbool = isEmptyCollection( [ 1, 2, 3 ] )\nbool = isEmptyCollection( {} )\n","isEmptyObject":"var bool = isEmptyObject( {} )\nbool = isEmptyObject( { 'beep': 'boop' } )\nbool = isEmptyObject( [] )\n","isEmptyString":"var bool = isEmptyString( '' )\nbool = isEmptyString( new String( '' ) )\nbool = isEmptyString( 'beep' )\nbool = isEmptyString( [] )\n","isEmptyString.isPrimitive":"var bool = isEmptyString.isPrimitive( '' )\nbool = isEmptyString.isPrimitive( new String( '' ) )\n","isEmptyString.isObject":"var bool = isEmptyString.isObject( new String( '' ) )\nbool = isEmptyString.isObject( '' )\n","isEnumerableProperty":"var beep = { 'boop': true };\nvar bool = isEnumerableProperty( beep, 'boop' )\nbool = isEnumerableProperty( beep, 'hasOwnProperty' )\n","isEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isEnumerablePropertyIn( obj, 'boop' )\nbool = isEnumerablePropertyIn( obj, 'beep' )\n","isError":"var bool = isError( new Error( 'beep' ) )\nbool = isError( {} )\n","isEvalError":"var bool = isEvalError( new EvalError( 'beep' ) )\nbool = isEvalError( {} )\n","isEven":"var bool = isEven( 4.0 )\nbool = isEven( new Number( 4.0 ) )\nbool = isEven( 3.0 )\nbool = isEven( -3.14 )\nbool = isEven( null )\n","isEven.isPrimitive":"var bool = isEven.isPrimitive( -4.0 )\nbool = isEven.isPrimitive( new Number( -4.0 ) )\n","isEven.isObject":"var bool = isEven.isObject( 4.0 )\nbool = isEven.isObject( new Number( 4.0 ) )\n","isFalsy":"var bool = isFalsy( false )\nbool = isFalsy( '' )\nbool = isFalsy( 0 )\nbool = isFalsy( null )\nbool = isFalsy( void 0 )\nbool = isFalsy( NaN )\nbool = isFalsy( {} )\nbool = isFalsy( [] )\n","isFalsyArray":"var bool = isFalsyArray( [ null, '' ] )\nbool = isFalsyArray( [ {}, [] ] )\nbool = isFalsyArray( [] )\n","isFinite":"var bool = isFinite( 5.0 )\nbool = isFinite( new Number( 5.0 ) )\nbool = isFinite( 1.0/0.0 )\nbool = isFinite( null )\n","isFinite.isPrimitive":"var bool = isFinite.isPrimitive( -3.0 )\nbool = isFinite.isPrimitive( new Number( -3.0 ) )\n","isFinite.isObject":"var bool = isFinite.isObject( 3.0 )\nbool = isFinite.isObject( new Number( 3.0 ) )\n","isFiniteArray":"var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n","isFiniteArray.primitives":"var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\nbool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isFiniteArray.objects":"var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n","isFloat32Array":"var bool = isFloat32Array( new Float32Array( 10 ) )\nbool = isFloat32Array( [] )\n","isFloat32MatrixLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32MatrixLike( M )\nbool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32MatrixLike( 3.14 )\nbool = isFloat32MatrixLike( {} )\n","isFloat32ndarrayLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32ndarrayLike( M )\nbool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32ndarrayLike( 3.14 )\nbool = isFloat32ndarrayLike( {} )\n","isFloat32VectorLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32VectorLike( M )\nbool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32VectorLike( 3.14 )\nbool = isFloat32VectorLike( {} )\n","isFloat64Array":"var bool = isFloat64Array( new Float64Array( 10 ) )\nbool = isFloat64Array( [] )\n","isFloat64MatrixLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64MatrixLike( M )\nbool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64MatrixLike( 3.14 )\nbool = isFloat64MatrixLike( {} )\n","isFloat64ndarrayLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64ndarrayLike( M )\nbool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64ndarrayLike( 3.14 )\nbool = isFloat64ndarrayLike( {} )\n","isFloat64VectorLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64VectorLike( M )\nbool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64VectorLike( 3.14 )\nbool = isFloat64VectorLike( {} )\n","isFunction":"function beep() {};\nvar bool = isFunction( beep )\nbool = isFunction( {} )\n","isFunctionArray":"function beep() {};\nfunction boop() {};\nvar bool = isFunctionArray( [ beep, boop ] )\nbool = isFunctionArray( [ {}, beep ] )\nbool = isFunctionArray( [] )\n","isGeneratorObject":"function* generateID() {\n var idx = 0;\n while ( idx < idx+1 ) {\n yield idx;\n idx += 1;\n }\n };\nvar bool = isGeneratorObject( generateID() )\nbool = isGeneratorObject( generateID )\nbool = isGeneratorObject( {} )\nbool = isGeneratorObject( null )\n","isGeneratorObjectLike":"var obj = {\n 'next': function noop() {},\n 'return': function noop() {},\n 'throw': function noop() {}\n };\nvar bool = isGeneratorObjectLike( obj )\nbool = isGeneratorObjectLike( {} )\nbool = isGeneratorObjectLike( null )\n","isgzipBuffer":"var buf = new Uint8Array( 20 );\nbuf[ 0 ] = 31; // 0x1f => magic number\nbuf[ 1 ] = 139; // 0x8b\nbuf[ 2 ] = 8; // 0x08 => compression method\nvar bool = isgzipBuffer( buf )\nbool = isgzipBuffer( [] )\n","isHexString":"var bool = isHexString( '0123456789abcdefABCDEF' )\nbool = isHexString( '0xffffff' )\nbool = isHexString( 'x' )\nbool = isHexString( '' )\n","isInfinite":"var bool = isInfinite( 1.0/0.0 )\nbool = isInfinite( new Number( -1.0/0.0 ) )\nbool = isInfinite( 5.0 )\nbool = isInfinite( '1.0/0.0' )\n","isInfinite.isPrimitive":"var bool = isInfinite.isPrimitive( -1.0/0.0 )\nbool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isInfinite.isObject":"var bool = isInfinite.isObject( 1.0/0.0 )\nbool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n","isInheritedProperty":"var beep = { 'boop': true };\nvar bool = isInheritedProperty( beep, 'boop' )\nbool = isInheritedProperty( beep, 'toString' )\nbool = isInheritedProperty( beep, 'bop' )\n","isInt8Array":"var bool = isInt8Array( new Int8Array( 10 ) )\nbool = isInt8Array( [] )\n","isInt16Array":"var bool = isInt16Array( new Int16Array( 10 ) )\nbool = isInt16Array( [] )\n","isInt32Array":"var bool = isInt32Array( new Int32Array( 10 ) )\nbool = isInt32Array( [] )\n","isInteger":"var bool = isInteger( 5.0 )\nbool = isInteger( new Number( 5.0 ) )\nbool = isInteger( -3.14 )\nbool = isInteger( null )\n","isInteger.isPrimitive":"var bool = isInteger.isPrimitive( -3.0 )\nbool = isInteger.isPrimitive( new Number( -3.0 ) )\n","isInteger.isObject":"var bool = isInteger.isObject( 3.0 )\nbool = isInteger.isObject( new Number( 3.0 ) )\n","isIntegerArray":"var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isIntegerArray( [ -3.0, '3.0' ] )\n","isIntegerArray.primitives":"var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\nbool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isIntegerArray.objects":"var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n","isIterableLike":"var bool = isIterableLike( [ 1, 2, 3 ] )\nbool = isIterableLike( {} )\nbool = isIterableLike( null )\n","isIteratorLike":"var obj = {\n 'next': function noop() {}\n };\nvar bool = isIteratorLike( obj )\nbool = isIteratorLike( {} )\nbool = isIteratorLike( null )\n","isJSON":"var bool = isJSON( '{\"a\":5}' )\nbool = isJSON( '{a\":5}' )\n","isLeapYear":"var bool = isLeapYear( new Date() )\nbool = isLeapYear( 1996 )\nbool = isLeapYear( 2001 )\n","isLocalhost":"var bool = isLocalhost( 'localhost' )\nbool = isLocalhost( '127.0.0.1' )\nbool = isLocalhost( 'stdlib.io' )\n","isLowercase":"var bool = isLowercase( 'hello' )\nbool = isLowercase( 'World' )\n","isMatrixLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isMatrixLike( M )\nbool = isMatrixLike( [ 1, 2, 3, 4 ] )\nbool = isMatrixLike( 3.14 )\nbool = isMatrixLike( {} )\n","isMethod":"var beep = { 'boop': function beep() { return 'beep'; } };\nvar bool = isMethod( beep, 'boop' )\nbool = isMethod( beep, 'toString' )\n","isMethodIn":"var beep = { 'boop': true };\nvar bool = isMethodIn( beep, 'toString' )\nbool = isMethodIn( beep, 'boop' )\nbool = isMethodIn( beep, 'bop' )\n","isMultiSlice":"var bool = isMultiSlice( new MultiSlice() )\nbool = isMultiSlice( 3.14 )\nbool = isMultiSlice( {} )\n","isNamedTypedTupleLike":"var Point = namedtypedtuple( [ 'x', 'y' ] );\nvar p = new Point();\nvar bool = isNamedTypedTupleLike( p )\nbool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\nbool = isNamedTypedTupleLike( 3.14 )\nbool = isNamedTypedTupleLike( {} )\n","isnan":"var bool = isnan( NaN )\nbool = isnan( new Number( NaN ) )\nbool = isnan( 3.14 )\nbool = isnan( null )\n","isnan.isPrimitive":"var bool = isnan.isPrimitive( NaN )\nbool = isnan.isPrimitive( 3.14 )\nbool = isnan.isPrimitive( new Number( NaN ) )\n","isnan.isObject":"var bool = isnan.isObject( NaN )\nbool = isnan.isObject( new Number( NaN ) )\n","isNaNArray":"var bool = isNaNArray( [ NaN, NaN, NaN ] )\nbool = isNaNArray( [ NaN, 2 ] )\n","isNaNArray.primitives":"var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\nbool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n","isNaNArray.objects":"var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n","isNativeFunction":"var bool = isNativeFunction( Date )\nfunction beep() {};\nbool = isNativeFunction( beep )\nbool = isNativeFunction( {} )\n","isndarrayLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLike( M )\nbool = isndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isndarrayLike( 3.14 )\nbool = isndarrayLike( {} )\n","isNegativeInteger":"var bool = isNegativeInteger( -5.0 )\nbool = isNegativeInteger( new Number( -5.0 ) )\nbool = isNegativeInteger( 5.0 )\nbool = isNegativeInteger( -3.14 )\nbool = isNegativeInteger( null )\n","isNegativeInteger.isPrimitive":"var bool = isNegativeInteger.isPrimitive( -3.0 )\nbool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n","isNegativeInteger.isObject":"var bool = isNegativeInteger.isObject( -3.0 )\nbool = isNegativeInteger.isObject( new Number( -3.0 ) )\n","isNegativeIntegerArray":"var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n","isNegativeIntegerArray.primitives":"var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeIntegerArray.objects":"var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumber":"var bool = isNegativeNumber( -5.0 )\nbool = isNegativeNumber( new Number( -5.0 ) )\nbool = isNegativeNumber( -3.14 )\nbool = isNegativeNumber( 5.0 )\nbool = isNegativeNumber( null )\n","isNegativeNumber.isPrimitive":"var bool = isNegativeNumber.isPrimitive( -3.0 )\nbool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n","isNegativeNumber.isObject":"var bool = isNegativeNumber.isObject( -3.0 )\nbool = isNegativeNumber.isObject( new Number( -3.0 ) )\n","isNegativeNumberArray":"var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n","isNegativeNumberArray.primitives":"var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumberArray.objects":"var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeZero":"var bool = isNegativeZero( -0.0 )\nbool = isNegativeZero( new Number( -0.0 ) )\nbool = isNegativeZero( -3.14 )\nbool = isNegativeZero( 0.0 )\nbool = isNegativeZero( null )\n","isNegativeZero.isPrimitive":"var bool = isNegativeZero.isPrimitive( -0.0 )\nbool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n","isNegativeZero.isObject":"var bool = isNegativeZero.isObject( -0.0 )\nbool = isNegativeZero.isObject( new Number( -0.0 ) )\n","isNodeBuiltin":"var bool = isNodeBuiltin( 'cluster' )\nbool = isNodeBuiltin( 'crypto' )\nbool = isNodeBuiltin( 'fs-extra' )\nbool = isNodeBuiltin( '' )\n","isNodeDuplexStreamLike":"var Stream = require( 'stream' ).Duplex;\ns = new Stream();\nvar bool = isNodeDuplexStreamLike( s )\nbool = isNodeDuplexStreamLike( {} )\n","isNodeReadableStreamLike":"var Stream = require( 'stream' ).Readable;\ns = new Stream();\nvar bool = isNodeReadableStreamLike( s )\nbool = isNodeReadableStreamLike( {} )\n","isNodeREPL":"var bool = isNodeREPL()\n","isNodeStreamLike":"var Stream = require( 'stream' ).Stream;\ns = new Stream();\nvar bool = isNodeStreamLike( s )\nbool = isNodeStreamLike( {} )\n","isNodeTransformStreamLike":"var Stream = require( 'stream' ).Transform;\ns = new Stream();\nvar bool = isNodeTransformStreamLike( s )\nbool = isNodeTransformStreamLike( {} )\n","isNodeWritableStreamLike":"var Stream = require( 'stream' ).Writable;\ns = new Stream();\nvar bool = isNodeWritableStreamLike( s )\nbool = isNodeWritableStreamLike( {} )\n","isNonConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurableProperty( obj, 'boop' )\nbool = isNonConfigurableProperty( obj, 'beep' )\n","isNonConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurablePropertyIn( obj, 'boop' )\nbool = isNonConfigurablePropertyIn( obj, 'beep' )\n","isNonEnumerableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerableProperty( obj, 'boop' )\nbool = isNonEnumerableProperty( obj, 'beep' )\n","isNonEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerablePropertyIn( obj, 'boop' )\nbool = isNonEnumerablePropertyIn( obj, 'beep' )\n","isNonNegativeFinite":"var bool = isNonNegativeFinite( 5.0 )\nbool = isNonNegativeFinite( new Number( 5.0 ) )\nbool = isNonNegativeFinite( 3.14 )\nbool = isNonNegativeFinite( -5.0 )\nbool = isNonNegativeFinite( null )\nbool = isNonNegativeFinite( PINF )\n","isNonNegativeFinite.isPrimitive":"var bool = isNonNegativeFinite.isPrimitive( 3.0 )\nbool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeFinite.isObject":"var bool = isNonNegativeFinite.isObject( 3.0 )\nbool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n","isNonNegativeInteger":"var bool = isNonNegativeInteger( 5.0 )\nbool = isNonNegativeInteger( new Number( 5.0 ) )\nbool = isNonNegativeInteger( 3.14 )\nbool = isNonNegativeInteger( -5.0 )\nbool = isNonNegativeInteger( null )\n","isNonNegativeInteger.isPrimitive":"var bool = isNonNegativeInteger.isPrimitive( 3.0 )\nbool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeInteger.isObject":"var bool = isNonNegativeInteger.isObject( 3.0 )\nbool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n","isNonNegativeIntegerArray":"var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n","isNonNegativeIntegerArray.primitives":"var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeIntegerArray.objects":"var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumber":"var bool = isNonNegativeNumber( 5.0 )\nbool = isNonNegativeNumber( new Number( 5.0 ) )\nbool = isNonNegativeNumber( 3.14 )\nbool = isNonNegativeNumber( -5.0 )\nbool = isNonNegativeNumber( null )\n","isNonNegativeNumber.isPrimitive":"var bool = isNonNegativeNumber.isPrimitive( 3.0 )\nbool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeNumber.isObject":"var bool = isNonNegativeNumber.isObject( 3.0 )\nbool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n","isNonNegativeNumberArray":"var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n","isNonNegativeNumberArray.primitives":"var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumberArray.objects":"var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonPositiveInteger":"var bool = isNonPositiveInteger( -5.0 )\nbool = isNonPositiveInteger( new Number( -5.0 ) )\nbool = isNonPositiveInteger( 5.0 )\nbool = isNonPositiveInteger( -3.14 )\nbool = isNonPositiveInteger( null )\n","isNonPositiveInteger.isPrimitive":"var bool = isNonPositiveInteger.isPrimitive( -3.0 )\nbool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveInteger.isObject":"var bool = isNonPositiveInteger.isObject( -3.0 )\nbool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n","isNonPositiveIntegerArray":"var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n","isNonPositiveIntegerArray.primitives":"var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveIntegerArray.objects":"var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumber":"var bool = isNonPositiveNumber( -5.0 )\nbool = isNonPositiveNumber( new Number( -5.0 ) )\nbool = isNonPositiveNumber( -3.14 )\nbool = isNonPositiveNumber( 5.0 )\nbool = isNonPositiveNumber( null )\n","isNonPositiveNumber.isPrimitive":"var bool = isNonPositiveNumber.isPrimitive( -3.0 )\nbool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveNumber.isObject":"var bool = isNonPositiveNumber.isObject( -3.0 )\nbool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n","isNonPositiveNumberArray":"var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n","isNonPositiveNumberArray.primitives":"var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumberArray.objects":"var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonSymmetricMatrix":"var buf = [ 1, 2, 3, 4 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isNonSymmetricMatrix( M )\nbool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isNonSymmetricMatrix( 3.14 )\nbool = isNonSymmetricMatrix( {} )\n","isNull":"var bool = isNull( null )\nbool = isNull( true )\n","isNullArray":"var bool = isNullArray( [ null, null, null ] )\nbool = isNullArray( [ NaN, 2, null ] )\n","isNumber":"var bool = isNumber( 3.14 )\nbool = isNumber( new Number( 3.14 ) )\nbool = isNumber( NaN )\nbool = isNumber( null )\n","isNumber.isPrimitive":"var bool = isNumber.isPrimitive( 3.14 )\nbool = isNumber.isPrimitive( NaN )\nbool = isNumber.isPrimitive( new Number( 3.14 ) )\n","isNumber.isObject":"var bool = isNumber.isObject( 3.14 )\nbool = isNumber.isObject( new Number( 3.14 ) )\n","isNumberArray":"var bool = isNumberArray( [ 1, 2, 3 ] )\nbool = isNumberArray( [ '1', 2, 3 ] )\n","isNumberArray.primitives":"var arr = [ 1, 2, 3 ];\nvar bool = isNumberArray.primitives( arr )\narr = [ 1, new Number( 2 ) ];\nbool = isNumberArray.primitives( arr )\n","isNumberArray.objects":"var arr = [ new Number( 1 ), new Number( 2 ) ];\nvar bool = isNumberArray.objects( arr )\narr = [ new Number( 1 ), 2 ];\nbool = isNumberArray.objects( arr )\n","isNumericArray":"var bool = isNumericArray( new Int8Array( 10 ) )\nbool = isNumericArray( [ 1, 2, 3 ] )\nbool = isNumericArray( [ '1', '2', '3' ] )\n","isObject":"var bool = isObject( {} )\nbool = isObject( true )\n","isObjectArray":"var bool = isObjectArray( [ {}, new Number(3.0) ] )\nbool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isObjectArray( [ {}, '3.0' ] )\n","isObjectLike":"var bool = isObjectLike( {} )\nbool = isObjectLike( [] )\nbool = isObjectLike( null )\n","isOdd":"var bool = isOdd( 5.0 )\nbool = isOdd( new Number( 5.0 ) )\nbool = isOdd( 4.0 )\nbool = isOdd( new Number( 4.0 ) )\nbool = isOdd( -3.14 )\nbool = isOdd( null )\n","isOdd.isPrimitive":"var bool = isOdd.isPrimitive( -5.0 )\nbool = isOdd.isPrimitive( new Number( -5.0 ) )\n","isOdd.isObject":"var bool = isOdd.isObject( 5.0 )\nbool = isOdd.isObject( new Number( 5.0 ) )\n","isoWeeksInYear":"var num = isoWeeksInYear()\nnum = isoWeeksInYear( 2015 )\nnum = isoWeeksInYear( 2017 )\n","isPersymmetricMatrix":"var buf = [ 1, 2, 3, 1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isPersymmetricMatrix( M )\nbool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isPersymmetricMatrix( 3.14 )\nbool = isPersymmetricMatrix( {} )\n","isPlainObject":"var bool = isPlainObject( {} )\nbool = isPlainObject( null )\n","isPlainObjectArray":"var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isPlainObjectArray( [ {}, new Number(3.0) ] )\nbool = isPlainObjectArray( [ {}, '3.0' ] )\n","isPositiveInteger":"var bool = isPositiveInteger( 5.0 )\nbool = isPositiveInteger( new Number( 5.0 ) )\nbool = isPositiveInteger( 3.14 )\nbool = isPositiveInteger( -5.0 )\nbool = isPositiveInteger( null )\n","isPositiveInteger.isPrimitive":"var bool = isPositiveInteger.isPrimitive( 3.0 )\nbool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n","isPositiveInteger.isObject":"var bool = isPositiveInteger.isObject( 3.0 )\nbool = isPositiveInteger.isObject( new Number( 3.0 ) )\n","isPositiveIntegerArray":"var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n","isPositiveIntegerArray.primitives":"var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveIntegerArray.objects":"var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveNumber":"var bool = isPositiveNumber( 5.0 )\nbool = isPositiveNumber( new Number( 5.0 ) )\nbool = isPositiveNumber( 3.14 )\nbool = isPositiveNumber( -5.0 )\nbool = isPositiveNumber( null )\n","isPositiveNumber.isPrimitive":"var bool = isPositiveNumber.isPrimitive( 3.0 )\nbool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n","isPositiveNumber.isObject":"var bool = isPositiveNumber.isObject( 3.0 )\nbool = isPositiveNumber.isObject( new Number( 3.0 ) )\n","isPositiveNumberArray":"var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n","isPositiveNumberArray.primitives":"var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveNumberArray.objects":"var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveZero":"var bool = isPositiveZero( 0.0 )\nbool = isPositiveZero( new Number( 0.0 ) )\nbool = isPositiveZero( -3.14 )\nbool = isPositiveZero( -0.0 )\nbool = isPositiveZero( null )\n","isPositiveZero.isPrimitive":"var bool = isPositiveZero.isPrimitive( 0.0 )\nbool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n","isPositiveZero.isObject":"var bool = isPositiveZero.isObject( 0.0 )\nbool = isPositiveZero.isObject( new Number( 0.0 ) )\n","isPrime":"var bool = isPrime( 5.0 )\nbool = isPrime( new Number( 5.0 ) )\nbool = isPrime( 3.14 )\nbool = isPrime( -5.0 )\nbool = isPrime( null )\n","isPrime.isPrimitive":"var bool = isPrime.isPrimitive( 5.0 )\nbool = isPrime.isPrimitive( new Number( 5.0 ) )\n","isPrime.isObject":"var bool = isPrime.isObject( 5.0 )\nbool = isPrime.isObject( new Number( 5.0 ) )\n","isPrimitive":"var bool = isPrimitive( true )\nbool = isPrimitive( {} )\n","isPrimitiveArray":"var bool = isPrimitiveArray( [ '3', 2, null ] )\nbool = isPrimitiveArray( [ {}, 2, 1 ] )\nbool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n","isPRNGLike":"var bool = isPRNGLike( base.random.randu )\nbool = isPRNGLike( [ 1, 2, 3, 4 ] )\nbool = isPRNGLike( 3.14 )\nbool = isPRNGLike( {} )\n","isProbability":"var bool = isProbability( 0.5 )\nbool = isProbability( new Number( 0.5 ) )\nbool = isProbability( 3.14 )\nbool = isProbability( -5.0 )\nbool = isProbability( null )\n","isProbability.isPrimitive":"var bool = isProbability.isPrimitive( 0.3 )\nbool = isProbability.isPrimitive( new Number( 0.3 ) )\n","isProbability.isObject":"var bool = isProbability.isObject( 0.77 )\nbool = isProbability.isObject( new Number( 0.77 ) )\n","isProbabilityArray":"var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\nbool = isProbabilityArray( [ 0.8, 1.2 ] )\nbool = isProbabilityArray( [ 0.8, '0.2' ] )\n","isProbabilityArray.primitives":"var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\nbool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n","isProbabilityArray.objects":"var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\nbool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n","isPropertyKey":"var out = isPropertyKey( 'foo' )\nout = isPropertyKey( 1 )\nout = isPropertyKey( true )\n","isPrototypeOf":"function Foo() { return this; };\nfunction Bar() { return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar bool = isPrototypeOf( bar, Foo.prototype )\n","isRangeError":"var bool = isRangeError( new RangeError( 'beep' ) )\nbool = isRangeError( {} )\n","isReadableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadableProperty( obj, 'boop' )\nbool = isReadableProperty( obj, 'beep' )\n","isReadablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadablePropertyIn( obj, 'boop' )\nbool = isReadablePropertyIn( obj, 'beep' )\n","isReadOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyProperty( obj, 'boop' )\nbool = isReadOnlyProperty( obj, 'beep' )\n","isReadOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyPropertyIn( obj, 'boop' )\nbool = isReadOnlyPropertyIn( obj, 'beep' )\n","isReadWriteProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWriteProperty( obj, 'boop' )\nbool = isReadWriteProperty( obj, 'beep' )\n","isReadWritePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWritePropertyIn( obj, 'boop' )\nbool = isReadWritePropertyIn( obj, 'beep' )\n","isReferenceError":"var bool = isReferenceError( new ReferenceError( 'beep' ) )\nbool = isReferenceError( {} )\n","isRegExp":"var bool = isRegExp( /\\.+/ )\nbool = isRegExp( {} )\n","isRegExpString":"var bool = isRegExpString( '/beep/' )\nbool = isRegExpString( 'beep' )\nbool = isRegExpString( '' )\nbool = isRegExpString( null )\n","isRelativePath":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( './foo/bar/baz' )\n","isRelativePath.posix":"var bool = isRelativePath.posix( './foo/bar/baz' )\nbool = isRelativePath.posix( '/foo/../bar/baz' )\n","isRelativePath.win32":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n","isSafeInteger":"var bool = isSafeInteger( 5.0 )\nbool = isSafeInteger( new Number( 5.0 ) )\nbool = isSafeInteger( 2.0e200 )\nbool = isSafeInteger( -3.14 )\nbool = isSafeInteger( null )\n","isSafeInteger.isPrimitive":"var bool = isSafeInteger.isPrimitive( -3.0 )\nbool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n","isSafeInteger.isObject":"var bool = isSafeInteger.isObject( 3.0 )\nbool = isSafeInteger.isObject( new Number( 3.0 ) )\n","isSafeIntegerArray":"var arr = [ -3.0, new Number(0.0), 2.0 ];\nvar bool = isSafeIntegerArray( arr )\narr = [ -3.0, '3.0' ];\nbool = isSafeIntegerArray( arr )\n","isSafeIntegerArray.primitives":"var arr = [ -1.0, 10.0 ];\nvar bool = isSafeIntegerArray.primitives( arr )\narr = [ -1.0, 0.0, 5.0 ];\nbool = isSafeIntegerArray.primitives( arr )\narr = [ -3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.primitives( arr )\n","isSafeIntegerArray.objects":"var arr = [ new Number(1.0), new Number(3.0) ];\nvar bool = isSafeIntegerArray.objects( arr )\narr = [ -1.0, 0.0, 3.0 ];\nbool = isSafeIntegerArray.objects( arr )\narr = [ 3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.objects( arr )\n","isSameArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArray( x, y )\n","isSameComplex64":"var x = new Complex64( 1.0, 2.0 );\nvar y = new Complex64( 1.0, 2.0 );\nvar bool = isSameComplex64( x, y )\nx = new Complex64( NaN, NaN );\ny = new Complex64( NaN, NaN );\nbool = isSameComplex64( x, y )\n","isSameComplex64Array":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex64Array( x, y )\nx = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex64Array( x, y )\n","isSameComplex128":"var x = new Complex128( 1.0, 2.0 );\nvar y = new Complex128( 1.0, 2.0 );\nvar bool = isSameComplex128( x, y )\nx = new Complex128( NaN, NaN );\ny = new Complex128( NaN, NaN );\nbool = isSameComplex128( x, y )\n","isSameComplex128Array":"var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex128Array( x, y )\nx = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex128Array( x, y )\n","isSameFloat32Array":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat32Array( x, y )\nx = new Float32Array( [ NaN, NaN, NaN ] );\ny = new Float32Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat32Array( x, y )\n","isSameFloat64Array":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat64Array( x, y )\nx = new Float64Array( [ NaN, NaN, NaN ] );\ny = new Float64Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat64Array( x, y )\n","isSameNativeClass":"var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\nbool = isSameNativeClass( 'beep', 'boop' )\nbool = isSameNativeClass( {}, [] )\n","isSameType":"var bool = isSameType( true, true )\nbool = isSameType( {}, [] )\nbool = isSameType( 3.12, -3.12 )\nbool = isSameType( 0.0, '0.0' )\n","isSameValue":"var bool = isSameValue( true, true )\nbool = isSameValue( {}, {} )\nbool = isSameValue( -0.0, -0.0 )\nbool = isSameValue( -0.0, 0.0 )\nbool = isSameValue( NaN, NaN )\n","isSameValueZero":"var bool = isSameValueZero( true, true )\nbool = isSameValueZero( {}, {} )\nbool = isSameValueZero( -0.0, -0.0 )\nbool = isSameValueZero( -0.0, 0.0 )\nbool = isSameValueZero( NaN, NaN )\n","isSharedArrayBuffer":"var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\nbool = isSharedArrayBuffer( [] )\n","isSkewCentrosymmetricMatrix":"var buf = [ 2, 1, -1, -2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewCentrosymmetricMatrix( M )\nbool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewCentrosymmetricMatrix( 3.14 )\nbool = isSkewCentrosymmetricMatrix( {} )\n","isSkewPersymmetricMatrix":"var buf = [ 1, 0, 0, -1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewPersymmetricMatrix( M )\nbool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewPersymmetricMatrix( 3.14 )\nbool = isSkewPersymmetricMatrix( {} )\n","isSkewSymmetricMatrix":"var buf = [ 0, -1, 1, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewSymmetricMatrix( M )\nbool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewSymmetricMatrix( 3.14 )\nbool = isSkewSymmetricMatrix( {} )\n","isSlice":"var bool = isSlice( new Slice( 10 ) )\nbool = isSlice( 3.14 )\nbool = isSlice( {} )\n","isSquareMatrix":"var buf = [ 0, 0, 0, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSquareMatrix( M )\nbool = isSquareMatrix( [ 1, 2, 3, 4 ] )\nbool = isSquareMatrix( 3.14 )\nbool = isSquareMatrix( {} )\n","isSquareNumber":"var bool = isSquareNumber( 4.0 )\nbool = isSquareNumber( new Number( 4.0 ) )\nbool = isSquareNumber( 3.14 )\nbool = isSquareNumber( -5.0 )\nbool = isSquareNumber( null )\n","isSquareNumber.isPrimitive":"var bool = isSquareNumber.isPrimitive( 4.0 )\nbool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n","isSquareNumber.isObject":"var bool = isSquareNumber.isObject( 4.0 )\nbool = isSquareNumber.isObject( new Number( 4.0 ) )\n","isSquareTriangularNumber":"var bool = isSquareTriangularNumber( 36.0 )\nbool = isSquareTriangularNumber( new Number( 36.0 ) )\nbool = isSquareTriangularNumber( 3.14 )\nbool = isSquareTriangularNumber( -5.0 )\nbool = isSquareTriangularNumber( null )\n","isSquareTriangularNumber.isPrimitive":"var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\nbool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isSquareTriangularNumber.isObject":"var bool = isSquareTriangularNumber.isObject( 36.0 )\nbool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n","isStrictEqual":"var bool = isStrictEqual( true, true )\nbool = isStrictEqual( {}, {} )\nbool = isStrictEqual( -0.0, -0.0 )\nbool = isStrictEqual( -0.0, 0.0 )\nbool = isStrictEqual( NaN, NaN )\n","isString":"var bool = isString( 'beep' )\nbool = isString( new String( 'beep' ) )\nbool = isString( 5 )\n","isString.isPrimitive":"var bool = isString.isPrimitive( 'beep' )\nbool = isString.isPrimitive( new String( 'beep' ) )\n","isString.isObject":"var bool = isString.isObject( new String( 'beep' ) )\nbool = isString.isObject( 'beep' )\n","isStringArray":"var bool = isStringArray( [ 'abc', 'def' ] )\nbool = isStringArray( [ 'abc', 123 ] )\n","isStringArray.primitives":"var arr = [ 'abc', 'def' ];\nvar bool = isStringArray.primitives( arr )\narr = [ 'abc', new String( 'def' ) ];\nbool = isStringArray.primitives( arr )\n","isStringArray.objects":"var arr = [ new String( 'ab' ), new String( 'cd' ) ];\nvar bool = isStringArray.objects( arr )\narr = [ new String( 'abc' ), 'def' ];\nbool = isStringArray.objects( arr )\n","isSymbol":"var bool = isSymbol( Symbol( 'beep' ) )\nbool = isSymbol( Object( Symbol( 'beep' ) ) )\nbool = isSymbol( {} )\nbool = isSymbol( null )\nbool = isSymbol( true )\n","isSymbolArray":"var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\nbool = isSymbolArray( Symbol( 'beep' ) )\nbool = isSymbolArray( [] )\nbool = isSymbolArray( {} )\nbool = isSymbolArray( null )\nbool = isSymbolArray( true )\n","isSymbolArray.primitives":"var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.primitives( [] )\nbool = isSymbolArray.primitives( {} )\nbool = isSymbolArray.primitives( null )\nbool = isSymbolArray.primitives( true )\n","isSymbolArray.objects":"var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.objects( [] )\nbool = isSymbolArray.objects( {} )\nbool = isSymbolArray.objects( null )\nbool = isSymbolArray.objects( true )\n","isSymmetricMatrix":"var buf = [ 0, 1, 1, 2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSymmetricMatrix( M )\nbool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSymmetricMatrix( 3.14 )\nbool = isSymmetricMatrix( {} )\n","isSyntaxError":"var bool = isSyntaxError( new SyntaxError( 'beep' ) )\nbool = isSyntaxError( {} )\n","isTriangularNumber":"var bool = isTriangularNumber( 36.0 )\nbool = isTriangularNumber( new Number( 36.0 ) )\nbool = isTriangularNumber( 3.14 )\nbool = isTriangularNumber( -5.0 )\nbool = isTriangularNumber( null )\n","isTriangularNumber.isPrimitive":"var bool = isTriangularNumber.isPrimitive( 36.0 )\nbool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isTriangularNumber.isObject":"var bool = isTriangularNumber.isObject( 36.0 )\nbool = isTriangularNumber.isObject( new Number( 36.0 ) )\n","isTruthy":"var bool = isTruthy( true )\nbool = isTruthy( {} )\nbool = isTruthy( [] )\nbool = isTruthy( false )\nbool = isTruthy( '' )\nbool = isTruthy( 0 )\nbool = isTruthy( null )\nbool = isTruthy( void 0 )\nbool = isTruthy( NaN )\n","isTruthyArray":"var bool = isTruthyArray( [ {}, [] ] )\nbool = isTruthyArray( [ null, '' ] )\nbool = isTruthyArray( [] )\n","isTypedArray":"var bool = isTypedArray( new Int8Array( 10 ) )\n","isTypedArrayLength":"var bool = isTypedArrayLength( 5 )\nbool = isTypedArrayLength( 2.0e200 )\nbool = isTypedArrayLength( -3.14 )\nbool = isTypedArrayLength( null )\n","isTypedArrayLike":"var bool = isTypedArrayLike( new Int16Array() )\nbool = isTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4\n })\n","isTypeError":"var bool = isTypeError( new TypeError( 'beep' ) )\nbool = isTypeError( {} )\n","isUint8Array":"var bool = isUint8Array( new Uint8Array( 10 ) )\nbool = isUint8Array( [] )\n","isUint8ClampedArray":"var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\nbool = isUint8ClampedArray( [] )\n","isUint16Array":"var bool = isUint16Array( new Uint16Array( 10 ) )\nbool = isUint16Array( [] )\n","isUint32Array":"var bool = isUint32Array( new Uint32Array( 10 ) )\nbool = isUint32Array( [] )\n","isUNCPath":"var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\nbool = isUNCPath( '/foo/bar/baz' )\n","isUndefined":"var bool = isUndefined( void 0 )\nbool = isUndefined( null )\n","isUndefinedOrNull":"var bool = isUndefinedOrNull( void 0 )\nbool = isUndefinedOrNull( null )\nbool = isUndefinedOrNull( false )\n","isUnityProbabilityArray":"var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\nbool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\nbool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\nbool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n","isUppercase":"var bool = isUppercase( 'HELLO' )\nbool = isUppercase( 'World' )\n","isURI":"var bool = isURI( 'http://google.com' )\nbool = isURI( 'http://localhost/' )\nbool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\nbool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\nbool = isURI( '' )\nbool = isURI( 'foo@bar' )\nbool = isURI( '://foo/' )\nbool = isURI( 'http://' )\nbool = isURI( 'http:////foo.html' )\nbool = isURI( 'http://example.w3.org/%a' )\n","isURIError":"var bool = isURIError( new URIError( 'beep' ) )\nbool = isURIError( {} )\n","isVectorLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isVectorLike( M )\nbool = isVectorLike( [ 1, 2, 3, 4 ] )\nbool = isVectorLike( 3.14 )\nbool = isVectorLike( {} )\n","isWhitespace":"var bool = isWhitespace( ' ' )\nbool = isWhitespace( 'abcdef' )\nbool = isWhitespace( '' )\n","isWritableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritableProperty( obj, 'boop' )\nbool = isWritableProperty( obj, 'beep' )\n","isWritablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritablePropertyIn( obj, 'boop' )\nbool = isWritablePropertyIn( obj, 'beep' )\n","isWriteOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyProperty( obj, 'boop' )\nbool = isWriteOnlyProperty( obj, 'beep' )\n","isWriteOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyPropertyIn( obj, 'boop' )\nbool = isWriteOnlyPropertyIn( obj, 'beep' )\n","iterAbs":"var it = iterAbs( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAbs2":"var it = iterAbs2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAcos":"var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcosh":"var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcot":"var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoth":"var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcovercos":"var it = iterAcovercos( random.iterators.uniform( -2.0, 0.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoversin":"var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAdd":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterAdd( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterAdvance":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar it = iterAdvance( arr, 4 );\nvar v = it.next().value\nvar bool = it.next().done\n","iterAhavercos":"var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAhaversin":"var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAny":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterAny( arr )\n","iterAnyBy":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v === 1 ); };\nvar bool = iterAnyBy( arr, fcn )\n","iterAsin":"var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAsinh":"var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan":"var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan2":"var x = random.iterators.uniform( -2.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterAtan2( y, x );\nvar r = it.next().value\nr = it.next().value\n","iterAtanh":"var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterator2array":"var opts = { 'iter': 10 };\nvar arr = iterator2array( random.iterators.randu( opts ) )\n","iterator2arrayview":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayview( it, out, 5, 15 )\n","iterator2arrayviewRight":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayviewRight( it, out, 5, 15 )\n","iteratorStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream( it );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","iteratorStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = iteratorStream.factory( opts );\n","iteratorStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream.objectMode( it );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","IteratorSymbol":"var s = IteratorSymbol\n","iterAvercos":"var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAversin":"var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterawgn":"var src = iterSineWave();\nvar it = iterawgn( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawln":"var src = iterSineWave();\nvar it = iterawln( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawun":"var src = iterSineWave();\nvar it = iterawun( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterBartlettHannPulse":"var it = iterBartlettHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBartlettPulse":"var it = iterBartlettPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBesselj0":"var it = iterBesselj0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBesselj1":"var it = iterBesselj1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely0":"var it = iterBessely0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely1":"var it = iterBessely1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBeta":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBeta( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBetaln":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBetaln( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBinet":"var it = iterBinet( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCbrt":"var it = iterCbrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil":"var it = iterCeil( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil2":"var it = iterCeil2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil10":"var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterCompositesSeq":"var it = iterCompositesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterConcat":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = array2iterator( [ 3, 4 ] );\nvar it = iterConcat( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterConstant":"var it = iterConstant( 3.14 );\nvar v = it.next().value\nv = it.next().value\n","iterContinuedFraction":"var terms = array2iterator( [ 3, 4, 12, 4 ] );\nvar v = iterContinuedFraction( terms )\n","iterContinuedFractionSeq":"var it = iterContinuedFractionSeq( 3.245 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\nit = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n","iterCos":"var it = iterCos( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCosh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterCosh( r );\nvar v = it.next().value\nv = it.next().value\n","iterCosineWave":"var it = iterCosineWave();\nvar v = it.next().value\nv = it.next().value\n","iterCosm1":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCosm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterCospi":"var it = iterCospi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCounter":"var it = iterCounter( random.iterators.randu() );\nvar v = it.next().value\nv = it.next().value\n","iterCovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterCoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterCubesSeq":"var it = iterCubesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","itercugmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercugmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercuhmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercuhmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumax( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumaxabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumean( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs2( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumidrange( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumin( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuminabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuprod( arr );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itercurange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercurange( arr );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\nr = it.next().value\n","itercusum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusum( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs2( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterDatespace":"var t1 = new Date();\nvar it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\nvar v = it.next().value\nv = it.next().value\n","iterDedupe":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nvar it = iterDedupe( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDedupeBy":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nfunction fcn( v ) { return v; };\nvar it = iterDedupeBy( arr, fcn );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDeg2rad":"var r = random.iterators.uniform( -360.0, 360.0 );\nvar it = iterDeg2rad( r );\nvar v = it.next().value\nv = it.next().value\n","iterDigamma":"var r = random.iterators.uniform( 0.01, 5.0 );\nvar it = iterDigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterDiracComb":"var it = iterDiracComb();\nvar v = it.next().value\nv = it.next().value\n","iterDiracDelta":"var it = iterDiracDelta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterDivide":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterDivide( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterEllipe":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipe( r );\nvar v = it.next().value\nv = it.next().value\n","iterEllipk":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipk( r );\nvar v = it.next().value\nv = it.next().value\n","iterEmpty":"var it = iterEmpty();\nvar bool = it.next().done\n","iterErf":"var it = iterErf( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfc":"var it = iterErfc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfcinv":"var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterErfinv":"var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterEta":"var it = iterEta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterEvenIntegersSeq":"var it = iterEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterEvery":"var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\nvar bool = iterEvery( arr )\n","iterEveryBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterEveryBy( arr, fcn )\n","iterExp":"var it = iterExp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterExp2":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp2( r );\nvar v = it.next().value\nv = it.next().value\n","iterExp10":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp10( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterExpit( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterExpm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1rel":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExpm1rel( r );\nvar v = it.next().value\nv = it.next().value\n","iterFactorial":"var it = iterFactorial( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialln":"var it = iterFactorialln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialsSeq":"var it = iterFactorialsSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFibonacciSeq":"var it = iterFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterFifthPowersSeq":"var it = iterFifthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFill":"var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterFilter":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilter( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFilterMap":"function f( v ) { if ( v > 2 ) { return v * 10 }; };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilterMap( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFirst":"var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\nvar v = iterFirst( arr )\n","iterFlatTopPulse":"var it = iterFlatTopPulse();\nvar v = it.next().value\nv = it.next().value\n","iterFloor":"var it = iterFloor( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFloor2":"var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFloor10":"var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFlow":"var o = {};\no.head = iterHead;\no.some = iterSome;\nvar fiter = iterFlow( o )\n","iterForEach":"function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterForEach( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterFourthPowersSeq":"var it = iterFourthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFresnelc":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnelc( r );\nvar v = it.next().value\nv = it.next().value\n","iterFresnels":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnels( r );\nvar v = it.next().value\nv = it.next().value\n","iterGamma":"var it = iterGamma( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterGamma1pm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterGamma1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterGammaln":"var it = iterGammaln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterHacovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHacoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHannPulse":"var it = iterHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterHavercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHavercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHaversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHaversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHead":"var it = iterHead( random.iterators.randu(), 5 );\nvar r = it.next().value\nr = it.next().value\n","iterIncrspace":"var it = iterIncrspace( 0, 101, 2 );\nvar v = it.next().value\nv = it.next().value\n","iterIntegersSeq":"var it = iterIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterIntersection":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterIntersection( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterIntersectionByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nfunction f( v ) { return v.toString(); };\nvar it = iterIntersectionByHash( it1, it2, f );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterInv":"var it = iterInv( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLanczosPulse":"var it = iterLanczosPulse();\nvar v = it.next().value\nv = it.next().value\n","iterLast":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar v = iterLast( arr )\n","iterLength":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar len = iterLength( arr )\n","iterLinspace":"var it = iterLinspace( 0, 99, 100 );\nvar v = it.next().value\nv = it.next().value\n","iterLn":"var it = iterLn( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog":"var x = random.iterators.uniform( 0.0, 100.0 );\nvar y = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterLog( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterLog1mexp":"var it = iterLog1mexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1p":"var it = iterLog1p( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1pexp":"var it = iterLog1pexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog2":"var it = iterLog2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog10":"var it = iterLog10( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLogit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterLogit( r );\nvar v = it.next().value\nv = it.next().value\n","iterLogspace":"var it = iterLogspace( 0, 3, 4 );\nvar v = it.next().value\nv = it.next().value\n","iterLucasSeq":"var it = iterLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterMap":"function f( v ) { return v * 10.0; };\nvar it = iterMap( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterMapN":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nfunction fcn( x, y ) { return x + y; };\nvar it = iterMapN( it1, it2, fcn );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermax":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermax( arr )\n","itermaxabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermaxabs( arr )\n","itermean":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = itermean( arr )\n","itermeanabs":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs( arr )\n","itermeanabs2":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs2( arr )\n","itermidrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = itermidrange( arr )\n","itermin":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermin( arr )\n","iterminabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = iterminabs( arr )\n","itermmax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmax( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmaxabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmean( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs2( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmidrange( arr, 3 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itermmin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmin( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermminabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","iterMod":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterMod( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermprod( arr, 3 );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itermrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermrange( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermsum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsum( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs2( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterMultiply":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterMultiply( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterNegaFibonacciSeq":"var it = iterNegaFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegaLucasSeq":"var it = iterNegaLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeEvenIntegersSeq":"var it = iterNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeIntegersSeq":"var it = iterNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeOddIntegersSeq":"var it = iterNegativeOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNone":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterNone( arr )\n","iterNoneBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v <= 0 ); };\nvar bool = iterNoneBy( arr, fcn )\n","iterNonFibonacciSeq":"var it = iterNonFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeEvenIntegersSeq":"var it = iterNonNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeIntegersSeq":"var it = iterNonNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveEvenIntegersSeq":"var it = iterNonPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveIntegersSeq":"var it = iterNonPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonSquaresSeq":"var it = iterNonSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterNth":"var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\nvar v = iterNth( arr, 3 )\n","iterOddIntegersSeq":"var it = iterOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterPeriodicSinc":"var it = iterPeriodicSinc( 7 );\nvar v = it.next().value\nv = it.next().value\n","iterPipeline":"var it1 = iterThunk( iterHead, 100 );\nfunction f( r ) { return ( r > 0.95 ); };\nvar it2 = iterThunk( iterSomeBy, 5, f );\nvar p = iterPipeline( it1, it2 );\nvar bool = p( random.iterators.randu() )\n","iterPop":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPop( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterPositiveEvenIntegersSeq":"var it = iterPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveIntegersSeq":"var it = iterPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveOddIntegersSeq":"var it = iterPositiveOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPow":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterPow( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterPrimesSeq":"var it = iterPrimesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterprod":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = iterprod( arr )\n","iterPulse":"var it = iterPulse();\nvar v = it.next().value\nv = it.next().value\n","iterPush":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPush( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterRad2deg":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterRad2deg( r );\nvar v = it.next().value\nv = it.next().value\n","iterRamp":"var it = iterRamp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = iterrange( arr )\n","iterReject":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterReject( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterReplicate":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nvar it2 = iterReplicate( it1, 2 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterReplicateBy":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nfunction f( v, i ) { return i + 1; };\nvar it2 = iterReplicateBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterRound":"var it = iterRound( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterRound2":"var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRound10":"var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRsqrt":"var it = iterRsqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSawtoothWave":"var it = iterSawtoothWave();\nvar v = it.next().value\nv = it.next().value\n","iterShift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterShift( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterSignum":"var it = iterSignum( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSin":"var it = iterSin( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSinc":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinc( r );\nvar v = it.next().value\nv = it.next().value\n","iterSineWave":"var it = iterSineWave();\nvar v = it.next().value\nv = it.next().value\n","iterSinh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinh( r );\nvar v = it.next().value\nv = it.next().value\n","iterSinpi":"var it = iterSinpi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSlice":"var it = iterSlice( random.iterators.randu(), 5, 10 );\nvar r = it.next().value\nr = it.next().value\n","iterSome":"var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = iterSome( arr, 3 )\n","iterSomeBy":"var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterSomeBy( arr, 3, fcn )\n","iterSpence":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSpence( r );\nvar v = it.next().value\nv = it.next().value\n","iterSqrt":"var it = iterSqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSqrt1pm1":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSqrt1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterSquaredTriangularSeq":"var it = iterSquaredTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquaresSeq":"var it = iterSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquareWave":"var it = iterSquareWave();\nvar v = it.next().value\nv = it.next().value\n","iterstdev":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar m = iterstdev( arr )\n","iterStep":"var it = iterStep( 0, 2, 10 );\nvar v = it.next().value\nv = it.next().value\n","iterStrided":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nvar it = iterStrided( arr, 2, 1 );\nvar r = it.next().value\nr = it.next().value\n","iterStridedBy":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nfunction stride( v, i ) { return (i % 10)+1; };\nvar it = iterStridedBy( arr, stride );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterSubtract":"var it1 = array2iterator( [ 1.0, 5.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterSubtract( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itersum":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = itersum( arr )\n","itersumabs":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs( arr )\n","itersumabs2":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs2( arr )\n","iterTan":"var r = random.iterators.uniform( -1.57, 1.57 );\nvar it = iterTan( r );\nvar v = it.next().value\nv = it.next().value\n","iterTanh":"var r = random.iterators.uniform( -4.0, 4.0 );\nvar it = iterTanh( r );\nvar v = it.next().value\nv = it.next().value\n","iterThunk":"var fcn = iterThunk( iterSome, 3 );\nvar arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = fcn( arr )\n","iterTriangleWave":"var it = iterTriangleWave();\nvar v = it.next().value\nv = it.next().value\n","iterTriangularSeq":"var it = iterTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterTrigamma":"var r = random.iterators.uniform( 0.01, 50.0 );\nvar it = iterTrigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterTrunc":"var it = iterTrunc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc2":"var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc10":"var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterUnion":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterUnion( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterUnique":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = iterUnique( it1 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueBy":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( a, b ) { return ( a !== b ); };\nvar it2 = iterUniqueBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( v ) { return v.toString(); };\nvar it2 = iterUniqueByHash( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUnitspace":"var it = iterUnitspace( 0, 99 );\nvar v = it.next().value\nv = it.next().value\n","iterUnshift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterUnshift( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","itervariance":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar s2 = itervariance( arr )\n","iterVercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterVersin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVersin( r );\nvar v = it.next().value\nv = it.next().value\n","iterZeta":"var r = random.iterators.uniform( 1.1, 50.0 );\nvar it = iterZeta( r );\nvar v = it.next().value\nv = it.next().value\n","joinStream":"var s = joinStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = joinStream.factory( opts );\nvar s = createStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.objectMode":"var s = joinStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","kde2d":"var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\nvar y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\nvar out = kde2d( x, y )\n","kebabcase":"var out = kebabcase( 'Hello World!' )\nout = kebabcase( 'I am a tiny little teapot' )\n","keyBy":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyBy( arr, toKey )\n","keyByRight":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyByRight( arr, toKey )\n","keysIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = keysIn( obj )\n","kruskalTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = kruskalTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = kruskalTest( arr, { 'groups': groups } )\n","kstest":"var rnorm = base.random.normal.factory({ 'seed': 4839 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\nvar out = kstest( x, 'normal', 0.0, 1.0 )\nout = kstest( x, 'normal', 3.0, 1.0 )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0 )\nout.print()\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\nx = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\nout = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n","leveneTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = leveneTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = leveneTest( arr, { 'groups': groups } )\n","LinkedList":"var list = LinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","linspace":"var arr = linspace( 0.0, 100.0, 6 )\narr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\narr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n","linspace.assign":"var arr = [ 0, 0, 0, 0, 0, 0 ];\nvar out = linspace.assign( 0, 100, arr )\nvar bool = ( arr === out )\narr = [ 0, 0, 0, 0, 0 ];\nout = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n","LIU_NEGATIVE_OPINION_WORDS_EN":"var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n","LIU_POSITIVE_OPINION_WORDS_EN":"var list = LIU_POSITIVE_OPINION_WORDS_EN()\n","LN_HALF":"LN_HALF\n","LN_PI":"LN_PI\n","LN_SQRT_TWO_PI":"LN_SQRT_TWO_PI\n","LN_TWO_PI":"LN_TWO_PI\n","LN2":"LN2\n","LN10":"LN10\n","LOG2E":"LOG2E\n","LOG10E":"LOG10E\n","logspace":"var arr = logspace( 0, 2, 6 )\n","lowercase":"var out = lowercase( 'bEEp' )\n","lowercaseKeys":"var obj = { 'A': 1, 'B': 2 };\nvar out = lowercaseKeys( obj )\n","lowess":"var x = new Float64Array( 100 );\nvar y = new Float64Array( x.length );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = i;\n y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n }\nvar out = lowess( x, y );\nvar yhat = out.y;\nvar h = Plot( [ x, x ], [ y, yhat ] );\nh.lineStyle = [ 'none', '-' ];\nh.symbols = [ 'closed-circle', 'none' ];\nh.view( 'window' );\n","lpad":"var out = lpad( 'a', 5 )\nout = lpad( 'beep', 10, 'b' )\nout = lpad( 'boop', 12, 'beep' )\n","ltrim":"var out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n","MALE_FIRST_NAMES_EN":"var list = MALE_FIRST_NAMES_EN()\n","map":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = map( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = map( arr, f );\nvar v = out.get( 1, 1 )\n","map.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","map2":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2( x, y, f );\nvar v = out.get( 1, 1 )\n","map2.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map2d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\nvar out = map2d( arr, f );\nout[ 0 ]\nout[ 1 ]\n","map2Right":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2Right( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2Right( x, y, f );\nvar v = out.get( 1, 1 )\n","map2Right.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2Right.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2Right.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map3d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\nvar out = map3d( arr, f );\nout[ 0 ][ 0 ]\nout[ 1 ][ 0 ]\n","map4d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\nvar out = map4d( arr, f );\nout[ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ]\n","map5d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\nvar out = map5d( arr, f );\nout[ 0 ][ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ][ 0 ]\n","mapArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nfunction clbk( v ) { return v * 2; };\nvar bar = mapArguments( foo, clbk );\nvar out = bar( 1, 2, 3 )\n","mapFun":"function fcn( i ) { return i; };\nvar arr = mapFun( fcn, 5 )\n","mapFunAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nmapFunAsync( fcn, 10, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nvar opts = { 'limit': 2 };\nmapFunAsync( fcn, 10, opts, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nvar opts = { 'series': true };\nmapFunAsync( fcn, 10, opts, done )\n","mapFunAsync.factory":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nvar opts = { 'series': true };\nvar f = mapFunAsync.factory( opts, fcn );\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nf( 10, done )\n","mapKeys":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapKeys( obj, transform )\n","mapKeysAsync":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapKeysAsync( obj, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\n","mapKeysAsync.factory":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapKeysAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","mapReduce":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduce( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduce( arr, 0.0, f1, f2 )\n","mapReduceRight":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduceRight( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduceRight( arr, 0.0, f1, f2 )\n","mapRight":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = mapRight( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapRight( arr, f );\nvar v = out.get( 1, 1 )\n","mapRight.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmapRight.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmapRight.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","mapValues":"function transform( value, key ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapValues( obj, transform )\n","mapValuesAsync":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapValuesAsync( obj, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\n","mapValuesAsync.factory":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapValuesAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","maskArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = maskArguments( foo, [ 1, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","MAX_ARRAY_LENGTH":"MAX_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"MAX_TYPED_ARRAY_LENGTH\n","maybeBroadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","maybeBroadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = maybeBroadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","memoize":"function factorial( n ) {\n var prod;\n var i;\n prod = 1;\n for ( i = n; i > 1; i-- ) {\n prod *= i;\n }\n return prod;\n };\nvar memoized = memoize( factorial );\nvar v = memoized( 5 )\nv = memoized( 5 )\n","merge":"var target = { 'a': 'beep' };\nvar source = { 'a': 'boop', 'b': 'bap' };\nvar out = merge( target, source )\nvar bool = ( out === target )\n","merge.factory":"var opts = {\n 'level': 100,\n 'copy': true,\n 'override': true,\n 'extend': true\n };\nvar merge = merge.factory( opts )\nmerge = merge.factory( { 'level': 2 } );\nvar target = {\n '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n };\nvar source = {\n '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n };\nvar out = merge( target, source )\nmerge = merge.factory( { 'copy': false } );\ntarget = {};\nsource = { 'a': [ 1, 2, 3 ] };\nout = merge( target, source );\nvar bool = ( out.a === source.a )\nmerge = merge.factory( { 'override': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'a': null, 'c': 'bop' };\nout = merge( target, source )\nfunction strategy( a, b, key ) {\n // a => target value\n // b => source value\n // key => object key\n if ( key === 'a' ) {\n return b;\n }\n if ( key === 'b' ) {\n return a;\n }\n return 'bebop';\n };\nmerge = merge.factory( { 'override': strategy } );\ntarget = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\nsource = { 'a': null, 'b': {}, 'c': 'bop' };\nout = merge( target, source )\nmerge = merge.factory( { 'extend': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'b': 'hello', 'c': 'world' };\nout = merge( target, source )\n","MILLISECONDS_IN_DAY":"var days = 3.14;\nvar ms = days * MILLISECONDS_IN_DAY\n","MILLISECONDS_IN_HOUR":"var hrs = 3.14;\nvar ms = hrs * MILLISECONDS_IN_HOUR\n","MILLISECONDS_IN_MINUTE":"var mins = 3.14;\nvar ms = mins * MILLISECONDS_IN_MINUTE\n","MILLISECONDS_IN_SECOND":"var secs = 3.14;\nvar ms = secs * MILLISECONDS_IN_SECOND\n","MILLISECONDS_IN_WEEK":"var weeks = 3.14;\nvar ms = weeks * MILLISECONDS_IN_WEEK\n","MINARD_NAPOLEONS_MARCH":"var data = MINARD_NAPOLEONS_MARCH();\nvar army = data.army\nvar cities = data.cities\nvar labels = data.labels\nvar river = data.river\nvar t = data.temperature\n","MINUTES_IN_DAY":"var days = 3.14;\nvar mins = days * MINUTES_IN_DAY\n","MINUTES_IN_HOUR":"var hrs = 3.14;\nvar mins = hrs * MINUTES_IN_HOUR\n","MINUTES_IN_WEEK":"var wks = 3.14;\nvar mins = wks * MINUTES_IN_WEEK\n","minutesInMonth":"var num = minutesInMonth()\nnum = minutesInMonth( 2 )\nnum = minutesInMonth( 2, 2016 )\nnum = minutesInMonth( 2, 2017 )\nnum = minutesInMonth( 'feb', 2016 )\nnum = minutesInMonth( 'february', 2016 )\n","minutesInYear":"var num = minutesInYear()\nnum = minutesInYear( 2016 )\nnum = minutesInYear( 2017 )\n","MOBY_DICK":"var data = MOBY_DICK()\n","MONTH_NAMES_EN":"var list = MONTH_NAMES_EN()\n","MONTHS_IN_YEAR":"var yrs = 3.14;\nvar mons = yrs * MONTHS_IN_YEAR\n","moveProperty":"var obj1 = { 'a': 'b' };\nvar obj2 = {};\nvar bool = moveProperty( obj1, 'a', obj2 )\nbool = moveProperty( obj1, 'c', obj2 )\n","MultiSlice":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\n","MultiSlice.prototype.ndims":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.ndims\n","MultiSlice.prototype.data":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.data\n","MultiSlice.prototype.toString":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.toString()\n","MultiSlice.prototype.toJSON":"var s = new Slice( 2, 10, 1 );\nvar ms = new MultiSlice( 2, s );\nms.toJSON()\n","namedtypedtuple":"var opts = {};\nopts.name = 'Point';\nvar factory = namedtypedtuple( [ 'x', 'y' ], opts );\nvar tuple = factory();\n","NAN":"NAN\n","naryFunction":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = naryFunction( foo, 2 );\nvar out = bar( 1, 2, 3 )\n","nativeClass":"var str = nativeClass( 'a' )\nstr = nativeClass( 5 )\nfunction Beep(){};\nstr = nativeClass( new Beep() )\n","ndarray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","ndarray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","ndarray2array":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2array( arr )\n","ndarrayCastingModes":"var out = ndarrayCastingModes()\n","ndarrayDataBuffer":"var opts = { 'dtype': 'float64' };\nvar out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataType":"var opts = { 'dtype': 'float64' };\nvar dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataTypes":"var out = ndarrayDataTypes()\nout = ndarrayDataTypes( 'floating_point' )\n","ndarrayDispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\nvar xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\nf( x, y );\nybuf\n","ndarrayFlag":"var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n","ndarrayFlags":"var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayIndexModes":"var out = ndarrayIndexModes()\n","ndarrayMinDataType":"var dt = ndarrayMinDataType( 3.141592653589793 )\ndt = ndarrayMinDataType( 3 )\ndt = ndarrayMinDataType( -3 )\ndt = ndarrayMinDataType( '-3' )\n","ndarrayMostlySafeCasts":"var out = ndarrayMostlySafeCasts( 'float32' )\n","ndarrayNextDataType":"var out = ndarrayNextDataType( 'float32' )\n","ndarrayOffset":"var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayOrder":"var opts = { 'order': 'row-major' };\nvar dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayOrders":"var out = ndarrayOrders()\n","ndarrayPromotionRules":"var out = ndarrayPromotionRules( 'float32', 'int32' )\n","ndarraySafeCasts":"var out = ndarraySafeCasts( 'float32' )\n","ndarraySameKindCasts":"var out = ndarraySameKindCasts( 'float32' )\n","ndarrayShape":"var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayStride":"var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n","ndarrayStrides":"var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n","ndat":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nndat( x, 0, 1 )\nndat( x, 1, 0 )\n","ndempty":"var arr = ndempty( [ 2, 2 ] )\nvar sh = arr.shape\nvar dt = arr.dtype\n","ndemptyLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = ndemptyLike( x )\nsh = y.shape\ndt = y.dtype\n","ndims":"var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n","nditerColumnEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumnEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerColumns":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumns( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerEntries( x );\nvar v = it.next().value\nv = it.next().value\n","nditerIndices":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerIndices( x.shape );\nvar v = it.next().value\nv = it.next().value\n","nditerMatrices":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrices( x );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrixEntries":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrixEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRowEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRowEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRows":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRows( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerValues":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerValues( x );\nvar v = it.next().value\nv = it.next().value\n","ndslice":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar s = new MultiSlice( null, 1 )\nvar y = ndslice( x, s )\ny.shape\nndarray2array( y )\n","ndsliceAssign":"var y = ndzeros( [ 2, 2 ] )\nvar x = scalar2ndarray( 3.0 )\nvar s = new MultiSlice( null, 1 )\nvar out = ndsliceAssign( x, y, s )\nvar bool = ( out === y )\nndarray2array( y )\n","ndsliceDimension":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimension( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionFrom( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceFrom( x, 0, 1 )\ny.shape\nndarray2array( y )\n","ndsliceTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndzeros":"var arr = ndzeros( [ 2, 2 ] )\nvar sh = arr.shape\nvar dt = arr.dtype\n","ndzerosLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = ndzerosLike( x )\nsh = y.shape\ndt = y.dtype\n","nextGraphemeClusterBreak":"var out = nextGraphemeClusterBreak( 'last man standing', 4 )\nout = nextGraphemeClusterBreak( 'presidential election', 8 )\nout = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\nout = nextGraphemeClusterBreak( '🌷' )\n","nextTick":"function f() { console.log( 'beep' ); };\nnextTick( f )\n","NIGHTINGALES_ROSE":"var data = NIGHTINGALES_ROSE()\n","NINF":"NINF\n","NODE_VERSION":"NODE_VERSION\n","none":"var arr = [ 0, 0, 0, 0, 0 ];\nvar bool = none( arr )\n","noneBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = noneBy( arr, negative )\n","noneByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\n","noneByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","noneByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ -1, -2, -3, -4 ];\nvar bool = noneByRight( arr, positive )\n","noneByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\n","noneByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","nonEnumerableProperties":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar props = nonEnumerableProperties( obj )\n","nonEnumerablePropertiesIn":"var props = nonEnumerablePropertiesIn( [] )\n","nonEnumerablePropertyNames":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNames( obj )\n","nonEnumerablePropertyNamesIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNamesIn( obj )\n","nonEnumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbols( obj )\n","nonEnumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbolsIn( obj )\n","nonIndexKeys":"function Foo() { this.beep = 'boop'; this[0] = 3.14; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = nonIndexKeys( obj )\n","noop":"noop();\n","now":"var ts = now()\n","NUM_CPUS":"NUM_CPUS\n","num2words":"var out = num2words( 123 )\nout = num2words( 16.31 )\nout = num2words( 123, { 'lang': 'de' } )\n","Number":"var v = new Number( 5 )\n","numel":"var n = numel( ndzeros( [ 3, 3, 3 ] ) )\n","numelDimension":"var out = numelDimension( ndzeros( [ 4, 2, 3 ] ), 0 )\n","numGraphemeClusters":"var out = numGraphemeClusters( 'beep' )\nout = numGraphemeClusters( '🌷' )\n","Object":"var o = new Object( null )\no = new Object( 5.0 )\no = new Object( 'beep' )\n","Object.assign":"var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n","Object.create":"var o = Object.create( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperties":"var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperty":"var o = Object.defineProperty( {}, 'a', {\n","Object.entries":"var o = Object.entries( { 'a': 1, 'b': 2 } )\n","Object.freeze":"var o = Object.freeze( { 'a': 1 } )\n","Object.getOwnPropertyDescriptor":"var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n","Object.getOwnPropertyDescriptors":"var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertyNames":"var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertySymbols":"var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n","Object.getPrototypeOf":"var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n","Object.hasOwn":"var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n","Object.is":"var o = Object.is( 1, 1 )\nvar o = Object.is( 1, '1' )\n","Object.isExtensible":"var o = Object.isExtensible( { 'a': 1 } )\n","Object.isFrozen":"var o = Object.isFrozen( { 'a': 1 } )\nvar o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n","Object.isSealed":"var o = Object.isSealed( { 'a': 1 } )\nvar o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n","Object.keys":"var o = Object.keys( { 'a': 1, 'b': 2 } )\n","Object.preventExtensions":"var o = Object.preventExtensions( { 'a': 1 } )\no.b = 2;\no\n","Object.seal":"var o = Object.seal( { 'a': 1 } )\no.b = 2;\no\ndelete o.a;\no\n","Object.setPrototypeOf":"var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\no.b\n","Object.values":"var o = Object.values( { 'a': 1, 'b': 2 } )\n","Object.prototype.toLocaleString":"var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.toString":"var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.valueOf":"var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.hasOwnProperty":"var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n","Object.prototype.isPrototypeOf":"var p = { 'a': 1 };\nvar o = { '__proto__': p };\nvar b = o.isPrototypeOf( p );\n","Object.prototype.propertyIsEnumerable":"var o = { 'a': 1, 'b': 2 };\nvar bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n","Object.prototype.constructor":"var o = new Object( null );\nvar ctr = o.constructor;\n","objectEntries":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar entries = objectEntries( obj )\n","objectEntriesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar entries = objectEntriesIn( obj )\n","objectFromEntries":"var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\nvar obj = objectFromEntries( entries )\n","objectInverse":"var obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverse( obj )\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverse( obj )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverse( obj, { 'duplicates': false } )\n","objectInverseBy":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverseBy( obj, transform )\nfunction transform( key, value ) { return value; };\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverseBy( obj, transform )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverseBy( obj, { 'duplicates': false }, transform )\n","objectKeys":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = objectKeys( obj )\n","objectValues":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar vals = objectValues( obj )\n","objectValuesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar values = objectValuesIn( obj )\n","omit":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omit( obj1, 'b' )\n","omitBy":"function predicate( key, value ) { return ( value > 1 ); };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omitBy( obj1, predicate )\n","open":"function onOpen( error, fd ) {\n if ( error ) {\n console.error( error.message );\n } else {\n close.sync( fd );\n }\n };\nopen( './beep/boop.txt', onOpen );\n","open.sync":"var fd = open.sync( './beep/boop.txt' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","openURL":"var out = openURL( 'https://google.com' );\n","ordinalize":"var out = ordinalize( '1' )\nout = ordinalize( 2, { 'suffixOnly': true } )\nout = ordinalize( '3', { 'lang': 'es' } )\n","PACE_BOSTON_HOUSE_PRICES":"var data = PACE_BOSTON_HOUSE_PRICES()\n","pad":"var out = pad( 'a', 5 )\nout = pad( 'a', 10, { 'lpad': 'b' } )\nout = pad( 'a', 12, { 'rpad': 'b' } )\nvar opts = { 'lpad': 'a', 'rpad': 'c' };\nout = pad( 'b', 11, opts )\nopts.centerRight = false;\nout = pad( 'b', 10, opts )\nopts.centerRight = true;\nout = pad( 'b', 10, opts )\nopts = { 'lpad': 'boop', 'rpad': 'woot' };\nout = pad( 'beep', 10, opts )\nout = pad( 'beep', 2 )\nopts = { 'lpad': 'b' };\nout = pad( 'beep', 2, opts )\nopts = { 'lpad': '@', 'rpad': '!' };\nout = pad( 'beep', 2, opts )\nout = pad( 'abcdef', 3, opts )\nopts.centerRight = true;\nout = pad( 'abcdef', 3, opts )\n","padjust":"var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\nvar out = padjust( pvalues, 'bh' )\nout = padjust( pvalues, 'bonferroni' )\nout = padjust( pvalues, 'by' )\nout = padjust( pvalues, 'holm' )\nout = padjust( pvalues, 'hommel' )\n","papply":"function add( x, y ) { return x + y; };\nvar add2 = papply( add, 2 );\nvar sum = add2( 3 )\n","papplyRight":"function say( text, name ) { return text + ', ' + name + '.'; };\nvar toGrace = papplyRight( say, 'Grace Hopper' );\nvar str = toGrace( 'Hello' )\nstr = toGrace( 'Thank you' )\n","parallel":"function done( error ) { if ( error ) { throw error; } };\nvar files = [ './a.js', './b.js' ];\nparallel( files, done );\nvar opts = { 'workers': 8 };\nparallel( files, opts, done );\n","parseJSON":"var obj = parseJSON( '{\"beep\":\"boop\"}' )\nfunction reviver( key, value ) {\n if ( key === '' ) { return value; }\n if ( key === 'beep' ) { return value; }\n };\nvar str = '{\"beep\":\"boop\",\"a\":\"b\"}';\nvar out = parseJSON( str, reviver )\n","pascalcase":"var out = pascalcase( 'Hello World!' )\nout = pascalcase( 'beep boop' )\n","PATH_DELIMITER":"PATH_DELIMITER\nvar path = '/usr/bin:/bin:/usr/sbin';\nvar parts = path.split( PATH_DELIMITER )\npath = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\nparts = path.split( PATH_DELIMITER )\n","PATH_DELIMITER_POSIX":"PATH_DELIMITER_POSIX\nvar PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\nvar paths = PATH.split( PATH_DELIMITER_POSIX )\n","PATH_DELIMITER_WIN32":"PATH_DELIMITER_WIN32\nvar PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\nvar paths = PATH.split( PATH_DELIMITER_WIN32 )\n","PATH_SEP":"PATH_SEP\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\nparts = 'foo/bar/baz'.split( PATH_SEP )\n","PATH_SEP_POSIX":"PATH_SEP_POSIX\nvar parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n","PATH_SEP_WIN32":"PATH_SEP_WIN32\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n","pcorrtest":"var rho = 0.5;\nvar x = new Array( 300 );\nvar y = new Array( 300 );\nfor ( var i = 0; i < 300; i++ ) {\nx[ i ] = base.random.normal( 0.0, 1.0 );\ny[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\nbase.sqrt( 1.0 - (rho*rho) ) );\n }\nvar out = pcorrtest( x, y )\nvar table = out.print()\n","percentEncode":"var out = percentEncode( '☃' )\n","PHI":"PHI\n","PI":"PI\n","PI_SQUARED":"PI_SQUARED\n","pick":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pick( obj1, 'b' )\n","pickArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = pickArguments( foo, [ 0, 2 ] );\nvar out = bar( 1, 2, 3 )\n","pickBy":"function predicate( key, value ) {\n return ( value > 1 );\n };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pickBy( obj1, predicate )\n","PINF":"PINF\n","pkg2alias":"var v = pkg2alias( '@stdlib/math/base/special/sin' )\nv = pkg2alias( '@stdlib/math-base-special-sin' )\n","pkg2related":"var v = pkg2related( '@stdlib/math/base/special/sin' )\nv = pkg2related( '@stdlib/math-base-special-sin' )\n","pkg2standalone":"var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n","PLATFORM":"PLATFORM\n","plot":"var plot = plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = plot( x, y )\n","Plot":"var plot = Plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = Plot( x, y )\n","pluck":"var arr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nvar out = pluck( arr, 'a' )\narr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nout = pluck( arr, 'a', { 'copy': false } )\nvar bool = ( arr[ 0 ] === out[ 0 ] )\n","pop":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = pop( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = pop( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = pop( arr )\n","porterStemmer":"var out = porterStemmer( 'walking' )\nout = porterStemmer( 'walked' )\nout = porterStemmer( 'walks' )\nout = porterStemmer( '' )\n","prepend":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = prepend( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = prepend( arr, [ 3.0, 4.0 ] )\narr = { 'length': 1, '0': 1.0 };\narr = prepend( arr, [ 2.0, 3.0 ] )\n","prevGraphemeClusterBreak":"var out = prevGraphemeClusterBreak( 'last man standing', 4 )\nout = prevGraphemeClusterBreak( 'presidential election', 8 )\nout = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\nout = prevGraphemeClusterBreak( '🌷', 1 )\n","PRIMES_100K":"var list = PRIMES_100K()\n","properties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = properties( obj )\n","propertiesIn":"var props = propertiesIn( [] )\n","propertyDescriptor":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptor( obj, 'a' )\n","propertyDescriptorIn":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptorIn( obj, 'a' )\n","propertyDescriptors":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptors( obj )\n","propertyDescriptorsIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = propertyDescriptorsIn( obj )\n","propertyNames":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNames( obj )\n","propertyNamesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNamesIn( obj )\n","propertySymbols":"var s = propertySymbols( {} )\n","propertySymbolsIn":"var s = propertySymbolsIn( [] )\n","Proxy":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = new Proxy( {}, h );\np.a = 3.14;\np.a\n","Proxy.revocable":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = Proxy.revocable( {}, h );\np.proxy.a = 3.14;\np.proxy.a\np.revoke();\n","push":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = push( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = push( arr, 3.0, 4.0 )\narr = { 'length': 0 };\narr = push( arr, 1.0, 2.0 )\n","quarterOfYear":"var q = quarterOfYear( new Date() )\nq = quarterOfYear( 4 )\nq = quarterOfYear( 'June' )\nq = quarterOfYear( 'April' )\nq = quarterOfYear( 'apr' )\n","random.array.arcsine":"var out = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.arcsine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.arcsine.factory":"var fcn = random.array.arcsine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.arcsine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.arcsine.PRNG":"var prng = random.array.arcsine.PRNG;\n","random.array.arcsine.seed":"var seed = random.array.arcsine.seed;\n","random.array.arcsine.seedLength":"var len = random.array.arcsine.seedLength;\n","random.array.arcsine.state":"var out = random.array.arcsine( 3, 2.0, 5.0 )\nvar state = random.array.arcsine.state\nout = random.array.arcsine( 3, 2.0, 5.0 )\nout = random.array.arcsine( 3, 2.0, 5.0 )\nrandom.array.arcsine.state = state;\nout = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.stateLength":"var len = random.array.arcsine.stateLength;\n","random.array.arcsine.byteLength":"var sz = random.array.arcsine.byteLength;\n","random.array.bernoulli":"var out = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.bernoulli.assign( 0.5, x )\nvar bool = ( out === x )\n","random.array.bernoulli.factory":"var fcn = random.array.bernoulli.factory();\nvar out = fcn( 3, 0.5 )\nfcn = random.array.bernoulli.factory( 0.5 );\nout = fcn( 3 )\n","random.array.bernoulli.PRNG":"var prng = random.array.bernoulli.PRNG;\n","random.array.bernoulli.seed":"var seed = random.array.bernoulli.seed;\n","random.array.bernoulli.seedLength":"var len = random.array.bernoulli.seedLength;\n","random.array.bernoulli.state":"var out = random.array.bernoulli( 3, 0.5 )\nvar state = random.array.bernoulli.state\nout = random.array.bernoulli( 3, 0.5 )\nout = random.array.bernoulli( 3, 0.5 )\nrandom.array.bernoulli.state = state;\nout = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.stateLength":"var len = random.array.bernoulli.stateLength;\n","random.array.bernoulli.byteLength":"var sz = random.array.bernoulli.byteLength;\n","random.array.beta":"var out = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.beta.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.beta.factory":"var fcn = random.array.beta.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.beta.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.beta.PRNG":"var prng = random.array.beta.PRNG;\n","random.array.beta.seed":"var seed = random.array.beta.seed;\n","random.array.beta.seedLength":"var len = random.array.beta.seedLength;\n","random.array.beta.state":"var out = random.array.beta( 3, 2.0, 5.0 )\nvar state = random.array.beta.state\nout = random.array.beta( 3, 2.0, 5.0 )\nout = random.array.beta( 3, 2.0, 5.0 )\nrandom.array.beta.state = state;\nout = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.stateLength":"var len = random.array.beta.stateLength;\n","random.array.beta.byteLength":"var sz = random.array.beta.byteLength;\n","random.array.betaprime":"var out = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.betaprime.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.betaprime.factory":"var fcn = random.array.betaprime.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.betaprime.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.betaprime.PRNG":"var prng = random.array.betaprime.PRNG;\n","random.array.betaprime.seed":"var seed = random.array.betaprime.seed;\n","random.array.betaprime.seedLength":"var len = random.array.betaprime.seedLength;\n","random.array.betaprime.state":"var out = random.array.betaprime( 3, 2.0, 5.0 )\nvar state = random.array.betaprime.state\nout = random.array.betaprime( 3, 2.0, 5.0 )\nout = random.array.betaprime( 3, 2.0, 5.0 )\nrandom.array.betaprime.state = state;\nout = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.stateLength":"var len = random.array.betaprime.stateLength;\n","random.array.betaprime.byteLength":"var sz = random.array.betaprime.byteLength;\n","random.array.binomial":"var out = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.binomial.assign( 17, 0.5, x )\nvar bool = ( out === x )\n","random.array.binomial.factory":"var fcn = random.array.binomial.factory();\nvar out = fcn( 3, 17, 0.5 )\nfcn = random.array.binomial.factory( 17, 0.5 );\nout = fcn( 3 )\n","random.array.binomial.PRNG":"var prng = random.array.binomial.PRNG;\n","random.array.binomial.seed":"var seed = random.array.binomial.seed;\n","random.array.binomial.seedLength":"var len = random.array.binomial.seedLength;\n","random.array.binomial.state":"var out = random.array.binomial( 3, 17, 0.5 )\nvar state = random.array.binomial.state\nout = random.array.binomial( 3, 17, 0.5 )\nout = random.array.binomial( 3, 17, 0.5 )\nrandom.array.binomial.state = state;\nout = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.stateLength":"var len = random.array.binomial.stateLength;\n","random.array.binomial.byteLength":"var sz = random.array.binomial.byteLength;\n","random.array.cauchy":"var out = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cauchy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cauchy.factory":"var fcn = random.array.cauchy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cauchy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cauchy.PRNG":"var prng = random.array.cauchy.PRNG;\n","random.array.cauchy.seed":"var seed = random.array.cauchy.seed;\n","random.array.cauchy.seedLength":"var len = random.array.cauchy.seedLength;\n","random.array.cauchy.state":"var out = random.array.cauchy( 3, 2.0, 5.0 )\nvar state = random.array.cauchy.state\nout = random.array.cauchy( 3, 2.0, 5.0 )\nout = random.array.cauchy( 3, 2.0, 5.0 )\nrandom.array.cauchy.state = state;\nout = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.stateLength":"var len = random.array.cauchy.stateLength;\n","random.array.cauchy.byteLength":"var sz = random.array.cauchy.byteLength;\n","random.array.chi":"var out = random.array.chi( 3, 2.0 )\n","random.array.chi.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chi.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chi.factory":"var fcn = random.array.chi.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chi.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chi.PRNG":"var prng = random.array.chi.PRNG;\n","random.array.chi.seed":"var seed = random.array.chi.seed;\n","random.array.chi.seedLength":"var len = random.array.chi.seedLength;\n","random.array.chi.state":"var out = random.array.chi( 3, 2.0 )\nvar state = random.array.chi.state\nout = random.array.chi( 3, 2.0 )\nout = random.array.chi( 3, 2.0 )\nrandom.array.chi.state = state;\nout = random.array.chi( 3, 2.0 )\n","random.array.chi.stateLength":"var len = random.array.chi.stateLength;\n","random.array.chi.byteLength":"var sz = random.array.chi.byteLength;\n","random.array.chisquare":"var out = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chisquare.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chisquare.factory":"var fcn = random.array.chisquare.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chisquare.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chisquare.PRNG":"var prng = random.array.chisquare.PRNG;\n","random.array.chisquare.seed":"var seed = random.array.chisquare.seed;\n","random.array.chisquare.seedLength":"var len = random.array.chisquare.seedLength;\n","random.array.chisquare.state":"var out = random.array.chisquare( 3, 2.0 )\nvar state = random.array.chisquare.state\nout = random.array.chisquare( 3, 2.0 )\nout = random.array.chisquare( 3, 2.0 )\nrandom.array.chisquare.state = state;\nout = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.stateLength":"var len = random.array.chisquare.stateLength;\n","random.array.chisquare.byteLength":"var sz = random.array.chisquare.byteLength;\n","random.array.cosine":"var out = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cosine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cosine.factory":"var fcn = random.array.cosine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cosine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cosine.PRNG":"var prng = random.array.cosine.PRNG;\n","random.array.cosine.seed":"var seed = random.array.cosine.seed;\n","random.array.cosine.seedLength":"var len = random.array.cosine.seedLength;\n","random.array.cosine.state":"var out = random.array.cosine( 3, 2.0, 5.0 )\nvar state = random.array.cosine.state\nout = random.array.cosine( 3, 2.0, 5.0 )\nout = random.array.cosine( 3, 2.0, 5.0 )\nrandom.array.cosine.state = state;\nout = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.stateLength":"var len = random.array.cosine.stateLength;\n","random.array.cosine.byteLength":"var sz = random.array.cosine.byteLength;\n","random.array.discreteUniform":"var out = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.discreteUniform.assign( -10, 10, x )\nvar bool = ( out === x )\n","random.array.discreteUniform.factory":"var fcn = random.array.discreteUniform.factory();\nvar out = fcn( 3, -10, 10 )\nfcn = random.array.discreteUniform.factory( -10, 10 );\nout = fcn( 3 )\n","random.array.discreteUniform.PRNG":"var prng = random.array.discreteUniform.PRNG;\n","random.array.discreteUniform.seed":"var seed = random.array.discreteUniform.seed;\n","random.array.discreteUniform.seedLength":"var len = random.array.discreteUniform.seedLength;\n","random.array.discreteUniform.state":"var out = random.array.discreteUniform( 3, -10, 10 )\nvar state = random.array.discreteUniform.state\nout = random.array.discreteUniform( 3, -10, 10 )\nout = random.array.discreteUniform( 3, -10, 10 )\nrandom.array.discreteUniform.state = state;\nout = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.stateLength":"var len = random.array.discreteUniform.stateLength;\n","random.array.discreteUniform.byteLength":"var sz = random.array.discreteUniform.byteLength;\n","random.array.erlang":"var out = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.erlang.assign( 2, 5.0, x )\nvar bool = ( out === x )\n","random.array.erlang.factory":"var fcn = random.array.erlang.factory();\nvar out = fcn( 3, 2, 5.0 )\nfcn = random.array.erlang.factory( 2, 5.0 );\nout = fcn( 3 )\n","random.array.erlang.PRNG":"var prng = random.array.erlang.PRNG;\n","random.array.erlang.seed":"var seed = random.array.erlang.seed;\n","random.array.erlang.seedLength":"var len = random.array.erlang.seedLength;\n","random.array.erlang.state":"var out = random.array.erlang( 3, 2, 5.0 )\nvar state = random.array.erlang.state\nout = random.array.erlang( 3, 2, 5.0 )\nout = random.array.erlang( 3, 2, 5.0 )\nrandom.array.erlang.state = state;\nout = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.stateLength":"var len = random.array.erlang.stateLength;\n","random.array.erlang.byteLength":"var sz = random.array.erlang.byteLength;\n","random.array.exponential":"var out = random.array.exponential( 3, 2.0 )\n","random.array.exponential.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.exponential.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.exponential.factory":"var fcn = random.array.exponential.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.exponential.factory( 2.0 );\nout = fcn( 3 )\n","random.array.exponential.PRNG":"var prng = random.array.exponential.PRNG;\n","random.array.exponential.seed":"var seed = random.array.exponential.seed;\n","random.array.exponential.seedLength":"var len = random.array.exponential.seedLength;\n","random.array.exponential.state":"var out = random.array.exponential( 3, 2.0 )\nvar state = random.array.exponential.state\nout = random.array.exponential( 3, 2.0 )\nout = random.array.exponential( 3, 2.0 )\nrandom.array.exponential.state = state;\nout = random.array.exponential( 3, 2.0 )\n","random.array.exponential.stateLength":"var len = random.array.exponential.stateLength;\n","random.array.exponential.byteLength":"var sz = random.array.exponential.byteLength;\n","random.array.f":"var out = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.f.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.f.factory":"var fcn = random.array.f.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.f.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.f.PRNG":"var prng = random.array.f.PRNG;\n","random.array.f.seed":"var seed = random.array.f.seed;\n","random.array.f.seedLength":"var len = random.array.f.seedLength;\n","random.array.f.state":"var out = random.array.f( 3, 2.0, 5.0 )\nvar state = random.array.f.state\nout = random.array.f( 3, 2.0, 5.0 )\nout = random.array.f( 3, 2.0, 5.0 )\nrandom.array.f.state = state;\nout = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.stateLength":"var len = random.array.f.stateLength;\n","random.array.f.byteLength":"var sz = random.array.f.byteLength;\n","random.array.frechet":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.frechet.factory":"var fcn = random.array.frechet.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.frechet.PRNG":"var prng = random.array.frechet.PRNG;\n","random.array.frechet.seed":"var seed = random.array.frechet.seed;\n","random.array.frechet.seedLength":"var len = random.array.frechet.seedLength;\n","random.array.frechet.state":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.frechet.state\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nrandom.array.frechet.state = state;\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.stateLength":"var len = random.array.frechet.stateLength;\n","random.array.frechet.byteLength":"var sz = random.array.frechet.byteLength;\n","random.array.gamma":"var out = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gamma.factory":"var fcn = random.array.gamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gamma.PRNG":"var prng = random.array.gamma.PRNG;\n","random.array.gamma.seed":"var seed = random.array.gamma.seed;\n","random.array.gamma.seedLength":"var len = random.array.gamma.seedLength;\n","random.array.gamma.state":"var out = random.array.gamma( 3, 2.0, 5.0 )\nvar state = random.array.gamma.state\nout = random.array.gamma( 3, 2.0, 5.0 )\nout = random.array.gamma( 3, 2.0, 5.0 )\nrandom.array.gamma.state = state;\nout = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.stateLength":"var len = random.array.gamma.stateLength;\n","random.array.gamma.byteLength":"var sz = random.array.gamma.byteLength;\n","random.array.geometric":"var out = random.array.geometric( 3, 0.01 )\n","random.array.geometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.geometric.assign( 0.01, x )\nvar bool = ( out === x )\n","random.array.geometric.factory":"var fcn = random.array.geometric.factory();\nvar out = fcn( 3, 0.01 )\nfcn = random.array.geometric.factory( 0.01 );\nout = fcn( 3 )\n","random.array.geometric.PRNG":"var prng = random.array.geometric.PRNG;\n","random.array.geometric.seed":"var seed = random.array.geometric.seed;\n","random.array.geometric.seedLength":"var len = random.array.geometric.seedLength;\n","random.array.geometric.state":"var out = random.array.geometric( 3, 0.01 )\nvar state = random.array.geometric.state\nout = random.array.geometric( 3, 0.01 )\nout = random.array.geometric( 3, 0.01 )\nrandom.array.geometric.state = state;\nout = random.array.geometric( 3, 0.01 )\n","random.array.geometric.stateLength":"var len = random.array.geometric.stateLength;\n","random.array.geometric.byteLength":"var sz = random.array.geometric.byteLength;\n","random.array.gumbel":"var out = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gumbel.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gumbel.factory":"var fcn = random.array.gumbel.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gumbel.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gumbel.PRNG":"var prng = random.array.gumbel.PRNG;\n","random.array.gumbel.seed":"var seed = random.array.gumbel.seed;\n","random.array.gumbel.seedLength":"var len = random.array.gumbel.seedLength;\n","random.array.gumbel.state":"var out = random.array.gumbel( 3, 2.0, 5.0 )\nvar state = random.array.gumbel.state\nout = random.array.gumbel( 3, 2.0, 5.0 )\nout = random.array.gumbel( 3, 2.0, 5.0 )\nrandom.array.gumbel.state = state;\nout = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.stateLength":"var len = random.array.gumbel.stateLength;\n","random.array.gumbel.byteLength":"var sz = random.array.gumbel.byteLength;\n","random.array.hypergeometric":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.hypergeometric.assign( 20, 10, 7, x )\nvar bool = ( out === x )\n","random.array.hypergeometric.factory":"var fcn = random.array.hypergeometric.factory();\nvar out = fcn( 3, 20, 10, 7 )\nfcn = random.array.hypergeometric.factory( 20, 10, 7 );\nout = fcn( 3 )\n","random.array.hypergeometric.PRNG":"var prng = random.array.hypergeometric.PRNG;\n","random.array.hypergeometric.seed":"var seed = random.array.hypergeometric.seed;\n","random.array.hypergeometric.seedLength":"var len = random.array.hypergeometric.seedLength;\n","random.array.hypergeometric.state":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\nvar state = random.array.hypergeometric.state\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nrandom.array.hypergeometric.state = state;\nout = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.stateLength":"var len = random.array.hypergeometric.stateLength;\n","random.array.hypergeometric.byteLength":"var sz = random.array.hypergeometric.byteLength;\n","random.array.invgamma":"var out = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.invgamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.invgamma.factory":"var fcn = random.array.invgamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.invgamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.invgamma.PRNG":"var prng = random.array.invgamma.PRNG;\n","random.array.invgamma.seed":"var seed = random.array.invgamma.seed;\n","random.array.invgamma.seedLength":"var len = random.array.invgamma.seedLength;\n","random.array.invgamma.state":"var out = random.array.invgamma( 3, 2.0, 5.0 )\nvar state = random.array.invgamma.state\nout = random.array.invgamma( 3, 2.0, 5.0 )\nout = random.array.invgamma( 3, 2.0, 5.0 )\nrandom.array.invgamma.state = state;\nout = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.stateLength":"var len = random.array.invgamma.stateLength;\n","random.array.invgamma.byteLength":"var sz = random.array.invgamma.byteLength;\n","random.array.kumaraswamy":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.kumaraswamy.factory":"var fcn = random.array.kumaraswamy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.kumaraswamy.PRNG":"var prng = random.array.kumaraswamy.PRNG;\n","random.array.kumaraswamy.seed":"var seed = random.array.kumaraswamy.seed;\n","random.array.kumaraswamy.seedLength":"var len = random.array.kumaraswamy.seedLength;\n","random.array.kumaraswamy.state":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\nvar state = random.array.kumaraswamy.state\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nrandom.array.kumaraswamy.state = state;\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.stateLength":"var len = random.array.kumaraswamy.stateLength;\n","random.array.kumaraswamy.byteLength":"var sz = random.array.kumaraswamy.byteLength;\n","random.array.laplace":"var out = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.laplace.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.laplace.factory":"var fcn = random.array.laplace.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.laplace.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.laplace.PRNG":"var prng = random.array.laplace.PRNG;\n","random.array.laplace.seed":"var seed = random.array.laplace.seed;\n","random.array.laplace.seedLength":"var len = random.array.laplace.seedLength;\n","random.array.laplace.state":"var out = random.array.laplace( 3, 2.0, 5.0 )\nvar state = random.array.laplace.state\nout = random.array.laplace( 3, 2.0, 5.0 )\nout = random.array.laplace( 3, 2.0, 5.0 )\nrandom.array.laplace.state = state;\nout = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.stateLength":"var len = random.array.laplace.stateLength;\n","random.array.laplace.byteLength":"var sz = random.array.laplace.byteLength;\n","random.array.levy":"var out = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.levy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.levy.factory":"var fcn = random.array.levy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.levy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.levy.PRNG":"var prng = random.array.levy.PRNG;\n","random.array.levy.seed":"var seed = random.array.levy.seed;\n","random.array.levy.seedLength":"var len = random.array.levy.seedLength;\n","random.array.levy.state":"var out = random.array.levy( 3, 2.0, 5.0 )\nvar state = random.array.levy.state\nout = random.array.levy( 3, 2.0, 5.0 )\nout = random.array.levy( 3, 2.0, 5.0 )\nrandom.array.levy.state = state;\nout = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.stateLength":"var len = random.array.levy.stateLength;\n","random.array.levy.byteLength":"var sz = random.array.levy.byteLength;\n","random.array.logistic":"var out = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.logistic.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.logistic.factory":"var fcn = random.array.logistic.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.logistic.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.logistic.PRNG":"var prng = random.array.logistic.PRNG;\n","random.array.logistic.seed":"var seed = random.array.logistic.seed;\n","random.array.logistic.seedLength":"var len = random.array.logistic.seedLength;\n","random.array.logistic.state":"var out = random.array.logistic( 3, 2.0, 5.0 )\nvar state = random.array.logistic.state\nout = random.array.logistic( 3, 2.0, 5.0 )\nout = random.array.logistic( 3, 2.0, 5.0 )\nrandom.array.logistic.state = state;\nout = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.stateLength":"var len = random.array.logistic.stateLength;\n","random.array.logistic.byteLength":"var sz = random.array.logistic.byteLength;\n","random.array.lognormal":"var out = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.lognormal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.lognormal.factory":"var fcn = random.array.lognormal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.lognormal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.lognormal.PRNG":"var prng = random.array.lognormal.PRNG;\n","random.array.lognormal.seed":"var seed = random.array.lognormal.seed;\n","random.array.lognormal.seedLength":"var len = random.array.lognormal.seedLength;\n","random.array.lognormal.state":"var out = random.array.lognormal( 3, 2.0, 5.0 )\nvar state = random.array.lognormal.state\nout = random.array.lognormal( 3, 2.0, 5.0 )\nout = random.array.lognormal( 3, 2.0, 5.0 )\nrandom.array.lognormal.state = state;\nout = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.stateLength":"var len = random.array.lognormal.stateLength;\n","random.array.lognormal.byteLength":"var sz = random.array.lognormal.byteLength;\n","random.array.minstd":"var out = random.array.minstd( 3 )\n","random.array.minstd.normalized":"var out = random.array.minstd.normalized( 3 )\n","random.array.minstd.factory":"var fcn = random.array.minstd.factory();\nvar out = fcn( 3 )\n","random.array.minstd.PRNG":"var prng = random.array.minstd.PRNG;\n","random.array.minstd.seed":"var seed = random.array.minstd.seed;\n","random.array.minstd.seedLength":"var len = random.array.minstd.seedLength;\n","random.array.minstd.state":"var out = random.array.minstd( 3 )\nvar state = random.array.minstd.state;\nout = random.array.minstd( 3 )\nout = random.array.minstd( 3 )\nrandom.array.minstd.state = state;\nout = random.array.minstd( 3 )\n","random.array.minstd.stateLength":"var len = random.array.minstd.stateLength;\n","random.array.minstd.byteLength":"var sz = random.array.minstd.byteLength;\n","random.array.minstdShuffle":"var out = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.normalized":"var out = random.array.minstdShuffle.normalized( 3 )\n","random.array.minstdShuffle.factory":"var fcn = random.array.minstdShuffle.factory();\nvar out = fcn( 3 )\n","random.array.minstdShuffle.PRNG":"var prng = random.array.minstdShuffle.PRNG;\n","random.array.minstdShuffle.seed":"var seed = random.array.minstdShuffle.seed;\n","random.array.minstdShuffle.seedLength":"var len = random.array.minstdShuffle.seedLength;\n","random.array.minstdShuffle.state":"var out = random.array.minstdShuffle( 3 )\nvar state = random.array.minstdShuffle.state;\nout = random.array.minstdShuffle( 3 )\nout = random.array.minstdShuffle( 3 )\nrandom.array.minstdShuffle.state = state;\nout = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.stateLength":"var len = random.array.minstdShuffle.stateLength;\n","random.array.minstdShuffle.byteLength":"var sz = random.array.minstdShuffle.byteLength;\n","random.array.mt19937":"var out = random.array.mt19937( 3 )\n","random.array.mt19937.normalized":"var out = random.array.mt19937.normalized( 3 )\n","random.array.mt19937.factory":"var fcn = random.array.mt19937.factory();\nvar out = fcn( 3 )\n","random.array.mt19937.PRNG":"var prng = random.array.mt19937.PRNG;\n","random.array.mt19937.seed":"var seed = random.array.mt19937.seed;\n","random.array.mt19937.seedLength":"var len = random.array.mt19937.seedLength;\n","random.array.mt19937.state":"var out = random.array.mt19937( 3 )\nvar state = random.array.mt19937.state;\nout = random.array.mt19937( 3 )\nout = random.array.mt19937( 3 )\nrandom.array.mt19937.state = state;\nout = random.array.mt19937( 3 )\n","random.array.mt19937.stateLength":"var len = random.array.mt19937.stateLength;\n","random.array.mt19937.byteLength":"var sz = random.array.mt19937.byteLength;\n","random.array.negativeBinomial":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.negativeBinomial.assign( 10, 0.5, x )\nvar bool = ( out === x )\n","random.array.negativeBinomial.factory":"var fcn = random.array.negativeBinomial.factory();\nvar out = fcn( 3, 10, 0.5 )\nfcn = random.array.negativeBinomial.factory( 10, 0.5 );\nout = fcn( 3 )\n","random.array.negativeBinomial.PRNG":"var prng = random.array.negativeBinomial.PRNG;\n","random.array.negativeBinomial.seed":"var seed = random.array.negativeBinomial.seed;\n","random.array.negativeBinomial.seedLength":"var len = random.array.negativeBinomial.seedLength;\n","random.array.negativeBinomial.state":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\nvar state = random.array.negativeBinomial.state\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nrandom.array.negativeBinomial.state = state;\nout = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.stateLength":"var len = random.array.negativeBinomial.stateLength;\n","random.array.negativeBinomial.byteLength":"var sz = random.array.negativeBinomial.byteLength;\n","random.array.normal":"var out = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.normal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.normal.factory":"var fcn = random.array.normal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.normal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.normal.PRNG":"var prng = random.array.normal.PRNG;\n","random.array.normal.seed":"var seed = random.array.normal.seed;\n","random.array.normal.seedLength":"var len = random.array.normal.seedLength;\n","random.array.normal.state":"var out = random.array.normal( 3, 2.0, 5.0 )\nvar state = random.array.normal.state\nout = random.array.normal( 3, 2.0, 5.0 )\nout = random.array.normal( 3, 2.0, 5.0 )\nrandom.array.normal.state = state;\nout = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.stateLength":"var len = random.array.normal.stateLength;\n","random.array.normal.byteLength":"var sz = random.array.normal.byteLength;\n","random.array.pareto1":"var out = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.pareto1.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.pareto1.factory":"var fcn = random.array.pareto1.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.pareto1.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.pareto1.PRNG":"var prng = random.array.pareto1.PRNG;\n","random.array.pareto1.seed":"var seed = random.array.pareto1.seed;\n","random.array.pareto1.seedLength":"var len = random.array.pareto1.seedLength;\n","random.array.pareto1.state":"var out = random.array.pareto1( 3, 2.0, 5.0 )\nvar state = random.array.pareto1.state\nout = random.array.pareto1( 3, 2.0, 5.0 )\nout = random.array.pareto1( 3, 2.0, 5.0 )\nrandom.array.pareto1.state = state;\nout = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.stateLength":"var len = random.array.pareto1.stateLength;\n","random.array.pareto1.byteLength":"var sz = random.array.pareto1.byteLength;\n","random.array.poisson":"var out = random.array.poisson( 3, 2.0 )\n","random.array.poisson.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.poisson.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.poisson.factory":"var fcn = random.array.poisson.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.poisson.factory( 2.0 );\nout = fcn( 3 )\n","random.array.poisson.PRNG":"var prng = random.array.poisson.PRNG;\n","random.array.poisson.seed":"var seed = random.array.poisson.seed;\n","random.array.poisson.seedLength":"var len = random.array.poisson.seedLength;\n","random.array.poisson.state":"var out = random.array.poisson( 3, 2.0 )\nvar state = random.array.poisson.state\nout = random.array.poisson( 3, 2.0 )\nout = random.array.poisson( 3, 2.0 )\nrandom.array.poisson.state = state;\nout = random.array.poisson( 3, 2.0 )\n","random.array.poisson.stateLength":"var len = random.array.poisson.stateLength;\n","random.array.poisson.byteLength":"var sz = random.array.poisson.byteLength;\n","random.array.randu":"var out = random.array.randu( 3 )\n","random.array.randu.factory":"var fcn = random.array.randu.factory();\nvar out = fcn( 3 )\n","random.array.randu.PRNG":"var prng = random.array.randu.PRNG;\n","random.array.randu.seed":"var seed = random.array.randu.seed;\n","random.array.randu.seedLength":"var len = random.array.randu.seedLength;\n","random.array.randu.state":"var out = random.array.randu( 3 )\nvar state = random.array.randu.state;\nout = random.array.randu( 3 )\nout = random.array.randu( 3 )\nrandom.array.randu.state = state;\nout = random.array.randu( 3 )\n","random.array.randu.stateLength":"var len = random.array.randu.stateLength;\n","random.array.randu.byteLength":"var sz = random.array.randu.byteLength;\n","random.array.rayleigh":"var out = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.rayleigh.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.rayleigh.factory":"var fcn = random.array.rayleigh.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.rayleigh.factory( 2.0 );\nout = fcn( 3 )\n","random.array.rayleigh.PRNG":"var prng = random.array.rayleigh.PRNG;\n","random.array.rayleigh.seed":"var seed = random.array.rayleigh.seed;\n","random.array.rayleigh.seedLength":"var len = random.array.rayleigh.seedLength;\n","random.array.rayleigh.state":"var out = random.array.rayleigh( 3, 2.0 )\nvar state = random.array.rayleigh.state\nout = random.array.rayleigh( 3, 2.0 )\nout = random.array.rayleigh( 3, 2.0 )\nrandom.array.rayleigh.state = state;\nout = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.stateLength":"var len = random.array.rayleigh.stateLength;\n","random.array.rayleigh.byteLength":"var sz = random.array.rayleigh.byteLength;\n","random.array.t":"var out = random.array.t( 3, 2.0 )\n","random.array.t.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.t.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.t.factory":"var fcn = random.array.t.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.t.factory( 2.0 );\nout = fcn( 3 )\n","random.array.t.PRNG":"var prng = random.array.t.PRNG;\n","random.array.t.seed":"var seed = random.array.t.seed;\n","random.array.t.seedLength":"var len = random.array.t.seedLength;\n","random.array.t.state":"var out = random.array.t( 3, 2.0 )\nvar state = random.array.t.state\nout = random.array.t( 3, 2.0 )\nout = random.array.t( 3, 2.0 )\nrandom.array.t.state = state;\nout = random.array.t( 3, 2.0 )\n","random.array.t.stateLength":"var len = random.array.t.stateLength;\n","random.array.t.byteLength":"var sz = random.array.t.byteLength;\n","random.array.triangular":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.triangular.factory":"var fcn = random.array.triangular.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.triangular.PRNG":"var prng = random.array.triangular.PRNG;\n","random.array.triangular.seed":"var seed = random.array.triangular.seed;\n","random.array.triangular.seedLength":"var len = random.array.triangular.seedLength;\n","random.array.triangular.state":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.triangular.state\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nrandom.array.triangular.state = state;\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.stateLength":"var len = random.array.triangular.stateLength;\n","random.array.triangular.byteLength":"var sz = random.array.triangular.byteLength;\n","random.array.uniform":"var out = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.uniform.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.uniform.factory":"var fcn = random.array.uniform.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.uniform.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.uniform.PRNG":"var prng = random.array.uniform.PRNG;\n","random.array.uniform.seed":"var seed = random.array.uniform.seed;\n","random.array.uniform.seedLength":"var len = random.array.uniform.seedLength;\n","random.array.uniform.state":"var out = random.array.uniform( 3, 2.0, 5.0 )\nvar state = random.array.uniform.state\nout = random.array.uniform( 3, 2.0, 5.0 )\nout = random.array.uniform( 3, 2.0, 5.0 )\nrandom.array.uniform.state = state;\nout = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.stateLength":"var len = random.array.uniform.stateLength;\n","random.array.uniform.byteLength":"var sz = random.array.uniform.byteLength;\n","random.array.weibull":"var out = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.weibull.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.weibull.factory":"var fcn = random.array.weibull.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.weibull.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.weibull.PRNG":"var prng = random.array.weibull.PRNG;\n","random.array.weibull.seed":"var seed = random.array.weibull.seed;\n","random.array.weibull.seedLength":"var len = random.array.weibull.seedLength;\n","random.array.weibull.state":"var out = random.array.weibull( 3, 2.0, 5.0 )\nvar state = random.array.weibull.state\nout = random.array.weibull( 3, 2.0, 5.0 )\nout = random.array.weibull( 3, 2.0, 5.0 )\nrandom.array.weibull.state = state;\nout = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.stateLength":"var len = random.array.weibull.stateLength;\n","random.array.weibull.byteLength":"var sz = random.array.weibull.byteLength;\n","random.iterators.arcsine":"var it = random.iterators.arcsine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.bernoulli":"var it = random.iterators.bernoulli( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.beta":"var it = random.iterators.beta( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.betaprime":"var it = random.iterators.betaprime( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.binomial":"var it = random.iterators.binomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.boxMuller":"var it = random.iterators.boxMuller();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cauchy":"var it = random.iterators.cauchy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chi":"var it = random.iterators.chi( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chisquare":"var it = random.iterators.chisquare( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cosine":"var it = random.iterators.cosine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.discreteUniform":"var it = random.iterators.discreteUniform( 0, 3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.erlang":"var it = random.iterators.erlang( 1, 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.exponential":"var it = random.iterators.exponential( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.f":"var it = random.iterators.f( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.frechet":"var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gamma":"var it = random.iterators.gamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.geometric":"var it = random.iterators.geometric( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gumbel":"var it = random.iterators.gumbel( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.hypergeometric":"var it = random.iterators.hypergeometric( 20, 10, 7 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.improvedZiggurat":"var it = random.iterators.improvedZiggurat();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.invgamma":"var it = random.iterators.invgamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.kumaraswamy":"var it = random.iterators.kumaraswamy( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.laplace":"var it = random.iterators.laplace( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.levy":"var it = random.iterators.levy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.logistic":"var it = random.iterators.logistic( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.lognormal":"var it = random.iterators.lognormal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstd":"var it = random.iterators.minstd();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstdShuffle":"var it = random.iterators.minstdShuffle();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.mt19937":"var it = random.iterators.mt19937();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.negativeBinomial":"var it = random.iterators.negativeBinomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.normal":"var it = random.iterators.normal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.pareto1":"var it = random.iterators.pareto1( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.poisson":"var it = random.iterators.poisson( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randi":"var it = random.iterators.randi();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randn":"var it = random.iterators.randn();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randu":"var it = random.iterators.randu();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.rayleigh":"var it = random.iterators.rayleigh( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.t":"var it = random.iterators.t( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.triangular":"var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.uniform":"var it = random.iterators.uniform( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.weibull":"var it = random.iterators.weibull( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.streams.arcsine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.arcsine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.arcsine.factory( opts );\n","random.streams.arcsine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.bernoulli":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.bernoulli.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.bernoulli.factory( opts );\n","random.streams.bernoulli.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.beta":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.beta.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.beta.factory( opts );\n","random.streams.beta.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.betaprime":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.betaprime.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.betaprime.factory( opts );\n","random.streams.betaprime.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.binomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial( 20, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.binomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.binomial.factory( opts );\n","random.streams.binomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial.objectMode( 20, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.boxMuller":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.boxMuller.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.boxMuller.factory( opts );\n","random.streams.boxMuller.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cauchy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cauchy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cauchy.factory( opts );\n","random.streams.cauchy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chi.factory( opts );\n","random.streams.chi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chisquare":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chisquare.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chisquare.factory( opts );\n","random.streams.chisquare.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cosine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cosine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cosine.factory( opts );\n","random.streams.cosine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.discreteUniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform( 2, 5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.discreteUniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.discreteUniform.factory( opts );\n","random.streams.discreteUniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform.objectMode( 2, 5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.erlang":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang( 2, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.erlang.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.erlang.factory( opts );\n","random.streams.erlang.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang.objectMode( 2, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.exponential":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.exponential.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.exponential.factory( opts );\n","random.streams.exponential.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.f":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.f.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.f.factory( opts );\n","random.streams.f.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.frechet":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.frechet.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.frechet.factory( opts );\n","random.streams.frechet.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gamma.factory( opts );\n","random.streams.gamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.geometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.geometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.geometric.factory( opts );\n","random.streams.geometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gumbel":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gumbel.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gumbel.factory( opts );\n","random.streams.gumbel.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.hypergeometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric( 5, 3, 2, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.hypergeometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.hypergeometric.factory( opts );\n","random.streams.hypergeometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.improvedZiggurat.factory( opts );\n","random.streams.improvedZiggurat.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.invgamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.invgamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.invgamma.factory( opts );\n","random.streams.invgamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.kumaraswamy.factory( opts );\n","random.streams.kumaraswamy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.laplace":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.laplace.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.laplace.factory( opts );\n","random.streams.laplace.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.levy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.levy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.levy.factory( opts );\n","random.streams.levy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.logistic":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.logistic.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.logistic.factory( opts );\n","random.streams.logistic.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.lognormal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.lognormal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.lognormal.factory( opts );\n","random.streams.lognormal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstd":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstd.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstd.factory( opts );\n","random.streams.minstd.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstdShuffle.factory( opts );\n","random.streams.minstdShuffle.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.mt19937":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.mt19937.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.mt19937.factory( opts );\n","random.streams.mt19937.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial( 20.0, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.negativeBinomial.factory( opts );\n","random.streams.negativeBinomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.normal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.normal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.normal.factory( opts );\n","random.streams.normal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.pareto1":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.pareto1.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.pareto1.factory( opts );\n","random.streams.pareto1.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.poisson":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.poisson.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.poisson.factory( opts );\n","random.streams.poisson.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randi.factory( opts );\n","random.streams.randi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randn":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randn.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randn.factory( opts );\n","random.streams.randn.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randu":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randu.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randu.factory( opts );\n","random.streams.randu.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.rayleigh":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.rayleigh.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.rayleigh.factory( opts );\n","random.streams.rayleigh.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.t":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.t.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.t.factory( opts );\n","random.streams.t.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.triangular":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.triangular.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.triangular.factory( opts );\n","random.streams.triangular.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.uniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.uniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.uniform.factory( opts );\n","random.streams.uniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.weibull":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.weibull.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.weibull.factory( opts );\n","random.streams.weibull.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.strided.arcsine":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n","random.strided.arcsine.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.bernoulli":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n","random.strided.bernoulli.factory":"var fcn = random.strided.bernoulli.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.PRNG":"var prng = random.strided.bernoulli.PRNG;\n","random.strided.bernoulli.seed":"var seed = random.strided.bernoulli.seed;\n","random.strided.bernoulli.seedLength":"var len = random.strided.bernoulli.seedLength;\n","random.strided.bernoulli.state":"var out = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nvar state = random.strided.bernoulli.state\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nrandom.strided.bernoulli.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.stateLength":"var len = random.strided.bernoulli.stateLength;\n","random.strided.bernoulli.byteLength":"var sz = random.strided.bernoulli.byteLength;\n","random.strided.beta":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta( 3, a, -2, b, 1, out, 1 )\n","random.strided.beta.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.betaprime":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n","random.strided.betaprime.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.chi":"var out = azeros( 5, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chi.factory":"var fcn = random.strided.chi.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.PRNG":"var prng = random.strided.chi.PRNG;\n","random.strided.chi.seed":"var seed = random.strided.chi.seed;\n","random.strided.chi.seedLength":"var len = random.strided.chi.seedLength;\n","random.strided.chi.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chi.state\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chi.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.stateLength":"var len = random.strided.chi.stateLength;\n","random.strided.chi.byteLength":"var sz = random.strided.chi.byteLength;\n","random.strided.chisquare":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chisquare.factory":"var fcn = random.strided.chisquare.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.PRNG":"var prng = random.strided.chisquare.PRNG;\n","random.strided.chisquare.seed":"var seed = random.strided.chisquare.seed;\n","random.strided.chisquare.seedLength":"var len = random.strided.chisquare.seedLength;\n","random.strided.chisquare.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chisquare.state\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chisquare.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.stateLength":"var len = random.strided.chisquare.stateLength;\n","random.strided.chisquare.byteLength":"var sz = random.strided.chisquare.byteLength;\n","random.strided.cosine":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n","random.strided.cosine.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n","random.strided.discreteUniform":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.discreteUniform.ndarray":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.exponential":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.exponential.factory":"var fcn = random.strided.exponential.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.PRNG":"var prng = random.strided.exponential.PRNG;\n","random.strided.exponential.seed":"var seed = random.strided.exponential.seed;\n","random.strided.exponential.seedLength":"var len = random.strided.exponential.seedLength;\n","random.strided.exponential.state":"var out = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.exponential.state\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.exponential.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.stateLength":"var len = random.strided.exponential.stateLength;\n","random.strided.exponential.byteLength":"var sz = random.strided.exponential.byteLength;\n","random.strided.gamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.gamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.geometric":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n","random.strided.geometric.factory":"var fcn = random.strided.geometric.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.PRNG":"var prng = random.strided.geometric.PRNG;\n","random.strided.geometric.seed":"var seed = random.strided.geometric.seed;\n","random.strided.geometric.seedLength":"var len = random.strided.geometric.seedLength;\n","random.strided.geometric.state":"var out = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nvar state = random.strided.geometric.state\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nrandom.strided.geometric.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.stateLength":"var len = random.strided.geometric.stateLength;\n","random.strided.geometric.byteLength":"var sz = random.strided.geometric.byteLength;\n","random.strided.invgamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.invgamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.lognormal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.lognormal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.minstd":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd( out.length, out, 1 )\n","random.strided.minstd.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.ndarray( out.length, out, 1, 0 )\n","random.strided.minstd.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized( out.length, out, 1 )\n","random.strided.minstd.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle( out.length, out, 1 )\n","random.strided.minstdShuffle.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized( out.length, out, 1 )\n","random.strided.minstdShuffle.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937( out.length, out, 1 )\n","random.strided.mt19937.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized( out.length, out, 1 )\n","random.strided.mt19937.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.normal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.normal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.poisson":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.poisson.factory":"var fcn = random.strided.poisson.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.PRNG":"var prng = random.strided.poisson.PRNG;\n","random.strided.poisson.seed":"var seed = random.strided.poisson.seed;\n","random.strided.poisson.seedLength":"var len = random.strided.poisson.seedLength;\n","random.strided.poisson.state":"var out = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.poisson.state\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.poisson.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.stateLength":"var len = random.strided.poisson.stateLength;\n","random.strided.poisson.byteLength":"var sz = random.strided.poisson.byteLength;\n","random.strided.randu":"var out = azeros( 5, 'generic' );\nrandom.strided.randu( out.length, out, 1 )\n","random.strided.randu.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.randu.ndarray( out.length, out, 1, 0 )\n","random.strided.rayleigh":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.rayleigh.factory":"var fcn = random.strided.rayleigh.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.PRNG":"var prng = random.strided.rayleigh.PRNG;\n","random.strided.rayleigh.seed":"var seed = random.strided.rayleigh.seed;\n","random.strided.rayleigh.seedLength":"var len = random.strided.rayleigh.seedLength;\n","random.strided.rayleigh.state":"var out = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.rayleigh.state\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.rayleigh.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.stateLength":"var len = random.strided.rayleigh.stateLength;\n","random.strided.rayleigh.byteLength":"var sz = random.strided.rayleigh.byteLength;\n","random.strided.t":"var out = azeros( 5, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.t.factory":"var fcn = random.strided.t.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.PRNG":"var prng = random.strided.t.PRNG;\n","random.strided.t.seed":"var seed = random.strided.t.seed;\n","random.strided.t.seedLength":"var len = random.strided.t.seedLength;\n","random.strided.t.state":"var out = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.t.state\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.t.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.stateLength":"var len = random.strided.t.stateLength;\n","random.strided.t.byteLength":"var sz = random.strided.t.byteLength;\n","random.strided.uniform":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.uniform.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","ranks":"var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\nvar out = ranks( arr )\narr = [ 2, 2, 1, 4, 3 ];\nout = ranks( arr )\narr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\nout = ranks( arr )\n","readDir":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadDir( './beep/boop', onRead );\n","readDir.sync":"var out = readDir.sync( './beep/boop' );\n","readFile":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadFile( './beep/boop.js', onRead );\n","readFile.sync":"var out = readFile.sync( './beep/boop.js' );\n","readFileList":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nvar filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nreadFileList( filepaths, onRead );\n","readFileList.sync":"var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nvar out = readFileList.sync( filepaths );\n","readJSON":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadJSON( './beep/boop.json', onRead );\n","readJSON.sync":"var out = readJSON.sync( './beep/boop.json' );\n","readWASM":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadWASM( './beep/boop.wasm', onRead );\n","readWASM.sync":"var out = readWASM.sync( './beep/boop.wasm' );\n","real":"var z = new Complex128( 5.0, 3.0 );\nvar re = real( z )\n","realarray":"var arr = realarray()\narr = realarray( 'float32' )\nvar arr = realarray( 5 )\narr = realarray( 5, 'int32' )\nvar arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = realarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = realarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = realarray( buf, 0, 4, 'float32' )\n","realarrayCtors":"var ctor = realarrayCtors( 'float64' )\nctor = realarrayCtors( 'float' )\n","realarrayDataTypes":"var out = realarrayDataTypes()\n","realf":"var z = new Complex64( 5.0, 3.0 );\nvar re = realf( z )\n","realmax":"var m = realmax( 'float16' )\nm = realmax( 'float32' )\n","realmin":"var m = realmin( 'float16' )\nm = realmin( 'float32' )\n","reBasename":"var RE = reBasename()\nvar RE_POSIX = reBasename( 'posix' );\nvar RE_WIN32 = reBasename( 'win32' );\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reBasename.REGEXP":"var RE = reBasename.REGEXP\n","reBasename.REGEXP_POSIX":"var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reBasename.REGEXP_WIN32":"var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reBasenamePosix":"var RE_BASENAME_POSIX = reBasenamePosix();\nvar base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n","reBasenamePosix.REGEXP":"var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n","reBasenameWindows":"var RE_BASENAME_WINDOWS = reBasenameWindows();\nvar base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n","reBasenameWindows.REGEXP":"var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n","reColorHexadecimal":"var RE = reColorHexadecimal();\nvar bool = RE.test( 'ffffff' )\nbool = RE.test( '000' )\nbool = RE.test( 'beep' )\n","reColorHexadecimal.REGEXP":"var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP.test( '000' )\nbool = reColorHexadecimal.REGEXP.test( 'beep' )\n","reColorHexadecimal.REGEXP_SHORTHAND":"var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n","reColorHexadecimal.REGEXP_EITHER":"var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n","reDecimalNumber":"var RE = reDecimalNumber();\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\nbool = RE.test( '0.0' )\nbool = RE.test( '.0' )\nbool = RE.test( '0' )\nbool = RE.test( 'beep' )\nvar re = reDecimalNumber({ 'flags': 'g' });\nvar str = '1.234 5.6, 7.8';\nvar out = str.match( re )\n","reDecimalNumber.REGEXP":"var RE = reDecimalNumber.REGEXP;\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\n","reDecimalNumber.REGEXP_CAPTURE":"var RE = reDecimalNumber.REGEXP_CAPTURE;\nvar str = '1.02';\nvar out = replace( str, RE, '$1 x $1' )\n","reDirname":"var RE = reDirname()\nvar RE_POSIX = reDirname( 'posix' );\nvar dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reDirname( 'win32' );\ndir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reDirname.REGEXP":"var RE = reDirname.REGEXP\n","reDirname.REGEXP_POSIX":"var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirname.REGEXP_WIN32":"var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reDirnamePosix":"var RE = reDirnamePosix();\nvar dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\ndir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\ndir = RE.exec( 'foo/file.pdf' )[ 1 ]\ndir = RE.exec( '/foo/bar/file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '.' )[ 1 ]\ndir = RE.exec( './' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnamePosix.REGEXP":"var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirnameWindows":"var RE = reDirnameWindows();\nvar dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\ndir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\ndir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\ndir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnameWindows.REGEXP":"var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n","reduce":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduce( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduce( arr, 0.0, f )\n","reduce2d":"var f = naryFunction( base.add, 2 );\nvar arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\nvar out = reduce2d( arr, [ 0, 0 ], f )\n","reduceAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\n","reduceAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 2000, 1500, 1000 ];\nf( arr, acc, done )\n","reduceRight":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduceRight( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduceRight( arr, 0.0, f )\n","reduceRightAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\n","reduceRightAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceRightAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 1000, 1500, 2000 ];\nf( arr, acc, done )\n","reEOL":"var RE_EOL = reEOL();\nvar bool = RE_EOL.test( '\\n' )\nbool = RE_EOL.test( '\\r\\n' )\nbool = RE_EOL.test( '\\\\r\\\\n' )\n","reEOL.REGEXP":"var bool = reEOL.REGEXP.test( 'abc' )\n","reEOL.REGEXP_CAPTURE":"var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n","reExtendedLengthPath":"var RE = reExtendedLengthPath();\nvar path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\nvar bool = RE.test( path )\npath = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\nbool = RE.test( path )\npath = 'C:\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '/c/foo/bar';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\n","reExtendedLengthPath.REGEXP":"var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n","reExtname":"var RE = reExtname()\nvar RE_POSIX = reExtname( 'posix' );\nvar ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reExtname( 'win32' );\next = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reExtname.REGEXP":"var RE = reExtname.REGEXP\n","reExtname.REGEXP_POSIX":"var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtname.REGEXP_WIN32":"var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reExtnamePosix":"var RE = reExtnamePosix();\nvar ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\next = RE.exec( './foo/bar/.gitignore' )[ 1 ]\next = RE.exec( 'foo/file.pdf' )[ 1 ]\next = RE.exec( '/foo/bar/file' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '.' )[ 1 ]\next = RE.exec( './' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnamePosix.REGEXP":"var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtnameWindows":"var RE = reExtnameWindows();\nvar ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\next = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\next = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\next = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\next = RE.exec( 'beep\\\\boop.' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnameWindows.REGEXP":"var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reFilename":"var RE = reFilename()\nvar RE_POSIX = reFilename( 'posix' );\nvar parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\nvar RE_WIN32 = reFilename( 'win32' );\nparts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reFilename.REGEXP":"var RE = reFilename.REGEXP\n","reFilename.REGEXP_POSIX":"var f = '/foo/bar/index.js';\nvar parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n","reFilename.REGEXP_WIN32":"var f = 'C:\\\\foo\\\\bar\\\\index.js';\nvar parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n","reFilenamePosix":"var RE = reFilenamePosix();\nvar parts = RE.exec( '/foo/bar/index.js' ).slice()\nparts = RE.exec( './foo/bar/.gitignore' ).slice()\nparts = RE.exec( 'foo/file.pdf' ).slice()\nparts = RE.exec( '/foo/bar/file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenamePosix.REGEXP":"var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n","reFilenameWindows":"var RE = reFilenameWindows();\nvar parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\nparts = RE.exec( 'foo\\\\file.pdf' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenameWindows.REGEXP":"var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n","reFromString":"var re = reFromString( '/beep/' )\nre = reFromString( '/beep' )\n","reFunctionName":"var RE_FUNCTION_NAME = reFunctionName();\nfunction beep() { return 'boop'; };\nvar name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\nname = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n","reFunctionName.REGEXP":"var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n","regexp2json":"var json = regexp2json( /ab+c/ )\n","reim":"var z = new Complex128( 5.0, 3.0 );\nvar out = reim( z )\n","reimf":"var z = new Complex64( 5.0, 3.0 );\nvar out = reimf( z )\n","rejectArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v === 2 ); };\nvar bar = rejectArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","removeFirst":"var out = removeFirst( 'beep' )\nout = removeFirst( 'Boop' )\nout = removeFirst( 'foo bar', 4 )\n","removeLast":"var out = removeLast( 'beep' )\nout = removeLast( 'Boop' )\nout = removeLast( 'foo bar', 4 )\n","removePunctuation":"var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\nvar out = removePunctuation( str )\nstr = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\nout = removePunctuation( str )\n","removeUTF8BOM":"var out = removeUTF8BOM( '\\ufeffbeep' )\n","removeWords":"var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\nout = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n","rename":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nrename( './beep/boop.txt', './beep/foo.txt', done );\n","rename.sync":"var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n","reNativeFunction":"var RE = reNativeFunction();\nvar bool = RE.test( Date.toString() )\nbool = RE.test( (function noop() {}).toString() )\n","reNativeFunction.REGEXP":"var bool = reNativeFunction.REGEXP.test( Date.toString() )\nbool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n","reorderArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reorderArguments( foo, [ 2, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","repeat":"var out = repeat( 'a', 5 )\nout = repeat( '', 100 )\nout = repeat( 'beep', 0 )\n","replace":"var out = replace( 'beep', 'e', 'o' )\nfunction replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nout = replace( str, /([^\\s]+)/gi, replacer )\nout = replace( 'beep', /e/, 'o' )\n","reRegExp":"var RE = reRegExp();\nvar bool = RE.test( '/^beep$/' )\nbool = RE.test( '/boop' )\nbool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\nbool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n","reRegExp.REGEXP":"var bool = reRegExp.REGEXP.test( '/^beep$/' )\nbool = reRegExp.REGEXP.test( '/boop' )\n","rescape":"var str = rescape( '[A-Z]*' )\n","reSemVer":"var RE_SEMVER = reSemVer()\nvar bool = RE_SEMVER.test( '1.0.0' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1' )\nbool = RE_SEMVER.test( 'abc' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n","reSemVer.REGEXP":"var bool = reSemVer.REGEXP.test( '1.0.0' )\nbool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n","resolveParentPath":"function onPath( error, path ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( path );\n }\n };\nresolveParentPath( 'package.json', onPath );\n","resolveParentPath.sync":"var out = resolveParentPath.sync( 'package.json' );\n","resolveParentPathBy":"function predicate( path, next ) {\n setTimeout( onTimeout, path );\n function onTimeout() {\n console.log( path );\n next( null, false );\n }\n };\nfunction onPath( error, path ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( path );\n }\n };\nresolveParentPathBy( 'package.json', predicate, onPath );\n","resolveParentPathBy.sync":"function predicate() { return false; };\nvar out = resolveParentPathBy.sync( 'package.json', predicate );\n","reUncPath":"var RE = reUncPath();\nvar path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = 'beep boop \\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server';\nbool = RE.test( path )\npath = '\\\\';\nbool = RE.test( path )\npath = '';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\nbool = RE.test( path )\npath = '//server/share';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\npath = 'foo/bar';\nbool = RE.test( path )\npath = './foo/bar';\nbool = RE.test( path )\npath = '/foo/../bar';\nbool = RE.test( path )\n","reUncPath.REGEXP":"var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = reUncPath.REGEXP.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = reUncPath.REGEXP.test( path )\n","reUtf16SurrogatePair":"var RE = reUtf16SurrogatePair();\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16SurrogatePair.REGEXP":"var RE = reUtf16SurrogatePair.REGEXP;\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16UnpairedSurrogate":"var RE = reUtf16UnpairedSurrogate();\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reUtf16UnpairedSurrogate.REGEXP":"var RE = reUtf16UnpairedSurrogate.REGEXP;\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reverseArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reverseArguments( foo );\nvar out = bar( 1, 2, 3 )\n","reverseString":"var out = reverseString( 'foo' )\nout = reverseString( 'abcdef' )\n","reviveBasePRNG":"var str = JSON.stringify( base.random.mt19937 );\nvar r = parseJSON( str, reviveBasePRNG )\n","reviveBuffer":"var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\nvar buf = parseJSON( str, reviveBuffer )\n","reviveComplex":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex )\n","reviveComplex64":"var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex64 )\n","reviveComplex128":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex128 )\n","reviveError":"var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\nvar err = JSON.parse( str, reviveError )\n","reviveRegExp":"var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\nvar v = parseJSON( str, reviveRegExp )\n","reviveTypedArray":"var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\nvar arr = parseJSON( str, reviveTypedArray )\n","reWhitespace":"var RE = reWhitespace();\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP":"var RE = reWhitespace.REGEXP;\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP_CAPTURE":"var RE = reWhitespace.REGEXP_CAPTURE;\nvar str = 'Duplicate capture';\nvar out = replace( str, RE, '$1$1' )\n","rpad":"var out = rpad( 'a', 5 )\nout = rpad( 'beep', 10, 'p' )\nout = rpad( 'beep', 12, 'boop' )\n","rtrim":"var out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","safeintmax":"var m = safeintmax( 'float16' )\nm = safeintmax( 'float32' )\n","safeintmin":"var m = safeintmin( 'float16' )\nm = safeintmin( 'float32' )\n","sample":"var out = sample( 'abc' )\nout = sample( [ 3, 6, 9 ] )\nvar bool = ( out.length === 3 )\nout = sample( [ 3, null, NaN, 'abc', function(){} ] )\nout = sample( [ 3, 6, 9 ], { 'size': 10 } )\nout = sample( [ 0, 1 ], { 'size': 20 } )\nout = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\nout = sample( [ 0, 1 ], { 'replace': false } )\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\nout = sample( x, { 'probs': probs } )\nout = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n","sample.factory":"var mysample = sample.factory({ 'seed': 232 } );\nvar out = mysample( 'abcdefg' )\nvar pool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\nout = mysample()\nout = mysample()\nvar opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\npool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, opts );\nout = mysample()\nout = mysample()\nout = mysample()\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'size': 10 })\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'replace': false })\nout = mysample()\n","SAVOY_STOPWORDS_FIN":"var list = SAVOY_STOPWORDS_FIN()\n","SAVOY_STOPWORDS_FR":"var list = SAVOY_STOPWORDS_FR()\n","SAVOY_STOPWORDS_GER":"var list = SAVOY_STOPWORDS_GER()\n","SAVOY_STOPWORDS_IT":"var list = SAVOY_STOPWORDS_IT()\n","SAVOY_STOPWORDS_POR":"var list = SAVOY_STOPWORDS_POR()\n","SAVOY_STOPWORDS_SP":"var list = SAVOY_STOPWORDS_SP()\n","SAVOY_STOPWORDS_SWE":"var list = SAVOY_STOPWORDS_SWE()\n","scalar2array":"var x = scalar2array( 1.0 )\n","scalar2ndarray":"var x = scalar2ndarray( 1.0 )\nvar sh = x.shape\nvar dt = x.dtype\nvar v = x.get()\n","sdot":"var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\nsdot( x, y )\n","SECONDS_IN_DAY":"var days = 3.14;\nvar secs = days * SECONDS_IN_DAY\n","SECONDS_IN_HOUR":"var hrs = 3.14;\nvar secs = hrs * SECONDS_IN_HOUR\n","SECONDS_IN_MINUTE":"var mins = 3.14;\nvar secs = mins * SECONDS_IN_MINUTE\n","SECONDS_IN_WEEK":"var wks = 3.14;\nvar secs = wks * SECONDS_IN_WEEK\n","secondsInMonth":"var num = secondsInMonth()\nnum = secondsInMonth( 2 )\nnum = secondsInMonth( 2, 2016 )\nnum = secondsInMonth( 2, 2017 )\nnum = secondsInMonth( 'feb', 2016 )\nnum = secondsInMonth( 'february', 2016 )\n","secondsInYear":"var num = secondsInYear()\nnum = secondsInYear( 2016 )\nnum = secondsInYear( 2017 )\n","seq2slice":"var s = new seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","setConfigurableReadOnly":"var obj = {};\nsetConfigurableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setConfigurableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetConfigurableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setConfigurableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setConfigurableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetConfigurableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setMemoizedConfigurableReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedConfigurableReadOnly( obj, 'foo', foo );\nobj.foo\n","setMemoizedReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedReadOnly( obj, 'foo', foo );\nobj.foo\n","setNonEnumerableProperty":"var obj = {};\nsetNonEnumerableProperty( obj, 'foo', 'bar' );\nobj.foo\nobjectKeys( obj )\n","setNonEnumerableReadOnly":"var obj = {};\nsetNonEnumerableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setNonEnumerableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setNonEnumerableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setNonEnumerableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setReadOnly":"var obj = {};\nsetReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","SharedArrayBuffer":"var buf = new SharedArrayBuffer( 5 )\n","SharedArrayBuffer.length":"SharedArrayBuffer.length\n","SharedArrayBuffer.prototype.byteLength":"var buf = new SharedArrayBuffer( 5 );\nbuf.byteLength\n","SharedArrayBuffer.prototype.slice":"var b1 = new SharedArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","shift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = shift( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = shift( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = shift( arr )\n","shuffle":"var data = [ 1, 2, 3 ];\nvar out = shuffle( data )\nout = shuffle( data, { 'copy': 'none' } );\nvar bool = ( data === out )\n","shuffle.factory":"var myshuffle = shuffle.factory();\nmyshuffle = shuffle.factory({ 'seed': 239 });\nvar arr = [ 0, 1, 2, 3, 4 ];\nvar out = myshuffle( arr )\nmyshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\narr = [ 1, 2, 3, 4, 5, 6 ];\nout = myshuffle( arr );\nvar bool = ( arr === out )\narr = [ 1, 2, 3, 4 ];\nout = myshuffle( arr, { 'copy': 'shallow' } );\nbool = ( arr === out )\n","sizeOf":"var s = sizeOf( 'int8' )\ns = sizeOf( 'uint32' )\n","Slice":"var s = new Slice();\ns = new Slice( 10 );\nvar s = new Slice( 2, 10 );\ns = new Slice( 2, 10, 1 );\n","Slice.prototype.start":"var s = new Slice( 10 );\ns.start\ns = new Slice( 2, 10 );\ns.start\n","Slice.prototype.stop":"var s = new Slice( 10 );\ns.stop\ns = new Slice( 2, 10 );\ns.stop\n","Slice.prototype.step":"var s = new Slice( 10 );\ns.step\ns = new Slice( 2, 10 );\ns.step\ns = new Slice( 2, 10, 1 );\ns.step\n","Slice.prototype.toString":"var s = new Slice( 10 );\ns.toString()\ns = new Slice( 2, 10, 1 );\ns.toString()\n","Slice.prototype.toJSON":"var s = new Slice( 10 );\ns.toJSON()\ns = new Slice( 2, 10, 1 );\ns.toJSON()\n","snakecase":"var out = snakecase( 'Hello World!' )\nout = snakecase( 'I am a tiny little teapot' )\n","some":"var arr = [ 0, 0, 1, 2, 3 ];\nvar bool = some( arr, 3 )\n","someBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, -3, 4, -1 ];\nvar bool = someBy( arr, 2, negative )\n","someByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\n","someByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, 2, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, 2, done )\n","someByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, -2, 3, 4 ];\nvar bool = someByRight( arr, 2, negative )\n","someByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\n","someByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, 2, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, 2, done )\n","SOTU":"var out = SOTU()\nvar opts = { 'name': 'Barack Obama' };\nout = SOTU( opts )\nopts = { 'party': [ 'Democratic', 'Federalist' ] };\nout = SOTU( opts )\nopts = { 'year': [ 2008, 2009, 2011 ] };\nout = SOTU( opts )\nopts = { 'range': [ 2008, 2016 ] }\nout = SOTU( opts )\n","SPACHE_REVISED":"var list = SPACHE_REVISED()\n","SPAM_ASSASSIN":"var data = SPAM_ASSASSIN()\n","SparklineBase":"var sparkline = new SparklineBase()\nvar data = [ 1, 2, 3 ];\nsparkline = new SparklineBase( data )\n","sparsearray2iterator":"var it = sparsearray2iterator( [ 1, , 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","sparsearray2iteratorRight":"var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\nvar v = it.next().value\nv = it.next().value\n","splitStream":"var s = splitStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = splitStream.factory( opts );\nvar s = createStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.objectMode":"var s = splitStream.objectMode();\ns.write( 'a\\nb\\c' );\ns.end();\n","SQRT_EPS":"SQRT_EPS\n","SQRT_HALF":"SQRT_HALF\n","SQRT_HALF_PI":"SQRT_HALF_PI\n","SQRT_PHI":"SQRT_PHI\n","SQRT_PI":"SQRT_PI\n","SQRT_THREE":"SQRT_THREE\n","SQRT_TWO":"SQRT_TWO\n","SQRT_TWO_PI":"SQRT_TWO_PI\n","SSA_US_BIRTHS_2000_2014":"var data = SSA_US_BIRTHS_2000_2014()\n","sswap":"var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\nsswap( x, y );\nx.data\ny.data\n","Stack":"var s = Stack();\ns.push( 'foo' ).push( 'bar' );\ns.length\ns.pop()\ns.length\ns.pop()\ns.length\n","standalone2pkg":"var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n","STANDARD_CARD_DECK":"var list = STANDARD_CARD_DECK()\n","startcase":"var out = startcase( 'beep boop' )\n","startsWith":"var bool = startsWith( 'Beep', 'Be' )\nbool = startsWith( 'Beep', 'ep' )\nbool = startsWith( 'Beep', 'ee', 1 )\nbool = startsWith( 'Beep', 'ee', -3 )\nbool = startsWith( 'Beep', '' )\n","STOPWORDS_EN":"var list = STOPWORDS_EN()\n","strided.abs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( 2, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2By":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.abs2By.ndarray":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -1.0, -2.0, -3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.absBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.absBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.absBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.add":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.add.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.cbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.cbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.ceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.deg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.deg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.dataTypes":"var out = strided.dataTypes()\n","strided.dispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1 );\ny\nf = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\ny\n","strided.dispatchBy":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\ny\nf = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\ny\n","strided.floor":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.floor.ndarray":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.inv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.inv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.mul":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.mul.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.ramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.rsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.rsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.sqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sub":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.sub.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.trunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.trunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","stridedarray2iterator":"var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\nvar v = it.next().value\nv = it.next().value\n","stridedArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","stridedArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = stridedArrayStream.factory( opts );\n","stridedArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","string2buffer":"var b = string2buffer( 'beep boop' )\nb = string2buffer( '7468697320697320612074c3a97374', 'hex' );\nb.toString()\n","sub2ind":"var d = [ 3, 3, 3 ];\nvar idx = sub2ind( d, 1, 2, 2 )\n","substringAfter":"var out = substringAfter( 'Hello World!', 'World' )\nout = substringAfter( 'Hello World!', 'Hello ' )\nout = substringAfter( 'Hello World!', 'l', 5 )\n","substringAfterLast":"var out = substringAfterLast( 'beep boop beep baz', 'beep' )\nout = substringAfterLast( 'Hello World!', 'Hello ' )\nout = substringAfterLast( 'Hello World!', 'o', 5 )\n","substringBefore":"var str = 'beep boop';\nvar out = substringBefore( str, ' ' )\nout = substringBefore( str, 'o' )\n","substringBeforeLast":"var str = 'Beep Boop Beep';\nvar out = substringBeforeLast( str, 'Beep' )\nout = substringBeforeLast( str, 'Boop' )\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n","Symbol":"var s = ( Symbol ) ? Symbol( 'beep' ) : null\n","tabulate":"var collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulate( collection )\n","tabulateBy":"function indicator( value ) { return value[ 0 ]; };\nvar collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulateBy( collection, indicator )\n","tabulateByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\n","tabulateByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = tabulateByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 750 ];\nf( arr, done )\n","thunk":"var fcn = thunk( base.add, 2, 3 );\nvar v = fcn()\nv = fcn()\n","tic":"var t = tic()\n","timeit":"var code = 'var x = Math.pow( Math.random(), 3 );';\ncode += 'if ( x !== x ) {';\ncode += 'throw new Error( \\'Something went wrong.\\' );';\ncode += '}';\nfunction done( error, results ) {\n if ( error ) {\n throw error;\n }\n console.dir( results );\n };\ntimeit( code, done )\n","tmpdir":"var dir = tmpdir()\n","toc":"var start = tic();\nvar delta = toc( start )\n","tokenize":"var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\nout = tokenize( 'Hello World!', true )\n","transformStream":"var s = transformStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = transformStream.factory( opts );\nfunction fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar s = createStream( fcn );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.objectMode":"var s = transformStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","transformStream.ctor":"function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar opts = { 'highWaterMark': 64, 'transform': fcn };\nvar customStream = transformStream.ctor( opts );\nvar s = customStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","trim":"var out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","truncate":"var str = 'beep boop';\nvar out = truncate( str, 5 )\nout = truncate( str, 5, '|' )\n","truncateMiddle":"var str = 'beep boop';\nvar out = truncateMiddle( str, 5 )\nout = truncateMiddle( str, 5, '|' )\n","trycatch":"function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n };\nvar z = trycatch( x, -1.0 )\n","trycatchAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n // process error...\n }\n console.log( result );\n };\ntrycatchAsync( x, 'boop', done )\n","tryFunction":"function fcn() { throw new Error( 'beep boop' ); };\nvar f = tryFunction( fcn );\nvar out = f();\nout.message\n","tryRequire":"var out = tryRequire( '_unknown_module_id_' )\n","trythen":"function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n };\nfunction y() {\n return -1.0;\n };\nvar z = trythen( x, y )\n","trythenAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ntrythenAsync( x, y, done )\n","ttest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ttest( x )\nrnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\nx = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n y[ i ] = rnorm();\n }\nout = ttest( x, y )\nvar table = out.print()\narr = [ 2, 4, 3, 1, 0 ];\nout = ttest( arr, { 'alpha': 0.01 } );\ntable = out.print()\nvar arr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest( arr, { 'alternative': 'greater' } );\ntable = out.print()\n","ttest2":"var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\nvar y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\nvar out = ttest2( x, y )\nvar table = out.print()\nout = ttest2( x, y, { 'alpha': 0.1 } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'greater' } );\ntable = out.print()\nx = [ 2, 3, 1, 4 ];\ny = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\nout = ttest2( x, y, { 'variance': 'equal' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 3.0 );\n }\ny = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 1.0, 3.0 );\n }\nout = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n","TWO_PI":"TWO_PI\n","typedarray":"var arr = typedarray()\narr = typedarray( 'float32' )\nvar arr = typedarray( 5 )\narr = typedarray( 5, 'int32' )\nvar arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = typedarray( buf, 0, 4, 'float32' )\n","typedarray2json":"var arr = new Float64Array( 2 );\narr[ 0 ] = 5.0;\narr[ 1 ] = 3.0;\nvar json = typedarray2json( arr )\n","typedarrayCtors":"var ctor = typedarrayCtors( 'float64' )\nctor = typedarrayCtors( 'float' )\n","typedarrayDataTypes":"var out = typedarrayDataTypes()\n","typedarraypool":"var arr = typedarraypool()\narr = typedarraypool( 'float32' )\nvar arr = typedarraypool( 5 )\narr = typedarraypool( 5, 'int32' )\nvar arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool( arr1, 'float32' )\n","typedarraypool.malloc":"var arr = typedarraypool.malloc()\narr = typedarraypool.malloc( 'float32' )\nvar arr = typedarraypool.malloc( 5 )\narr = typedarraypool.malloc( 5, 'int32' )\nvar arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\n","typedarraypool.calloc":"var arr = typedarraypool.calloc()\narr = typedarraypool.calloc( 'float32' )\nvar arr = typedarraypool.calloc( 5 )\narr = typedarraypool.calloc( 5, 'int32' )\n","typedarraypool.free":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr )\n","typedarraypool.clear":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\ntypedarraypool.clear()\n","typedarraypool.highWaterMark":"typedarraypool.highWaterMark\n","typedarraypool.nbytes":"var arr = typedarraypool( 5 )\ntypedarraypool.nbytes\n","typedarraypool.factory":"var pool = typedarraypool.factory();\nvar arr1 = pool( 3, 'float64' )\n","typemax":"var m = typemax( 'int8' )\nm = typemax( 'uint32' )\n","typemin":"var m = typemin( 'int8' )\nm = typemin( 'uint32' )\n","typeOf":"var t = typeOf( 'a' )\nt = typeOf( 5 )\nt = typeOf( NaN )\nt = typeOf( true )\nt = typeOf( false )\nt = typeOf( null )\nt = typeOf( undefined )\nt = typeOf( [] )\nt = typeOf( {} )\nt = typeOf( function noop() {} )\nt = typeOf( Symbol( 'beep' ) )\nt = typeOf( /.+/ )\nt = typeOf( new String( 'beep' ) )\nt = typeOf( new Number( 5 ) )\nt = typeOf( new Boolean( false ) )\nt = typeOf( new Array() )\nt = typeOf( new Object() )\nt = typeOf( new Int8Array( 10 ) )\nt = typeOf( new Uint8Array( 10 ) )\nt = typeOf( new Uint8ClampedArray( 10 ) )\nt = typeOf( new Int16Array( 10 ) )\nt = typeOf( new Uint16Array( 10 ) )\nt = typeOf( new Int32Array( 10 ) )\nt = typeOf( new Uint32Array( 10 ) )\nt = typeOf( new Float32Array( 10 ) )\nt = typeOf( new Float64Array( 10 ) )\nt = typeOf( new ArrayBuffer( 10 ) )\nt = typeOf( new Date() )\nt = typeOf( new RegExp( '.+' ) )\nt = typeOf( new Map() )\nt = typeOf( new Set() )\nt = typeOf( new WeakMap() )\nt = typeOf( new WeakSet() )\nt = typeOf( new Error( 'beep' ) )\nt = typeOf( new TypeError( 'beep' ) )\nt = typeOf( new SyntaxError( 'beep' ) )\nt = typeOf( new ReferenceError( 'beep' ) )\nt = typeOf( new URIError( 'beep' ) )\nt = typeOf( new RangeError( 'beep' ) )\nt = typeOf( new EvalError( 'beep' ) )\nt = typeOf( Math )\nt = typeOf( JSON )\nfunction beep() { return arguments; };\nt = typeOf( beep() )\nt = typeOf( new Buffer( 10 ) )\nfunction Person() { return this };\nt = typeOf( new Person() )\nvar Foo = function () { return this; };\nt = typeOf( new Foo() )\n","UINT8_MAX":"UINT8_MAX\n","UINT8_NUM_BYTES":"UINT8_NUM_BYTES\n","Uint8Array":"var arr = new Uint8Array()\nvar arr = new Uint8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8Array( buf, 0, 4 )\n","Uint8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n","Uint8Array.of":"var arr = Uint8Array.of( 1, 2 )\n","Uint8Array.BYTES_PER_ELEMENT":"Uint8Array.BYTES_PER_ELEMENT\n","Uint8Array.name":"Uint8Array.name\n","Uint8Array.prototype.buffer":"var arr = new Uint8Array( 5 );\narr.buffer\n","Uint8Array.prototype.byteLength":"var arr = new Uint8Array( 5 );\narr.byteLength\n","Uint8Array.prototype.byteOffset":"var arr = new Uint8Array( 5 );\narr.byteOffset\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8Array.prototype.length":"var arr = new Uint8Array( 5 );\narr.length\n","Uint8Array.prototype.copyWithin":"var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8Array.prototype.entries":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.every":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8Array.prototype.fill":"var arr = new Uint8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8Array.prototype.filter":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8Array.prototype.find":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8Array.prototype.findIndex":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8Array.prototype.forEach":"var arr = new Uint8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8Array.prototype.includes":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8Array.prototype.indexOf":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8Array.prototype.join":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8Array.prototype.keys":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.lastIndexOf":"var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8Array.prototype.map":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn );\n","Uint8Array.prototype.reduce":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8Array.prototype.reduceRight":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8Array.prototype.reverse":"var arr = new Uint8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8Array.prototype.set":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8Array.prototype.slice":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8Array.prototype.some":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8Array.prototype.sort":"var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8Array.prototype.subarray":"var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8Array.prototype.toLocaleString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8Array.prototype.toString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint8Array.prototype.values":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray":"var arr = new Uint8ClampedArray()\nvar arr = new Uint8ClampedArray( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8ClampedArray( buf, 0, 4 )\n","Uint8ClampedArray.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n","Uint8ClampedArray.of":"var arr = Uint8ClampedArray.of( 1, 2 )\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"Uint8ClampedArray.BYTES_PER_ELEMENT\n","Uint8ClampedArray.name":"Uint8ClampedArray.name\n","Uint8ClampedArray.prototype.buffer":"var arr = new Uint8ClampedArray( 5 );\narr.buffer\n","Uint8ClampedArray.prototype.byteLength":"var arr = new Uint8ClampedArray( 5 );\narr.byteLength\n","Uint8ClampedArray.prototype.byteOffset":"var arr = new Uint8ClampedArray( 5 );\narr.byteOffset\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8ClampedArray( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8ClampedArray.prototype.length":"var arr = new Uint8ClampedArray( 5 );\narr.length\n","Uint8ClampedArray.prototype.copyWithin":"var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8ClampedArray.prototype.entries":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.every":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8ClampedArray.prototype.fill":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8ClampedArray.prototype.filter":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8ClampedArray.prototype.find":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8ClampedArray.prototype.findIndex":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8ClampedArray.prototype.forEach":"var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8ClampedArray.prototype.includes":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8ClampedArray.prototype.indexOf":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8ClampedArray.prototype.join":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8ClampedArray.prototype.keys":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.lastIndexOf":"var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8ClampedArray.prototype.map":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn );\n","Uint8ClampedArray.prototype.reduce":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8ClampedArray.prototype.reduceRight":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8ClampedArray.prototype.reverse":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8ClampedArray.prototype.set":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8ClampedArray.prototype.slice":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8ClampedArray.prototype.some":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8ClampedArray.prototype.sort":"var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8ClampedArray.prototype.subarray":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8ClampedArray.prototype.toLocaleString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8ClampedArray.prototype.toString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toString()\n","Uint8ClampedArray.prototype.values":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","UINT16_MAX":"UINT16_MAX\n","UINT16_NUM_BYTES":"UINT16_NUM_BYTES\n","Uint16Array":"var arr = new Uint16Array()\nvar arr = new Uint16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Uint16Array( buf, 0, 4 )\n","Uint16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n","Uint16Array.of":"var arr = Uint16Array.of( 1, 2 )\n","Uint16Array.BYTES_PER_ELEMENT":"Uint16Array.BYTES_PER_ELEMENT\n","Uint16Array.name":"Uint16Array.name\n","Uint16Array.prototype.buffer":"var arr = new Uint16Array( 5 );\narr.buffer\n","Uint16Array.prototype.byteLength":"var arr = new Uint16Array( 5 );\narr.byteLength\n","Uint16Array.prototype.byteOffset":"var arr = new Uint16Array( 5 );\narr.byteOffset\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint16Array.prototype.length":"var arr = new Uint16Array( 5 );\narr.length\n","Uint16Array.prototype.copyWithin":"var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint16Array.prototype.entries":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.every":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint16Array.prototype.fill":"var arr = new Uint16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint16Array.prototype.filter":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint16Array.prototype.find":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint16Array.prototype.findIndex":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint16Array.prototype.forEach":"var arr = new Uint16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint16Array.prototype.includes":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint16Array.prototype.indexOf":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint16Array.prototype.join":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint16Array.prototype.keys":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.lastIndexOf":"var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint16Array.prototype.map":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn );\n","Uint16Array.prototype.reduce":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint16Array.prototype.reduceRight":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint16Array.prototype.reverse":"var arr = new Uint16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint16Array.prototype.set":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint16Array.prototype.slice":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint16Array.prototype.some":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint16Array.prototype.sort":"var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint16Array.prototype.subarray":"var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint16Array.prototype.toLocaleString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint16Array.prototype.toString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint16Array.prototype.values":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","UINT32_MAX":"UINT32_MAX\n","UINT32_NUM_BYTES":"UINT32_NUM_BYTES\n","Uint32Array":"var arr = new Uint32Array()\nvar arr = new Uint32Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Uint32Array( buf, 0, 4 )\n","Uint32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n","Uint32Array.of":"var arr = Uint32Array.of( 1, 2 )\n","Uint32Array.BYTES_PER_ELEMENT":"Uint32Array.BYTES_PER_ELEMENT\n","Uint32Array.name":"Uint32Array.name\n","Uint32Array.prototype.buffer":"var arr = new Uint32Array( 5 );\narr.buffer\n","Uint32Array.prototype.byteLength":"var arr = new Uint32Array( 5 );\narr.byteLength\n","Uint32Array.prototype.byteOffset":"var arr = new Uint32Array( 5 );\narr.byteOffset\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint32Array.prototype.length":"var arr = new Uint32Array( 5 );\narr.length\n","Uint32Array.prototype.copyWithin":"var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint32Array.prototype.entries":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.every":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint32Array.prototype.fill":"var arr = new Uint32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint32Array.prototype.filter":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint32Array.prototype.find":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint32Array.prototype.findIndex":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint32Array.prototype.forEach":"var arr = new Uint32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint32Array.prototype.includes":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint32Array.prototype.indexOf":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint32Array.prototype.join":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint32Array.prototype.keys":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.lastIndexOf":"var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint32Array.prototype.map":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn );\n","Uint32Array.prototype.reduce":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint32Array.prototype.reduceRight":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint32Array.prototype.reverse":"var arr = new Uint32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint32Array.prototype.set":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint32Array.prototype.slice":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint32Array.prototype.some":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint32Array.prototype.sort":"var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint32Array.prototype.subarray":"var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint32Array.prototype.toLocaleString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint32Array.prototype.toString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint32Array.prototype.values":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","umask":"var mask = umask()\nmask = umask( { 'symbolic': true } )\n","uncapitalize":"var out = uncapitalize( 'Beep' )\nout = uncapitalize( 'bOOp' )\n","uncapitalizeKeys":"var obj = { 'AA': 1, 'BB': 2 };\nvar out = uncapitalizeKeys( obj )\n","uncurry":"function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n };\nvar fcn = uncurry( addX );\nvar sum = fcn( 2, 3 )\nfunction add( x ) {\n return function add( y ) {\n return x + y;\n };\n };\nfcn = uncurry( add, 2 );\nsum = fcn( 9 )\nfunction addX( x ) {\n this.x = x;\n return addY;\n };\nfunction addY( y ) {\n return this.x + y;\n };\nfcn = uncurry( addX, {} );\nsum = fcn( 2, 3 )\n","uncurryRight":"function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n };\nvar fcn = uncurryRight( addX );\nvar sum = fcn( 3, 2 )\nfunction add( y ) {\n return function add( x ) {\n return x + y;\n };\n };\nfcn = uncurryRight( add, 2 );\nsum = fcn( 9 )\nfunction addY( y ) {\n this.y = y;\n return addX;\n };\nfunction addX( x ) {\n return x + this.y;\n };\nfcn = uncurryRight( addY, {} );\nsum = fcn( 3, 2 )\n","UNICODE_MAX":"UNICODE_MAX\n","UNICODE_MAX_BMP":"UNICODE_MAX_BMP\n","UnicodeColumnChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeColumnChartSparkline( data );\nchart.render()\n","UnicodeLineChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeLineChartSparkline( data );\nchart.render()\n","UnicodeSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeSparkline( data );\nchart.render()\nchart.type = 'line';\nchart.render()\n","UnicodeTristateChartSparkline":"var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\nvar chart = new UnicodeTristateChartSparkline( data );\nchart.render()\n","UnicodeUpDownChartSparkline":"var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\nvar chart = new UnicodeUpDownChartSparkline( data );\nchart.render()\n","UnicodeWinLossChartSparkline":"var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\nvar chart = new UnicodeWinLossChartSparkline( data );\nchart.render()\n","unlink":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nunlink( './beep/boop.txt', done );\n","unlink.sync":"var out = unlink.sync( './beep/boop.txt' );\n","unshift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = unshift( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = unshift( arr, 3.0, 4.0 )\narr = { 'length': 1, '0': 1.0 };\narr = unshift( arr, 2.0, 3.0 )\n","until":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nuntil( predicate, beep )\n","untilAsync":"function predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nuntilAsync( predicate, fcn, done )\n","untilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nuntilEach( arr, predicate, logger )\n","untilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nuntilEachRight( arr, predicate, logger )\n","unzip":"var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nvar out = unzip( arr )\narr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nout = unzip( arr, [ 0, 2 ] )\n","uppercase":"var out = uppercase( 'bEEp' )\n","uppercaseKeys":"var obj = { 'a': 1, 'b': 2 };\nvar out = uppercaseKeys( obj )\n","US_STATES_ABBR":"var list = US_STATES_ABBR()\n","US_STATES_CAPITALS":"var list = US_STATES_CAPITALS()\n","US_STATES_CAPITALS_NAMES":"var out = US_STATES_CAPITALS_NAMES()\n","US_STATES_NAMES":"var list = US_STATES_NAMES()\n","US_STATES_NAMES_CAPITALS":"var out = US_STATES_NAMES_CAPITALS()\n","utf16ToUTF8Array":"var str = '☃';\nvar out = utf16ToUTF8Array( str )\n","vartest":"var x = [ 610, 610, 550, 590, 565, 570 ];\nvar y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\nvar out = vartest( x, y )\nvar table = out.print()\n","waterfall":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nwaterfall( fcns, done );\n","waterfall.factory":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nvar waterfall = waterfall.factory( fcns, done );\nwaterfall();\nwaterfall();\nwaterfall();\n","whileAsync":"function predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nwhileAsync( predicate, fcn, done )\n","whileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nwhileEach( arr, predicate, logger )\n","whileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nwhileEachRight( arr, predicate, logger )\n","whilst":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nwhilst( predicate, beep )\n","wilcoxon":"var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\nvar out = wilcoxon( x )\nrunif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\nvar x = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = runif();\n y[ i ] = runif();\n }\nout = wilcoxon( x, y )\nvar table = out.print()\nout = wilcoxon( arr, { 'alpha': 0.01 });\ntable = out.print()\nout = wilcoxon( arr, { 'mu': 10 })\nout = wilcoxon( arr, { 'alternative': 'less' });\ntable = out.print()\nout = wilcoxon( arr, { 'alternative': 'greater' });\ntable = out.print()\n","writableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = writableProperties( obj )\n","writablePropertiesIn":"var props = writablePropertiesIn( [] )\n","writablePropertyNames":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNames( obj )\n","writablePropertyNamesIn":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNamesIn( obj )\n","writablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbols( obj )\n","writablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbolsIn( obj )\n","writeFile":"function onWrite( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nwriteFile( './beep/boop.txt', 'beep boop', onWrite );\n","writeFile.sync":"var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n","zip":"var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\nvar opts = { 'trunc': false };\nout = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n","ztest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ztest( x, 2.0 )\narr = [ 2, 4, 3, 1, 0 ];\nout = ztest( arr, 2.0, { 'alpha': 0.01 } );\ntable = out.print()\nvar arr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'alternative': 'less' } )\nout = ztest( arr, 1.0, { 'alternative': 'greater' } )\n","ztest2":"var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\nvar y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\nvar out = ztest2( x, y, 2.0, 2.0 )\nvar table = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 1.0 );\n }\ny = new Array( 100 );\n for ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 0.0, 2.0 );\n }\nout = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n"} \ No newline at end of file diff --git a/lib/node_modules/@stdlib/repl/data/contributor.json b/lib/node_modules/@stdlib/repl/data/contributor.json index 435ff022ba08..adff88e240ae 100644 --- a/lib/node_modules/@stdlib/repl/data/contributor.json +++ b/lib/node_modules/@stdlib/repl/data/contributor.json @@ -1 +1 @@ -["Adarsh Palaskar","Aditya Sapra","AgPriyanshu18","Ali Salesi","Aman Bhansali","Amit Jimiwal","Anudeep Sanapala","Athan Reines","Ayaka","Brendan Graetz","Bruno Fenzl","Bryan Elee","Chinmay Joshi","Christopher Dambamuromo","Dan Rose","Daniel Killenberger","Dominik Moritz","Dorrin Sotoudeh","EuniceSim142","Frank Kovacs","Golden Kumar","Gunj Joshi","Harshita Kalani","Jaimin Godhani","James Gelok","Jaysukh Makvana","Jithin KS","Joel Mathew Koshy","Joey Reed","Jordan Gallivan","Joris Labie","Justin Dennison","Karthik Prakash","Khaldon","Lovelin","Manik Sharma","Marcus Fantham","Matt Cochrane","Mihir Pandit","Milan Raj","Momtchil Momtchev","Muhammad Haris","Naresh Jagadeesan","Nithin Katta","Ognjen Jevremović","Oneday12323","Philipp Burckhardt","Prajwal Kulkarni","Pranav Goswami","Praneki","Pratik","Priyansh","Raunak Kumar Gupta","Rejoan Sardar","Ricky Reusser","Robert Gislason","Roman Stetsyk","Rutam","Ryan Seal","Sai Srikar Dumpeti","Seyyed Parsa Neshaei","Shashank Shekhar Singh","Shraddheya Shendre","Shubham Mishra","Snehil Shah","Spandan Barve","Stephannie Jiménez Gacha","Suraj kumar","Tirtadwipa Manunggal","Utkarsh","Utkarsh Raj","Varad Gupta","Yernar Yergaziyev","naveen","nishant-s7","orimiles5","rei2hu"] +["Adarsh Palaskar","Aditya Sapra","AgPriyanshu18","Ali Salesi","Aman Bhansali","Amit Jimiwal","Anudeep Sanapala","Athan Reines","Brendan Graetz","Bruno Fenzl","Chinmay Joshi","Christopher Dambamuromo","Dan Rose","Daniel Killenberger","Dominik Moritz","Dorrin Sotoudeh","EuniceSim142","Frank Kovacs","Golden Kumar","Gunj Joshi","Harshita Kalani","Jaimin Godhani","James Gelok","Jaysukh Makvana","Jithin KS","Joel Mathew Koshy","Joey Reed","Jordan Gallivan","Joris Labie","Justin Dennison","Karthik Prakash","Khaldon","Lovelin","Manik Sharma","Marcus Fantham","Matt Cochrane","Mihir Pandit","Milan Raj","Momtchil Momtchev","Naresh Jagadeesan","Nithin Katta","Ognjen Jevremović","Oneday12323","Philipp Burckhardt","Prajwal Kulkarni","Pranav Goswami","Praneki","Pratik","Priyansh","Raunak Kumar Gupta","Rejoan Sardar","Ricky Reusser","Robert Gislason","Roman Stetsyk","Rutam","Ryan Seal","Sai Srikar Dumpeti","Seyyed Parsa Neshaei","Shashank Shekhar Singh","Shraddheya Shendre","Shubham Mishra","Snehil Shah","Spandan Barve","Stephannie Jiménez Gacha","Utkarsh","Utkarsh Raj","Varad Gupta","Yernar Yergaziyev","nishant-s7","orimiles5","rei2hu"] diff --git a/lib/node_modules/@stdlib/repl/help/data/data.csv b/lib/node_modules/@stdlib/repl/help/data/data.csv index 0edcd0b756f7..05a7b2d0c135 100644 --- a/lib/node_modules/@stdlib/repl/help/data/data.csv +++ b/lib/node_modules/@stdlib/repl/help/data/data.csv @@ -1510,12 +1510,12 @@ base.strided.dabs,"\nbase.strided.dabs( N, x, strideX, y, strideY )\n Compute base.strided.dabs.ndarray,"\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs" base.strided.dabs2,"\nbase.strided.dabs2( N, x, strideX, y, strideY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2( x.length, x, 1, y, 1 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2( N, x, 2, y, -1 )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dabs2( N, x1, -2, y1, 1 )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs2\n" base.strided.dabs2.ndarray,"\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs2" -base.strided.dapx,"\nbase.strided.dapx( N, alpha, x, stride )\n Adds a constant to each element in a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns the strided array unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx( 3, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.dapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gapx, base.strided.sapx\n" -base.strided.dapx.ndarray,"\nbase.strided.dapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gapx, base.strided.sapx" +base.strided.dapx,"\nbase.strided.dapx( N, alpha, x, stride )\n Adds a constant to each element in a double-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > var alpha = 5.0;\n > base.strided.dapx( x.length, alpha, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.dapx( N, alpha, x, stride )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > alpha = 5.0;\n > stride = 2;\n > base.strided.dapx( N, alpha, x1, stride )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\nbase.strided.dapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > var alpha = 5.0;\n > base.strided.dapx.ndarray( x.length, alpha, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.dapx.ndarray( N, alpha, x, stride, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gapx, base.strided.sapx\n" +base.strided.dapx.ndarray,"\nbase.strided.dapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > var alpha = 5.0;\n > base.strided.dapx.ndarray( x.length, alpha, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.dapx.ndarray( N, alpha, x, stride, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gapx, base.strided.sapx" base.strided.dapxsum,"\nbase.strided.dapxsum( N, alpha, x, stride )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dapxsum( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dapxsum( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.dapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum\n" base.strided.dapxsum.ndarray,"\nbase.strided.dapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum" -base.strided.dapxsumkbn,"\nbase.strided.dapxsumkbn( N, alpha, x, stride )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided \n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumkbn( 3, 5.0, x1, 2)\n 14.0\n\n\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn\n" -base.strided.dapxsumkbn.ndarray,"\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn" +base.strided.dapxsumkbn,"\nbase.strided.dapxsumkbn( N, alpha, x, stride )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dapxsumkbn( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dapxsumkbn( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn\n" +base.strided.dapxsumkbn.ndarray,"\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn" base.strided.dapxsumkbn2,"\nbase.strided.dapxsumkbn2( N, alpha, x, stride )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dapxsumkbn2( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dapxsumkbn2( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2\n" base.strided.dapxsumkbn2.ndarray,"\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2" base.strided.dapxsumors,"\nbase.strided.dapxsumors( N, alpha, x, stride )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dapxsumors( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dapxsumors( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.dapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors\n" @@ -1726,8 +1726,8 @@ base.strided.drev,"\nbase.strided.drev( N, x, stride )\n Reverses a double-pr base.strided.drev.ndarray,"\nbase.strided.drev.ndarray( N, x, stride, offset )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.drev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.grev, base.strided.srev" base.strided.drsqrt,"\nbase.strided.drsqrt( N, x, strideX, y, strideY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt( x.length, x, 1, y, 1 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt( N, x, 2, y, -1 )\n [ ~0.333, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.drsqrt( N, x1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt\n" base.strided.drsqrt.ndarray,"\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt" -base.strided.dsapxsum,"\nbase.strided.dsapxsum( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dsapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum\n" -base.strided.dsapxsum.ndarray,"\nbase.strided.dsapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum" +base.strided.dsapxsum,"\nbase.strided.dsapxsum( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsapxsum( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsapxsum( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.dsapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum\n" +base.strided.dsapxsum.ndarray,"\nbase.strided.dsapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum" base.strided.dsapxsumpw,"\nbase.strided.dsapxsumpw( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsapxsumpw( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsapxsumpw( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw\n" base.strided.dsapxsumpw.ndarray,"\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw" base.strided.dscal,"\nbase.strided.dscal( N, alpha, x, stride )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `stride <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal( x.length, 5.0, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy\n" @@ -1804,8 +1804,8 @@ base.strided.dstdevwd,"\nbase.strided.dstdevwd( N, correction, x, stride )\n base.strided.dstdevwd.ndarray,"\nbase.strided.dstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd" base.strided.dstdevyc,"\nbase.strided.dstdevyc( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc\n" base.strided.dstdevyc.ndarray,"\nbase.strided.dstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc" -base.strided.dsum,"\nbase.strided.dsum( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsum.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum\n" -base.strided.dsum.ndarray,"\nbase.strided.dsum.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum" +base.strided.dsum,"\nbase.strided.dsum( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsum( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsum( N, x1, stride )\n -1.0\n\nbase.strided.dsum.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum\n" +base.strided.dsum.ndarray,"\nbase.strided.dsum.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum" base.strided.dsumkbn,"\nbase.strided.dsumkbn( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsumkbn( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsumkbn( N, x1, stride )\n -1.0\n\nbase.strided.dsumkbn.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn\n" base.strided.dsumkbn.ndarray,"\nbase.strided.dsumkbn.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn" base.strided.dsumkbn2,"\nbase.strided.dsumkbn2( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsumkbn2( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsumkbn2( N, x1, stride )\n -1.0\n\nbase.strided.dsumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2\n" @@ -2032,18 +2032,18 @@ base.strided.sabs,"\nbase.strided.sabs( N, x, strideX, y, strideY )\n Compute base.strided.sabs.ndarray,"\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs, base.strided.sabs2" base.strided.sabs2,"\nbase.strided.sabs2( N, x, strideX, y, strideY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2( x.length, x, 1, y, 1 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2( N, x, 2, y, -1 )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sabs2( N, x1, -2, y1, 1 )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs2, base.strided.sabs\n" base.strided.sabs2.ndarray,"\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs2, base.strided.sabs" -base.strided.sapx,"\nbase.strided.sapx( N, alpha, x, stride )\n Adds a constant to each element in a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns the strided array unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx( 3, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.sapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx\n" -base.strided.sapx.ndarray,"\nbase.strided.sapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx" -base.strided.sapxsum,"\nbase.strided.sapxsum( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum\n" -base.strided.sapxsum.ndarray,"\nbase.strided.sapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum" -base.strided.sapxsumkbn,"\nbase.strided.sapxsumkbn( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn\n" -base.strided.sapxsumkbn.ndarray,"\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn" +base.strided.sapx,"\nbase.strided.sapx( N, alpha, x, stride )\n Adds a constant to each element in a single-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > var alpha = 5.0;\n > base.strided.sapx( x.length, alpha, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.sapx( N, alpha, x, stride )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > alpha = 5.0;\n > stride = 2;\n > base.strided.sapx( N, alpha, x1, stride )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\nbase.strided.sapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > var alpha = 5.0;\n > base.strided.sapx.ndarray( x.length, alpha, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.sapx.ndarray( N, alpha, x, stride, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx\n" +base.strided.sapx.ndarray,"\nbase.strided.sapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > var alpha = 5.0;\n > base.strided.sapx.ndarray( x.length, alpha, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.sapx.ndarray( N, alpha, x, stride, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx" +base.strided.sapxsum,"\nbase.strided.sapxsum( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sapxsum( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sapxsum( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.sapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum\n" +base.strided.sapxsum.ndarray,"\nbase.strided.sapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum" +base.strided.sapxsumkbn,"\nbase.strided.sapxsumkbn( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sapxsumkbn( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sapxsumkbn( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn\n" +base.strided.sapxsumkbn.ndarray,"\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn" base.strided.sapxsumkbn2,"\nbase.strided.sapxsumkbn2( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sapxsumkbn2( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sapxsumkbn2( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2\n" base.strided.sapxsumkbn2.ndarray,"\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2" base.strided.sapxsumors,"\nbase.strided.sapxsumors( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sapxsumors( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sapxsumors( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.sapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors\n" base.strided.sapxsumors.ndarray,"\nbase.strided.sapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors" -base.strided.sapxsumpw,"\nbase.strided.sapxsumpw( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var stride = 2;\n > base.strided.sapxsumpw( 3, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.sapxsumpw( 3, 5.0, x1, stride )\n 14.0\n\n\nbase.strided.sapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw\n" -base.strided.sapxsumpw.ndarray,"\nbase.strided.sapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw" +base.strided.sapxsumpw,"\nbase.strided.sapxsumpw( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sapxsumpw( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sapxsumpw( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.sapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw\n" +base.strided.sapxsumpw.ndarray,"\nbase.strided.sapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw" base.strided.sasum,"\nbase.strided.sasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and stride parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum( x.length, x, 1 )\n 15.0\n\n // Sum every other value:\n > s = base.strided.sasum( 3, x, 2 )\n 9.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.sasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.gasum\n" base.strided.sasum.ndarray,"\nbase.strided.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.gasum" base.strided.sasumpw,"\nbase.strided.sasumpw( N, x, stride )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sasumpw( N, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sasumpw( N, x1, stride )\n 5.0\n\nbase.strided.sasumpw.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sasumpw.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw\n" @@ -2064,24 +2064,24 @@ base.strided.scumin,"\nbase.strided.scumin( N, x, strideX, y, strideY )\n Com base.strided.scumin.ndarray,"\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumin, base.strided.scumax" base.strided.scuminabs,"\nbase.strided.scuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scuminabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scuminabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin\n" base.strided.scuminabs.ndarray,"\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin" -base.strided.scusum,"\nbase.strided.scusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements.\n\n The `N` and `stride` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw\n" -base.strided.scusum.ndarray,"\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw" -base.strided.scusumkbn,"\nbase.strided.scusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scusumkbn( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2\n" -base.strided.scusumkbn.ndarray,"\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2" -base.strided.scusumkbn2,"\nbase.strided.scusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided \n array elements using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use \n a typed array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scusumkbn2( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameter supports indexing semantics\n based on starting indices.\n\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn\n" -base.strided.scusumkbn2.ndarray,"\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameter supports indexing semantics\n based on starting indices.\n\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn" -base.strided.scusumors,"\nbase.strided.scusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum\n" -base.strided.scusumors.ndarray,"\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum" -base.strided.scusumpw,"\nbase.strided.scusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum\n" -base.strided.scusumpw.ndarray,"\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum" +base.strided.scusum,"\nbase.strided.scusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusum( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scusum( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw\n" +base.strided.scusum.ndarray,"\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw" +base.strided.scusumkbn,"\nbase.strided.scusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumkbn( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scusumkbn( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2\n" +base.strided.scusumkbn.ndarray,"\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2" +base.strided.scusumkbn2,"\nbase.strided.scusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumkbn2( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scusumkbn2( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn\n" +base.strided.scusumkbn2.ndarray,"\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn" +base.strided.scusumors,"\nbase.strided.scusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumors( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scusumors( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum\n" +base.strided.scusumors.ndarray,"\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum" +base.strided.scusumpw,"\nbase.strided.scusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumpw( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scusumpw( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum\n" +base.strided.scusumpw.ndarray,"\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum" base.strided.sdeg2rad,"\nbase.strided.sdeg2rad( N, x, strideX, y, strideY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad( x.length, x, 1, y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad( N, x, 2, y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sdeg2rad( N, x1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, strided.deg2rad\n" base.strided.sdeg2rad.ndarray,"\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, strided.deg2rad" base.strided.sdot,"\nbase.strided.sdot( N, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.sdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot\n" base.strided.sdot.ndarray,"\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot" -base.strided.sdsapxsum,"\nbase.strided.sdsapxsum( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sdsapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum\n" -base.strided.sdsapxsum.ndarray,"\nbase.strided.sdsapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum" -base.strided.sdsapxsumpw,"\nbase.strided.sdsapxsumpw( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw" -base.strided.sdsapxsumpw.ndarray,"\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw" +base.strided.sdsapxsum,"\nbase.strided.sdsapxsum( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsapxsum( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsapxsum( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.sdsapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum\n" +base.strided.sdsapxsum.ndarray,"\nbase.strided.sdsapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum" +base.strided.sdsapxsumpw,"\nbase.strided.sdsapxsumpw( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsapxsumpw( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsapxsumpw( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw\n" +base.strided.sdsapxsumpw.ndarray,"\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw" base.strided.sdsdot,"\nbase.strided.sdsdot( N, scalar, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns the provided scalar constant.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdot\n" base.strided.sdsdot.ndarray,"\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdot" base.strided.sdsmean,"\nbase.strided.sdsmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean\n" @@ -2278,8 +2278,8 @@ base.strided.ssum,"\nbase.strided.ssum( N, x, stride )\n Computes the sum of base.strided.ssum.ndarray,"\nbase.strided.ssum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum" base.strided.ssumkbn,"\nbase.strided.ssumkbn( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumkbn.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw\n" base.strided.ssumkbn.ndarray,"\nbase.strided.ssumkbn.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw" -base.strided.ssumkbn2,"\nbase.strided.ssumkbn2( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumkbn2( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumkbn2( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw\n" -base.strided.ssumkbn2.ndarray,"\nbase.strided.ssumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw" +base.strided.ssumkbn2,"\nbase.strided.ssumkbn2( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.ssumkbn2( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.ssumkbn2( N, x1, stride )\n -1.0\n\nbase.strided.ssumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw\n" +base.strided.ssumkbn2.ndarray,"\nbase.strided.ssumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw" base.strided.ssumors,"\nbase.strided.ssumors( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumors.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw\n" base.strided.ssumors.ndarray,"\nbase.strided.ssumors.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw" base.strided.ssumpw,"\nbase.strided.ssumpw( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors\n" diff --git a/lib/node_modules/@stdlib/repl/help/data/data.json b/lib/node_modules/@stdlib/repl/help/data/data.json index aeb415cf3de7..c9aeae40413a 100644 --- a/lib/node_modules/@stdlib/repl/help/data/data.json +++ b/lib/node_modules/@stdlib/repl/help/data/data.json @@ -1 +1 @@ -{"abs":"\nabs( x[, options] )\n Computes the absolute value.\n\n If provided a number, the function returns a number.\n\n If provided an ndarray or array-like object, the function performs element-\n wise computation.\n\n If provided an array-like object, the function returns an array-like object\n having the same length and data type as `x`.\n\n If provided an ndarray, the function returns an ndarray having the same\n shape and data type as `x`.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject|number\n Input value.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Output array order (either row-major (C-style) or column-major (Fortran-\n style)). Only applicable when the input array is an ndarray. By default,\n the output array order is inferred from the input array.\n\n options.dtype: string (optional)\n Output array data type. Only applicable when the input array is either\n an ndarray or array-like object. By default, the output array data type\n is inferred from the input array.\n\n Returns\n -------\n y: ndarray|ArrayLikeObject|number\n Results.\n\n Examples\n --------\n // Provide a number:\n > var y = abs( -1.0 )\n 1.0\n\n // Provide an array-like object:\n > var x = new Float64Array( [ -1.0, -2.0 ] );\n > y = abs( x )\n [ 1.0, 2.0 ]\n\n > x = [ -1.0, -2.0 ];\n > y = abs( x )\n [ 1.0, 2.0 ]\n\n // Provide an ndarray:\n > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n > y = abs( x )\n \n > y.get( 0, 1 )\n 2.0\n\n\nabs.assign( x, y )\n Computes the absolute value and assigns results to a provided output array.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n Input array.\n\n y: ndarray|ArrayLikeObject\n Output array. Must be the same data \"kind\" (i.e., ndarray or array-like\n object) as the input array.\n\n Returns\n -------\n y: ndarray|ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Provide an array-like object:\n > var x = new Float64Array( [ -1.0, -2.0 ] );\n > var y = new Float64Array( x.length );\n > var out = abs.assign( x, y )\n [ 1.0, 2.0 ]\n > var bool = ( out === y )\n true\n\n > x = [ -1.0, -2.0 ];\n > y = [ 0.0, 0.0 ];\n > out = abs.assign( x, y )\n [ 1.0, 2.0 ]\n > bool = ( out === y )\n true\n\n // Provide an ndarray:\n > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n > y = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\n > out = abs.assign( x, y )\n \n > out.get( 0, 1 )\n 2.0\n > bool = ( out === y )\n true\n\n","abs.assign":"\nabs.assign( x, y )\n Computes the absolute value and assigns results to a provided output array.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n Input array.\n\n y: ndarray|ArrayLikeObject\n Output array. Must be the same data \"kind\" (i.e., ndarray or array-like\n object) as the input array.\n\n Returns\n -------\n y: ndarray|ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Provide an array-like object:\n > var x = new Float64Array( [ -1.0, -2.0 ] );\n > var y = new Float64Array( x.length );\n > var out = abs.assign( x, y )\n [ 1.0, 2.0 ]\n > var bool = ( out === y )\n true\n\n > x = [ -1.0, -2.0 ];\n > y = [ 0.0, 0.0 ];\n > out = abs.assign( x, y )\n [ 1.0, 2.0 ]\n > bool = ( out === y )\n true\n\n // Provide an ndarray:\n > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n > y = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\n > out = abs.assign( x, y )\n \n > out.get( 0, 1 )\n 2.0\n > bool = ( out === y )\n true","acartesianPower":"\nacartesianPower( x, n )\n Returns the Cartesian power.\n\n If provided an empty array, the function returns an empty array.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n n: integer\n Power.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x = [ 1, 2 ];\n > var out = acartesianPower( x, 2 )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianProduct, acartesianSquare\n","acartesianProduct":"\nacartesianProduct( x1, x2 )\n Returns the Cartesian product.\n\n If provided one or more empty arrays, the function returns an empty array.\n\n Parameters\n ----------\n x1: ArrayLikeObject\n First input array.\n\n x2: ArrayLikeObject\n Second input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x1 = [ 1, 2 ];\n > var x2 = [ 3, 4 ];\n > var out = acartesianProduct( x1, x2 )\n [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n See Also\n --------\n acartesianPower, acartesianSquare\n","acartesianSquare":"\nacartesianSquare( x )\n Returns the Cartesian square.\n\n If provided an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var out = acartesianSquare( [ 1, 2 ] )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianPower, acartesianProduct\n","acronym":"\nacronym( str[, options] )\n Generates an acronym for a given string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n options: Object (optional)\n Options.\n\n options.stopwords: Array (optional)\n Array of custom stop words.\n\n Returns\n -------\n out: string\n Acronym for the given string.\n\n Examples\n --------\n > var out = acronym( 'the quick brown fox' )\n 'QBF'\n > out = acronym( 'Hard-boiled eggs' )\n 'HBE'\n","aempty":"\naempty( length[, dtype] )\n Creates an uninitialized array having a specified length.\n\n In browser environments, the function always returns zero-filled arrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled array.\n\n In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n is *not* initialized. Memory contents are unknown and may contain\n *sensitive* data.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aempty( 2 )\n \n > arr = aempty( 2, 'float32' )\n \n\n See Also\n --------\n aemptyLike, afull, aones, azeros, ndempty\n","aemptyLike":"\naemptyLike( x[, dtype] )\n Creates an uninitialized array having the same length and data type as a\n provided input array.\n\n In browser environments, the function always returns zero-filled arrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled array.\n\n In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n is *not* initialized. Memory contents are unknown and may contain\n *sensitive* data.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var arr = aemptyLike( x )\n \n > arr = aemptyLike( x, 'float32' )\n \n\n See Also\n --------\n aempty, afullLike, aonesLike, azerosLike, ndemptyLike\n","AFINN_96":"\nAFINN_96()\n Returns a list of English words rated for valence.\n\n The returned list contains 1468 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list is an earlier version of AFINN-111.\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_96()\n [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_111\n","AFINN_111":"\nAFINN_111()\n Returns a list of English words rated for valence.\n\n The returned list contains 2477 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Words may contain numbers; e.g., \"n00b\".\n - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain diaeresis; e.g., \"naïve\".\n - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_111()\n [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_96\n","afull":"\nafull( length, value[, dtype] )\n Returns a filled array having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n value: any\n Fill value.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = afull( 2, 1.0 )\n [ 1.0, 1.0 ]\n > arr = afull( 2, 1.0, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afullLike, aones, azeros\n","afullLike":"\nafullLike( x[, dtype] )\n Returns a filled array having the same length and data type as a provided\n input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = afullLike( x, 1.0 )\n [ 1.0, 1.0 ]\n > y = afullLike( x, 1.0, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afull, aonesLike, azerosLike\n","alias2pkg":"\nalias2pkg( alias )\n Returns the package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Package name.\n\n Examples\n --------\n > var v = alias2pkg( 'base.sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n","alias2related":"\nalias2related( alias )\n Returns aliases related to a specified alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: Array|null\n Related aliases.\n\n Examples\n --------\n > var v = alias2related( 'base.sin' )\n [...]\n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n","alias2standalone":"\nalias2standalone( alias )\n Returns the standalone package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Standalone package name.\n\n Examples\n --------\n > var v = alias2standalone( 'base.sin' )\n '@stdlib/math-base-special-sin'\n\n See Also\n --------\n alias2pkg, alias2related, aliases, pkg2alias, pkg2standalone\n","aliases":"\naliases( [namespace] )\n Returns a list of standard library aliases.\n\n Parameters\n ----------\n namespace: string (optional)\n Namespace filter.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n > o = aliases( '@stdlib/math/base/special' )\n [...]\n\n See Also\n --------\n alias2pkg, alias2related, pkg2alias\n","allocUnsafe":"\nallocUnsafe( size )\n Allocates a buffer having a specified number of bytes.\n\n The underlying memory of returned buffers is not initialized. Memory\n contents are unknown and may contain sensitive data.\n\n When the size is less than half a buffer pool size, memory is allocated from\n the buffer pool for faster allocation of Buffer instances.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = allocUnsafe( 100 )\n \n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","amskfilter":"\namskfilter( x, mask )\n Returns a new array by applying a mask to a provided input array.\n\n If a mask array element is truthy, the corresponding element in `x` is\n included in the output array; otherwise, the corresponding element in `x` is\n \"masked\" and thus excluded from the output array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n mask: Array|TypedArray|Object\n Mask array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = amskfilter( x, [ 0, 1, 0, 1 ] )\n [ 2, 4 ]\n\n See Also\n --------\n amskreject\n","amskreject":"\namskreject( x, mask )\n Returns a new array by applying a mask to a provided input array.\n\n If a mask array element is falsy, the corresponding element in `x` is\n included in the output array; otherwise, the corresponding element in `x` is\n \"masked\" and thus excluded from the output array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n mask: Array|TypedArray|Object\n Mask array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = amskreject( x, [ 0, 1, 0, 1 ] )\n [ 1, 3 ]\n\n See Also\n --------\n amskfilter\n","anans":"\nanans( length[, dtype] )\n Returns an array filled with NaNs and having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = anans( 2 )\n [ NaN, NaN ]\n > arr = anans( 2, 'float32' )\n [ NaN, NaN ]\n\n See Also\n --------\n afull, anansLike, aones, azeros\n","anansLike":"\nanansLike( x[, dtype] )\n Returns an array filled with NaNs and having the same length and data type\n as a provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - generic: generic JavaScript values\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = anansLike( x )\n [ NaN, NaN ]\n > y = anansLike( x, 'float32' )\n [ NaN, NaN ]\n\n See Also\n --------\n afullLike, anans, aonesLike, azerosLike\n","anova1":"\nanova1( x, factor[, options] )\n Performs a one-way analysis of variance.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n factor: Array\n Array of treatments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.means: Object\n Group means alongside sample sizes and standard errors.\n\n out.treatment: Object\n Treatment results.\n\n out.treatment.df: number\n Treatment degrees of freedom.\n\n out.treatment.ss: number\n Treatment sum of squares.\n\n out.treatment.ms: number\n Treatment mean sum of squares.\n\n out.error: Object\n Error results.\n\n out.error.df: number\n Error degrees of freedom.\n\n out.error.ss: number\n Error sum of squares.\n\n out.error.ms: number\n Error mean sum of squares.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n > var f = [\n ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ... ];\n > var out = anova1( x, f )\n {...}\n\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n\n Anscombe's quartet is a set of 4 datasets which all have nearly identical\n simple statistical properties but vary considerably when graphed. Anscombe\n created the datasets to demonstrate why graphical data exploration should\n precede statistical data analysis and to show the effect of outliers on\n statistical properties.\n\n Returns\n -------\n out: Array\n Anscombe's quartet.\n\n Examples\n --------\n > var d = ANSCOMBES_QUARTET()\n [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n References\n ----------\n - Anscombe, Francis J. 1973. \"Graphs in Statistical Analysis.\" *The American\n Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n Ltd.]: 17–21. .\n\n","any":"\nany( collection )\n Tests whether at least one element in a collection is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an element is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 1 ];\n > var bool = any( arr )\n true\n\n See Also\n --------\n anyBy, every, forEach, none, some\n","anyBy":"\nanyBy( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4, -1 ];\n > var bool = anyBy( arr, negative )\n true\n\n See Also\n --------\n anyByAsync, anyByRight, everyBy, forEach, noneBy, someBy\n","anyByAsync":"\nanyByAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync\n","anyByAsync.factory":"\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync","anyByRight":"\nanyByRight( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, 2, 3, 4 ];\n > var bool = anyByRight( arr, negative )\n true\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByRight, forEachRight, noneByRight, someByRight\n","anyByRightAsync":"\nanyByRightAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync","aones":"\naones( length[, dtype] )\n Returns an array filled with ones and having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aones( 2 )\n [ 1.0, 1.0 ]\n > arr = aones( 2, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afull, anans, aonesLike, azeros\n","aonesLike":"\naonesLike( x[, dtype] )\n Returns an array filled with ones and having the same length and data type\n as a provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = aonesLike( x )\n [ 1.0, 1.0 ]\n > y = aonesLike( x, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afullLike, anansLike, aones, azerosLike\n","aoneTo":"\naoneTo( n[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n If `n` is equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: integer\n Number of elements.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aoneTo( 2 )\n [ 1.0, 2.0 ]\n > arr = aoneTo( 2, 'float32' )\n [ 1.0, 2.0 ]\n\n See Also\n --------\n afull, aones, aoneToLike, azeroTo\n","aoneToLike":"\naoneToLike( x[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one and having the same length and data type as a provided\n input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aoneToLike( [ 0, 0 ] )\n [ 1, 2 ]\n > arr = aoneToLike( [ 0, 0 ], 'float32' )\n [ 1.0, 2.0 ]\n\n See Also\n --------\n afullLike, aonesLike, aoneTo, azeroToLike\n","APERY":"\nAPERY\n Apéry's constant.\n\n Examples\n --------\n > APERY\n 1.2020569031595942\n\n","append":"\nappend( collection1, collection2 )\n Adds the elements of one collection to the end of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = append( arr, [ 6.0, 7.0 ] )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = append( arr, [ 3.0, 4.0 ] )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = append( arr, [ 1.0, 2.0 ] )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n prepend, push\n","ARCH":"\nARCH\n Operating system CPU architecture for which the JavaScript runtime binary\n was compiled.\n\n Current possible values:\n\n - arm\n - arm64\n - ia32\n - mips\n - mipsel\n - ppc\n - ppc64\n - s390\n - s390x\n - x32\n - x64\n\n Examples\n --------\n > ARCH\n \n\n See Also\n --------\n PLATFORM\n","argumentFunction":"\nargumentFunction( idx )\n Returns a function which always returns a specified argument.\n\n The input argument corresponds to the zero-based index of the argument to\n return.\n\n Parameters\n ----------\n idx: integer\n Argument index to return (zero-based).\n\n Returns\n -------\n out: Function\n Argument function.\n\n Examples\n --------\n > var argn = argumentFunction( 1 );\n > var v = argn( 3.14, -3.14, 0.0 )\n -3.14\n > v = argn( -1.0, -0.0, 1.0 )\n -0.0\n > v = argn( 'beep', 'boop', 'bop' )\n 'boop'\n > v = argn( 'beep' )\n undefined\n\n See Also\n --------\n constantFunction, identity\n","ARGV":"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n\n The first element is the absolute pathname of the executable that started\n the calling process.\n\n The second element is the path of the executed file.\n\n Any additional elements are additional command-line arguments.\n\n In browser environments, the array is empty.\n\n Examples\n --------\n > var execPath = ARGV[ 0 ]\n e.g., /usr/local/bin/node\n\n See Also\n --------\n ENV\n","array":"\narray( [buffer,] [options] )\n Returns a multidimensional array.\n\n Parameters\n ----------\n buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source.\n\n options: Object (optional)\n Options.\n\n options.buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source. If provided along with a `buffer` argument, the argument\n takes precedence.\n\n options.dtype: string (optional)\n Underlying storage data type. If not specified and a data source is\n provided, the data type is inferred from the provided data source. If an\n input data source is not of the same type, this option specifies the\n data type to which to cast the input data. For non-ndarray generic array\n data sources, the function casts generic array data elements to the\n default data type. In order to prevent this cast, the `dtype` option\n must be explicitly set to `'generic'`. Any time a cast is required, the\n `copy` option is set to `true`, as memory must be copied from the data\n source to an output data buffer. Default: 'float64'.\n\n options.order: string (optional)\n Specifies the memory layout of the data source as either row-major (C-\n style) or column-major (Fortran-style). The option may be one of the\n following values:\n\n - 'row-major': the order of the returned array is row-major.\n - 'column-major': the order of the returned array is column-major.\n - 'any': if a data source is column-major and not row-major, the order\n of the returned array is column-major; otherwise, the order of the\n returned array is row-major.\n - 'same': the order of the returned array matches the order of an input\n data source.\n\n Note that specifying an order which differs from the order of a\n provided data source does *not* entail a conversion from one memory\n layout to another. In short, this option is descriptive, not\n prescriptive. Default: 'row-major'.\n\n options.shape: Array (optional)\n Array shape (dimensions). If a shape is not specified, the function\n attempts to infer a shape based on a provided data source. For example,\n if provided a nested array, the function resolves nested array\n dimensions. If provided a multidimensional array data source, the\n function uses the array's associated shape. For most use cases, such\n inference suffices. For the remaining use cases, specifying a shape is\n necessary. For example, provide a shape to create a multidimensional\n array view over a linear data buffer, ignoring any existing shape meta\n data associated with a provided data source.\n\n options.flatten: boolean (optional)\n Boolean indicating whether to automatically flatten generic array data\n sources. If an array shape is not specified, the shape is inferred from\n the dimensions of nested arrays prior to flattening. If a use case\n requires partial flattening, partially flatten prior to invoking this\n function and set the option value to `false` to prevent further\n flattening during invocation. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to (shallow) copy source data to a new data\n buffer. The function does *not* perform a deep copy. To prevent\n undesired shared changes in state for generic arrays containing objects,\n perform a deep copy prior to invoking this function. Default: false.\n\n options.ndmin: integer (optional)\n Specifies the minimum number of dimensions. If an array shape has fewer\n dimensions than required by `ndmin`, the function prepends singleton\n dimensions to the array shape in order to satisfy the dimensions\n requirement. Default: 0.\n\n options.casting: string (optional)\n Specifies the casting rule used to determine acceptable casts. The\n option may be one of the following values:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow \"safe\" casts.\n - 'mostly-safe': allow \"safe casts\" and, for floating-point data types,\n downcasts.\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers\n and floats).\n\n Default: 'safe'.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. The\n option may be one of the following values:\n\n - 'throw': an ndarray instance throws an error when an index exceeds\n array dimensions.\n - 'normalize': an ndarray instance normalizes negative indices and\n throws an error when an index exceeds array dimensions.\n - 'wrap': an ndarray instance wraps around indices exceeding array\n dimensions using modulo arithmetic.\n - 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index.\n\n Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to\n\n - 'throw': an ndarray instance throws an error when a subscript exceeds\n array dimensions.\n - 'normalize': an ndarray instance normalizes negative subscripts and\n throws an error when a subscript exceeds array dimensions.\n - 'wrap': an ndarray instance wraps around subscripts exceeding array\n dimensions using modulo arithmetic.\n - 'clamp': an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index.\n\n If the number of modes is fewer than the number of dimensions, the\n function recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Multidimensional array.\n\n Examples\n --------\n // Create a 2x2 matrix:\n > var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n See Also\n --------\n ndarray\n","array2buffer":"\narray2buffer( arr )\n Allocates a buffer using an octet array.\n\n Parameters\n ----------\n arr: Array\n Array (or array-like object) of octets from which to copy.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = array2buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n Buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","array2fancy":"\narray2fancy( x[, options] )\n Converts an array to an object supporting fancy indexing.\n\n An array supporting fancy indexing is an array which supports slicing via\n indexing expressions for both retrieval and assignment.\n\n A fancy array shares the *same* data as the provided input array. Hence, any\n mutations to the returned array will affect the underlying input array and\n vice versa.\n\n For operations returning a new array (e.g., when slicing or invoking an\n instance method), a fancy array returns a new fancy array having the same\n configuration as specified by provided options.\n\n A fancy array supports indexing using positive and negative integers (both\n numeric literals and strings), Slice instances, subsequence expressions,\n mask arrays, boolean arrays, and integer arrays.\n\n A fancy array supports all properties and methods of the input array, and,\n thus, a fancy array can be consumed by any API which supports array-like\n objects.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on array views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use (e.g., in the\n REPL) and scripting. For performance critical applications, prefer\n equivalent functional APIs supporting array-like objects.\n\n Fancy arrays support broadcasting in which assigned scalars and single-\n element arrays are repeated (without additional memory allocation) to match\n the length of a target array instance.\n\n Fancy array broadcasting follows the same rules as for ndarrays.\n\n Consequently, when assigning arrays to slices, the array on the right-hand-\n side must be broadcast-compatible with number of elements in the slice.\n\n Fancy arrays support (mostly) safe casts (i.e., any cast which can be\n performed without overflow or loss of precision, with the exception of\n floating-point arrays which are also allowed to downcast from higher\n precision to lower precision).\n\n When attempting to perform an unsafe cast, fancy arrays will raise an\n exception.\n\n When assigning a real-valued scalar to a complex number array (e.g.,\n Complex128Array or Complex64Array), a fancy array will cast the real-valued\n scalar to a complex number argument having an imaginary component equal to\n zero.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking. Default:\n false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array supporting fancy indexing.\n\n Examples\n --------\n > var y = array2fancy( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]\n\n\narray2fancy.factory( [options] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an array to an object supporting fancy indexing.\n\n Examples\n --------\n > var f = array2fancy.factory();\n > var y = f( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]\n\n\narray2fancy.idx( x[, options] )\n Wraps a provided array as an array index object.\n\n For documentation and usage, see `ArrayIndex`.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n See Also\n --------\n aslice, FancyArray\n","array2fancy.factory":"\narray2fancy.factory( [options] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an array to an object supporting fancy indexing.\n\n Examples\n --------\n > var f = array2fancy.factory();\n > var y = f( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]","array2fancy.idx":"\narray2fancy.idx( x[, options] )\n Wraps a provided array as an array index object.\n\n For documentation and usage, see `ArrayIndex`.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n See Also\n --------\n aslice, FancyArray","array2iterator":"\narray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, circarray2iterator, array2iteratorRight, stridedarray2iterator\n","array2iteratorRight":"\narray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator\n","ArrayBuffer":"\nArrayBuffer( size )\n Returns an array buffer having a specified number of bytes.\n\n Buffer contents are initialized to 0.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: ArrayBuffer\n An array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n\n\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1\n\n\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > ArrayBuffer.isView( arr )\n true\n\n\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","ArrayBuffer.length":"\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1","ArrayBuffer.isView":"\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > ArrayBuffer.isView( arr )\n true","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","arraybuffer2buffer":"\narraybuffer2buffer( buf[, byteOffset[, length]] )\n Allocates a buffer from an ArrayBuffer.\n\n The behavior of this function varies across Node.js versions due to changes\n in the underlying Node.js APIs:\n\n - <3.0.0: the function copies ArrayBuffer bytes to a new Buffer instance.\n - >=3.0.0 and <5.10.0: if provided a byte offset, the function copies\n ArrayBuffer bytes to a new Buffer instance; otherwise, the function\n returns a view of an ArrayBuffer without copying the underlying memory.\n - <6.0.0: if provided an empty ArrayBuffer, the function returns an empty\n Buffer which is not an ArrayBuffer view.\n - >=6.0.0: the function returns a view of an ArrayBuffer without copying\n the underlying memory.\n\n Parameters\n ----------\n buf: ArrayBuffer\n Input array buffer.\n\n byteOffset: integer (optional)\n Index offset specifying the location of the first byte.\n\n length: integer (optional)\n Number of bytes to expose from the underlying ArrayBuffer.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var ab = new ArrayBuffer( 10 )\n \n > var buf = arraybuffer2buffer( ab )\n \n > var len = buf.length\n 10\n > buf = arraybuffer2buffer( ab, 2, 6 )\n \n > len = buf.length\n 6\n\n See Also\n --------\n Buffer, array2buffer, copyBuffer, string2buffer\n","arrayCtors":"\narrayCtors( dtype )\n Returns an array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = arrayCtors( 'float64' )\n \n > ctor = arrayCtors( 'float' )\n null\n\n See Also\n --------\n typedarrayCtors\n","arrayDataType":"\narrayDataType( array )\n Returns the data type of an array.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n array: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > var dt = arrayDataType( arr )\n 'float64'\n > dt = arrayDataType( 'beep' )\n null\n\n See Also\n --------\n arrayDataTypes\n","arrayDataTypes":"\narrayDataTypes( [kind] )\n Returns a list of array data types.\n\n When not provided a data type \"kind\", the function returns an array\n containing the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n The function supports the following data type \"kinds\":\n\n - floating_point: floating-point data types.\n - real_floating_point: real-valued floating-point data types.\n - complex_floating_point: complex-valued floating-point data types.\n - integer: integer data types.\n - signed_integer: signed integer data types.\n - unsigned_integer: unsigned integer data types.\n - real: real-valued data types.\n - numeric: numeric data types.\n - typed: \"typed\" data types.\n - all: all data types.\n\n Additionally, the function supports extending the \"kinds\" listed above by\n appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n Parameters\n ----------\n kind: string (optional)\n Data type kind.\n\n Returns\n -------\n out: Array\n List of array data types.\n\n Examples\n --------\n > var out = arrayDataTypes()\n [...]\n > out = arrayDataTypes( 'floating_point' )\n [...]\n > out = arrayDataTypes( 'floating_point_and_generic' )\n [...]\n\n See Also\n --------\n typedarrayDataTypes, ndarrayDataTypes\n","ArrayIndex":"\nArrayIndex( x[, options] )\n Wraps a provided array as an array index object.\n\n Array index instances have no explicit functionality; however, they are used\n by \"fancy\" arrays for element retrieval and assignment.\n\n By default, an instance is invalidated and removed from an internal cache\n immediately after a consumer resolves the underlying data associated with an\n instance using the `get` static method. Immediate invalidation and cache\n removal ensures that references to the underlying array are not the source\n of memory leaks.\n\n Because instances leverage an internal cache implementing the Singleton\n pattern, one must be sure to use the same constructor as consumers. If one\n uses a different constructor, the consumer will *not* be able to resolve the\n original wrapped array, as the consumer will attempt to resolve an instance\n in the wrong internal cache.\n\n Because non-persisted instances are freed after first use, in order to avoid\n holding onto memory and to allow garbage collection, one should avoid\n scenarios in which an instance is never used.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n\n\nArrayIndex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > // ...\n > ArrayIndex.free( idx.id )\n\n\nArrayIndex.get( id )\n Returns the array associated with the instance having a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing array data.\n\n out.data: Array|TypedArray|Object\n The underlying array associated with the provided identifier.\n\n out.type: string\n The type of array index.\n\n out.dtype: string\n The data type of the underlying array.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.get( idx.id )\n {...}\n\n\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array data type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.data\n [ 1, 2, 3, 4 ]\n\n\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.dtype\n 'generic'\n\n\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.id\n \n\n\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an array index is actively cached.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.isCached\n true\n\n\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n\n Returns\n -------\n out: string\n Array index type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.type\n \n\n\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toString()\n\n\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toJSON()\n { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n See Also\n --------\n array2fancy\n","ArrayIndex.free":"\nArrayIndex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > // ...\n > ArrayIndex.free( idx.id )","ArrayIndex.get":"\nArrayIndex.get( id )\n Returns the array associated with the instance having a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing array data.\n\n out.data: Array|TypedArray|Object\n The underlying array associated with the provided identifier.\n\n out.type: string\n The type of array index.\n\n out.dtype: string\n The data type of the underlying array.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.get( idx.id )\n {...}","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array data type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.data\n [ 1, 2, 3, 4 ]","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.dtype\n 'generic'","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.id\n ","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an array index is actively cached.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.isCached\n true","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n\n Returns\n -------\n out: string\n Array index type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.type\n ","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toString()","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toJSON()\n { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n See Also\n --------\n array2fancy","arrayMinDataType":"\narrayMinDataType( value )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n real numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n Array data type.\n\n Examples\n --------\n > var dt = arrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = arrayMinDataType( 3 )\n 'uint8'\n > dt = arrayMinDataType( -3 )\n 'int8'\n > dt = arrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n arrayDataTypes, arrayPromotionRules, arraySafeCasts\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast and, for floating-point data types, can be downcast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type value.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be cast.\n\n Examples\n --------\n > var out = arrayMostlySafeCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, arraySameKindCasts, ndarrayMostlySafeCasts\n","arrayNextDataType":"\narrayNextDataType( [dtype] )\n Returns the next larger array data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = arrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n arrayDataType, arrayDataTypes\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1, dtype2] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: any (optional)\n Array data type.\n\n dtype2: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = arrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n arrayDataTypes, arraySafeCasts, ndarrayPromotionRules\n","arraySafeCasts":"\narraySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = arraySafeCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arrayMostlySafeCasts, arraySameKindCasts, ndarraySafeCasts\n","arraySameKindCasts":"\narraySameKindCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast or cast within\n the same \"kind\".\n\n Examples\n --------\n > var out = arraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, ndarraySameKindCasts\n","arrayShape":"\narrayShape( arr )\n Determines array dimensions.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Array shape.\n\n Examples\n --------\n > var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n [ 2, 3 ]\n\n See Also\n --------\n ndarray\n","arrayStream":"\narrayStream( src[, options] )\n Creates a readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = arrayStream( [ 1, 2, 3 ] );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );\n\n\narrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n circularArrayStream, iteratorStream, stridedArrayStream\n","arrayStream.factory":"\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );","arrayStream.objectMode":"\narrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n circularArrayStream, iteratorStream, stridedArrayStream","arrayview2iterator":"\narrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like object\n view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, stridedarray2iterator, arrayview2iteratorRight\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, stridedarray2iterator, arrayview2iterator\n","aslice":"\naslice( x[, start[, end]] )\n Returns a shallow copy of a portion of an array.\n\n If provided an array-like object having a `slice` method, the function\n defers execution to that method and assumes that the method has the\n following signature:\n\n x.slice( start, end )\n\n If provided an array-like object without a `slice` method, the function\n copies input array elements to a new generic array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n start: integer (optional)\n Starting index (inclusive). Default: 0.\n\n end: integer (optional)\n Ending index (exclusive). Default: x.length.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = aslice( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n > out = aslice( [ 1, 2, 3, 4 ], 1 )\n [ 2, 3, 4 ]\n > out = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n [ 2, 3 ]\n\n See Also\n --------\n atake\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n Async iterator symbol.\n\n This symbol specifies the default async iterator for an object.\n\n The symbol is only supported in ES2018+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = AsyncIteratorSymbol\n\n See Also\n --------\n Symbol, IteratorSymbol\n","atake":"\natake( x, indices[, options] )\n Takes elements from an array.\n\n If `indices` is an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n indices: ArrayLikeObject\n List of element indices.\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n Specifies how to handle an index outside the interval [0, max], where\n `max` is the maximum possible array index. If equal to 'throw', the\n function throws an error. If equal to 'normalize', the function throws\n an error if provided an out-of-bounds normalized index. If equal to\n 'wrap', the function wraps around an index using modulo arithmetic. If\n equal to 'clamp', the function sets an index to either 0 (minimum index)\n or the maximum index. Default: 'normalize'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = atake( x, [ 1, 3 ] )\n [ 2, 4 ]\n\n See Also\n --------\n aslice\n","azeros":"\nazeros( length[, dtype] )\n Returns a zero-filled array having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeros( 2 )\n [ 0.0, 0.0 ]\n > arr = azeros( 2, 'float32' )\n [ 0.0, 0.0 ]\n\n See Also\n --------\n aempty, afull, anans, aones, azerosLike, ndzeros\n","azerosLike":"\nazerosLike( x[, dtype] )\n Returns a zero-filled array having the same length and data type as a\n provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = azerosLike( x )\n [ 0.0, 0.0 ]\n > y = azerosLike( x, 'float32' )\n [ 0.0, 0.0 ]\n\n See Also\n --------\n aemptyLike, afullLike, anansLike, aonesLike, azeros, ndzerosLike\n","azeroTo":"\nazeroTo( n[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n If `n` is equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: integer\n Number of elements.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeroTo( 2 )\n [ 0.0, 1.0 ]\n > arr = azeroTo( 2, 'float32' )\n [ 0.0, 1.0 ]\n\n See Also\n --------\n aempty, afull, aoneTo, azeroToLike, azeros\n","azeroToLike":"\nazeroToLike( x[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero and having the same length and data type as a provided\n input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeroToLike( [ 0, 0 ] )\n [ 0, 1 ]\n > arr = azeroToLike( [ 0, 0 ], 'float32' )\n [ 0.0, 1.0 ]\n\n See Also\n --------\n aemptyLike, afullLike, anansLike, aoneToLike, aonesLike, azeroTo, azerosLike\n","bartlettTest":"\nbartlettTest( ...x[, options] )\n Computes Bartlett’s test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = bartlettTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = bartlettTest( arr, { 'groups': groups } )\n\n See Also\n --------\n vartest, leveneTest\n","base.abs":"\nbase.abs( x )\n Computes the absolute value of a double-precision floating-point number `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.abs( -1.0 )\n 1.0\n > y = base.abs( 2.0 )\n 2.0\n > y = base.abs( 0.0 )\n 0.0\n > y = base.abs( -0.0 )\n 0.0\n > y = base.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs2, base.absf, base.labs\n","base.abs2":"\nbase.abs2( x )\n Computes the squared absolute value of a double-precision floating-point\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2( -1.0 )\n 1.0\n > y = base.abs2( 2.0 )\n 4.0\n > y = base.abs2( 0.0 )\n 0.0\n > y = base.abs2( -0.0 )\n 0.0\n > y = base.abs2( NaN )\n NaN\n\n See Also\n --------\n base.abs, base.abs2f\n","base.abs2f":"\nbase.abs2f( x )\n Computes the squared absolute value of a single-precision floating-point\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2f( -1.0 )\n 1.0\n > y = base.abs2f( 2.0 )\n 4.0\n > y = base.abs2f( 0.0 )\n 0.0\n > y = base.abs2f( -0.0 )\n 0.0\n > y = base.abs2f( NaN )\n NaN\n\n See Also\n --------\n base.abs2, base.absf\n","base.absdiff":"\nbase.absdiff( x, y )\n Computes the absolute difference.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Absolute difference.\n\n Examples\n --------\n > var d = base.absdiff( 2.0, 5.0 )\n 3.0\n > d = base.absdiff( -1.0, 3.14 )\n ~4.14\n > d = base.absdiff( 10.1, -2.05 )\n ~12.15\n > d = base.absdiff( -0.0, 0.0 )\n +0.0\n > d = base.absdiff( NaN, 5.0 )\n NaN\n > d = base.absdiff( PINF, NINF )\n Infinity\n > d = base.absdiff( PINF, PINF )\n NaN\n\n See Also\n --------\n base.reldiff, base.epsdiff\n","base.absf":"\nbase.absf( x )\n Computes the absolute value of a single-precision floating-point number `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.absf( -1.0 )\n 1.0\n > y = base.absf( 2.0 )\n 2.0\n > y = base.absf( 0.0 )\n 0.0\n > y = base.absf( -0.0 )\n 0.0\n > y = base.absf( NaN )\n NaN\n\n See Also\n --------\n base.abs, base.abs2f, base.labs\n","base.acos":"\nbase.acos( x )\n Compute the arccosine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in radians).\n\n Examples\n --------\n > var y = base.acos( 1.0 )\n 0.0\n > y = base.acos( 0.707 )\n ~0.7855\n > y = base.acos( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asin, base.atan\n","base.acosh":"\nbase.acosh( x )\n Computes the hyperbolic arccosine of a double-precision floating-point\n number.\n\n If `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosine.\n\n Examples\n --------\n > var y = base.acosh( 1.0 )\n 0.0\n > y = base.acosh( 2.0 )\n ~1.317\n > y = base.acosh( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atanh\n","base.acot":"\nbase.acot( x )\n Computes the inverse cotangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse cotangent (in radians).\n\n Examples\n --------\n > var y = base.acot( 2.0 )\n ~0.4636\n > y = base.acot( 0.0 )\n ~1.5708\n > y = base.acot( 0.5 )\n ~1.1071\n > y = base.acot( 1.0 )\n ~0.7854\n > y = base.acot( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.atan, base.cot\n","base.acoth":"\nbase.acoth( x )\n Computes the inverse hyperbolic cotangent of a double-precision floating-\n point number.\n\n The domain of the inverse hyperbolic cotangent is the union of the intervals\n (-inf,-1] and [1,inf).\n\n If provided a value on the open interval (-1,1), the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse hyperbolic cotangent.\n\n Examples\n --------\n > var y = base.acoth( 2.0 )\n ~0.5493\n > y = base.acoth( 0.0 )\n NaN\n > y = base.acoth( 0.5 )\n NaN\n > y = base.acoth( 1.0 )\n Infinity\n > y = base.acoth( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.acot, base.asinh, base.atanh\n","base.acovercos":"\nbase.acovercos( x )\n Computes the inverse coversed cosine.\n\n The inverse coversed cosine is defined as `asin(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed cosine.\n\n Examples\n --------\n > var y = base.acovercos( -1.5 )\n ~-0.5236\n > y = base.acovercos( -0.0 )\n ~1.5708\n\n See Also\n --------\n base.acoversin, base.avercos, base.covercos, base.vercos\n","base.acoversin":"\nbase.acoversin( x )\n Computes the inverse coversed sine.\n\n The inverse coversed sine is defined as `asin(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed sine.\n\n Examples\n --------\n > var y = base.acoversin( 1.5 )\n ~-0.5236\n > y = base.acoversin( 0.0 )\n ~1.5708\n\n See Also\n --------\n base.acovercos, base.aversin, base.coversin, base.versin\n","base.acsc":"\nbase.acsc( x )\n Computes the arccosecant of a number.\n\n If `|x| < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in radians).\n\n Examples\n --------\n > var y = base.acsc( 1.0 )\n ~1.57\n > y = base.acsc( PI )\n ~0.32\n > y = base.acsc( -PI )\n ~-0.32\n > y = base.acsc( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acsch, base.asec, base.asin\n","base.acsch":"\nbase.acsch( x )\n Computes the hyperbolic arccosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosecant.\n\n Examples\n --------\n > var y = base.acsch( 0.0 )\n Infinity\n > y = base.acsch( -1.0 )\n ~-0.881\n > y = base.acsch( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.acsc, base.asech, base.asinh, base.csch\n","base.add":"\nbase.add( x, y )\n Computes the sum of two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Sum.\n\n Examples\n --------\n > var v = base.add( -1.0, 5.0 )\n 4.0\n > v = base.add( 2.0, 5.0 )\n 7.0\n > v = base.add( 0.0, 5.0 )\n 5.0\n > v = base.add( -0.0, 0.0 )\n 0.0\n > v = base.add( NaN, NaN )\n NaN\n\n See Also\n --------\n base.div, base.mul, base.sub\n","base.add3":"\nbase.add3( x, y, z )\n Computes the sum of three double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add3( -1.0, 5.0, 2.0 )\n 6.0\n > v = base.add3( 2.0, 5.0, 2.0 )\n 9.0\n > v = base.add3( 0.0, 5.0, 2.0 )\n 7.0\n > v = base.add3( -0.0, 0.0, -0.0 )\n 0.0\n > v = base.add3( NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.add4":"\nbase.add4( x, y, z, w )\n Computes the sum of four double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n w: number\n Fourth input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\n 3.0\n > v = base.add4( 2.0, 5.0, 2.0, -3.0 )\n 6.0\n > v = base.add4( 0.0, 5.0, 2.0, -3.0 )\n 4.0\n > v = base.add4( -0.0, 0.0, -0.0, -0.0 )\n 0.0\n > v = base.add4( NaN, NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.add5":"\nbase.add5( x, y, z, w, u )\n Computes the sum of five double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n w: number\n Fourth input value.\n\n u: number\n Fifth input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\n 7.0\n > v = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\n 10.0\n > v = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\n 8.0\n > v = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\n 0.0\n > v = base.add5( NaN, NaN, NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.addf":"\nbase.addf( x, y )\n Computes the sum of two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Sum.\n\n Examples\n --------\n > var v = base.addf( -1.0, 5.0 )\n 4.0\n > v = base.addf( 2.0, 5.0 )\n 7.0\n > v = base.addf( 0.0, 5.0 )\n 5.0\n > v = base.addf( -0.0, 0.0 )\n 0.0\n > v = base.addf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.divf, base.mulf, base.subf\n","base.ahavercos":"\nbase.ahavercos( x )\n Computes the inverse half-value versed cosine.\n\n The inverse half-value versed cosine is defined as `2*acos(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed cosine.\n\n Examples\n --------\n > var y = base.ahavercos( 0.5 )\n ~1.5708\n > y = base.ahavercos( 0.0 )\n ~3.1416\n\n See Also\n --------\n base.ahaversin, base.havercos, base.vercos\n","base.ahaversin":"\nbase.ahaversin( x )\n Computes the inverse half-value versed sine.\n\n The inverse half-value versed sine is defined as `2*asin(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed sine.\n\n Examples\n --------\n > var y = base.ahaversin( 0.5 )\n ~1.5708\n > y = base.ahaversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.ahavercos, base.haversin, base.versin\n","base.asec":"\nbase.asec( x )\n Computes the inverse (arc) secant of a number.\n\n If `x > -1` and `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse (arc) secant.\n\n Examples\n --------\n > var y = base.asec( 1.0 )\n 0.0\n > y = base.asec( 2.0 )\n ~1.0472\n > y = base.asec( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acsc, base.asech, base.acos\n","base.asech":"\nbase.asech( x )\n Computes the hyperbolic arcsecant of a number.\n\n If `x < 0` or `x > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsecant.\n\n Examples\n --------\n > var y = base.asech( 1.0 )\n 0.0\n > y = base.asech( 0.5 )\n ~1.317\n > y = base.asech( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asec, base.asech, base.acoth\n","base.asin":"\nbase.asin( x )\n Computes the arcsine of a double-precision floating-point number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in radians).\n\n Examples\n --------\n > var y = base.asin( 0.0 )\n 0.0\n > y = base.asin( -PI/6.0 )\n ~-0.551\n > y = base.asin( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atan\n","base.asinh":"\nbase.asinh( x )\n Computes the hyperbolic arcsine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsine.\n\n Examples\n --------\n > var y = base.asinh( 0.0 )\n 0.0\n > y = base.asinh( 2.0 )\n ~1.444\n > y = base.asinh( -2.0 )\n ~-1.444\n > y = base.asinh( NaN )\n NaN\n > y = base.asinh( NINF )\n -Infinity\n > y = base.asinh( PINF )\n Infinity\n\n See Also\n --------\n base.acosh, base.asin, base.atanh\n","base.atan":"\nbase.atan( x )\n Computes the arctangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in radians).\n\n Examples\n --------\n > var y = base.atan( 0.0 )\n ~0.0\n > y = base.atan( -PI/2.0 )\n ~-1.004\n > y = base.atan( PI/2.0 )\n ~1.004\n > y = base.atan( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asin, base.atanh\n","base.atan2":"\nbase.atan2( y, x )\n Computes the angle in the plane (in radians) between the positive x-axis and\n the ray from (0,0) to the point (x,y).\n\n Parameters\n ----------\n y: number\n Coordinate along y-axis.\n\n x: number\n Coordinate along x-axis.\n\n Returns\n -------\n out: number\n Angle (in radians).\n\n Examples\n --------\n > var v = base.atan2( 2.0, 2.0 )\n ~0.785\n > v = base.atan2( 6.0, 2.0 )\n ~1.249\n > v = base.atan2( -1.0, -1.0 )\n ~-2.356\n > v = base.atan2( 3.0, 0.0 )\n ~1.571\n > v = base.atan2( -2.0, 0.0 )\n ~-1.571\n > v = base.atan2( 0.0, 0.0 )\n 0.0\n > v = base.atan2( 3.0, NaN )\n NaN\n > v = base.atan2( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.atan\n","base.atanh":"\nbase.atanh( x )\n Computes the hyperbolic arctangent of a double-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arctangent.\n\n Examples\n --------\n > var y = base.atanh( 0.0 )\n 0.0\n > y = base.atanh( 0.9 )\n ~1.472\n > y = base.atanh( 1.0 )\n Infinity\n > y = base.atanh( -1.0 )\n -Infinity\n > y = base.atanh( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asinh, base.atan\n","base.avercos":"\nbase.avercos( x )\n Computes the inverse versed cosine.\n\n The inverse versed cosine is defined as `acos(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed cosine.\n\n Examples\n --------\n > var y = base.avercos( -1.5 )\n ~2.0944\n > y = base.avercos( -0.0 )\n 0.0\n\n See Also\n --------\n base.aversin, base.versin\n","base.aversin":"\nbase.aversin( x )\n Computes the inverse versed sine.\n\n The inverse versed sine is defined as `acos(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed sine.\n\n Examples\n --------\n > var y = base.aversin( 1.5 )\n ~2.0944\n > y = base.aversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.avercos, base.vercos\n","base.bernoulli":"\nbase.bernoulli( n )\n Computes the nth Bernoulli number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Bernoulli number.\n\n Examples\n --------\n > var y = base.bernoulli( 0 )\n 1.0\n > y = base.bernoulli( 1 )\n 0.0\n > y = base.bernoulli( 2 )\n ~0.167\n > y = base.bernoulli( 3 )\n 0.0\n > y = base.bernoulli( 4 )\n ~-0.033\n > y = base.bernoulli( 5 )\n 0.0\n > y = base.bernoulli( 20 )\n ~-529.124\n > y = base.bernoulli( 260 )\n -Infinity\n > y = base.bernoulli( 262 )\n Infinity\n > y = base.bernoulli( NaN )\n NaN\n\n","base.besselj0":"\nbase.besselj0( x )\n Computes the Bessel function of the first kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj0( 0.0 )\n 1.0\n > y = base.besselj0( 1.0 )\n ~0.765\n > y = base.besselj0( PINF )\n 0.0\n > y = base.besselj0( NINF )\n 0.0\n > y = base.besselj0( NaN )\n NaN\n\n See Also\n --------\n base.besselj1, base.bessely0, base.bessely1\n","base.besselj1":"\nbase.besselj1( x )\n Computes the Bessel function of the first kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj1( 0.0 )\n 0.0\n > y = base.besselj1( 1.0 )\n ~0.440\n > y = base.besselj1( PINF )\n 0.0\n > y = base.besselj1( NINF )\n 0.0\n > y = base.besselj1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.bessely0, base.bessely1\n","base.bessely0":"\nbase.bessely0( x )\n Computes the Bessel function of the second kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely0( 0.0 )\n -Infinity\n > y = base.bessely0( 1.0 )\n ~0.088\n > y = base.bessely0( -1.0 )\n NaN\n > y = base.bessely0( PINF )\n 0.0\n > y = base.bessely0( NINF )\n NaN\n > y = base.bessely0( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely1\n","base.bessely1":"\nbase.bessely1( x )\n Computes the Bessel function of the second kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely1( 0.0 )\n -Infinity\n > y = base.bessely1( 1.0 )\n ~-0.781\n > y = base.bessely1( -1.0 )\n NaN\n > y = base.bessely1( PINF )\n 0.0\n > y = base.bessely1( NINF )\n NaN\n > y = base.bessely1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely0\n","base.beta":"\nbase.beta( x, y )\n Evaluates the beta function.\n\n Parameters\n ----------\n x: number\n First function parameter (nonnegative).\n\n y: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Evaluated beta function.\n\n Examples\n --------\n > var v = base.beta( 0.0, 0.5 )\n Infinity\n > v = base.beta( 1.0, 1.0 )\n 1.0\n > v = base.beta( -1.0, 2.0 )\n NaN\n > v = base.beta( 5.0, 0.2 )\n ~3.382\n > v = base.beta( 4.0, 1.0 )\n 0.25\n > v = base.beta( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.betainc, base.betaincinv, base.betaln\n","base.betainc":"\nbase.betainc( x, a, b[, regularized[, upper]] )\n Computes the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `NaN`.\n\n If provided `a < 0` or `b < 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betainc( 0.5, 2.0, 2.0 )\n 0.5\n > y = base.betainc( 0.5, 2.0, 2.0, false )\n ~0.083\n > y = base.betainc( 0.2, 1.0, 2.0 )\n 0.36\n > y = base.betainc( 0.2, 1.0, 2.0, true, true )\n 0.64\n > y = base.betainc( NaN, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.8, NaN, 1.0 )\n NaN\n > y = base.betainc( 0.8, 1.0, NaN )\n NaN\n > y = base.betainc( 1.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betainc( 0.5, 2.0, -2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betaincinv, base.betaln\n","base.betaincinv":"\nbase.betaincinv( p, a, b[, upper] )\n Computes the inverse of the lower incomplete beta function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second and third arguments are `a` and `b`,\n respectively.\n\n By default, the function inverts the lower regularized incomplete beta\n function. To invert the upper function, set the `upper` argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betaincinv( 0.2, 3.0, 3.0 )\n ~0.327\n > y = base.betaincinv( 0.4, 3.0, 3.0 )\n ~0.446\n > y = base.betaincinv( 0.4, 3.0, 3.0, true )\n ~0.554\n > y = base.betaincinv( 0.4, 1.0, 6.0 )\n ~0.082\n > y = base.betaincinv( 0.8, 1.0, 6.0 )\n ~0.235\n > y = base.betaincinv( NaN, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, NaN, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, 1.0, NaN )\n NaN\n > y = base.betaincinv( 1.2, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 0.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, -2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, 0.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaln\n","base.betaln":"\nbase.betaln( a, b )\n Evaluates the natural logarithm of the beta function.\n\n Parameters\n ----------\n a: number\n First function parameter (nonnegative).\n\n b: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Natural logarithm of the beta function.\n\n Examples\n --------\n > var v = base.betaln( 0.0, 0.0 )\n Infinity\n > v = base.betaln( 1.0, 1.0 )\n 0.0\n > v = base.betaln( -1.0, 2.0 )\n NaN\n > v = base.betaln( 5.0, 0.2 )\n ~1.218\n > v = base.betaln( 4.0, 1.0 )\n ~-1.386\n > v = base.betaln( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaincinv\n","base.binet":"\nbase.binet( x )\n Evaluates Binet's formula extended to real numbers.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function result.\n\n Examples\n --------\n > var y = base.binet( 0.0 )\n 0.0\n > y = base.binet( 1.0 )\n 1.0\n > y = base.binet( 2.0 )\n 1.0\n > y = base.binet( 3.0 )\n 2.0\n > y = base.binet( 4.0 )\n 3.0\n > y = base.binet( 5.0 )\n ~5.0\n > y = base.binet( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negafibonacci\n","base.binomcoef":"\nbase.binomcoef( n, k )\n Computes the binomial coefficient of two integers.\n\n If `k < 0`, the function returns `0`.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = base.binomcoef( 8, 2 )\n 28\n > v = base.binomcoef( 0, 0 )\n 1\n > v = base.binomcoef( -4, 2 )\n 10\n > v = base.binomcoef( 5, 3 )\n 10\n > v = base.binomcoef( NaN, 3 )\n NaN\n > v = base.binomcoef( 5, NaN )\n NaN\n > v = base.binomcoef( NaN, NaN )\n NaN\n\n","base.binomcoefln":"\nbase.binomcoefln( n, k )\n Computes the natural logarithm of the binomial coefficient of two integers.\n\n If `k < 0`, the function returns negative infinity.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Natural logarithm of the binomial coefficient.\n\n Examples\n --------\n > var v = base.binomcoefln( 8, 2 )\n ~3.332\n > v = base.binomcoefln( 0, 0 )\n 0.0\n > v = base.binomcoefln( -4, 2 )\n ~2.303\n > v = base.binomcoefln( 88, 3 )\n ~11.606\n > v = base.binomcoefln( NaN, 3 )\n NaN\n > v = base.binomcoefln( 5, NaN )\n NaN\n > v = base.binomcoefln( NaN, NaN )\n NaN\n\n","base.boxcox":"\nbase.boxcox( x, lambda )\n Computes a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox( 1.0, 2.5 )\n 0.0\n > v = base.boxcox( 4.0, 2.5 )\n 12.4\n > v = base.boxcox( 10.0, 2.5 )\n ~126.0911\n > v = base.boxcox( 2.0, 0.0 )\n ~0.6931\n > v = base.boxcox( -1.0, 2.5 )\n NaN\n > v = base.boxcox( 0.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcoxinv, base.boxcox1p, base.boxcox1pinv","base.boxcox1p":"\nbase.boxcox1p( x, lambda )\n Computes a one-parameter Box-Cox transformation of 1+x.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1p( 1.0, 2.5 )\n ~1.8627\n > v = base.boxcox1p( 4.0, 2.5 )\n ~21.9607\n > v = base.boxcox1p( 10.0, 2.5 )\n ~160.1246\n > v = base.boxcox1p( 2.0, 0.0 )\n ~1.0986\n > v = base.boxcox1p( -1.0, 2.5 )\n -0.4\n > v = base.boxcox1p( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1p( -1.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcox, base.boxcox1pinv, base.boxcoxinv","base.boxcox1pinv":"\nbase.boxcox1pinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1pinv( 1.0, 2.5 )\n ~0.6505\n > v = base.boxcox1pinv( 4.0, 2.5 )\n ~1.6095\n > v = base.boxcox1pinv( 10.0, 2.5 )\n ~2.6812\n > v = base.boxcox1pinv( 2.0, 0.0 )\n ~6.3891\n > v = base.boxcox1pinv( -1.0, 2.5 )\n NaN\n > v = base.boxcox1pinv( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1pinv( 1.0, NaN )\n NaN\n > v = base.boxcox1pinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcoxinv","base.boxcoxinv":"\nbase.boxcoxinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcoxinv( 1.0, 2.5 )\n ~1.6505\n > v = base.boxcoxinv( 4.0, 2.5 )\n ~2.6095\n > v = base.boxcoxinv( 10.0, 2.5 )\n ~3.6812\n > v = base.boxcoxinv( 2.0, 0.0 )\n ~7.3891\n > v = base.boxcoxinv( -1.0, 2.5 )\n NaN\n > v = base.boxcoxinv( 0.0, -1.0 )\n 1.0\n > v = base.boxcoxinv( 1.0, NaN )\n NaN\n > v = base.boxcoxinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcox1pinv","base.cabs":"\nbase.cabs( z )\n Computes the absolute value of a double-precision complex floating-point\n number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n ~5.831\n\n See Also\n --------\n base.cabs2, base.abs\n","base.cabs2":"\nbase.cabs2( z )\n Computes the squared absolute value of a double-precision complex floating-\n point number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n 34.0\n\n See Also\n --------\n base.cabs, base.abs2\n","base.cabs2f":"\nbase.cabs2f( z )\n Computes the squared absolute value of a single-precision complex floating-\n point number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n 34.0\n\n See Also\n --------\n base.cabs2, base.cabsf, base.abs2f\n","base.cabsf":"\nbase.cabsf( z )\n Computes the absolute value of a single-precision complex floating-point\n number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n ~5.831\n\n See Also\n --------\n base.cabs, base.cabs2f, base.absf\n","base.cadd":"\nbase.cadd( z1, z2 )\n Adds two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var out = base.cadd( z, z )\n \n > var re = real( out )\n 10.0\n > var im = imag( out )\n 6.0\n\n See Also\n --------\n base.cdiv, base.cmul, base.csub\n","base.caddf":"\nbase.caddf( z1, z2 )\n Adds two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var out = base.caddf( z, z )\n \n > var re = realf( out )\n 10.0\n > var im = imagf( out )\n 6.0\n\n See Also\n --------\n base.cadd, base.cmulf, base.csubf\n","base.cbrt":"\nbase.cbrt( x )\n Computes the cube root of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrt( 64.0 )\n 4.0\n > y = base.cbrt( 27.0 )\n 3.0\n > y = base.cbrt( 0.0 )\n 0.0\n > y = base.cbrt( -0.0 )\n -0.0\n > y = base.cbrt( -9.0 )\n ~-2.08\n > y = base.cbrt( NaN )\n NaN\n\n See Also\n --------\n base.pow, base.sqrt\n","base.cbrtf":"\nbase.cbrtf( x )\n Computes the cube root of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrtf( 64.0 )\n 4.0\n > y = base.cbrtf( 27.0 )\n 3.0\n > y = base.cbrtf( 0.0 )\n 0.0\n > y = base.cbrtf( -0.0 )\n -0.0\n > y = base.cbrtf( -9.0 )\n ~-2.08\n > y = base.cbrtf( NaN )\n NaN\n\n See Also\n --------\n base.cbrt, base.sqrtf\n","base.cceil":"\nbase.cceil( z )\n Rounds a double-precision complex floating-point number toward positive\n infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cceil( new Complex128( -1.5, 2.5 ) )\n \n > var re = real( v )\n -1.0\n > var im = imag( v )\n 3.0\n\n See Also\n --------\n base.cceiln, base.cfloor, base.cround\n","base.cceilf":"\nbase.cceilf( z )\n Rounds a single-precision complex floating-point number toward positive\n infinity.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\n \n > var re = real( v )\n -1.0\n > var im = imag( v )\n 3.0\n\n See Also\n --------\n base.cceil\n","base.cceiln":"\nbase.cceiln( z, n )\n Rounds each component of a double-precision complex number to the nearest\n multiple of `10^n` toward positive infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Complex128\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\n \n > var re = real( out )\n 5.56\n > var im = imag( out )\n -3.33\n\n See Also\n --------\n base.cceil, base.cfloorn, base.croundn\n","base.ccis":"\nbase.ccis( z )\n Evaluates the cis function for a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex number.\n\n Examples\n --------\n > var y = base.ccis( new Complex128( 0.0, 0.0 ) )\n \n > var re = real( y )\n 1.0\n > var im = imag( y )\n 0.0\n > y = base.ccis( new Complex128( 1.0, 0.0 ) )\n \n > re = real( y )\n ~0.540\n > im = imag( y )\n ~0.841\n\n","base.cdiv":"\nbase.cdiv( z1, z2 )\n Divides two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( -13.0, -1.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var y = base.cdiv( z1, z2 )\n \n > var re = real( y )\n 5.0\n > var im = imag( y )\n 3.0\n\n See Also\n --------\n base.cadd, base.cmul, base.csub\n","base.ceil":"\nbase.ceil( x )\n Rounds a double-precision floating-point number toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil( 3.14 )\n 4.0\n > y = base.ceil( -4.2 )\n -4.0\n > y = base.ceil( -4.6 )\n -4.0\n > y = base.ceil( 9.5 )\n 10.0\n > y = base.ceil( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceiln, base.floor, base.round\n","base.ceil2":"\nbase.ceil2( x )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil2( 3.14 )\n 4.0\n > y = base.ceil2( -4.2 )\n -4.0\n > y = base.ceil2( -4.6 )\n -4.0\n > y = base.ceil2( 9.5 )\n 16.0\n > y = base.ceil2( 13.0 )\n 16.0\n > y = base.ceil2( -13.0 )\n -8.0\n > y = base.ceil2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil10, base.floor2, base.round2\n","base.ceil10":"\nbase.ceil10( x )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil10( 3.14 )\n 10.0\n > y = base.ceil10( -4.2 )\n -1.0\n > y = base.ceil10( -4.6 )\n -1.0\n > y = base.ceil10( 9.5 )\n 10.0\n > y = base.ceil10( 13.0 )\n 100.0\n > y = base.ceil10( -13.0 )\n -10.0\n > y = base.ceil10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil2, base.floor10, base.round10\n","base.ceilb":"\nbase.ceilb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.ceilb( 3.14159, -4, 10 )\n 3.1416\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.ceilb( 3.14159, 0, 2 )\n 4.0\n\n // Round to nearest multiple of two toward positive infinity:\n > y = base.ceilb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceil, base.ceiln, base.floorb, base.roundb\n","base.ceilf":"\nbase.ceilf( x )\n Rounds a single-precision floating-point number toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilf( 3.14 )\n 4.0\n > y = base.ceilf( -4.2 )\n -4.0\n > y = base.ceilf( -4.6 )\n -4.0\n > y = base.ceilf( 9.5 )\n 10.0\n > y = base.ceilf( -0.0 )\n -0.0\n\n See Also\n --------\n base.floorf\n","base.ceiln":"\nbase.ceiln( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.ceiln( 3.14159, -2 )\n 3.15\n\n // If `n = 0`, standard round toward positive infinity behavior:\n > y = base.ceiln( 3.14159, 0 )\n 4.0\n\n // Round to nearest thousand:\n > y = base.ceiln( 12368.0, 3 )\n 13000.0\n\n\n See Also\n --------\n base.ceil, base.ceilb, base.floorn, base.roundn\n","base.ceilsd":"\nbase.ceilsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilsd( 3.14159, 5 )\n 3.1416\n > y = base.ceilsd( 3.14159, 1 )\n 4.0\n > y = base.ceilsd( 12368.0, 2 )\n 13000.0\n > y = base.ceilsd( 0.0313, 2, 2 )\n 0.046875\n\n See Also\n --------\n base.ceil, base.floorsd, base.roundsd, base.truncsd\n","base.cexp":"\nbase.cexp( z )\n Evaluates the exponential function for a double-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex number.\n\n Examples\n --------\n > var y = base.cexp( new Complex128( 0.0, 0.0 ) )\n \n > var re = real( y )\n 1.0\n > var im = imag( y )\n 0.0\n > y = base.cexp( new Complex128( 0.0, 1.0 ) )\n \n > re = real( y )\n ~0.540\n > im = imag( y )\n ~0.841\n\n","base.cflipsign":"\nbase.cflipsign( z, y )\n Returns a double-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\n \n > var re = real( v )\n 4.2\n > var im = imag( v )\n -5.5\n\n See Also\n --------\n base.cneg, base.csignum\n","base.cflipsignf":"\nbase.cflipsignf( z, y )\n Returns a single-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\n \n > var re = real( v )\n 4.0\n > var im = imag( v )\n -5.0\n\n See Also\n --------\n base.cnegf, base.cflipsign\n","base.cfloor":"\nbase.cfloor( z )\n Rounds a double-precision complex floating-point number toward negative\n infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\n \n > var re = real( v )\n 5.0\n > var im = imag( v )\n 3.0\n\n See Also\n --------\n base.cceil, base.cfloorn, base.cround\n","base.cfloorn":"\nbase.cfloorn( z, n )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n` toward negative infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n z: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\n \n > var re = real( v )\n 5.55\n > var im = imag( v )\n -3.34\n\n See Also\n --------\n base.cceiln, base.cfloor, base.croundn\n","base.cidentity":"\nbase.cidentity( z )\n Evaluates the identity function for a double-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex128\n Input value.\n\n Returns\n -------\n v: Complex128\n Input value.\n\n Examples\n --------\n > var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\n \n > var re = real( v )\n -1.0\n > var img = imag( v )\n 2.0\n\n See Also\n --------\n base.cidentityf, base.identity\n","base.cidentityf":"\nbase.cidentityf( z )\n Evaluates the identity function for a single-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex64\n Input value.\n\n Returns\n -------\n v: Complex64\n Input value.\n\n Examples\n --------\n > var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\n \n > var re = real( v )\n -1.0\n > var img = imag( v )\n 2.0\n\n See Also\n --------\n base.cidentity, base.identityf\n","base.cinv":"\nbase.cinv( z )\n Computes the inverse of a double-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cinv( new Complex128( 2.0, 4.0 ) )\n \n > var re = real( v )\n 0.1\n > var im = imag( v )\n -0.2\n\n See Also\n --------\n base.cdiv\n","base.clamp":"\nbase.clamp( v, min, max )\n Restricts a double-precision floating-point number to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clamp( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clamp( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clamp( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clamp( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clampf, base.wrap\n","base.clampf":"\nbase.clampf( v, min, max )\n Restricts a single-precision floating-point number to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clampf( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clampf( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clampf( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clampf( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clampf( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clampf( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clamp\n","base.cmul":"\nbase.cmul( z1, z2 )\n Multiplies two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( 5.0, 3.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var out = base.cmul( z1, z2 )\n \n > var re = real( out )\n -13.0\n > var im = imag( out )\n -1.0\n\n See Also\n --------\n base.cadd, base.cdiv, base.csub\n","base.cmulf":"\nbase.cmulf( z1, z2 )\n Multiplies two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z1 = new Complex64( 5.0, 3.0 )\n \n > var z2 = new Complex64( -2.0, 1.0 )\n \n > var out = base.cmulf( z1, z2 )\n \n > var re = realf( out )\n -13.0\n > var im = imagf( out )\n -1.0\n\n See Also\n --------\n base.caddf, base.cmul, base.csubf\n","base.cneg":"\nbase.cneg( z )\n Negates a double-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z = new Complex128( -4.2, 5.5 )\n \n > var v = base.cneg( z )\n \n > var re = real( v )\n 4.2\n > var im = imag( v )\n -5.5\n\n See Also\n --------\n base.cabs\n","base.cnegf":"\nbase.cnegf( z )\n Negates a single-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z = new Complex64( -4.0, 5.0 )\n \n > var v = base.cnegf( z )\n \n > var re = realf( v )\n 4.0\n > var im = imagf( v )\n -5.0\n\n See Also\n --------\n base.cneg, base.cabsf\n","base.continuedFraction":"\nbase.continuedFraction( generator[, options] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n\n `generator` can be either a function which returns an array with two\n elements, the `a` and `b` terms of the fraction, or an ES6 Generator object.\n\n By default, the function computes\n\n a1\n ---------------\n b1 + a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n To evaluate\n\n b0 +\t a1\n ---------------\n b1 +\t a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n set the `keep` option to `true`.\n\n Parameters\n ----------\n generator: Function\n Function returning terms of continued fraction expansion.\n\n options: Object (optional)\n Options.\n\n options.maxIter: integer (optional)\n Maximum number of iterations. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n current term times the tolerance. Default: `2.22e-16`.\n\n options.keep: boolean (optional)\n Boolean indicating whether to keep the `b0` term in the continued\n fraction. Default: `false`.\n\n Returns\n -------\n out: number\n Value of continued fraction.\n\n Examples\n --------\n // Continued fraction for (e-1)^(-1):\n > function closure() {\n ... var i = 0;\n ... return function() {\n ... i += 1;\n ... return [ i, i ];\n ... };\n ... };\n > var gen = closure();\n > var out = base.continuedFraction( gen )\n ~0.582\n\n // Using an ES6 generator:\n > function* generator() {\n ... var i = 0;\n ... while ( true ) {\n ... i += 1;\n ... yield [ i, i ];\n ... }\n ... };\n > gen = generator();\n > out = base.continuedFraction( gen )\n ~0.582\n\n // Set options:\n > out = base.continuedFraction( generator(), { 'keep': true } )\n ~1.718\n > out = base.continuedFraction( generator(), { 'maxIter': 10 } )\n ~0.582\n > out = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n ~0.579\n\n","base.copysign":"\nbase.copysign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysign( -3.14, 10.0 )\n 3.14\n > z = base.copysign( 3.14, -1.0 )\n -3.14\n > z = base.copysign( 1.0, -0.0 )\n -1.0\n > z = base.copysign( -3.14, -0.0 )\n -3.14\n > z = base.copysign( -0.0, 1.0 )\n 0.0\n\n See Also\n --------\n base.flipsign\n","base.copysignf":"\nbase.copysignf( x, y )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Single-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysignf( -3.0, 10.0 )\n 3.0\n > z = base.copysignf( 3.0, -1.0 )\n -3.0\n > z = base.copysignf( 1.0, -0.0 )\n -1.0\n > z = base.copysignf( -3.0, -0.0 )\n -3.0\n > z = base.copysignf( -0.0, 1.0 )\n 0.0\n\n See Also\n --------\n base.copysign, base.flipsignf\n","base.cos":"\nbase.cos( x )\n Computes the cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine.\n\n Examples\n --------\n > var y = base.cos( 0.0 )\n 1.0\n > y = base.cos( PI/4.0 )\n ~0.707\n > y = base.cos( -PI/6.0 )\n ~0.866\n > y = base.cos( NaN )\n NaN\n\n See Also\n --------\n base.cospi, base.cosm1, base.sin, base.tan\n","base.cosh":"\nbase.cosh( x )\n Computes the hyperbolic cosine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic cosine.\n\n Examples\n --------\n > var y = base.cosh( 0.0 )\n 1.0\n > y = base.cosh( 2.0 )\n ~3.762\n > y = base.cosh( -2.0 )\n ~3.762\n > y = base.cosh( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinh, base.tanh\n","base.cosm1":"\nbase.cosm1( x )\n Computes the cosine of a number minus one.\n\n This function should be used instead of manually calculating `cos(x)-1` when\n `x` is near unity.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine minus one.\n\n Examples\n --------\n > var y = base.cosm1( 0.0 )\n 0.0\n > y = base.cosm1( PI/4.0 )\n ~-0.293\n > y = base.cosm1( -PI/6.0 )\n ~-0.134\n > y = base.cosm1( NaN )\n NaN\n\n See Also\n --------\n base.cos\n","base.cospi":"\nbase.cospi( x )\n Computes the value of `cos(πx)`.\n\n This function computes `cos(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.cospi( 0.0 )\n 1.0\n > y = base.cospi( 0.5 )\n 0.0\n > y = base.cospi( 0.1 )\n ~0.951\n > y = base.cospi( NaN )\n NaN\n\n See Also\n --------\n base.cos\n","base.cot":"\nbase.cot( x )\n Computes the cotangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cotangent.\n\n Examples\n --------\n > var y = base.cot( 0.0 )\n Infinity\n > y = base.cot( -PI/4.0 )\n ~-1.0\n > y = base.cot( PI/4.0 )\n ~1.0\n > y = base.cot( NaN )\n NaN\n\n See Also\n --------\n base.tan\n","base.coth":"\nbase.coth( x )\n Computes the hyperbolic cotangent of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic cotangent.\n\n Examples\n --------\n > var y = base.coth( 0.0 )\n Infinity\n > y = base.coth( -0.0 )\n -Infinity\n > y = base.coth( 2.0 )\n ~1.0373\n > y = base.coth( -2.0 )\n ~-1.0373\n > y = base.coth( +Infinity )\n ~1\n > y = base.coth( -Infinity )\n ~-1\n > y = base.coth( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.cot, base.csch, base.tanh\n","base.covercos":"\nbase.covercos( x )\n Computes the coversed cosine.\n\n The coversed cosine is defined as `1 + sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed cosine.\n\n Examples\n --------\n > var y = base.covercos( 3.14 )\n ~1.0016\n > y = base.covercos( -4.2 )\n ~1.8716\n > y = base.covercos( -4.6 )\n ~1.9937\n > y = base.covercos( 9.5 )\n ~0.9248\n > y = base.covercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.coversin, base.vercos\n","base.coversin":"\nbase.coversin( x )\n Computes the coversed sine.\n\n The coversed sine is defined as `1 - sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed sine.\n\n Examples\n --------\n > var y = base.coversin( 3.14 )\n ~0.9984\n > y = base.coversin( -4.2 )\n ~0.1284\n > y = base.coversin( -4.6 )\n ~0.0063\n > y = base.coversin( 9.5 )\n ~1.0752\n > y = base.coversin( -0.0 )\n 1.0\n\n See Also\n --------\n base.covercos, base.versin\n","base.cphase":"\nbase.cphase( z )\n Computes the argument of a double-precision complex floating-point number\n in radians.\n\n The argument of a complex number, also known as the phase, is the angle of\n the radius extending from the origin to the complex number plotted in the\n complex plane and the positive real axis.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n phi: number\n Argument.\n\n Examples\n --------\n > var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n ~0.5404\n\n See Also\n --------\n base.cabs\n","base.cpolar":"\nbase.cpolar( z )\n Returns the absolute value and phase of a double-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Array\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n [ ~5.83, ~0.5404 ]\n\n\nbase.cpolar.assign( z, out, stride, offset )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n out: Array|TypedArray|Object\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs, base.cphase","base.cpolar.assign":"\nbase.cpolar.assign( z, out, stride, offset )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n out: Array|TypedArray|Object\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs, base.cphase","base.cround":"\nbase.cround( z )\n Rounds each component of a double-precision complex floating-point number\n to the nearest integer.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Rounded complex number.\n\n Examples\n --------\n > var v = base.cround( new Complex128( 5.5, 3.3 ) )\n \n > var re = real( v )\n 6.0\n > var im = imag( v )\n 3.0\n\n See Also\n --------\n base.cceil, base.cfloor, base.croundn\n","base.croundn":"\nbase.croundn( z, n )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\n \n > var re = real( v )\n 5.56\n > var im = imag( v )\n -3.34\n\n See Also\n --------\n base.cceiln, base.cfloorn, base.cround\n","base.csch":"\nbase.csch( x )\n Computes the hyperbolic cosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic cosecant.\n\n Examples\n --------\n > var y = base.csch( +0.0 )\n +Infinity\n > var y = base.csch( -0.0 )\n -Infinity\n > var y = base.csch( +Infinity )\n +0.0\n > var y = base.csch( -Infinity )\n -0.0\n > y = base.csch( 2.0 )\n ~0.2757\n > y = base.csch( -2.0 )\n ~-0.2757\n > y = base.csch( NaN )\n NaN\n\n See Also\n --------\n base.acsch, base.coth, base.sinh\n","base.csignum":"\nbase.csignum( z )\n Evaluates the signum function of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.csignum( new Complex128( -4.2, 5.5 ) )\n \n > var re = real( v )\n -0.6069136033622302\n > var im = imag( v )\n 0.79476781392673\n\n See Also\n --------\n base.signum\n","base.csub":"\nbase.csub( z1, z2 )\n Subtracts two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( 5.0, 3.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var out = base.csub( z1, z2 )\n \n > var re = real( out )\n 7.0\n > var im = imag( out )\n 2.0\n\n See Also\n --------\n base.cadd, base.cdiv, base.cmul\n","base.csubf":"\nbase.csubf( z1, z2 )\n Subtracts two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z1 = new Complex64( 5.0, 3.0 )\n \n > var z2 = new Complex64( -2.0, 1.0 )\n \n > var out = base.csubf( z1, z2 )\n \n > var re = realf( out )\n 7.0\n > var im = imagf( out )\n 2.0\n\n See Also\n --------\n base.caddf, base.cmulf, base.csub\n","base.deg2rad":"\nbase.deg2rad( x )\n Converts an angle from degrees to radians.\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2rad( 90.0 )\n ~1.571\n > r = base.deg2rad( -45.0 )\n ~-0.785\n > r = base.deg2rad( NaN )\n NaN\n\n See Also\n --------\n base.rad2deg\n","base.deg2radf":"\nbase.deg2radf( x )\n Converts an angle from degrees to radians (single-precision).\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2radf( 90.0 )\n ~1.571\n > r = base.deg2radf( -45.0 )\n ~-0.785\n > r = base.deg2radf( NaN )\n NaN\n\n See Also\n --------\n base.deg2rad\n","base.digamma":"\nbase.digamma( x )\n Evaluates the digamma function.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.digamma( -2.5 )\n ~1.103\n > y = base.digamma( 1.0 )\n ~-0.577\n > y = base.digamma( 10.0 )\n ~2.252\n > y = base.digamma( NaN )\n NaN\n > y = base.digamma( -1.0 )\n NaN\n\n See Also\n --------\n base.gamma, base.trigamma\n","base.diracDelta":"\nbase.diracDelta( x )\n Evaluates the Dirac delta function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.diracDelta( 3.14 )\n 0.0\n > y = base.diracDelta( 0.0 )\n Infinity\n\n See Also\n --------\n base.kroneckerDelta\n","base.div":"\nbase.div( x, y )\n Divides two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value (dividend).\n\n y: number\n Second input value (divisor).\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.div( -1.0, 5.0 )\n -0.2\n > v = base.div( 2.0, 5.0 )\n 0.4\n > v = base.div( 0.0, 5.0 )\n 0.0\n > v = base.div( -0.0, 5.0 )\n -0.0\n > v = base.div( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.mul, base.sub\n","base.divf":"\nbase.divf( x, y )\n Divides two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value (dividend).\n\n y: number\n Second input value (divisor).\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.divf( -1.0, 5.0 )\n ~-0.2\n > v = base.divf( 2.0, 5.0 )\n ~0.4\n > v = base.divf( 0.0, 5.0 )\n 0.0\n > v = base.divf( -0.0, 5.0 )\n -0.0\n > v = base.divf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.div, base.mulf, base.subf\n","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a, b] )\n Returns an arcsine distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be less than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n arcsine: Object\n Distribution instance.\n\n arcsine.a: number\n Minimum support. If set, the value must be less than `b`.\n\n arcsine.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n arcsine.entropy: number\n Read-only property which returns the differential entropy.\n\n arcsine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n arcsine.mean: number\n Read-only property which returns the expected value.\n\n arcsine.median: number\n Read-only property which returns the median.\n\n arcsine.mode: number\n Read-only property which returns the mode.\n\n arcsine.skewness: number\n Read-only property which returns the skewness.\n\n arcsine.stdev: number\n Read-only property which returns the standard deviation.\n\n arcsine.variance: number\n Read-only property which returns the variance.\n\n arcsine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n arcsine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n arcsine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n arcsine.pdf: Function\n Evaluates the probability density function (PDF).\n\n arcsine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\n > arcsine.a\n 0.0\n > arcsine.b\n 1.0\n > arcsine.entropy\n ~-0.242\n > arcsine.kurtosis\n -1.5\n > arcsine.mean\n 0.5\n > arcsine.median\n 0.5\n > arcsine.mode\n 0.0\n > arcsine.skewness\n 0.0\n > arcsine.stdev\n ~0.354\n > arcsine.variance\n 0.125\n > arcsine.cdf( 0.8 )\n ~0.705\n > arcsine.logcdf( 0.8 )\n ~-0.35\n > arcsine.logpdf( 0.4 )\n ~-0.431\n > arcsine.pdf( 0.8 )\n ~0.796\n > arcsine.quantile( 0.8 )\n ~0.905\n\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\n ~0.795\n > y = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\n ~0.333\n > y = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705\n\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a, b )\n Returns the differential entropy of an arcsine distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.arcsine.entropy( 0.0, 1.0 )\n ~-0.242\n > v = base.dists.arcsine.entropy( 4.0, 12.0 )\n ~1.838\n > v = base.dists.arcsine.entropy( 2.0, 8.0 )\n ~1.55\n\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a, b )\n Returns the excess kurtosis of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 4.0, 12.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n -1.5\n\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\n ~-0.229\n > y = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\n ~-1.1\n > y = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35\n\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\n ~-1.838\n > y = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\n ~-0.308\n > y = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity\n\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a, b )\n Returns the expected value of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.arcsine.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a, b )\n Returns the median of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.arcsine.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a, b )\n Returns the mode of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.arcsine.mode( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.mode( 4.0, 12.0 )\n 4.0\n > v = base.dists.arcsine.mode( 2.0, 8.0 )\n 2.0\n\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x, a, b )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\n ~0.159\n > y = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\n ~0.735\n > y = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n Infinity\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n Infinity\n > y = myPDF( 5.0 )\n 0.0","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p, a, b )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\n ~0.905\n > y = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\n ~5.0\n\n > y = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n ~3.618\n\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n ~3.618","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a, b )\n Returns the skewness of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.arcsine.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a, b )\n Returns the standard deviation of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.arcsine.stdev( 0.0, 1.0 )\n ~0.354\n > v = base.dists.arcsine.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.arcsine.stdev( 2.0, 8.0 )\n ~2.121\n\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a, b )\n Returns the variance of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.arcsine.variance( 0.0, 1.0 )\n ~0.125\n > v = base.dists.arcsine.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.variance( 2.0, 8.0 )\n ~4.5\n\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p] )\n Returns a Bernoulli distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n bernoulli: Object\n Distribution instance.\n\n bernoulli.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n bernoulli.entropy: number\n Read-only property which returns the differential entropy.\n\n bernoulli.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n bernoulli.mean: number\n Read-only property which returns the expected value.\n\n bernoulli.median: number\n Read-only property which returns the median.\n\n bernoulli.skewness: number\n Read-only property which returns the skewness.\n\n bernoulli.stdev: number\n Read-only property which returns the standard deviation.\n\n bernoulli.variance: number\n Read-only property which returns the variance.\n\n bernoulli.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n bernoulli.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n bernoulli.pmf: Function\n Evaluates the probability mass function (PMF).\n\n bernoulli.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\n > bernoulli.p\n 0.6\n > bernoulli.entropy\n ~0.673\n > bernoulli.kurtosis\n ~-1.833\n > bernoulli.mean\n 0.6\n > bernoulli.median\n 1.0\n > bernoulli.skewness\n ~-0.408\n > bernoulli.stdev\n ~0.49\n > bernoulli.variance\n ~0.24\n > bernoulli.cdf( 0.5 )\n 0.4\n > bernoulli.mgf( 3.0 )\n ~12.451\n > bernoulli.pmf( 0.0 )\n 0.4\n > bernoulli.quantile( 0.7 )\n 1.0\n\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\n 0.5\n > y = base.dists.bernoulli.cdf( 0.8, 0.1 )\n 0.9\n > y = base.dists.bernoulli.cdf( -1.0, 0.4 )\n 0.0\n > y = base.dists.bernoulli.cdf( 1.5, 0.4 )\n 1.0\n > y = base.dists.bernoulli.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.bernoulli.cdf( 0.0, NaN )\n NaN\n // Invalid probability:\n > y = base.dists.bernoulli.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.bernoulli.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 1.0\n > y = mycdf( 0.7 )\n 0.5\n\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 1.0\n > y = mycdf( 0.7 )\n 0.5","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.bernoulli.entropy( 0.1 )\n ~0.325\n > v = base.dists.bernoulli.entropy( 0.5 )\n ~0.693\n\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.bernoulli.kurtosis( 0.1 )\n ~5.111\n > v = base.dists.bernoulli.kurtosis( 0.5 )\n -2.0\n\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mean( 0.1 )\n 0.1\n > v = base.dists.bernoulli.mean( 0.5 )\n 0.5\n\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p )\n Returns the median of a Bernoulli distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.bernoulli.median( 0.1 )\n 0\n > v = base.dists.bernoulli.median( 0.8 )\n 1\n\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\n ~1.111\n > y = base.dists.bernoulli.mgf( 0.4, 0.5 )\n ~1.246\n > y = base.dists.bernoulli.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.bernoulli.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.855\n\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.855","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n\n For `p = 0.5`, the mode is either `0` or `1`. This implementation returns\n `0` for `p = 0.5`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mode( 0.1 )\n 0\n > v = base.dists.bernoulli.mode( 0.8 )\n 1\n\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x, p )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\n 0.3\n > y = base.dists.bernoulli.pmf( 0.0, 0.7 )\n 0.3\n > y = base.dists.bernoulli.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.bernoulli.pmf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.bernoulli.pmf( 0.0, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n > var y = mypmf( 1.0 )\n 0.5\n > y = mypmf( 0.0 )\n 0.5\n\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n > var y = mypmf( 1.0 )\n 0.5\n > y = mypmf( 0.0 )\n 0.5","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r, p )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\n 1\n > y = base.dists.bernoulli.quantile( 0.5, 0.4 )\n 0\n > y = base.dists.bernoulli.quantile( 0.9, 0.1 )\n 0\n\n > y = base.dists.bernoulli.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.bernoulli.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.bernoulli.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.quantile.factory( p )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 1\n > y = myquantile( 1.0 )\n 1\n\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 1\n > y = myquantile( 1.0 )\n 1","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.bernoulli.skewness( 0.1 )\n ~2.667\n > v = base.dists.bernoulli.skewness( 0.5 )\n 0.0\n\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.bernoulli.stdev( 0.1 )\n ~0.3\n > v = base.dists.bernoulli.stdev( 0.5 )\n 0.5\n\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.bernoulli.variance( 0.1 )\n ~0.09\n > v = base.dists.bernoulli.variance( 0.5 )\n 0.25\n\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α, β] )\n Returns a beta distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n beta: Object\n Distribution instance.\n\n beta.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n beta.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n beta.entropy: number\n Read-only property which returns the differential entropy.\n\n beta.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n beta.mean: number\n Read-only property which returns the expected value.\n\n beta.median: number\n Read-only property which returns the median.\n\n beta.mode: number\n Read-only property which returns the mode.\n\n beta.skewness: number\n Read-only property which returns the skewness.\n\n beta.stdev: number\n Read-only property which returns the standard deviation.\n\n beta.variance: number\n Read-only property which returns the variance.\n\n beta.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n beta.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n beta.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n beta.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n beta.pdf: Function\n Evaluates the probability density function (PDF).\n\n beta.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var beta = base.dists.beta.Beta( 1.0, 1.0 );\n > beta.alpha\n 1.0\n > beta.beta\n 1.0\n > beta.entropy\n 0.0\n > beta.kurtosis\n -1.2\n > beta.mean\n 0.5\n > beta.median\n 0.5\n > beta.mode\n NaN\n > beta.skewness\n 0.0\n > beta.stdev\n ~0.289\n > beta.variance\n ~0.0833\n > beta.cdf( 0.8 )\n 0.8\n > beta.logcdf( 0.8 )\n ~-0.223\n > beta.logpdf( 1.0 )\n 0.0\n > beta.mgf( 3.14 )\n ~7.0394\n > beta.pdf( 1.0 )\n 1.0\n > beta.quantile( 0.8 )\n 0.8\n\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\n ~0.813\n > y = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\n ~0.104\n > y = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\n ~0.967\n > y = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.705\n > y = mycdf( 0.3 )\n ~0.369\n\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.705\n > y = mycdf( 0.3 )\n ~0.369","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α, β )\n Returns the differential entropy of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.beta.entropy( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.entropy( 4.0, 12.0 )\n ~-0.869\n > v = base.dists.beta.entropy( 8.0, 2.0 )\n ~-0.795\n\n > v = base.dists.beta.entropy( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.entropy( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.entropy( 2.0, NaN )\n NaN\n > v = base.dists.beta.entropy( NaN, 2.0 )\n NaN\n\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α, β )\n Returns the excess kurtosis of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.beta.kurtosis( 1.0, 1.0 )\n -1.2\n > v = base.dists.beta.kurtosis( 4.0, 12.0 )\n ~0.082\n > v = base.dists.beta.kurtosis( 8.0, 2.0 )\n ~0.490\n\n > v = base.dists.beta.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.kurtosis( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.beta.kurtosis( NaN, 2.0 )\n NaN\n\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\n ~-0.208\n > y = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\n ~-2.263\n > y = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\n ~-0.034\n > y = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.35\n > y = mylogcdf( 0.3 )\n ~-0.997\n\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.35\n > y = mylogcdf( 0.3 )\n ~-0.997","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\n ~0.223\n > y = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\n ~-0.041\n > y = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\n ~-0.556\n > y = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-0.228\n > y = mylogpdf( 0.3 )\n ~-0.364\n\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-0.228\n > y = mylogpdf( 0.3 )\n ~-0.364","base.dists.beta.mean":"\nbase.dists.beta.mean( α, β )\n Returns the expected value of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.beta.mean( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.mean( 4.0, 12.0 )\n 0.25\n > v = base.dists.beta.mean( 8.0, 2.0 )\n 0.8\n\n","base.dists.beta.median":"\nbase.dists.beta.median( α, β )\n Returns the median of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.beta.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.median( 4.0, 12.0 )\n ~0.239\n > v = base.dists.beta.median( 8.0, 2.0 )\n ~0.820\n\n > v = base.dists.beta.median( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.median( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.median( 2.0, NaN )\n NaN\n > v = base.dists.beta.median( NaN, 2.0 )\n NaN\n\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\n ~1.297\n > y = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\n ~1.186\n > y = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\n ~5.575\n > y = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\n ~0.676\n\n > y = base.dists.beta.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n NaN\n\n\nbase.dists.beta.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n > var y = myMGF( 0.8 )\n ~1.552\n > y = myMGF( 0.3 )\n ~1.168\n\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n > var y = myMGF( 0.8 )\n ~1.552\n > y = myMGF( 0.3 )\n ~1.168","base.dists.beta.mode":"\nbase.dists.beta.mode( α, β )\n Returns the mode of a beta distribution.\n\n If `α <= 1` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.beta.mode( 4.0, 12.0 )\n ~0.214\n > v = base.dists.beta.mode( 8.0, 2.0 )\n ~0.875\n > v = base.dists.beta.mode( 1.0, 1.0 )\n NaN\n\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\n 1.25\n > y = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\n ~0.96\n > y = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\n ~0.573\n > y = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.796\n > y = mypdf( 0.3 )\n ~0.695\n\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.796\n > y = mypdf( 0.3 )\n ~0.695","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p, α, β )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\n ~0.894\n > y = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\n ~0.686\n > y = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.beta.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.beta.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n > y = myquantile( 0.8 )\n ~0.713\n > y = myquantile( 0.4 )\n ~0.433\n\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n > y = myquantile( 0.8 )\n ~0.713\n > y = myquantile( 0.4 )\n ~0.433","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α, β )\n Returns the skewness of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.beta.skewness( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.skewness( 4.0, 12.0 )\n ~0.529\n > v = base.dists.beta.skewness( 8.0, 2.0 )\n ~-0.829\n\n > v = base.dists.beta.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.skewness( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.skewness( 2.0, NaN )\n NaN\n > v = base.dists.beta.skewness( NaN, 2.0 )\n NaN\n\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α, β )\n Returns the standard deviation of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.beta.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.beta.stdev( 4.0, 12.0 )\n ~0.105\n > v = base.dists.beta.stdev( 8.0, 2.0 )\n ~0.121\n\n > v = base.dists.beta.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.stdev( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.stdev( 2.0, NaN )\n NaN\n > v = base.dists.beta.stdev( NaN, 2.0 )\n NaN\n\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α, β )\n Returns the variance of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.beta.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.beta.variance( 4.0, 12.0 )\n ~0.011\n > v = base.dists.beta.variance( 8.0, 2.0 )\n ~0.015\n\n > v = base.dists.beta.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.variance( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.variance( 2.0, NaN )\n NaN\n > v = base.dists.beta.variance( NaN, 2.0 )\n NaN\n\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α, β] )\n Returns a beta prime distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n betaprime: Object\n Distribution instance.\n\n betaprime.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n betaprime.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n betaprime.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n betaprime.mean: number\n Read-only property which returns the expected value.\n\n betaprime.mode: number\n Read-only property which returns the mode.\n\n betaprime.skewness: number\n Read-only property which returns the skewness.\n\n betaprime.stdev: number\n Read-only property which returns the standard deviation.\n\n betaprime.variance: number\n Read-only property which returns the variance.\n\n betaprime.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n betaprime.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n betaprime.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n betaprime.pdf: Function\n Evaluates the probability density function (PDF).\n\n betaprime.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\n > betaprime.alpha\n 6.0\n > betaprime.beta\n 5.0\n > betaprime.kurtosis\n 44.4\n > betaprime.mean\n 1.5\n > betaprime.mode\n ~0.833\n > betaprime.skewness\n ~3.578\n > betaprime.stdev\n ~1.118\n > betaprime.variance\n 1.25\n > betaprime.cdf( 0.8 )\n ~0.25\n > betaprime.logcdf( 0.8 )\n ~-1.387\n > betaprime.logpdf( 1.0 )\n ~-0.486\n > betaprime.pdf( 1.0 )\n ~0.615\n > betaprime.quantile( 0.8 )\n ~2.06\n\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\n ~0.333\n > y = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\n ~0.539\n > y = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\n ~0.074\n > y = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\n ~0.38\n > y = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.465\n > y = mycdf( 0.3 )\n ~0.319\n\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.465\n > y = mycdf( 0.3 )\n ~0.319","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α, β )\n Returns the excess kurtosis of a beta prime distribution.\n\n If `α <= 0` or `β <= 4`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\n ~26.143\n > v = base.dists.betaprime.kurtosis( 4.0, 12.0 )\n ~5.764\n > v = base.dists.betaprime.kurtosis( 8.0, 6.0 )\n ~19.962\n\n > v = base.dists.betaprime.kurtosis( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.kurtosis( -0.1, 5.0 )\n NaN\n\n > v = base.dists.betaprime.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.kurtosis( NaN, 6.0 )\n NaN\n\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\n ~-1.099\n > y = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\n ~-0.618\n > y = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\n ~-2.603\n > y = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\n ~-0.968\n > y = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.767\n > y = mylogcdf( 0.3 )\n ~-1.143\n\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.767\n > y = mylogcdf( 0.3 )\n ~-1.143","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\n ~-0.811\n > y = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\n ~-0.13\n > y = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\n ~-0.547\n > y = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\n ~-0.43\n > y = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-1.62\n > y = mylogpdf( 0.3 )\n ~-0.805\n\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-1.62\n > y = mylogpdf( 0.3 )\n ~-0.805","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α, β )\n Returns the expected value of a beta prime distribution.\n\n If `α <= 0` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.betaprime.mean( 1.0, 2.0 )\n 1.0\n > v = base.dists.betaprime.mean( 4.0, 12.0 )\n ~0.364\n > v = base.dists.betaprime.mean( 8.0, 2.0 )\n 8.0\n\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α, β )\n Returns the mode of a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.betaprime.mode( 1.0, 2.0 )\n 0.0\n > v = base.dists.betaprime.mode( 4.0, 12.0 )\n ~0.231\n > v = base.dists.betaprime.mode( 8.0, 2.0 )\n ~2.333\n\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\n ~0.444\n > y = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\n ~0.878\n > y = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\n ~0.579\n > y = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\n ~0.65\n > y = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.198\n > y = mypdf( 0.3 )\n ~0.447\n\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.198\n > y = mypdf( 0.3 )\n ~0.447","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p, α, β )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\n ~8.472\n > y = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\n ~2.187\n > y = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.betaprime.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n > y = myQuantile( 0.8 )\n ~2.483\n > y = myQuantile( 0.4 )\n ~0.763\n\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n > y = myQuantile( 0.8 )\n ~2.483\n > y = myQuantile( 0.4 )\n ~0.763","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α, β )\n Returns the skewness of a beta prime distribution.\n\n If `α <= 0` or `β <= 3`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.betaprime.skewness( 2.0, 4.0 )\n ~6.261\n > v = base.dists.betaprime.skewness( 4.0, 12.0 )\n ~1.724\n > v = base.dists.betaprime.skewness( 8.0, 4.0 )\n ~5.729\n\n > v = base.dists.betaprime.skewness( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.skewness( -0.1, 4.0 )\n NaN\n\n > v = base.dists.betaprime.skewness( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.skewness( NaN, 4.0 )\n NaN\n\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α, β )\n Returns the standard deviation of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.betaprime.stdev( 1.0, 2.5 )\n ~1.491\n > v = base.dists.betaprime.stdev( 4.0, 12.0 )\n ~0.223\n > v = base.dists.betaprime.stdev( 8.0, 2.5 )\n ~8.219\n\n > v = base.dists.betaprime.stdev( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.stdev( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.stdev( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.stdev( NaN, 3.0 )\n NaN\n\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α, β )\n Returns the variance of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.betaprime.variance( 1.0, 2.5 )\n ~2.222\n > v = base.dists.betaprime.variance( 4.0, 12.0 )\n ~0.05\n > v = base.dists.betaprime.variance( 8.0, 2.5 )\n ~67.556\n\n > v = base.dists.betaprime.variance( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.variance( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.variance( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.variance( NaN, 3.0 )\n NaN\n\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n, p] )\n Returns a binomial distribution object.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials. Must be a positive integer. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n binomial: Object\n Distribution instance.\n\n binomial.n: number\n Number of trials. If set, the value must be a positive integer.\n\n binomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n binomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n binomial.mean: number\n Read-only property which returns the expected value.\n\n binomial.median: number\n Read-only property which returns the median.\n\n binomial.mode: number\n Read-only property which returns the mode.\n\n binomial.skewness: number\n Read-only property which returns the skewness.\n\n binomial.stdev: number\n Read-only property which returns the standard deviation.\n\n binomial.variance: number\n Read-only property which returns the variance.\n\n binomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n binomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n binomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n binomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n binomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var binomial = base.dists.binomial.Binomial( 8, 0.5 );\n > binomial.n\n 8.0\n > binomial.p\n 0.5\n > binomial.kurtosis\n -0.25\n > binomial.mean\n 4.0\n > binomial.median\n 4.0\n > binomial.mode\n 4.0\n > binomial.skewness\n 0.0\n > binomial.stdev\n ~1.414\n > binomial.variance\n 2.0\n > binomial.cdf( 2.9 )\n ~0.145\n > binomial.logpmf( 3.0 )\n ~-1.52\n > binomial.mgf( 0.2 )\n ~2.316\n > binomial.pmf( 3.0 )\n ~0.219\n > binomial.quantile( 0.8 )\n 5.0\n\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x, n, p )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\n ~0.411\n > y = base.dists.binomial.cdf( 21.0, 20, 0.2 )\n 1.0\n > y = base.dists.binomial.cdf( 5.0, 10, 0.4 )\n ~0.834\n > y = base.dists.binomial.cdf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.cdf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.cdf.factory( n, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n > var y = mycdf( 3.0 )\n ~0.172\n > y = mycdf( 1.0 )\n ~0.011\n\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n > var y = mycdf( 3.0 )\n ~0.172\n > y = mycdf( 1.0 )\n ~0.011","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n, p )\n Returns the entropy of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.binomial.entropy( 100, 0.1 )\n ~2.511\n > v = base.dists.binomial.entropy( 20, 0.5 )\n ~2.223\n > v = base.dists.binomial.entropy( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.entropy( 20, 1.1 )\n NaN\n > v = base.dists.binomial.entropy( 20, NaN )\n NaN\n\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n, p )\n Returns the excess kurtosis of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.binomial.kurtosis( 100, 0.1 )\n ~0.051\n > v = base.dists.binomial.kurtosis( 20, 0.5 )\n ~-0.1\n > v = base.dists.binomial.kurtosis( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, 1.1 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, NaN )\n NaN\n\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x, n, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\n ~-1.583\n > y = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\n -Infinity\n > y = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\n ~-1.606\n > y = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\n ~-5.108\n > y = base.dists.binomial.logpmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.logpmf.factory( n, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.144\n > y = mylogpmf( 5.0 )\n ~-1.402\n\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.144\n > y = mylogpmf( 5.0 )\n ~-1.402","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n, p )\n Returns the expected value of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.binomial.mean( 100, 0.1 )\n 10.0\n > v = base.dists.binomial.mean( 20, 0.5 )\n 10.0\n > v = base.dists.binomial.mean( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mean( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mean( 20, NaN )\n NaN\n\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n, p )\n Returns the median of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.binomial.median( 100, 0.1 )\n 10\n > v = base.dists.binomial.median( 20, 0.5 )\n 10\n > v = base.dists.binomial.median( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.median( 20, 1.1 )\n NaN\n > v = base.dists.binomial.median( 20, NaN )\n NaN\n\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t, n, p )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\n ~11.471\n > y = base.dists.binomial.mgf( 5.0, 20, 0.2 )\n ~4.798e+29\n > y = base.dists.binomial.mgf( 0.9, 10, 0.4 )\n ~99.338\n > y = base.dists.binomial.mgf( 0.0, 10, 0.4 )\n 1.0\n\n > y = base.dists.binomial.mgf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, 20, NaN )\n NaN\n\n > y = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.mgf.factory( n, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n > var y = myMGF( 0.3 )\n ~5.013\n\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n > var y = myMGF( 0.3 )\n ~5.013","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n, p )\n Returns the mode of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.binomial.mode( 100, 0.1 )\n 10\n > v = base.dists.binomial.mode( 20, 0.5 )\n 10\n > v = base.dists.binomial.mode( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mode( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mode( 20, NaN )\n NaN\n\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x, n, p )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\n ~0.205\n > y = base.dists.binomial.pmf( 21.0, 20, 0.2 )\n 0.0\n > y = base.dists.binomial.pmf( 5.0, 10, 0.4 )\n ~0.201\n > y = base.dists.binomial.pmf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.pmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.pmf.factory( n, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n > var y = mypmf( 3.0 )\n ~0.117\n > y = mypmf( 5.0 )\n ~0.246\n\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n > var y = mypmf( 3.0 )\n ~0.117\n > y = mypmf( 5.0 )\n ~0.246","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r, n, p )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\n 3\n > y = base.dists.binomial.quantile( 0.8, 20, 0.2 )\n 5\n > y = base.dists.binomial.quantile( 0.5, 10, 0.4 )\n 4\n > y = base.dists.binomial.quantile( 0.0, 10, 0.4 )\n 0\n > y = base.dists.binomial.quantile( 1.0, 10, 0.4 )\n 10\n\n > y = base.dists.binomial.quantile( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, 20, NaN )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 20, -1.0 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.quantile.factory( n, p )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n > var y = myquantile( 0.1 )\n 3\n > y = myquantile( 0.9 )\n 7\n\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n, p )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n > var y = myquantile( 0.1 )\n 3\n > y = myquantile( 0.9 )\n 7","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n, p )\n Returns the skewness of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.binomial.skewness( 100, 0.1 )\n ~0.267\n > v = base.dists.binomial.skewness( 20, 0.5 )\n 0.0\n > v = base.dists.binomial.skewness( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.skewness( 20, 1.1 )\n NaN\n > v = base.dists.binomial.skewness( 20, NaN )\n NaN\n\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n, p )\n Returns the standard deviation of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.binomial.stdev( 100, 0.1 )\n 3.0\n > v = base.dists.binomial.stdev( 20, 0.5 )\n ~2.236\n > v = base.dists.binomial.stdev( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.stdev( 20, 1.1 )\n NaN\n > v = base.dists.binomial.stdev( 20, NaN )\n NaN\n\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n, p )\n Returns the variance of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.binomial.variance( 100, 0.1 )\n 9\n > v = base.dists.binomial.variance( 20, 0.5 )\n 5\n > v = base.dists.binomial.variance( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.variance( 20, 1.1 )\n NaN\n > v = base.dists.binomial.variance( 20, NaN )\n NaN\n\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0, Ɣ] )\n Returns a Cauchy distribution object.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter. Default: `0.0`.\n\n Ɣ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cauchy: Object\n Distribution instance.\n\n cauchy.x0: number\n Location parameter.\n\n cauchy.gamma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cauchy.entropy: number\n Read-only property which returns the differential entropy.\n\n cauchy.median: number\n Read-only property which returns the median.\n\n cauchy.mode: number\n Read-only property which returns the mode.\n\n cauchy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cauchy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cauchy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cauchy.pdf: Function\n Evaluates the probability density function (PDF).\n\n cauchy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\n > cauchy.x0\n 0.0\n > cauchy.gamma\n 1.0\n > cauchy.entropy\n ~2.531\n > cauchy.median\n 0.0\n > cauchy.mode\n 0.0\n > cauchy.cdf( 0.8 )\n ~0.715\n > cauchy.logcdf( 1.0 )\n ~-0.288\n > cauchy.logpdf( 1.0 )\n ~-1.838\n > cauchy.pdf( 1.0 )\n ~0.159\n > cauchy.quantile( 0.8 )\n ~1.376\n\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x, x0, Ɣ )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\n ~0.852\n > y = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\n ~0.648\n > y = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\n 0.25\n > y = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n > var y = myCDF( 1.0 )\n ~0.447\n\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n > var y = myCDF( 1.0 )\n ~0.447","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0, Ɣ )\n Returns the differential entropy of a Cauchy distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.cauchy.entropy( 10.0, 7.0 )\n ~4.477\n > v = base.dists.cauchy.entropy( 22.0, 0.5 )\n ~1.838\n > v = base.dists.cauchy.entropy( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\n ~-0.16\n > y = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\n ~-0.435\n > y = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\n ~-1.386\n > y = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of CDF.\n\n Examples\n --------\n > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n > var y = mylogCDF( 1.0 )\n ~-0.804\n\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of CDF.\n\n Examples\n --------\n > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n > var y = mylogCDF( 1.0 )\n ~-0.804","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\n ~-1.838\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\n ~-3.457\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\n ~-2.349\n > y = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.838\n\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.838","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0, Ɣ )\n Returns the median of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.cauchy.median( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.median( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.median( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0, Ɣ )\n Returns the mode of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.cauchy.mode( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.mode( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.mode( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x, x0, Ɣ )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\n ~0.159\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\n ~0.0315\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\n ~0.095\n > y = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.159\n\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.159","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p, x0, Ɣ )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\n ~0.547\n > y = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\n ~12.753\n > y = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\n ~3.845\n\n > y = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chi.cdf( 2.0, 3.0 )\n ~0.739\n > y = base.dists.chi.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chi.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chi.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chi.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chi.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chi.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chi.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.954\n > y = mycdf( 1.2 )\n ~0.77\n\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.954\n > y = mycdf( 1.2 )\n ~0.77","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k] )\n Returns a chi distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chi: Object\n Distribution instance.\n\n chi.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chi.entropy: number\n Read-only property which returns the differential entropy.\n\n chi.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chi.mean: number\n Read-only property which returns the expected value.\n\n chi.mode: number\n Read-only property which returns the mode.\n\n chi.skewness: number\n Read-only property which returns the skewness.\n\n chi.stdev: number\n Read-only property which returns the standard deviation.\n\n chi.variance: number\n Read-only property which returns the variance.\n\n chi.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chi.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n chi.pdf: Function\n Evaluates the probability density function (PDF).\n\n chi.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chi = base.dists.chi.Chi( 6.0 );\n > chi.k\n 6.0\n > chi.entropy\n ~1.04\n > chi.kurtosis\n ~0.025\n > chi.mean\n ~2.35\n > chi.mode\n ~2.236\n > chi.skewness\n ~0.318\n > chi.stdev\n ~0.691\n > chi.variance\n ~0.478\n > chi.cdf( 1.0 )\n ~0.014\n > chi.logpdf( 1.5 )\n ~-1.177\n > chi.pdf( 1.5 )\n ~0.308\n > chi.quantile( 0.5 )\n ~2.313\n\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k )\n Returns the differential entropy of a chi distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chi.entropy( 11.0 )\n ~1.056\n > v = base.dists.chi.entropy( 1.5 )\n ~0.878\n\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k )\n Returns the excess kurtosis of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chi.kurtosis( 9.0 )\n ~0.011\n > v = base.dists.chi.kurtosis( 1.5 )\n ~0.424\n\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chi.logpdf( 0.3, 4.0 )\n ~-4.35\n > y = base.dists.chi.logpdf( 0.7, 0.7 )\n ~-0.622\n > y = base.dists.chi.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n > var y = mylogPDF( 3.0 )\n ~-1.086\n\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n > var y = mylogPDF( 3.0 )\n ~-1.086","base.dists.chi.mean":"\nbase.dists.chi.mean( k )\n Returns the expected value of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chi.mean( 11.0 )\n ~3.242\n > v = base.dists.chi.mean( 4.5 )\n ~2.008\n\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k )\n Returns the mode of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chi.mode( 11.0 )\n ~3.162\n > v = base.dists.chi.mode( 1.5 )\n ~0.707\n\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chi.pdf( 0.3, 4.0 )\n ~0.013\n > y = base.dists.chi.pdf( 0.7, 0.7 )\n ~0.537\n > y = base.dists.chi.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.337\n\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.337","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p, k )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chi.quantile( 0.8, 1.0 )\n ~1.282\n > y = base.dists.chi.quantile( 0.5, 4.0 )\n ~1.832\n > y = base.dists.chi.quantile( 0.8, 0.1 )\n ~0.116\n > y = base.dists.chi.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chi.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chi.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chi.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chi.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chi.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.845\n > y = myquantile( 0.7 )\n ~1.552\n\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.845\n > y = myquantile( 0.7 )\n ~1.552","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k )\n Returns the skewness of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chi.skewness( 11.0 )\n ~0.225\n > v = base.dists.chi.skewness( 1.5 )\n ~0.763\n\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k )\n Returns the standard deviation of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chi.stdev( 11.0 )\n ~0.699\n > v = base.dists.chi.stdev( 1.5 )\n ~0.637\n\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k )\n Returns the variance of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chi.variance( 11.0 )\n ~0.488\n > v = base.dists.chi.variance( 1.5 )\n ~0.406\n\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.cdf( 2.0, 3.0 )\n ~0.428\n > y = base.dists.chisquare.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chisquare.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chisquare.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chisquare.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chisquare.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chisquare.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.843\n > y = mycdf( 1.2 )\n ~0.727\n\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.843\n > y = mycdf( 1.2 )\n ~0.727","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k] )\n Returns a chi-squared distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chisquare: Object\n Distribution instance.\n\n chisquare.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chisquare.entropy: number\n Read-only property which returns the differential entropy.\n\n chisquare.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chisquare.mean: number\n Read-only property which returns the expected value.\n\n chisquare.median: number\n Read-only property which returns the median.\n\n chisquare.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n chisquare.mode: number\n Read-only property which returns the mode.\n\n chisquare.skewness: number\n Read-only property which returns the skewness.\n\n chisquare.stdev: number\n Read-only property which returns the standard deviation.\n\n chisquare.variance: number\n Read-only property which returns the variance.\n\n chisquare.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chisquare.pdf: Function\n Evaluates the probability density function (PDF).\n\n chisquare.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\n > chisquare.k\n 6.0\n > chisquare.entropy\n ~2.541\n > chisquare.kurtosis\n 2.0\n > chisquare.mean\n 6.0\n > chisquare.median\n ~5.348\n > chisquare.mode\n 4.0\n > chisquare.skewness\n ~1.155\n > chisquare.stdev\n ~3.464\n > chisquare.variance\n 12.0\n > chisquare.cdf( 3.0 )\n ~0.191\n > chisquare.mgf( 0.2 )\n ~4.63\n > chisquare.pdf( 1.5 )\n ~0.066\n > chisquare.quantile( 0.5 )\n ~5.348\n\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k )\n Returns the differential entropy of a chi-squared distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chisquare.entropy( 11.0 )\n ~2.901\n > v = base.dists.chisquare.entropy( 1.5 )\n ~1.375\n\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k )\n Returns the excess kurtosis of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chisquare.kurtosis( 9.0 )\n ~1.333\n > v = base.dists.chisquare.kurtosis( 1.5 )\n 8.0\n\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\n ~-2.74\n > y = base.dists.chisquare.logpdf( 0.7, 0.7 )\n ~-1.295\n > y = base.dists.chisquare.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n > var y = myLogPDF( 3.0 )\n ~-2.075\n\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n > var y = myLogPDF( 3.0 )\n ~-2.075","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k )\n Returns the expected value of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chisquare.mean( 11.0 )\n 11.0\n > v = base.dists.chisquare.mean( 4.5 )\n 4.5\n\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k )\n Returns the median of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var k = base.dists.chisquare.median( 9.0 )\n ~8.343\n > k = base.dists.chisquare.median( 2.0 )\n ~1.386\n\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t, k )\n Evaluates the moment-generating function (MGF) for a chi-squared\n distribution with degrees of freedom `k` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.chisquare.mgf( 0.4, 2 )\n ~5.0\n > y = base.dists.chisquare.mgf( -1.0, 5.0 )\n ~0.0642\n > y = base.dists.chisquare.mgf( 0.0, 10.0 )\n 1.0\n\n\nbase.dists.chisquare.mgf.factory( k )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n > var y = mymgf( 0.2 )\n ~1.291\n > y = mymgf( 0.4 )\n ~2.236\n\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n > var y = mymgf( 0.2 )\n ~1.291\n > y = mymgf( 0.4 )\n ~2.236","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k )\n Returns the mode of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chisquare.mode( 11.0 )\n 9.0\n > v = base.dists.chisquare.mode( 1.5 )\n 0.0\n\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.pdf( 0.3, 4.0 )\n ~0.065\n > y = base.dists.chisquare.pdf( 0.7, 0.7 )\n ~0.274\n > y = base.dists.chisquare.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.126\n\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.126","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p, k )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chisquare.quantile( 0.8, 1.0 )\n ~1.642\n > y = base.dists.chisquare.quantile( 0.5, 4.0 )\n ~3.357\n > y = base.dists.chisquare.quantile( 0.8, 0.1 )\n ~0.014\n > y = base.dists.chisquare.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chisquare.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chisquare.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.713\n > y = myquantile( 0.7 )\n ~2.408\n\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.713\n > y = myquantile( 0.7 )\n ~2.408","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k )\n Returns the skewness of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chisquare.skewness( 11.0 )\n ~0.853\n > v = base.dists.chisquare.skewness( 1.5 )\n ~2.309\n\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k )\n Returns the standard deviation of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chisquare.stdev( 11.0 )\n ~4.69\n > v = base.dists.chisquare.stdev( 1.5 )\n ~1.732\n\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k )\n Returns the variance of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chisquare.variance( 11.0 )\n 22.0\n > v = base.dists.chisquare.variance( 1.5 )\n 3.0\n\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\n ~0.971\n > y = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\n ~0.196\n\n > y = base.dists.cosine.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.cosine.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.9 )\n ~0.015\n\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.9 )\n ~0.015","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ, s] )\n Returns a raised cosine distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cosine: Object\n Distribution instance.\n\n cosine.mu: number\n Location parameter.\n\n cosine.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cosine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n cosine.mean: number\n Read-only property which returns the expected value.\n\n cosine.median: number\n Read-only property which returns the median.\n\n cosine.mode: number\n Read-only property which returns the mode.\n\n cosine.skewness: number\n Read-only property which returns the skewness.\n\n cosine.stdev: number\n Read-only property which returns the standard deviation.\n\n cosine.variance: number\n Read-only property which returns the variance.\n\n cosine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cosine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cosine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cosine.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n cosine.pdf: Function\n Evaluates the probability density function (PDF).\n\n cosine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\n > cosine.mu\n -2.0\n > cosine.s\n 3.0\n > cosine.kurtosis\n ~-0.594\n > cosine.mean\n -2.0\n > cosine.median\n -2.0\n > cosine.mode\n -2.0\n > cosine.skewness\n 0.0\n > cosine.stdev\n ~1.085\n > cosine.variance\n ~1.176\n > cosine.cdf( 0.5 )\n ~0.996\n > cosine.logcdf( 0.5 )\n ~-0.004\n > cosine.logpdf( -1.0 )\n ~-1.386\n > cosine.mgf( 0.2 )\n ~0.686\n > cosine.pdf( -2.0 )\n ~0.333\n > cosine.quantile( 0.9 )\n ~-0.553\n\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ, s )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( 4.0, 2.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x, μ, s )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\n ~-0.029\n > y = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\n ~-1.632\n\n > y = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n 0.0\n\n\nbase.dists.cosine.logcdf.factory( μ, s )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.9 )\n ~-4.2\n\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ, s )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.9 )\n ~-4.2","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\n ~-2.485\n > y = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\n ~-3.307\n > y = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-0.693\n\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-0.693","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ, s )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.cosine.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mean( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mean( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ, s )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.cosine.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.median( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.median( 0.0, NaN )\n NaN\n > y = base.dists.cosine.median( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\n ~7.234\n > y = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\n ~1.606e+47\n\n > y = base.dists.cosine.mgf( 0.5, 0.0, NaN )\n NaN\n > y = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.cosine.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n > var y = mymgf( 1.9 )\n ~495.57\n\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n > var y = mymgf( 1.9 )\n ~495.57","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ, s )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.cosine.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mode( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mode( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\n ~0.083\n > y = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\n ~0.048\n > y = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n > var y = myPDF( 2.0 )\n ~0.083\n\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n > var y = myPDF( 2.0 )\n ~0.083","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p, μ, s )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\n ~0.327\n > y = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\n ~4.0\n\n > y = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cosine.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.3 )\n ~9.586\n\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.3 )\n ~9.586","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ, s )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.cosine.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.cosine.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.skewness( 0.0, NaN )\n NaN\n > y = base.dists.cosine.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ, s )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.cosine.stdev( 0.0, 1.0 )\n ~0.362\n > y = base.dists.cosine.stdev( 4.0, 2.0 )\n ~0.723\n > y = base.dists.cosine.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.stdev( 0.0, NaN )\n NaN\n > y = base.dists.cosine.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ, s )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.cosine.variance( 0.0, 1.0 )\n ~0.131\n > y = base.dists.cosine.variance( 4.0, 2.0 )\n ~0.523\n > y = base.dists.cosine.variance( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.variance( 0.0, NaN )\n NaN\n > y = base.dists.cosine.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x, μ )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.cdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.cdf( 4.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.cdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.cdf.factory( μ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n > var y = myCDF( 3.0 )\n 0.0\n > y = myCDF( 6.0 )\n 1.0\n\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n > var y = myCDF( 3.0 )\n 0.0\n > y = myCDF( 6.0 )\n 1.0","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ] )\n Returns a degenerate distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Constant value of distribution.\n\n Returns\n -------\n degenerate: Object\n Distribution instance.\n\n degenerate.mu: number\n Constant value of distribution.\n\n degenerate.entropy: number\n Read-only property which returns the differential entropy.\n\n degenerate.mean: number\n Read-only property which returns the expected value.\n\n degenerate.median: number\n Read-only property which returns the median.\n\n degenerate.stdev: number\n Read-only property which returns the standard deviation.\n\n degenerate.variance: number\n Read-only property which returns the variance.\n\n degenerate.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n degenerate.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n degenerate.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n degenerate.logpmf: Function\n Evaluates the natural logarithm of the probability mass function\n (PMF).\n\n degenerate.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n degenerate.pmf: Function\n Evaluates the probability mass function (PMF).\n\n degenerate.pdf: Function\n Evaluates the probability density function (PDF).\n\n degenerate.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var degenerate = base.dists.degenerate.Degenerate( 2.0 );\n > degenerate.mu\n 2.0\n > degenerate.entropy\n 0.0\n > degenerate.mean\n 2.0\n > degenerate.mode\n 2.0\n > degenerate.median\n 2.0\n > degenerate.stdev\n 0.0\n > degenerate.variance\n 0.0\n > degenerate.cdf( 0.5 )\n 0.0\n > degenerate.logcdf( 2.5 )\n 0.0\n > degenerate.logpdf( 0.5 )\n -Infinity\n > degenerate.logpmf( 2.5 )\n -Infinity\n > degenerate.mgf( 0.2 )\n ~1.492\n > degenerate.pdf( 2.0 )\n +Infinity\n > degenerate.pmf( 2.0 )\n 1.0\n > degenerate.quantile( 0.7 )\n 2.0\n\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.degenerate.entropy( 20.0 )\n 0.0\n > v = base.dists.degenerate.entropy( -10.0 )\n 0.0\n\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x, μ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logcdf( 4.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( 3.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logcdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logcdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of cumulative distribution\n function (logCDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n > var y = mylogcdf( 3.0 )\n -Infinity\n > y = mylogcdf( 6.0 )\n 0\n\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of cumulative distribution\n function (logCDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n > var y = mylogcdf( 3.0 )\n -Infinity\n > y = mylogcdf( 6.0 )\n 0","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x, μ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.logpdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n > var y = mylogPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n > var y = mylogPDF( 10.0 )\n Infinity","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x, μ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpmf( 3.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.logpmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpmf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n > var y = mylogPMF( 10.0 )\n 0.0\n\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n > var y = mylogPMF( 10.0 )\n 0.0","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.degenerate.mean( 20.0 )\n 20.0\n > v = base.dists.degenerate.mean( -10.0 )\n -10.0\n\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ )\n Returns the median of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.degenerate.median( 20.0 )\n 20.0\n > v = base.dists.degenerate.median( -10.0 )\n -10.0\n\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x, μ )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.degenerate.mgf( 1.0, 1.0 )\n ~2.718\n > y = base.dists.degenerate.mgf( 2.0, 3.0 )\n ~403.429\n > y = base.dists.degenerate.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.mgf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.mgf.factory( μ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n > var y = myMGF( 0.1 )\n ~2.718\n\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n > var y = myMGF( 0.1 )\n ~2.718","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ )\n Returns the mode of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.degenerate.mode( 20.0 )\n 20.0\n > v = base.dists.degenerate.mode( -10.0 )\n -10.0\n\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x, μ )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.pdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pdf.factory( μ )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n > var y = myPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n > var y = myPDF( 10.0 )\n Infinity","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x, μ )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pmf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pmf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.pmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pmf.factory( μ )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n > var y = myPMF( 10.0 )\n 1.0\n\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n > var y = myPMF( 10.0 )\n 1.0","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p, μ )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.degenerate.quantile( 0.5, 2.0 )\n 2.0\n > y = base.dists.degenerate.quantile( 0.9, 4.0 )\n 4.0\n > y = base.dists.degenerate.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( -0.2, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.degenerate.stdev( 20.0 )\n 0.0\n > v = base.dists.degenerate.stdev( -10.0 )\n 0.0\n\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ )\n Returns the variance of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.degenerate.variance( 20.0 )\n 0.0\n > v = base.dists.degenerate.variance( -10.0 )\n 0.0\n\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\n ~0.909\n > y = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\n ~0.333\n > y = base.dists.discreteUniform.cdf( PINF, 2, 4 )\n 1.0\n > y = base.dists.discreteUniform.cdf( NINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.cdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818\n\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a, b] )\n Returns a discrete uniform distribution object.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support. Must be an integer smaller than `b`. Default: `0`.\n\n b: integer (optional)\n Maximum support. Must be an integer greater than `a`. Default: `1`.\n\n Returns\n -------\n discreteUniform: Object\n Distribution instance.\n\n discreteUniform.a: integer\n Minimum support. If set, the value must be an integer smaller than or\n equal to `b`.\n\n discreteUniform.b: integer\n Maximum support. If set, the value must be an integer greater than or\n equal to `a`.\n\n discreteUniform.entropy: number\n Read-only property which returns the entropy.\n\n discreteUniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n discreteUniform.mean: number\n Read-only property which returns the expected value.\n\n discreteUniform.median: number\n Read-only property which returns the median.\n\n discreteUniform.skewness: number\n Read-only property which returns the skewness.\n\n discreteUniform.stdev: number\n Read-only property which returns the standard deviation.\n\n discreteUniform.variance: number\n Read-only property which returns the variance.\n\n discreteUniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n discreteUniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n discreteUniform.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n discreteUniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n discreteUniform.pmf: Function\n Evaluates the probability mass function (PMF).\n\n discreteUniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\n > discreteUniform.a\n -2\n > discreteUniform.b\n 2\n > discreteUniform.entropy\n ~1.609\n > discreteUniform.kurtosis\n -1.3\n > discreteUniform.mean\n 0.0\n > discreteUniform.median\n 0.0\n > discreteUniform.skewness\n 0.0\n > discreteUniform.stdev\n ~1.414\n > discreteUniform.variance\n 2.0\n > discreteUniform.cdf( 0.8 )\n 0.6\n > discreteUniform.logcdf( 0.5 )\n ~-0.511\n > discreteUniform.logpmf( 1.0 )\n ~-1.609\n > discreteUniform.mgf( 0.8 )\n ~1.766\n > discreteUniform.pmf( 0.0 )\n 0.2\n > discreteUniform.quantile( 0.8 )\n 2.0\n\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a, b )\n Returns the excess kurtosis of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.kurtosis( 0, 1 )\n -2.0\n > v = base.dists.discreteUniform.kurtosis( 4, 12 )\n ~-1.23\n > v = base.dists.discreteUniform.kurtosis( -4, 8 )\n ~-1.214\n\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\n ~-0.095\n > y = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\n ~-1.099\n > y = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201\n\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x, a, b )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\n ~-1.609\n > y = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\n ~-2.197\n > y = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity\n\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a, b )\n Returns the expected value of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.mean( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.mean( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.mean( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a, b )\n Returns the median of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.median( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.median( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.median( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\n ~689.475\n > y = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\n ~0.697\n > y = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\n ~4.195\n > y = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\n NaN\n > y = base.dists.discreteUniform.mgf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n NaN\n\n\nbase.dists.discreteUniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n > var y = mymgf( 0.1 )\n ~1.918\n > y = mymgf( 1.1 )\n ~1471.722\n\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n > var y = mymgf( 0.1 )\n ~1.918\n > y = mymgf( 1.1 )\n ~1471.722","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x, a, b )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\n ~0.2\n > y = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\n 0.0\n > y = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\n ~0.111\n > y = base.dists.discreteUniform.pmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.pmf.factory( a, b )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n > var y = myPMF( 7.0 )\n 0.5\n > y = myPMF( 5.0 )\n 0.0\n\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a, b )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n > var y = myPMF( 7.0 )\n 0.5\n > y = myPMF( 5.0 )\n 0.0","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p, a, b )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n If provided `a > b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\n 1\n > y = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\n 5\n\n > y = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\n NaN\n > y = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\n NaN\n\n > y = base.dists.discreteUniform.quantile( NaN, -2, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\n NaN\n\n > y = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n NaN\n\n\nbase.dists.discreteUniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n > var y = myQuantile( 0.8 )\n 4\n\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n > var y = myQuantile( 0.8 )\n 4","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a, b )\n Returns the skewness of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.skewness( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 4, 12 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 2, 8 )\n 0.0\n\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a, b )\n Returns the standard deviation of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.stdev( 0, 1 )\n ~0.5\n > v = base.dists.discreteUniform.stdev( 4, 12 )\n ~2.582\n > v = base.dists.discreteUniform.stdev( 2, 8 )\n 2.0\n\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a, b )\n Returns the variance of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.variance( 0, 1 )\n ~0.25\n > v = base.dists.discreteUniform.variance( 4, 12 )\n ~6.667\n > v = base.dists.discreteUniform.variance( 2, 8 )\n 4.0\n\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\n ~0.865\n > y = base.dists.erlang.cdf( 2.0, 3, 1.0 )\n ~0.323\n > y = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( -1.0, 2, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( PINF, 4, 2.0 )\n 1.0\n > y = base.dists.erlang.cdf( NINF, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( NaN, 0, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.erlang.cdf( 2.0, -1, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264\n\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k, λ )\n Returns the differential entropy of an Erlang distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.erlang.entropy( 1, 1.0 )\n ~1.0\n > v = base.dists.erlang.entropy( 4, 12.0 )\n ~-0.462\n > v = base.dists.erlang.entropy( 8, 2.0 )\n ~1.723\n\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k, λ] )\n Returns an Erlang distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be a positive integer. Default: `1.0`.\n\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n erlang: Object\n Distribution instance.\n\n erlang.k: number\n Shape parameter. If set, the value must be a positive integer.\n\n erlang.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n erlang.entropy: number\n Read-only property which returns the differential entropy.\n\n erlang.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n erlang.mean: number\n Read-only property which returns the expected value.\n\n erlang.mode: number\n Read-only property which returns the mode.\n\n erlang.skewness: number\n Read-only property which returns the skewness.\n\n erlang.stdev: number\n Read-only property which returns the standard deviation.\n\n erlang.variance: number\n Read-only property which returns the variance.\n\n erlang.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n erlang.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n erlang.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n erlang.pdf: Function\n Evaluates the probability density function (PDF).\n\n erlang.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var erlang = base.dists.erlang.Erlang( 6, 5.0 );\n > erlang.k\n 6\n > erlang.lambda\n 5.0\n > erlang.entropy\n ~0.647\n > erlang.kurtosis\n 1.0\n > erlang.mean\n 1.2\n > erlang.mode\n 1.0\n > erlang.skewness\n ~0.816\n > erlang.stdev\n ~0.49\n > erlang.variance\n 0.24\n > erlang.cdf( 3.0 )\n ~0.997\n > erlang.logpdf( 3.0 )\n ~-4.638\n > erlang.mgf( -0.5 )\n ~0.564\n > erlang.pdf( 3.0 )\n ~0.01\n > erlang.quantile( 0.8 )\n ~1.581\n\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k, λ )\n Returns the excess kurtosis of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.erlang.kurtosis( 1, 1.0 )\n 6.0\n > v = base.dists.erlang.kurtosis( 4, 12.0 )\n 1.5\n > v = base.dists.erlang.kurtosis( 8, 2.0 )\n 0.75\n\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x, k, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\n ~-0.1\n > y = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\n ~-0.111\n > y = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.logpdf.factory( k, λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n > y = myLogPDF( 7.0 )\n ~-32.382\n\n\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k, λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n > y = myLogPDF( 7.0 )\n ~-32.382","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k, λ )\n Returns the expected value of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.erlang.mean( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.mean( 4, 12.0 )\n ~0.333\n > v = base.dists.erlang.mean( 8, 2.0 )\n 4.0\n\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t, k, λ )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\n ~1.429\n > y = base.dists.erlang.mgf( 2.0, 2, 3.0 )\n ~9.0\n > y = base.dists.erlang.mgf( -1.0, 2, 2.0 )\n ~0.444\n\n > y = base.dists.erlang.mgf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, 1, NaN )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, -2, 0.5 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, 1, 0.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n NaN\n\n\nbase.dists.erlang.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n > var y = myMGF( 0.2 )\n ~2.778\n > y = myMGF( -0.5 )\n 0.25\n\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n > var y = myMGF( 0.2 )\n ~2.778\n > y = myMGF( -0.5 )\n 0.25","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k, λ )\n Returns the mode of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.erlang.mode( 1, 1.0 )\n 0.0\n > v = base.dists.erlang.mode( 4, 12.0 )\n 0.25\n > v = base.dists.erlang.mode( 8, 2.0 )\n 3.5\n\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\n ~0.905\n > y = base.dists.erlang.pdf( 0.5, 2, 2.5 )\n ~0.895\n > y = base.dists.erlang.pdf( -1.0, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.pdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.pdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n > y = myPDF( 7.0 )\n ~8.639e-15\n\n\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n > y = myPDF( 7.0 )\n ~8.639e-15","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p, k, λ )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive number for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\n ~2.994\n > y = base.dists.erlang.quantile( 0.5, 4, 2.0 )\n ~1.836\n\n > y = base.dists.erlang.quantile( 1.1, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( -0.2, 1, 1.0 )\n NaN\n\n > y = base.dists.erlang.quantile( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, 1, NaN )\n NaN\n\n // Non-integer shape parameter:\n > y = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\n NaN\n // Non-positive shape parameter:\n > y = base.dists.erlang.quantile( 0.5, -1, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n > var y = myQuantile( 0.4 )\n ~4.452\n\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n > var y = myQuantile( 0.4 )\n ~4.452","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k, λ )\n Returns the skewness of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.erlang.skewness( 1, 1.0 )\n 2.0\n > v = base.dists.erlang.skewness( 4, 12.0 )\n 1.0\n > v = base.dists.erlang.skewness( 8, 2.0 )\n ~0.707\n\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k, λ )\n Returns the standard deviation of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.erlang.stdev( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.stdev( 4, 12.0 )\n ~0.167\n > v = base.dists.erlang.stdev( 8, 2.0 )\n ~1.414\n\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k, λ )\n Returns the variance of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.erlang.variance( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.variance( 4, 12.0 )\n ~0.028\n > v = base.dists.erlang.variance( 8, 2.0 )\n 2.0\n\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.exponential.cdf( 2.0, 0.1 )\n ~0.181\n > y = base.dists.exponential.cdf( 1.0, 2.0 )\n ~0.865\n > y = base.dists.exponential.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.exponential.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.cdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.cdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n > var y = myCDF( 3.0 )\n ~0.777\n\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n > var y = myCDF( 3.0 )\n ~0.777","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ )\n Returns the differential entropy of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.exponential.entropy( 11.0 )\n ~-1.398\n > v = base.dists.exponential.entropy( 4.5 )\n ~-0.504\n\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ] )\n Returns an exponential distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n exponential: Object\n Distribution instance.\n\n exponential.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n exponential.entropy: number\n Read-only property which returns the differential entropy.\n\n exponential.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n exponential.mean: number\n Read-only property which returns the expected value.\n\n exponential.median: number\n Read-only property which returns the median.\n\n exponential.mode: number\n Read-only property which returns the mode.\n\n exponential.skewness: number\n Read-only property which returns the skewness.\n\n exponential.stdev: number\n Read-only property which returns the standard deviation.\n\n exponential.variance: number\n Read-only property which returns the variance.\n\n exponential.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n exponential.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n exponential.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n exponential.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n exponential.pdf: Function\n Evaluates the probability density function (PDF).\n\n exponential.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var exponential = base.dists.exponential.Exponential( 6.0 );\n > exponential.lambda\n 6.0\n > exponential.entropy\n ~-0.792\n > exponential.kurtosis\n 6.0\n > exponential.mean\n ~0.167\n > exponential.median\n ~0.116\n > exponential.mode\n 0.0\n > exponential.skewness\n 2.0\n > exponential.stdev\n ~0.167\n > exponential.variance\n ~0.028\n > exponential.cdf( 1.0 )\n ~0.998\n > exponential.logcdf( 1.0 )\n ~-0.002\n > exponential.logpdf( 1.5 )\n ~-7.208\n > exponential.mgf( -0.5 )\n ~0.923\n > exponential.pdf( 1.5 )\n ~0.001\n > exponential.quantile( 0.5 )\n ~0.116\n\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ )\n Returns the excess kurtosis of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.exponential.kurtosis( 11.0 )\n 6.0\n > v = base.dists.exponential.kurtosis( 4.5 )\n 6.0\n\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x, λ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logcdf( 2.0, 0.1 )\n ~-1.708\n > y = base.dists.exponential.logcdf( 1.0, 2.0 )\n ~-0.145\n > y = base.dists.exponential.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.exponential.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.logcdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.logcdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logcdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n > var y = mylogCDF( 3.0 )\n ~-0.252\n\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n > var y = mylogCDF( 3.0 )\n ~-0.252","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logpdf( 0.3, 4.0 )\n ~0.186\n > y = base.dists.exponential.logpdf( 2.0, 0.7 )\n ~-1.757\n > y = base.dists.exponential.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.exponential.logpdf( 0, NaN )\n NaN\n > y = base.dists.exponential.logpdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.logpdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logpdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n > var y = mylogpdf( 3.0 )\n ~-2.193\n\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n > var y = mylogpdf( 3.0 )\n ~-2.193","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ )\n Returns the expected value of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.exponential.mean( 11.0 )\n ~0.091\n > v = base.dists.exponential.mean( 4.5 )\n ~0.222\n\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ )\n Returns the median of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.exponential.median( 11.0 )\n ~0.063\n > v = base.dists.exponential.median( 4.5 )\n ~0.154\n\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t, λ )\n Evaluates the moment-generating function (MGF) for an exponential\n distribution with rate parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var v = base.dists.exponential.mgf( 2.0, 3.0 )\n 3.0\n > v = base.dists.exponential.mgf( 0.4, 1.2 )\n 1.5\n > v = base.dists.exponential.mgf( 0.8, 1.6 )\n 2.0\n > v = base.dists.exponential.mgf( 4.0, 3.0 )\n NaN\n > v = base.dists.exponential.mgf( NaN, 3.0 )\n NaN\n > v = base.dists.exponential.mgf( 2.0, NaN )\n NaN\n\n\nbase.dists.exponential.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n mg: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n > var y = myMGF( 3.0 )\n 4.0\n > y = myMGF( 0.5 )\n ~1.143\n\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n mg: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n > var y = myMGF( 3.0 )\n 4.0\n > y = myMGF( 0.5 )\n ~1.143","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ )\n Returns the mode of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.exponential.mode( 11.0 )\n 0.0\n > v = base.dists.exponential.mode( 4.5 )\n 0.0\n\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x, λ )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.exponential.pdf( 0.3, 4.0 )\n ~1.205\n > y = base.dists.exponential.pdf( 2.0, 0.7 )\n ~0.173\n > y = base.dists.exponential.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.exponential.pdf( 0, NaN )\n NaN\n > y = base.dists.exponential.pdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.pdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.pdf.factory( λ )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n > var y = myPDF( 3.0 )\n ~0.112\n\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n > var y = myPDF( 3.0 )\n ~0.112","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p, λ )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.exponential.quantile( 0.8, 1.0 )\n ~1.609\n > y = base.dists.exponential.quantile( 0.5, 4.0 )\n ~0.173\n > y = base.dists.exponential.quantile( 0.5, 0.1 )\n ~6.931\n\n > y = base.dists.exponential.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.exponential.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.quantile( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.exponential.quantile.factory( λ )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~1.277\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~1.277\n > y = myQuantile( 1.0 )\n Infinity","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ )\n Returns the skewness of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.exponential.skewness( 11.0 )\n 2.0\n > v = base.dists.exponential.skewness( 4.5 )\n 2.0\n\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ )\n Returns the standard deviation of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.exponential.stdev( 9.0 )\n ~0.11\n > v = base.dists.exponential.stdev( 1.0 )\n 1.0\n\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ )\n Returns the variance of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.exponential.variance( 9.0 )\n ~0.012\n > v = base.dists.exponential.variance( 1.0 )\n 1.0\n\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x, d1, d2 )\n Evaluates the cumulative distribution function (CDF) for an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\n ~0.608\n > var y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\n ~0.737\n > var y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > var y = base.dists.f.cdf( PINF, 4.0, 2.0 )\n 1.0\n > var y = base.dists.f.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > var y = base.dists.f.cdf( NaN, 1.0, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, NaN, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, 1.0, NaN )\n NaN\n\n > var y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\n NaN\n > var y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884\n\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884","base.dists.f.entropy":"\nbase.dists.f.entropy( d1, d2 )\n Returns the differential entropy of an F distribution (in nats).\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.f.entropy( 3.0, 7.0 )\n ~1.298\n > v = base.dists.f.entropy( 4.0, 12.0 )\n ~1.12\n > v = base.dists.f.entropy( 8.0, 2.0 )\n ~2.144\n\n","base.dists.f.F":"\nbase.dists.f.F( [d1, d2] )\n Returns an F distribution object.\n\n Parameters\n ----------\n d1: number (optional)\n Numerator degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n d2: number (optional)\n Denominator degrees of freedom. Must be greater than `0`.\n Default: `1.0`.\n\n Returns\n -------\n f: Object\n Distribution instance.\n\n f.d1: number\n Numerator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.d2: number\n Denominator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.entropy: number\n Read-only property which returns the differential entropy.\n\n f.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n f.mean: number\n Read-only property which returns the expected value.\n\n f.mode: number\n Read-only property which returns the mode.\n\n f.skewness: number\n Read-only property which returns the skewness.\n\n f.stdev: number\n Read-only property which returns the standard deviation.\n\n f.variance: number\n Read-only property which returns the variance.\n\n f.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n f.pdf: Function\n Evaluates the probability density function (PDF).\n\n f.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var f = base.dists.f.F( 6.0, 9.0 );\n > f.d1\n 6.0\n > f.d2\n 9.0\n > f.entropy\n ~1.134\n > f.kurtosis\n ~104.564\n > f.mean\n ~1.286\n > f.mode\n ~0.545\n > f.skewness\n ~4.535\n > f.stdev\n ~1.197\n > f.variance\n ~1.433\n > f.cdf( 3.0 )\n ~0.932\n > f.pdf( 2.5 )\n ~0.095\n > f.quantile( 0.8 )\n ~1.826\n\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1, d2 )\n Returns the excess kurtosis of an F distribution.\n\n If `d1 <= 0` or `d2 <= 8`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.f.kurtosis( 3.0, 9.0 )\n ~124.667\n > v = base.dists.f.kurtosis( 4.0, 12.0 )\n ~26.143\n > v = base.dists.f.kurtosis( 8.0, 9.0 )\n ~100.167\n\n","base.dists.f.mean":"\nbase.dists.f.mean( d1, d2 )\n Returns the expected value of an F distribution.\n\n If `d1 <= 0` or `d2 <= 2`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.f.mean( 3.0, 5.0 )\n ~1.667\n > v = base.dists.f.mean( 4.0, 12.0 )\n ~1.2\n > v = base.dists.f.mean( 8.0, 4.0 )\n 2.0\n\n","base.dists.f.mode":"\nbase.dists.f.mode( d1, d2 )\n Returns the mode of an F distribution.\n\n If `d1 <= 2` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.f.mode( 3.0, 5.0 )\n ~0.238\n > v = base.dists.f.mode( 4.0, 12.0 )\n ~0.429\n > v = base.dists.f.mode( 8.0, 4.0 )\n 0.5\n\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x, d1, d2 )\n Evaluates the probability density function (PDF) for an F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\n ~0.057\n > y = base.dists.f.pdf( 0.1, 1.0, 1.0 )\n ~0.915\n > y = base.dists.f.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.f.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.f.pdf( 2.0, 1.0, -1.0 )\n NaN\n > y = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.pdf.factory( d1, d2 )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n ~0.004\n > y = myPDF( 2.0 )\n ~0.166\n\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1, d2 )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n ~0.004\n > y = myPDF( 2.0 )\n ~0.166","base.dists.f.quantile":"\nbase.dists.f.quantile( p, d1, d2 )\n Evaluates the quantile function for an F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\n ~9.472\n > y = base.dists.f.quantile( 0.5, 4.0, 2.0 )\n ~1.207\n\n > y = base.dists.f.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.f.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.f.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.f.quantile.factory( d1, d2 )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~0.527\n > y = myQuantile( 0.8 )\n ~4.382\n\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1, d2 )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~0.527\n > y = myQuantile( 0.8 )\n ~4.382","base.dists.f.skewness":"\nbase.dists.f.skewness( d1, d2 )\n Returns the skewness of an F distribution.\n\n If `d1 <= 0` or `d2 <= 6`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.f.skewness( 3.0, 7.0 )\n 11.0\n > v = base.dists.f.skewness( 4.0, 12.0 )\n ~3.207\n > v = base.dists.f.skewness( 8.0, 7.0 )\n ~10.088\n\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1, d2 )\n Returns the standard deviation of an F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.f.stdev( 3.0, 5.0 )\n ~3.333\n > v = base.dists.f.stdev( 4.0, 12.0 )\n ~1.122\n > v = base.dists.f.stdev( 8.0, 5.0 )\n ~2.764\n\n","base.dists.f.variance":"\nbase.dists.f.variance( d1, d2 )\n Returns the variance of an F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.f.variance( 3.0, 5.0 )\n ~11.111\n > v = base.dists.f.variance( 4.0, 12.0 )\n ~1.26\n > v = base.dists.f.variance( 8.0, 5.0 )\n ~7.639\n\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x, α, s, m )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\n ~0.914\n > y = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\n ~0.105\n > y = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\n ~0.018\n > y = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.cdf.factory( α, s, m )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n > var y = myCDF( 10.0 )\n ~0.806\n > y = myCDF( 7.0 )\n ~0.034\n\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α, s, m )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n > var y = myCDF( 10.0 )\n ~0.806\n > y = myCDF( 7.0 )\n ~0.034","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α, s, m )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\n ~2.154\n > y = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\n ~1.028\n > y = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α, s, m] )\n Returns a Fréchet distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n m: number (optional)\n Location parameter. Default: `0.0`.\n\n Returns\n -------\n frechet: Object\n Distribution instance.\n\n frechet.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n frechet.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n frechet.m: number\n Location parameter.\n\n frechet.entropy: number\n Read-only property which returns the differential entropy.\n\n frechet.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n frechet.mean: number\n Read-only property which returns the expected value.\n\n frechet.median: number\n Read-only property which returns the median.\n\n frechet.mode: number\n Read-only property which returns the mode.\n\n frechet.skewness: number\n Read-only property which returns the skewness.\n\n frechet.stdev: number\n Read-only property which returns the standard deviation.\n\n frechet.variance: number\n Read-only property which returns the variance.\n\n frechet.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n frechet.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n frechet.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n frechet.pdf: Function\n Evaluates the probability density function (PDF).\n\n frechet.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\n > frechet.alpha\n 1.0\n > frechet.s\n 1.0\n > frechet.m\n 0.0\n > frechet.entropy\n ~2.154\n > frechet.kurtosis\n Infinity\n > frechet.mean\n Infinity\n > frechet.median\n ~1.443\n > frechet.mode\n 0.5\n > frechet.skewness\n Infinity\n > frechet.stdev\n Infinity\n > frechet.variance\n Infinity\n > frechet.cdf( 0.8 )\n ~0.287\n > frechet.logcdf( 0.8 )\n -1.25\n > frechet.logpdf( 0.8 )\n ~-0.804\n > frechet.pdf( 0.8 )\n ~0.448\n > frechet.quantile( 0.8 )\n ~4.481\n\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α, s, m )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 4` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\n ~45.092\n > var y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\n ~45.092\n > y = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x, α, s, m )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\n ~-0.09\n > y = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\n ~-2.25\n > y = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\n -4.0\n > y = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.logcdf.factory( α, s, m )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.216\n > y = mylogcdf( 7.0 )\n ~-3.375\n\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α, s, m )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.216\n > y = mylogcdf( 7.0 )\n ~-3.375","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x, α, s, m )\n Evaluates the logarithm of the probability density function (PDF) for a\n Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\n ~-2.72\n > y = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\n ~-1.901\n > y = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\n ~-0.307\n > y = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.logpdf.factory( α, s, m )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n > var y = mylogPDF( 10.0 )\n ~-3.812\n > y = mylogPDF( 2.0 )\n ~-6.11\n\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α, s, m )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n > var y = mylogPDF( 10.0 )\n ~-3.812\n > y = mylogPDF( 2.0 )\n ~-6.11","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α, s, m )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 1` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\n ~3.451\n > y = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.mean( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α, s, m )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\n ~3.192\n > var y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\n ~-0.808\n > y = base.dists.frechet.median( 0.5, 2.0, 1.0 )\n ~5.163\n > y = base.dists.frechet.median( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α, s, m )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\n ~2.891\n > var y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\n ~-1.109\n > y = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\n ~1.222\n > y = base.dists.frechet.mode( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x, α, s, m )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.pdf.factory( α, s, m )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n > var y = myPDF( 10.0 )\n ~0.933\n > y = myPDF( 2.0 )\n ~0.368\n\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α, s, m )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n > var y = myPDF( 10.0 )\n ~0.933\n > y = myPDF( 2.0 )\n ~0.368","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p, α, s, m )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\n ~4.963\n > y = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\n ~5.56\n > y = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\n ~6.491\n > y = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.quantile.factory( α, s, m )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~5.402\n > y = myQuantile( 0.2 )\n ~4.576\n\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α, s, m )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~5.402\n > y = myQuantile( 0.2 )\n ~4.576","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α, s, m )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 3` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\n ~5.605\n > var y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\n ~5.605\n > y = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α, s, m )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\n ~1.041\n > var y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\n ~1.041\n > y = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α, s, m )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\n ~1.083\n > var y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\n ~1.083\n > y = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.variance( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\n ~0.323\n > y = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0` when `α = 0.0`:\n > y = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264\n\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α, β )\n Returns the differential entropy of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.gamma.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.entropy( 4.0, 12.0 )\n ~-0.462\n > v = base.dists.gamma.entropy( 8.0, 2.0 )\n ~1.723\n\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α, β] )\n Returns a gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gamma: Object\n Distribution instance.\n\n gamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n gamma.beta: number\n Rate parameter. If set, the value must be greater than `0`.\n\n gamma.entropy: number\n Read-only property which returns the differential entropy.\n\n gamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gamma.mean: number\n Read-only property which returns the expected value.\n\n gamma.mode: number\n Read-only property which returns the mode.\n\n gamma.skewness: number\n Read-only property which returns the skewness.\n\n gamma.stdev: number\n Read-only property which returns the standard deviation.\n\n gamma.variance: number\n Read-only property which returns the variance.\n\n gamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gamma.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n gamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gamma.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n gamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\n > gamma.alpha\n 6.0\n > gamma.beta\n 5.0\n > gamma.entropy\n ~0.647\n > gamma.kurtosis\n 1.0\n > gamma.mean\n 1.2\n > gamma.mode\n 1.0\n > gamma.skewness\n ~0.816\n > gamma.stdev\n ~0.49\n > gamma.variance\n 0.24\n > gamma.cdf( 0.8 )\n ~0.215\n > gamma.logcdf( 0.8 )\n ~-1.538\n > gamma.logpdf( 1.0 )\n ~-0.131\n > gamma.mgf( -0.5 )\n ~0.564\n > gamma.pdf( 1.0 )\n ~0.877\n > gamma.quantile( 0.8 )\n ~1.581\n\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α, β )\n Returns the excess kurtosis of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.gamma.kurtosis( 4.0, 12.0 )\n 1.5\n > v = base.dists.gamma.kurtosis( 8.0, 2.0 )\n 0.75\n\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x, α, β )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\n ~-0.047\n > y = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\n ~-2.352\n > y = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.gamma.logcdf.factory( α, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n > var y = mylogCDF( 2.0 )\n ~-0.006\n\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n > var y = mylogCDF( 2.0 )\n ~-0.006","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x, α, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.919\n > y = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.logpdf.factory( α, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-3.646\n\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-3.646","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α, β )\n Returns the expected value of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.gamma.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.mean( 4.0, 12.0 )\n ~0.333\n > v = base.dists.gamma.mean( 8.0, 2.0 )\n 4.0\n\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\n ~1.414\n > y = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\n ~1.111\n > y = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\n ~0.198\n\n > y = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.gamma.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n > var y = myMGF( 1.0 )\n ~27.0\n > y = myMGF( 0.5 )\n ~3.375\n\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n > var y = myMGF( 1.0 )\n ~27.0\n > y = myMGF( 0.5 )\n ~3.375","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α, β )\n Returns the mode of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.gamma.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.gamma.mode( 4.0, 12.0 )\n 0.25\n > v = base.dists.gamma.mode( 8.0, 2.0 )\n 3.5\n\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\n ~0.054\n > y = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.026\n\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.026","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p, α, β )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\n ~2.994\n > y = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\n ~1.836\n\n > y = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~1.497\n > y = myQuantile( 0.4 )\n ~0.688\n\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~1.497\n > y = myQuantile( 0.4 )\n ~0.688","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α, β )\n Returns the skewness of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.gamma.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.gamma.skewness( 4.0, 12.0 )\n 1.0\n > v = base.dists.gamma.skewness( 8.0, 2.0 )\n ~0.707\n\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α, β )\n Returns the standard deviation of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.gamma.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.stdev( 4.0, 12.0 )\n ~0.167\n > v = base.dists.gamma.stdev( 8.0, 2.0 )\n ~1.414\n\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α, β )\n Returns the variance of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.gamma.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.variance( 4.0, 12.0 )\n ~0.028\n > v = base.dists.gamma.variance( 8.0, 2.0 )\n 2.0\n\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.geometric.cdf( 2.0, 0.5 )\n 0.875\n > y = base.dists.geometric.cdf( 2.0, 0.1 )\n ~0.271\n > y = base.dists.geometric.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.geometric.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.cdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 0.9375\n > y = mycdf( 1.0 )\n 0.75\n\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 0.9375\n > y = mycdf( 1.0 )\n 0.75","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.geometric.entropy( 0.1 )\n ~3.251\n > v = base.dists.geometric.entropy( 0.5 )\n ~1.386\n\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p] )\n Returns a geometric distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n geometric: Object\n Distribution instance.\n\n geometric.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n geometric.entropy: number\n Read-only property which returns the differential entropy.\n\n geometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n geometric.mean: number\n Read-only property which returns the expected value.\n\n geometric.median: number\n Read-only property which returns the median.\n\n geometric.mode: number\n Read-only property which returns the mode.\n\n geometric.skewness: number\n Read-only property which returns the skewness.\n\n geometric.stdev: number\n Read-only property which returns the standard deviation.\n\n geometric.variance: number\n Read-only property which returns the variance.\n\n geometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n geometric.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n geometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n geometric.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n geometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n geometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var geometric = base.dists.geometric.Geometric( 0.6 );\n > geometric.p\n 0.6\n > geometric.entropy\n ~1.122\n > geometric.kurtosis\n ~6.9\n > geometric.mean\n ~0.667\n > geometric.median\n 0.0\n > geometric.mode\n 0.0\n > geometric.skewness\n ~2.214\n > geometric.stdev\n ~1.054\n > geometric.variance\n ~1.111\n > geometric.cdf( 3.0 )\n ~0.974\n > geometric.logcdf( 3.0 )\n ~-0.026\n > geometric.logpmf( 4.0 )\n ~-4.176\n > geometric.mgf( 0.5 )\n ~2.905\n > geometric.pmf( 2.0 )\n ~0.096\n > geometric.quantile( 0.7 )\n 1.0\n\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.geometric.kurtosis( 0.1 )\n ~6.011\n > v = base.dists.geometric.kurtosis( 0.5 )\n 6.5\n\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x, p )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.geometric.logcdf( 2.0, 0.5 )\n ~-0.134\n > y = base.dists.geometric.logcdf( 2.0, 0.1 )\n ~-1.306\n > y = base.dists.geometric.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.geometric.logcdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.logcdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.logcdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.logcdf.factory( p )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.065\n > y = mylogcdf( 1.0 )\n ~-0.288\n\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.065\n > y = mylogcdf( 1.0 )\n ~-0.288","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x, p )\n Evaluates the logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.geometric.logpmf( 4.0, 0.3 )\n ~-2.631\n > y = base.dists.geometric.logpmf( 2.0, 0.7 )\n ~-2.765\n > y = base.dists.geometric.logpmf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.geometric.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.logpmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.logpmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.logpmf.factory( p )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.773\n > y = mylogpmf( 1.0 )\n ~-1.386\n\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.773\n > y = mylogpmf( 1.0 )\n ~-1.386","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.geometric.mean( 0.1 )\n 9.0\n > v = base.dists.geometric.mean( 0.5 )\n 1.0\n\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p )\n Returns the median of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.geometric.median( 0.1 )\n 6\n > v = base.dists.geometric.median( 0.5 )\n 0\n\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `t >= -ln(1-p)`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.geometric.mgf( 0.2, 0.5 )\n ~1.569\n > y = base.dists.geometric.mgf( 0.4, 0.5 )\n ~2.936\n // Case: t >= -ln(1-p)\n > y = base.dists.geometric.mgf( 0.8, 0.5 )\n NaN\n > y = base.dists.geometric.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.geometric.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.783\n\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.783","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p )\n Returns the mode of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.geometric.mode( 0.1 )\n 0\n > v = base.dists.geometric.mode( 0.5 )\n 0\n\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x, p )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.geometric.pmf( 4.0, 0.3 )\n ~0.072\n > y = base.dists.geometric.pmf( 2.0, 0.7 )\n ~0.063\n > y = base.dists.geometric.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.geometric.pmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.pmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n > var y = mypmf( 3.0 )\n 0.0625\n > y = mypmf( 1.0 )\n 0.25\n\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n > var y = mypmf( 3.0 )\n 0.0625\n > y = mypmf( 1.0 )\n 0.25","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r, p )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.geometric.quantile( 0.8, 0.4 )\n 3\n > y = base.dists.geometric.quantile( 0.5, 0.4 )\n 1\n > y = base.dists.geometric.quantile( 0.9, 0.1 )\n 21\n\n > y = base.dists.geometric.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.geometric.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.geometric.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.geometric.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.geometric.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.geometric.quantile.factory( p )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 3\n > y = myquantile( 1.0 )\n Infinity\n\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 3\n > y = myquantile( 1.0 )\n Infinity","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.geometric.skewness( 0.1 )\n ~2.003\n > v = base.dists.geometric.skewness( 0.5 )\n ~2.121\n\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.geometric.stdev( 0.1 )\n ~9.487\n > v = base.dists.geometric.stdev( 0.5 )\n ~1.414\n\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p )\n Returns the variance of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.geometric.variance( 0.1 )\n ~90.0\n > v = base.dists.geometric.variance( 0.5 )\n 2.0\n\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x, μ, β )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.cdf.factory( μ, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.933\n > y = myCDF( 2.0 )\n ~0.368\n\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.933\n > y = myCDF( 2.0 )\n ~0.368","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ, β )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.gumbel.entropy( 0.0, 1.0 )\n ~1.577\n > y = base.dists.gumbel.entropy( 4.0, 2.0 )\n ~2.27\n > y = base.dists.gumbel.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ, β] )\n Returns a Gumbel distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gumbel: Object\n Distribution instance.\n\n gumbel.mu: number\n Location parameter.\n\n gumbel.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n gumbel.entropy: number\n Read-only property which returns the differential entropy.\n\n gumbel.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gumbel.mean: number\n Read-only property which returns the expected value.\n\n gumbel.median: number\n Read-only property which returns the median.\n\n gumbel.mode: number\n Read-only property which returns the mode.\n\n gumbel.skewness: number\n Read-only property which returns the skewness.\n\n gumbel.stdev: number\n Read-only property which returns the standard deviation.\n\n gumbel.variance: number\n Read-only property which returns the variance.\n\n gumbel.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gumbel.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n gumbel.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gumbel.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gumbel.pdf: Function\n Evaluates the probability density function (PDF).\n\n gumbel.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\n > gumbel.mu\n -2.0\n > gumbel.beta\n 3.0\n > gumbel.entropy\n ~2.676\n > gumbel.kurtosis\n 2.4\n > gumbel.mean\n ~-0.268\n > gumbel.median\n ~-0.9\n > gumbel.mode\n -2.0\n > gumbel.skewness\n ~1.14\n > gumbel.stdev\n ~3.848\n > gumbel.variance\n ~14.804\n > gumbel.cdf( 0.8 )\n ~0.675\n > gumbel.logcdf( 0.8 )\n ~-0.393\n > gumbel.logpdf( 1.0 )\n ~-2.466\n > gumbel.mgf( 0.2 )\n ~1.487\n > gumbel.pdf( 1.0 )\n ~0.085\n > gumbel.quantile( 0.8 )\n ~2.5\n\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ, β )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( 4.0, 2.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x, μ, β )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\n ~-0.036\n > y = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\n ~-1.948\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\n ~-1.0\n > y = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logcdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n > var y = myLCDF( 10.0 )\n ~-0.069\n > y = myLCDF( 2.0 )\n ~-1.0\n\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n > var y = myLCDF( 10.0 )\n ~-0.069\n > y = myLCDF( 2.0 )\n ~-1.0","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x, μ, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\n ~-1.693\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\n ~-1\n > y = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\n ~-2.411\n > y = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logpdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-1.693\n > y = mylogpdf( 12.0 )\n ~-2.061\n\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-1.693\n > y = mylogpdf( 12.0 )\n ~-2.061","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ, β )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.gumbel.mean( 0.0, 1.0 )\n ~0.577\n > y = base.dists.gumbel.mean( 4.0, 2.0 )\n ~5.154\n > y = base.dists.gumbel.mean( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mean( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ, β )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.gumbel.median( 0.0, 1.0 )\n ~0.367\n > y = base.dists.gumbel.median( 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.median( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.median( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.median( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t, μ, β )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\n 6.0\n > y = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\n ~1.298\n\n > y = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\n NaN\n\n // Case: `t >= 1/beta`\n > y = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\n NaN\n\n // Non-positive scale parameter:\n > y = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.mgf.factory( μ, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n > var y = myMGF( -1.5 )\n ~52.343\n > y = myMGF( -1.0 )\n 6.0\n\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n > var y = myMGF( -1.5 )\n ~52.343\n > y = myMGF( -1.0 )\n 6.0","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ, β )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.gumbel.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.gumbel.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.gumbel.mode( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mode( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x, μ, β )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\n ~0.184\n > y = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\n ~0.09\n > y = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.pdf.factory( μ, β )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.184\n > y = myPDF( 12.0 )\n ~0.127\n\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ, β )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.184\n > y = myPDF( 12.0 )\n ~0.127","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p, μ, β )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\n ~1.5\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\n ~5.466\n\n > y = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.quantile.factory( μ, β )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~8.733\n > y = myQuantile( 0.7 )\n ~10.062\n\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ, β )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~8.733\n > y = myQuantile( 0.7 )\n ~10.062","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ, β )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.gumbel.skewness( 0.0, 1.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( 4.0, 2.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ, β )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.gumbel.stdev( 0.0, 1.0 )\n ~1.283\n > y = base.dists.gumbel.stdev( 4.0, 2.0 )\n ~2.565\n > y = base.dists.gumbel.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ, β )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.gumbel.variance( 0.0, 1.0 )\n ~1.645\n > y = base.dists.gumbel.variance( 4.0, 2.0 )\n ~6.58\n > y = base.dists.gumbel.variance( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.variance( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x, N, K, n )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceeds population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\n 1.0\n > y = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\n ~0.214\n\n > y = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n > var y = myCDF( 4.0 )\n ~0.891\n > y = myCDF( 1.0 )\n ~0.031\n\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n > var y = myCDF( 4.0 )\n ~0.891\n > y = myCDF( 1.0 )\n ~0.031","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N, K, n] )\n Returns a hypergeometric distribution object.\n\n Parameters\n ----------\n N: integer (optional)\n Population size. Must be a nonnegative integer larger than or equal to\n `K` and `n`.\n\n K: integer (optional)\n Subpopulation size. Must be a nonnegative integer smaller than or equal\n to `N`.\n\n n: integer (optional)\n Number of draws. Must be a nonnegative integer smaller than or equal to\n `N`.\n\n Returns\n -------\n hypergeometric: Object\n Distribution instance.\n\n hypergeometric.N: number\n Population size. If set, the value must be a nonnegative integer larger\n than or equal to `K` and `n`.\n\n hypergeometric.K: number\n Subpopulation size. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.n: number\n Number of draws. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n hypergeometric.mean: number\n Read-only property which returns the expected value.\n\n hypergeometric.mode: number\n Read-only property which returns the mode.\n\n hypergeometric.skewness: number\n Read-only property which returns the skewness.\n\n hypergeometric.stdev: number\n Read-only property which returns the standard deviation.\n\n hypergeometric.variance: number\n Read-only property which returns the variance.\n\n hypergeometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n hypergeometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n hypergeometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n hypergeometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\n > hypergeometric.N\n 100.0\n > hypergeometric.K\n 70.0\n > hypergeometric.n\n 20.0\n > hypergeometric.kurtosis\n ~-0.063\n > hypergeometric.mean\n 14.0\n > hypergeometric.mode\n 14.0\n > hypergeometric.skewness\n ~-0.133\n > hypergeometric.stdev\n ~1.842\n > hypergeometric.variance\n ~3.394\n > hypergeometric.cdf( 2.9 )\n ~0.0\n > hypergeometric.logpmf( 10 )\n ~-3.806\n > hypergeometric.pmf( 10 )\n ~0.022\n > hypergeometric.quantile( 0.8 )\n 16.0\n\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N, K, n )\n Returns the excess kurtosis of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceed population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\n ~-0.326\n > v = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x, N, K, n )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K`, or draws `n`\n which is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\n ~-0.56\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\n -Infinity\n\n > y = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n > var y = mylogPMF( 4.0 )\n ~-1.079\n > y = mylogPMF( 1.0 )\n ~-3.524\n\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n > var y = mylogPMF( 4.0 )\n ~-1.079\n > y = mylogPMF( 1.0 )\n ~-3.524","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N, K, n )\n Returns the expected value of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mean( 16, 11, 4 )\n 2.75\n > v = base.dists.hypergeometric.mean( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.mean( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mean( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mean( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N, K, n )\n Returns the mode of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mode( 16, 11, 4 )\n 3\n > v = base.dists.hypergeometric.mode( 2, 1, 1 )\n 1\n\n > v = base.dists.hypergeometric.mode( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mode( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mode( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x, N, K, n )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\n ~0.571\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\n 0.0\n\n > y = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n > var y = myPMF( 4.0 )\n ~0.34\n > y = myPMF( 1.0 )\n ~0.029\n\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n > var y = myPMF( 4.0 )\n ~0.34\n > y = myPMF( 1.0 )\n ~0.029","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p, N, K, n )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\n 5\n > y = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\n 15\n > y = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\n 1\n > y = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\n 0\n > y = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\n 20\n\n > y = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n NaN\n\n\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n > var y = myQuantile( 0.2 )\n 1\n > y = myQuantile( 0.9 )\n 4\n\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n > var y = myQuantile( 0.2 )\n 1\n > y = myQuantile( 0.9 )\n 4","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N, K, n )\n Returns the skewness of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\n ~-0.258\n > v = base.dists.hypergeometric.skewness( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.skewness( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.skewness( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N, K, n )\n Returns the standard deviation of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\n ~0.829\n > v = base.dists.hypergeometric.stdev( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.stdev( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.stdev( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N, K, n )\n Returns the variance of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.variance( 16, 11, 4 )\n ~0.688\n > v = base.dists.hypergeometric.variance( 2, 1, 1 )\n 0.25\n\n > v = base.dists.hypergeometric.variance( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.variance( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.variance( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, 10, NaN )\n NaN\n\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\n ~0.607\n > y = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\n ~0.986\n > y = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974\n\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α, β )\n Returns the differential entropy of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.invgamma.entropy( 1.0, 1.0 )\n ~2.154\n > v = base.dists.invgamma.entropy( 4.0, 12.0 )\n ~1.996\n > v = base.dists.invgamma.entropy( 8.0, 2.0 )\n ~-0.922\n\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α, β] )\n Returns an inverse gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n invgamma: Object\n Distribution instance.\n\n invgamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n invgamma.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n invgamma.entropy: number\n Read-only property which returns the differential entropy.\n\n invgamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n invgamma.mean: number\n Read-only property which returns the expected value.\n\n invgamma.mode: number\n Read-only property which returns the mode.\n\n invgamma.skewness: number\n Read-only property which returns the skewness.\n\n invgamma.stdev: number\n Read-only property which returns the standard deviation.\n\n invgamma.variance: number\n Read-only property which returns the variance.\n\n invgamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n invgamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n invgamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n invgamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\n > invgamma.alpha\n 6.0\n > invgamma.beta\n 5.0\n > invgamma.entropy\n ~0.454\n > invgamma.kurtosis\n 19.0\n > invgamma.mean\n 1.0\n > invgamma.mode\n ~0.714\n > invgamma.skewness\n ~2.667\n > invgamma.stdev\n 0.5\n > invgamma.variance\n 0.25\n > invgamma.cdf( 0.8 )\n ~0.406\n > invgamma.pdf( 1.0 )\n ~0.877\n > invgamma.logpdf( 1.0 )\n ~-0.131\n > invgamma.quantile( 0.8 )\n ~1.281\n\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α, β )\n Returns the excess kurtosis of an inverse gamma distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\n 12.0\n > v = base.dists.invgamma.kurtosis( 6.0, 12.0 )\n 19.0\n > v = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n ~8.7\n\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.112\n > y = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\n ~-1.781\n > y = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-1.464\n\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-1.464","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α, β )\n Returns the expected value of an inverse gamma distribution.\n\n If `α <= 1` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.invgamma.mean( 4.0, 12.0 )\n 4.0\n > v = base.dists.invgamma.mean( 8.0, 2.0 )\n ~0.286\n\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α, β )\n Returns the mode of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.invgamma.mode( 1.0, 1.0 )\n 0.5\n > v = base.dists.invgamma.mode( 4.0, 12.0 )\n 2.4\n > v = base.dists.invgamma.mode( 8.0, 2.0 )\n ~0.222\n\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\n ~0.121\n > y = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\n ~0.168\n > y = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.231\n\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.231","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p, α, β )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\n ~1.213\n > y = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\n ~0.545\n > y = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n\n // Non-positive rate parameter:\n > y = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~2.426\n > y = myQuantile( 0.4 )\n ~0.989\n\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~2.426\n > y = myQuantile( 0.4 )\n ~0.989","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α, β )\n Returns the skewness of an inverse gamma distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.invgamma.skewness( 4.0, 12.0 )\n ~5.657\n > v = base.dists.invgamma.skewness( 8.0, 2.0 )\n ~1.96\n\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α, β )\n Returns the standard deviation of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.invgamma.stdev( 5.0, 7.0 )\n ~1.01\n > v = base.dists.invgamma.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.invgamma.stdev( 8.0, 2.0 )\n ~0.117\n\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α, β )\n Returns the variance of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.invgamma.variance( 5.0, 7.0 )\n ~1.021\n > v = base.dists.invgamma.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.invgamma.variance( 8.0, 2.0 )\n ~0.014\n\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\n ~0.5\n > y = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\n ~0.684\n > y = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\n ~0.078\n > y = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\n ~0.878\n > y = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n > var y = mycdf( 0.8 )\n ~0.894\n > y = mycdf( 0.3 )\n ~0.548\n\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n > var y = mycdf( 0.8 )\n ~0.894\n > y = mycdf( 0.3 )\n ~0.548","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a, b] )\n Returns a Kumaraswamy's double bounded distribution object.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n b: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n kumaraswamy: Object\n Distribution instance.\n\n kumaraswamy.a: number\n First shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.b: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n kumaraswamy.mean: number\n Read-only property which returns the expected value.\n\n kumaraswamy.mode: number\n Read-only property which returns the mode.\n\n kumaraswamy.skewness: number\n Read-only property which returns the skewness.\n\n kumaraswamy.stdev: number\n Read-only property which returns the standard deviation.\n\n kumaraswamy.variance: number\n Read-only property which returns the variance.\n\n kumaraswamy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n kumaraswamy.pdf: Function\n Evaluates the probability density function (PDF).\n\n kumaraswamy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\n > kumaraswamy.a\n 6.0\n > kumaraswamy.b\n 5.0\n > kumaraswamy.kurtosis\n ~3.194\n > kumaraswamy.mean\n ~0.696\n > kumaraswamy.mode\n ~0.746\n > kumaraswamy.skewness\n ~-0.605\n > kumaraswamy.stdev\n ~0.126\n > kumaraswamy.variance\n ~0.016\n > kumaraswamy.cdf( 0.8 )\n ~0.781\n > kumaraswamy.pdf( 1.0 )\n ~0.0\n > kumaraswamy.quantile( 0.8 )\n ~0.807\n\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a, b )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\n ~1.8\n > v = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\n ~2.704\n > v = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n ~4.311\n\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\n ~-0.38\n > y = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\n ~-2.546\n > y = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\n ~-0.13\n > y = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n > var y = mylogcdf( 0.8 )\n ~-0.112\n > y = mylogcdf( 0.3 )\n ~-0.602\n\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n > var y = mylogcdf( 0.8 )\n ~-0.112\n > y = mylogcdf( 0.3 )\n ~-0.602","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x, a, b )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\n ~0.523\n > y = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\n ~-0.264\n > y = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\n ~0.522\n > y = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n > var y = mylogpdf( 0.8 )\n ~-0.582\n > y = mylogpdf( 0.3 )\n ~-0.091\n\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n > var y = mylogpdf( 0.8 )\n ~-0.582\n > y = mylogpdf( 0.3 )\n ~-0.091","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a, b )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\n ~0.512\n > v = base.dists.kumaraswamy.mean( 4.0, 12.0 )\n ~0.481\n > v = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n ~0.846\n\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a, b )\n Returns the median of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.kumaraswamy.median( 4.0, 12.0 )\n ~0.487\n > v = base.dists.kumaraswamy.median( 16.0, 8.0 )\n ~0.856\n\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a, b )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a < 1`, `b < 1`, or `a = b = 1`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\n ~0.543\n > v = base.dists.kumaraswamy.mode( 4.0, 12.0 )\n ~0.503\n > v = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n ~0.875\n\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x, a, b )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\n ~1.688\n > y = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\n ~0.768\n > y = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\n ~1.686\n > y = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n > var y = mypdf( 0.8 )\n ~0.559\n > y = mypdf( 0.3 )\n ~0.913\n\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n > var y = mypdf( 0.8 )\n ~0.559\n > y = mypdf( 0.3 )\n ~0.913","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p, a, b )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\n ~0.399\n > y = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\n ~0.325\n > y = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\n ~0.759\n\n > y = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n > var y = myQuantile( 0.8 )\n ~0.64\n > y = myQuantile( 0.3 )\n ~0.09\n\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n > var y = myQuantile( 0.8 )\n ~0.64\n > y = myQuantile( 0.3 )\n ~0.09","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a, b )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\n ~1.154e-15\n > v = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\n ~-0.201\n > v = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n ~-0.94\n\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a, b )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\n ~0.13\n > v = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n ~0.062\n\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a, b )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.kumaraswamy.variance( 4.0, 12.0 )\n ~0.017\n > v = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n ~0.004\n\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x, μ, b )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\n ~0.932\n > y = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\n ~0.094\n > y = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.cdf.factory( μ, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.965\n > y = myCDF( 2.0 )\n 0.5\n\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.965\n > y = myCDF( 2.0 )\n 0.5","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ, b )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.laplace.entropy( 0.0, 1.0 )\n ~1.693\n > y = base.dists.laplace.entropy( 4.0, 2.0 )\n ~2.386\n > y = base.dists.laplace.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.entropy( 0.0, NaN )\n NaN\n > y = base.dists.laplace.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ, b )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( 4.0, 2.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ, b] )\n Returns a Laplace distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n b: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n laplace: Object\n Distribution instance.\n\n laplace.mu: number\n Location parameter.\n\n laplace.b: number\n Scale parameter. If set, the value must be greater than `0`.\n\n laplace.entropy: number\n Read-only property which returns the differential entropy.\n\n laplace.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n laplace.mean: number\n Read-only property which returns the expected value.\n\n laplace.median: number\n Read-only property which returns the median.\n\n laplace.mode: number\n Read-only property which returns the mode.\n\n laplace.skewness: number\n Read-only property which returns the skewness.\n\n laplace.stdev: number\n Read-only property which returns the standard deviation.\n\n laplace.variance: number\n Read-only property which returns the variance.\n\n laplace.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n laplace.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n laplace.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n laplace.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n laplace.pdf: Function\n Evaluates the probability density function (PDF).\n\n laplace.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\n > laplace.mu\n -2.0\n > laplace.b\n 3.0\n > laplace.entropy\n ~2.792\n > laplace.kurtosis\n 3.0\n > laplace.mean\n -2.0\n > laplace.median\n -2.0\n > laplace.mode\n -2.0\n > laplace.skewness\n 0.0\n > laplace.stdev\n ~4.243\n > laplace.variance\n 18.0\n > laplace.cdf( 0.8 )\n ~0.803\n > laplace.logcdf( 0.8 )\n ~-0.219\n > laplace.logpdf( 1.0 )\n ~-2.792\n > laplace.mgf( 0.2 )\n ~1.047\n > laplace.pdf( 2.0 )\n ~0.044\n > laplace.quantile( 0.9 )\n ~2.828\n\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x, μ, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\n ~-0.07\n > y = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\n ~-2.36\n > y = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logcdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.035\n > y = mylogcdf( 2.0 )\n ~-0.693\n\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.035\n > y = mylogcdf( 2.0 )\n ~-0.693","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x, μ, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\n ~-2.693\n > y = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\n ~-2.792\n > y = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\n ~-1.958\n > y = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logpdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.386\n\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.386","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ, b )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.laplace.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mean( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mean( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ, b )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.laplace.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.median( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.median( 0.0, NaN )\n NaN\n > y = base.dists.laplace.median( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t, μ, b )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\n ~1.333\n > y = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\n ~0.019\n > y = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\n NaN\n > y = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.mgf.factory( μ, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n > var y = mymgf( 0.2 )\n ~2.649\n > y = mymgf( 0.4 )\n ~13.758\n\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n > var y = mymgf( 0.2 )\n ~2.649\n > y = mymgf( 0.4 )\n ~13.758","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ, b )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.laplace.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mode( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mode( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x, μ, b )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\n ~0.068\n > y = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\n ~0.061\n > y = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\n ~0.141\n > y = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.pdf.factory( μ, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.25\n\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.25","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p, μ, b )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\n ~0.916\n > y = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\n 4.0\n\n > y = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.quantile.factory( μ, b )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n > y = myQuantile( 0.8 )\n ~11.833\n\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ, b )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n > y = myQuantile( 0.8 )\n ~11.833","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ, b )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.laplace.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.laplace.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.skewness( 0.0, NaN )\n NaN\n > y = base.dists.laplace.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ, b )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.laplace.stdev( 0.0, 1.0 )\n ~1.414\n > y = base.dists.laplace.stdev( 4.0, 2.0 )\n ~2.828\n > y = base.dists.laplace.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.stdev( 0.0, NaN )\n NaN\n > y = base.dists.laplace.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ, b )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.laplace.variance( 0.0, 1.0 )\n 2.0\n > y = base.dists.laplace.variance( 4.0, 2.0 )\n 8.0\n > y = base.dists.laplace.variance( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.variance( 0.0, NaN )\n NaN\n > y = base.dists.laplace.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x, μ, c )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\n ~0.48\n > y = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\n ~0.221\n > y = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\n 0.0\n > y = base.dists.levy.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0\n\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ, c )\n Returns the entropy of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.levy.entropy( 0.0, 1.0 )\n ~3.324\n > y = base.dists.levy.entropy( 4.0, 2.0 )\n ~4.018\n > y = base.dists.levy.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.levy.entropy( 0.0, NaN )\n NaN\n > y = base.dists.levy.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ, c] )\n Returns a Lévy distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n c: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n levy: Object\n Distribution instance.\n\n levy.mu: number\n Location parameter.\n\n levy.c: number\n Scale parameter. If set, the value must be greater than `0`.\n\n levy.entropy: number\n Read-only property which returns the differential entropy.\n\n levy.mean: number\n Read-only property which returns the expected value.\n\n levy.median: number\n Read-only property which returns the median.\n\n levy.mode: number\n Read-only property which returns the mode.\n\n levy.stdev: number\n Read-only property which returns the standard deviation.\n\n levy.variance: number\n Read-only property which returns the variance.\n\n levy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n levy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n levy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n levy.pdf: Function\n Evaluates the probability density function (PDF).\n\n levy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var levy = base.dists.levy.Levy( -2.0, 3.0 );\n > levy.mu\n -2.0\n > levy.c\n 3.0\n > levy.entropy\n ~4.423\n > levy.mean\n Infinity\n > levy.median\n ~4.594\n > levy.mode\n -1.0\n > levy.stdev\n Infinity\n > levy.variance\n Infinity\n > levy.cdf( 0.8 )\n ~0.3\n > levy.logcdf( 0.8 )\n ~-1.2\n > levy.logpdf( 1.0 )\n ~-2.518\n > levy.pdf( 1.0 )\n ~0.081\n > levy.quantile( 0.8 )\n ~44.74\n\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x, μ, c )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Lévy distribution with location parameter `μ` and scale parameter `c` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\n ~-0.735\n > y = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\n ~-1.51\n > y = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\n -Infinity\n > y = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity\n\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x, μ, c )\n Evaluates the logarithm of the probability density function (PDF) for a Lévy\n distribution with location parameter `μ` and scale parameter `c` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\n ~-2.209\n > y = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logpdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 11.0 )\n ~-1.572\n\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 11.0 )\n ~-1.572","base.dists.levy.mean":"\nbase.dists.levy.mean( μ, c )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.levy.mean( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.mean( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.mean( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mean( 0.0, NaN )\n NaN\n > y = base.dists.levy.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.median":"\nbase.dists.levy.median( μ, c )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.levy.median( 0.0, 1.0 )\n ~2.198\n > y = base.dists.levy.median( 4.0, 3.0 )\n ~10.594\n > y = base.dists.levy.median( NaN, 1.0 )\n NaN\n > y = base.dists.levy.median( 0.0, NaN )\n NaN\n > y = base.dists.levy.median( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ, c )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.levy.mode( 0.0, 1.0 )\n ~0.333\n > y = base.dists.levy.mode( 4.0, 3.0 )\n 5.0\n > y = base.dists.levy.mode( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mode( 0.0, NaN )\n NaN\n > y = base.dists.levy.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x, μ, c )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\n ~0.11\n > y = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.levy.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.pdf.factory( μ, c )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 11.0 )\n ~0.208\n\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ, c )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 11.0 )\n ~0.208","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p, μ, c )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\n ~15.58\n > y = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\n ~8.396\n\n > y = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.levy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.quantile.factory( μ, c )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~14.396\n\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ, c )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~14.396","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ, c )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.levy.stdev( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.stdev( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.levy.stdev( 0.0, NaN )\n NaN\n > y = base.dists.levy.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ, c )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.levy.variance( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.variance( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.variance( NaN, 1.0 )\n NaN\n > y = base.dists.levy.variance( 0.0, NaN )\n NaN\n > y = base.dists.levy.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\n ~0.881\n > y = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\n ~0.159\n\n > y = base.dists.logistic.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209\n\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ, s )\n Returns the entropy of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.logistic.entropy( 0.0, 1.0 )\n 2.0\n > y = base.dists.logistic.entropy( 4.0, 2.0 )\n ~2.693\n > y = base.dists.logistic.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.entropy( 0.0, NaN )\n NaN\n > y = base.dists.logistic.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ, s )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( 4.0, 2.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, 0.0 )\n NaN\n\n\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x, μ, s )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\n ~-0.127\n > y = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\n ~-1.84\n > y = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567\n\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ, s] )\n Returns a logistic distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n logistic: Object\n Distribution instance.\n\n logistic.mu: number\n Location parameter.\n\n logistic.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n logistic.entropy: number\n Read-only property which returns the differential entropy.\n\n logistic.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n logistic.mean: number\n Read-only property which returns the expected value.\n\n logistic.median: number\n Read-only property which returns the median.\n\n logistic.mode: number\n Read-only property which returns the mode.\n\n logistic.skewness: number\n Read-only property which returns the skewness.\n\n logistic.stdev: number\n Read-only property which returns the standard deviation.\n\n logistic.variance: number\n Read-only property which returns the variance.\n\n logistic.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n logistic.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n logistic.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n logistic.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n logistic.pdf: Function\n Evaluates the probability density function (PDF).\n\n logistic.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\n > logistic.mu\n -2.0\n > logistic.s\n 3.0\n > logistic.entropy\n ~3.1\n > logistic.kurtosis\n 1.2\n > logistic.mean\n -2.0\n > logistic.median\n -2.0\n > logistic.mode\n -2.0\n > logistic.skewness\n 0.0\n > logistic.stdev\n ~5.441\n > logistic.variance\n ~29.609\n > logistic.cdf( 0.8 )\n ~0.718\n > logistic.logcdf( 0.8 )\n ~-0.332\n > logistic.logpdf( 2.0 )\n ~-2.9\n > logistic.mgf( 0.2 )\n ~1.329\n > logistic.pdf( 2.0 )\n ~0.055\n > logistic.quantile( 0.9 )\n ~4.592\n\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\n ~-2.254\n > y = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\n ~-3.351\n > y = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-2.079\n\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-2.079","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ, s )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.logistic.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mean( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mean( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ, s )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.logistic.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.median( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.median( 0.0, NaN )\n NaN\n > y = base.dists.logistic.median( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\n ~9.15\n > y = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\n ~1.971\n > y = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\n ~1.921\n > y = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\n Infinity\n > y = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.logistic.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n > var y = mymgf( 0.5 )\n ~164.846\n > y = mymgf( 2.0 )\n Infinity\n\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n > var y = mymgf( 0.5 )\n ~164.846\n > y = mymgf( 2.0 )\n Infinity","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ, s )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.logistic.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mode( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mode( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\n ~0.105\n > y = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\n ~0.035\n > y = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.125\n\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.125","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p, μ, s )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\n ~1.386\n > y = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.logistic.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ, s )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.logistic.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.logistic.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.skewness( 0.0, NaN )\n NaN\n > y = base.dists.logistic.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ, s )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.logistic.stdev( 0.0, 1.0 )\n ~1.814\n > y = base.dists.logistic.stdev( 4.0, 2.0 )\n ~3.628\n > y = base.dists.logistic.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.stdev( 0.0, NaN )\n NaN\n > y = base.dists.logistic.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ, s )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.logistic.variance( 0.0, 1.0 )\n ~3.29\n > y = base.dists.logistic.variance( 4.0, 2.0 )\n ~13.159\n > y = base.dists.logistic.variance( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.variance( 0.0, NaN )\n NaN\n > y = base.dists.logistic.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\n ~0.756\n > y = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\n ~0.003\n\n > y = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n > var y = myCDF( 1.0 )\n ~0.023\n > y = myCDF( 4.0 )\n ~0.141\n\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n > var y = myCDF( 1.0 )\n ~0.023\n > y = myCDF( 4.0 )\n ~0.141","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ, σ )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.lognormal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.lognormal.entropy( 5.0, 2.0 )\n ~7.112\n > y = base.dists.lognormal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ, σ )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\n ~110.936\n > y = base.dists.lognormal.kurtosis( 5.0, 2.0 )\n ~9220556.977\n > y = base.dists.lognormal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ, σ] )\n Returns a lognormal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n lognormal: Object\n Distribution instance.\n\n lognormal.mu: number\n Location parameter.\n\n lognormal.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n lognormal.entropy: number\n Read-only property which returns the differential entropy.\n\n lognormal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n lognormal.mean: number\n Read-only property which returns the expected value.\n\n lognormal.median: number\n Read-only property which returns the median.\n\n lognormal.mode: number\n Read-only property which returns the mode.\n\n lognormal.skewness: number\n Read-only property which returns the skewness.\n\n lognormal.stdev: number\n Read-only property which returns the standard deviation.\n\n lognormal.variance: number\n Read-only property which returns the variance.\n\n lognormal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n lognormal.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n lognormal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n lognormal.pdf: Function\n Evaluates the probability density function (PDF).\n\n lognormal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\n > lognormal.mu\n -2.0\n > lognormal.sigma\n 3.0\n > lognormal.entropy\n ~0.518\n > lognormal.kurtosis\n 4312295840576300\n > lognormal.mean\n ~12.182\n > lognormal.median\n ~0.135\n > lognormal.mode\n ~0.0\n > lognormal.skewness\n ~729551.383\n > lognormal.stdev\n ~1096.565\n > lognormal.variance\n ~1202455.871\n > lognormal.cdf( 0.8 )\n ~0.723\n > lognormal.logcdf( 0.8 )\n ~-4.334\n > lognormal.logpdf( 2.0 )\n ~-3.114\n > lognormal.pdf( 2.0 )\n ~0.044\n > lognormal.quantile( 0.9 )\n ~6.326\n\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x, μ, σ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a lognormal distribution with mean `μ` and standard deviation `σ`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logcdf.\n\n Examples\n --------\n > var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\n ~-0.2799\n > y = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\n ~-1.442\n > y = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n -Infinity\n\n\nbase.dists.lognormal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-9.732\n\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-9.732","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\n ~-1.852\n > y = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\n ~-0.919\n > y = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\n ~-5.419\n > y = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-4.275\n > y = mylogPDF( 2.0 )\n ~-3.672\n\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-4.275\n > y = mylogPDF( 2.0 )\n ~-3.672","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ, σ )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.lognormal.mean( 0.0, 1.0 )\n ~1.649\n > y = base.dists.lognormal.mean( 4.0, 2.0 )\n ~403.429\n > y = base.dists.lognormal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mean( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ, σ )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.lognormal.median( 0.0, 1.0 )\n 1.0\n > y = base.dists.lognormal.median( 5.0, 2.0 )\n ~148.413\n > y = base.dists.lognormal.median( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.median( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ, σ )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.lognormal.mode( 0.0, 1.0 )\n ~0.368\n > y = base.dists.lognormal.mode( 5.0, 2.0 )\n ~2.718\n > y = base.dists.lognormal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mode( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\n ~0.157\n > y = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\n ~0.399\n > y = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\n ~0.004\n > y = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.014\n > y = myPDF( 2.0 )\n ~0.025\n\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.014\n > y = myPDF( 2.0 )\n ~0.025","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p, μ, σ )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\n ~2.32\n > y = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\n ~54.598\n > y = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~10.143\n > y = myQuantile( 0.8 )\n ~293.901\n\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~10.143\n > y = myQuantile( 0.8 )\n ~293.901","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ, σ )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.lognormal.skewness( 0.0, 1.0 )\n ~6.185\n > y = base.dists.lognormal.skewness( 5.0, 2.0 )\n ~414.359\n > y = base.dists.lognormal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ, σ )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.lognormal.stdev( 0.0, 1.0 )\n ~2.161\n > y = base.dists.lognormal.stdev( 4.0, 2.0 )\n ~2953.533\n > y = base.dists.lognormal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ, σ )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.lognormal.variance( 0.0, 1.0 )\n ~4.671\n > y = base.dists.lognormal.variance( 4.0, 2.0 )\n ~8723355.729\n > y = base.dists.lognormal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.variance( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x, r, p )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\n ~0.617\n > y = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\n ~0.622\n > y = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\n ~0.034\n > y = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\n ~0.859\n > y = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\n ~0.131\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.cdf.factory( r, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n > var y = myCDF( 3.0 )\n ~0.046\n > y = myCDF( 11.0 )\n ~0.668\n\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n > var y = myCDF( 3.0 )\n ~0.046\n > y = myCDF( 11.0 )\n ~0.668","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r, p )\n Returns the excess kurtosis of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\n ~0.061\n > v = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n ~0.325\n\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x, r, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\n ~-1.853\n > y = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\n ~-2.818\n > y = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\n ~-4.115\n > y = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\n ~-1.054\n > y = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\n ~-3.292\n > y = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\n ~-2.976\n\n > y = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n > var y = mylogPMF( 3.0 )\n ~-3.617\n > y = mylogPMF( 5.0 )\n ~-2.795\n\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n > var y = mylogPMF( 3.0 )\n ~-3.617\n > y = mylogPMF( 5.0 )\n ~-2.795","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r, p )\n Returns the expected value of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mean( 100, 0.2 )\n 400\n > v = base.dists.negativeBinomial.mean( 20, 0.5 )\n 20\n\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x, r, p )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\n ~267.839\n > y = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\n ~9.347\n > y = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\n ~42822.023\n\n > y = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.mgf.factory( r, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n > var y = myMGF( 0.2 )\n ~4.696\n > y = myMGF( 0.4 )\n ~30.83\n\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n > var y = myMGF( 0.2 )\n ~4.696\n > y = myMGF( 0.4 )\n ~30.83","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r, p )\n Returns the mode of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mode( 100, 0.2 )\n 396\n > v = base.dists.negativeBinomial.mode( 20, 0.5 )\n 19\n\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r, p] )\n Returns a negative binomial distribution object.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped. Must be a positive\n number. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n nbinomial: Object\n Distribution instance.\n\n nbinomial.r: number\n Number of trials. If set, the value must be a positive number.\n\n nbinomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n nbinomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n nbinomial.mean: number\n Read-only property which returns the expected value.\n\n nbinomial.mode: number\n Read-only property which returns the mode.\n\n nbinomial.skewness: number\n Read-only property which returns the skewness.\n\n nbinomial.stdev: number\n Read-only property which returns the standard deviation.\n\n nbinomial.variance: number\n Read-only property which returns the variance.\n\n nbinomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n nbinomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n nbinomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n nbinomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n nbinomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\n > nbinomial.r\n 8.0\n > nbinomial.p\n 0.5\n > nbinomial.kurtosis\n 0.8125\n > nbinomial.mean\n 8.0\n > nbinomial.mode\n 7.0\n > nbinomial.skewness\n 0.75\n > nbinomial.stdev\n 4.0\n > nbinomial.variance\n 16.0\n > nbinomial.cdf( 2.9 )\n ~0.055\n > nbinomial.logpmf( 3.0 )\n ~-2.837\n > nbinomial.mgf( 0.2 )\n ~36.675\n > nbinomial.pmf( 3.0 )\n ~0.059\n > nbinomial.quantile( 0.8 )\n 11.0\n\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x, r, p )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\n ~0.157\n > y = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\n ~0.06\n > y = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\n ~0.016\n > y = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\n ~0.037\n > y = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\n ~0.051\n\n > y = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.pmf.factory( r, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n > var y = myPMF( 3.0 )\n ~0.027\n > y = myPMF( 5.0 )\n ~0.061\n\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n > var y = myPMF( 3.0 )\n ~0.027\n > y = myPMF( 5.0 )\n ~0.061","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k, r, p )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n\n If provided a `k` outside of `[0,1]`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n k: number\n Input probability.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\n 106\n > y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\n 8\n > y = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\n 14\n > y = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\n 0\n\n > y = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\n 12\n > y = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\n 10\n\n > y = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.quantile.factory( r, p )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n > var y = myQuantile( 0.1 )\n 5\n > y = myQuantile( 0.9 )\n 16\n\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r, p )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n > var y = myQuantile( 0.1 )\n 5\n > y = myQuantile( 0.9 )\n 16","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r, p )\n Returns the skewness of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\n ~0.201\n > v = base.dists.negativeBinomial.skewness( 20, 0.5 )\n ~0.474\n\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r, p )\n Returns the standard deviation of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\n ~44.721\n > v = base.dists.negativeBinomial.stdev( 20, 0.5 )\n ~6.325\n\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r, p )\n Returns the variance of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.variance( 100, 0.2 )\n 2000.0\n > v = base.dists.negativeBinomial.variance( 20, 0.5 )\n 40.0\n\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\n ~0.977\n > y = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\n 0.5\n > y = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\n ~0.006\n > y = base.dists.normal.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.normal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n 0.5\n\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n 0.5","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ, σ )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.normal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.normal.entropy( 4.0, 3.0 )\n ~2.518\n > y = base.dists.normal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.normal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.normal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ, σ )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.normal.kurtosis( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.kurtosis( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x, μ, σ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logcdf.\n\n Examples\n --------\n > var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\n ~-0.023\n > y = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\n ~-5.082\n > y = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.logcdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n 0.0\n\n\nbase.dists.normal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.693\n\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.693","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\n ~-2.919\n > y = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\n ~-4.737\n > y = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.normal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n > var y = myLogPDF( 10.0 )\n ~-1.612\n\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n > var y = myLogPDF( 10.0 )\n ~-1.612","base.dists.normal.mean":"\nbase.dists.normal.mean( μ, σ )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.normal.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mean( 0.0, NaN )\n NaN\n > y = base.dists.normal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.median":"\nbase.dists.normal.median( μ, σ )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.normal.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.median( NaN, 1.0 )\n NaN\n > y = base.dists.normal.median( 0.0, NaN )\n NaN\n > y = base.dists.normal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x, μ, σ )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\n ~7.389\n > y = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\n ~0.1353\n > y = base.dists.normal.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.normal.mgf.factory( μ, σ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n > var y = myMGF( 1.0 )\n ~403.429\n > y = myMGF( 0.5 )\n ~12.182\n\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ, σ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n > var y = myMGF( 1.0 )\n ~403.429\n > y = myMGF( 0.5 )\n ~12.182","base.dists.normal.mode":"\nbase.dists.normal.mode( μ, σ )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.normal.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mode( 0.0, NaN )\n NaN\n > y = base.dists.normal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ, σ] )\n Returns a normal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Mean parameter. Default: `0.0`.\n\n σ: number (optional)\n Standard deviation. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n normal: Object\n Distribution instance.\n\n normal.mu: number\n Mean parameter.\n\n normal.sigma: number\n Standard deviation. If set, the value must be greater than `0`.\n\n normal.entropy: number\n Read-only property which returns the differential entropy.\n\n normal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n normal.mean: number\n Read-only property which returns the expected value.\n\n normal.median: number\n Read-only property which returns the median.\n\n normal.mode: number\n Read-only property which returns the mode.\n\n normal.skewness: number\n Read-only property which returns the skewness.\n\n normal.stdev: number\n Read-only property which returns the standard deviation.\n\n normal.variance: number\n Read-only property which returns the variance.\n\n normal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n normal.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n normal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n normal.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n normal.pdf: Function\n Evaluates the probability density function (PDF).\n\n normal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var normal = base.dists.normal.Normal( -2.0, 3.0 );\n > normal.mu\n -2.0\n > normal.sigma\n 3.0\n > normal.entropy\n ~2.518\n > normal.kurtosis\n 0.0\n > normal.mean\n -2.0\n > normal.median\n -2.0\n > normal.mode\n -2.0\n > normal.skewness\n 0.0\n > normal.stdev\n 3.0\n > normal.variance\n 9.0\n > normal.cdf( 0.8 )\n ~0.825\n > normal.logcdf( 0.8 )\n ~-0.193\n > normal.logpdf( 2.0 )\n ~-2.9\n > normal.mgf( 0.2 )\n ~0.803\n > normal.pdf( 2.0 )\n ~0.055\n > normal.quantile( 0.9 )\n ~1.845\n\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\n ~0.054\n > y = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\n ~0.009\n > y = base.dists.normal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n infinity\n\n\nbase.dists.normal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.199\n\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.199","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p, μ, σ )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\n ~0.842\n > y = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.normal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\n 8.0\n > y = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n 8.0\n\n\nbase.dists.normal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ, σ )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.normal.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.skewness( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.normal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.normal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ, σ )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.normal.stdev( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.stdev( 4.0, 3.0 )\n 3.0\n > y = base.dists.normal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.normal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.normal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ, σ )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.normal.variance( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.variance( 4.0, 3.0 )\n 9.0\n > y = base.dists.normal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.normal.variance( 0.0, NaN )\n NaN\n > y = base.dists.normal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\n 0.5\n > y = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\n ~0.36\n > y = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\n 0.75\n > y = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893\n\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α, β )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.pareto1.entropy( 0.8, 1.0 )\n ~2.473\n > v = base.dists.pareto1.entropy( 4.0, 12.0 )\n ~2.349\n > v = base.dists.pareto1.entropy( 8.0, 2.0 )\n ~-0.261\n\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α, β )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\n ~70.8\n > v = base.dists.pareto1.kurtosis( 4.5, 12.0 )\n ~146.444\n > v = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n ~19.725\n\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\n ~-1.022\n > y = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\n ~-0.288\n > y = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114\n\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\n ~-2.773\n > y = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\n ~-3.689\n > y = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\n ~-1.561\n > y = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\n ~-5.238\n > y = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079\n\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α, β )\n Returns the expected value of a Pareto (Type I) distribution.\n\n If `0 < α <= 1`, the function returns `Infinity`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.pareto1.mean( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.mean( 4.0, 12.0 )\n 16.0\n > v = base.dists.pareto1.mean( 8.0, 2.0 )\n ~2.286\n\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α, β )\n Returns the median of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.pareto1.median( 0.8, 1.0 )\n ~2.378\n > v = base.dists.pareto1.median( 4.0, 12.0 )\n ~14.27\n > v = base.dists.pareto1.median( 8.0, 2.0 )\n ~2.181\n\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α, β )\n Returns the mode of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.pareto1.mode( 0.8, 1.0 )\n 1.0\n > v = base.dists.pareto1.mode( 4.0, 12.0 )\n 12.0\n > v = base.dists.pareto1.mode( 8.0, 2.0 )\n 2.0\n\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α, β] )\n Returns a Pareto (Type I) distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n pareto1: Object\n Distribution instance.\n\n pareto1.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n pareto1.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n pareto1.entropy: number\n Read-only property which returns the differential entropy.\n\n pareto1.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n pareto1.mean: number\n Read-only property which returns the expected value.\n\n pareto1.median: number\n Read-only property which returns the median.\n\n pareto1.mode: number\n Read-only property which returns the mode.\n\n pareto1.skewness: number\n Read-only property which returns the skewness.\n\n pareto1.variance: number\n Read-only property which returns the variance.\n\n pareto1.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n pareto1.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF).\n\n pareto1.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (logPDF).\n\n pareto1.pdf: Function\n Evaluates the probability density function (PDF).\n\n pareto1.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\n > pareto1.alpha\n 6.0\n > pareto1.beta\n 5.0\n > pareto1.entropy\n ~0.984\n > pareto1.kurtosis\n ~35.667\n > pareto1.mean\n 6.0\n > pareto1.median\n ~5.612\n > pareto1.mode\n 5.0\n > pareto1.skewness\n ~3.81\n > pareto1.variance\n 1.5\n > pareto1.cdf( 7.0 )\n ~0.867\n > pareto1.logcdf( 7.0 )\n ~-0.142\n > pareto1.logpdf( 5.0 )\n ~0.182\n > pareto1.pdf( 5.0 )\n 1.2\n > pareto1.quantile( 0.8 )\n ~6.538\n\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\n ~0.063\n > y = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\n 0.025\n > y = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\n ~0.21\n > y = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\n ~0.005\n > y = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n > var y = myPDF( 0.8 )\n ~0.494\n > y = myPDF( 2.0 )\n ~0.125\n\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n > var y = myPDF( 0.8 )\n ~0.494\n > y = myPDF( 2.0 )\n ~0.125","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p, α, β )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\n ~2.236\n > y = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\n ~50.0\n > y = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\n ~11.111\n\n > y = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.pareto1.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n > var y = myQuantile( 0.5 )\n ~0.66\n > y = myQuantile( 0.8 )\n ~0.952\n\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n > var y = myQuantile( 0.5 )\n ~0.66\n > y = myQuantile( 0.8 )\n ~0.952","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α, β )\n Returns the skewness of a Pareto (Type I) distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.pareto1.skewness( 3.5, 1.0 )\n ~11.784\n > v = base.dists.pareto1.skewness( 4.0, 12.0 )\n ~7.071\n > v = base.dists.pareto1.skewness( 8.0, 2.0 )\n ~3.118\n\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α, β )\n Returns the standard deviation of a Pareto (Type I) distribution.\n\n If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.pareto1.stdev( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.stdev( 4.0, 12.0 )\n ~5.657\n > v = base.dists.pareto1.stdev( 8.0, 2.0 )\n ~0.33\n\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α, β )\n Returns the variance of a Pareto (Type I) distribution.\n\n If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.pareto1.variance( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.variance( 4.0, 12.0 )\n 32.0\n > v = base.dists.pareto1.variance( 8.0, 2.0 )\n ~0.109\n\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.poisson.cdf( 2.0, 0.5 )\n ~0.986\n > y = base.dists.poisson.cdf( 2.0, 10.0 )\n ~0.003\n > y = base.dists.poisson.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.poisson.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.poisson.cdf( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.poisson.cdf( 10.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n > var y = mycdf( 3.0 )\n ~0.265\n > y = mycdf( 8.0 )\n ~0.932\n\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n > var y = mycdf( 3.0 )\n ~0.265\n > y = mycdf( 8.0 )\n ~0.932","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ )\n Returns the entropy of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.poisson.entropy( 11.0 )\n ~2.61\n > v = base.dists.poisson.entropy( 4.5 )\n ~2.149\n\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ )\n Returns the excess kurtosis of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.poisson.kurtosis( 11.0 )\n ~0.091\n > v = base.dists.poisson.kurtosis( 4.5 )\n ~0.222\n\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x, λ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.poisson.logpmf( 4.0, 3.0 )\n ~-1.784\n > y = base.dists.poisson.logpmf( 1.0, 3.0 )\n ~-1.901\n > y = base.dists.poisson.logpmf( -1.0, 2.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.logpmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.logpmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.logpmf( 2.0, 0.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, 0.0 )\n 0.0\n\n\nbase.dists.poisson.logpmf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n > var y = mylogpmf( 3.0 )\n ~-2.792\n > y = mylogpmf( 1.0 )\n ~-1.0\n\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n > var y = mylogpmf( 3.0 )\n ~-2.792\n > y = mylogpmf( 1.0 )\n ~-1.0","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ )\n Returns the expected value of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.poisson.mean( 11.0 )\n 11.0\n > v = base.dists.poisson.mean( 4.5 )\n 4.5\n\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ )\n Returns the median of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.poisson.median( 11.0 )\n 11\n > v = base.dists.poisson.median( 4.5 )\n 4\n\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x, λ )\n Evaluates the moment-generating function (MGF) for a Poisson distribution\n with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.poisson.mgf( 1.0, 1.5 )\n ~13.163\n > y = base.dists.poisson.mgf( 0.5, 0.5 )\n ~1.383\n > y = base.dists.poisson.mgf( NaN, 0.5 )\n NaN\n > y = base.dists.poisson.mgf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.mgf( -2.0, -1.0 )\n NaN\n\n\nbase.dists.poisson.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n > var y = myMGF( 0.1 )\n ~1.234\n\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n > var y = myMGF( 0.1 )\n ~1.234","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ )\n Returns the mode of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.poisson.mode( 11.0 )\n 11\n > v = base.dists.poisson.mode( 4.5 )\n 4\n\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x, λ )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.poisson.pmf( 4.0, 3.0 )\n ~0.168\n > y = base.dists.poisson.pmf( 1.0, 3.0 )\n ~0.149\n > y = base.dists.poisson.pmf( -1.0, 2.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.pmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.pmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.pmf( 2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.pmf.factory( λ )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n > var y = mypmf( 3.0 )\n ~0.061\n > y = mypmf( 1.0 )\n ~0.368\n\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n > var y = mypmf( 3.0 )\n ~0.061\n > y = mypmf( 1.0 )\n ~0.368","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ] )\n Returns a Poisson distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Mean parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n poisson: Object\n Distribution instance.\n\n poisson.lambda: number\n Mean parameter. If set, the value must be greater than `0`.\n\n poisson.entropy: number\n Read-only property which returns the differential entropy.\n\n poisson.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n poisson.mean: number\n Read-only property which returns the expected value.\n\n poisson.median: number\n Read-only property which returns the median.\n\n poisson.mode: number\n Read-only property which returns the mode.\n\n poisson.skewness: number\n Read-only property which returns the skewness.\n\n poisson.stdev: number\n Read-only property which returns the standard deviation.\n\n poisson.variance: number\n Read-only property which returns the variance.\n\n poisson.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n poisson.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n poisson.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n poisson.pmf: Function\n Evaluates the probability mass function (PMF).\n\n poisson.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var poisson = base.dists.poisson.Poisson( 6.0 );\n > poisson.lambda\n 6.0\n > poisson.entropy\n ~2.3\n > poisson.kurtosis\n ~0.167\n > poisson.mean\n 6.0\n > poisson.median\n 6.0\n > poisson.mode\n 6.0\n > poisson.skewness\n ~0.408\n > poisson.stdev\n ~2.449\n > poisson.variance\n 6.0\n > poisson.cdf( 4.0 )\n ~0.285\n > poisson.logpmf( 2.0 )\n ~-3.11\n > poisson.mgf( 0.5 )\n ~49.025\n > poisson.pmf( 2.0 )\n ~0.045\n > poisson.quantile( 0.5 )\n 6.0\n\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p, λ )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.poisson.quantile( 0.5, 2.0 )\n 2\n > y = base.dists.poisson.quantile( 0.9, 4.0 )\n 7\n > y = base.dists.poisson.quantile( 0.1, 200.0 )\n 182\n\n > y = base.dists.poisson.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.poisson.quantile( -0.2, 0.0 )\n NaN\n\n > y = base.dists.poisson.quantile( NaN, 0.5 )\n NaN\n > y = base.dists.poisson.quantile( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.quantile( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.quantile( 0.1, 0.0 )\n 0.0\n > y = base.dists.poisson.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.poisson.quantile.factory( λ )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n 0.0\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n 0.0\n > y = myQuantile( 1.0 )\n Infinity","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ )\n Returns the skewness of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.poisson.skewness( 11.0 )\n ~0.302\n > v = base.dists.poisson.skewness( 4.5 )\n ~0.471\n\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ )\n Returns the standard deviation of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.poisson.stdev( 11.0 )\n ~3.317\n > v = base.dists.poisson.stdev( 4.5 )\n ~2.121\n\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ )\n Returns the variance of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.poisson.variance( 11.0 )\n 11.0\n > v = base.dists.poisson.variance( 4.5 )\n 4.5\n\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x, sigma )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\n ~0.199\n > y = base.dists.rayleigh.cdf( 1.0, 2.0 )\n ~0.118\n > y = base.dists.rayleigh.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.cdf( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.rayleigh.cdf( 2.0, 0.0 )\n 1.0\n\n\nbase.dists.rayleigh.cdf.factory( sigma )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n > var y = myCDF( 1.0 )\n ~0.865\n > y = myCDF( 0.5 )\n ~0.393\n\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n > var y = myCDF( 1.0 )\n ~0.865\n > y = myCDF( 0.5 )\n ~0.393","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ )\n Returns the differential entropy of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.rayleigh.entropy( 11.0 )\n ~3.34\n > v = base.dists.rayleigh.entropy( 4.5 )\n ~2.446\n\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ )\n Returns the excess kurtosis of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.rayleigh.kurtosis( 11.0 )\n ~0.245\n > v = base.dists.rayleigh.kurtosis( 4.5 )\n ~0.245\n\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x, sigma )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\n ~-1.613\n > y = base.dists.rayleigh.logcdf( 1.0, 2.0 )\n ~-2.141\n > y = base.dists.rayleigh.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.rayleigh.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.logcdf( 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logcdf.factory( sigma )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n > var y = mylogcdf( 1.0 )\n ~-0.145\n > y = mylogcdf( 0.5 )\n ~-0.933\n\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n > var y = mylogcdf( 1.0 )\n ~-0.145\n > y = mylogcdf( 0.5 )\n ~-0.933","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x, sigma )\n Evaluates the logarithm of the probability density function (PDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\n ~-1.249\n > y = base.dists.rayleigh.logpdf( 2.0, 0.8 )\n ~-1.986\n > y = base.dists.rayleigh.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.rayleigh.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.logpdf( NaN, 2.0 )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logpdf.factory( sigma )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n > var y = mylogpdf( 6.0 )\n ~-2.106\n > y = mylogpdf( 4.0 )\n ~-1.886\n\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n > var y = mylogpdf( 6.0 )\n ~-2.106\n > y = mylogpdf( 4.0 )\n ~-1.886","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ )\n Returns the expected value of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mean( 11.0 )\n ~13.786\n > v = base.dists.rayleigh.mean( 4.5 )\n ~5.64\n\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ )\n Returns the median of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.rayleigh.median( 11.0 )\n ~12.952\n > v = base.dists.rayleigh.median( 4.5 )\n ~5.298\n\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t, sigma )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\n ~678.508\n > y = base.dists.rayleigh.mgf( 1.0, 2.0 )\n ~38.65\n > y = base.dists.rayleigh.mgf( -1.0, 4.0 )\n ~-0.947\n > y = base.dists.rayleigh.mgf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.mgf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.mgf( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.mgf.factory( sigma )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n > var y = myMGF( 1.0 )\n ~2.715\n > y = myMGF( 0.5 )\n ~1.888\n\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n > var y = myMGF( 1.0 )\n ~2.715\n > y = myMGF( 0.5 )\n ~1.888","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ )\n Returns the mode of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mode( 11.0 )\n 11.0\n > v = base.dists.rayleigh.mode( 4.5 )\n 4.5\n\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x, sigma )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\n ~0.287\n > y = base.dists.rayleigh.pdf( 2.0, 0.8 )\n ~0.137\n > y = base.dists.rayleigh.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.pdf( NaN, 2.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.pdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, 0.0 )\n Infinity\n > y = base.dists.rayleigh.pdf( 2.0, 0.0 )\n 0.0\n\n\nbase.dists.rayleigh.pdf.factory( sigma )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n > var y = myPDF( 6.0 )\n ~0.122\n > y = myPDF( 4.0 )\n ~0.152\n\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n > var y = myPDF( 6.0 )\n ~0.122\n > y = myPDF( 4.0 )\n ~0.152","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p, sigma )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative probability for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\n ~1.794\n > y = base.dists.rayleigh.quantile( 0.5, 4.0 )\n ~4.71\n\n > y = base.dists.rayleigh.quantile( 1.1, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( -0.2, 1.0 )\n NaN\n\n > y = base.dists.rayleigh.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.quantile.factory( sigma )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~0.404\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~0.404\n > y = myQuantile( 1.0 )\n Infinity","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ] )\n Returns a Rayleigh distribution object.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n rayleigh: Object\n Distribution instance.\n\n rayleigh.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n rayleigh.entropy: number\n Read-only property which returns the differential entropy.\n\n rayleigh.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n rayleigh.mean: number\n Read-only property which returns the expected value.\n\n rayleigh.median: number\n Read-only property which returns the median.\n\n rayleigh.mode: number\n Read-only property which returns the mode.\n\n rayleigh.skewness: number\n Read-only property which returns the skewness.\n\n rayleigh.stdev: number\n Read-only property which returns the standard deviation.\n\n rayleigh.variance: number\n Read-only property which returns the variance.\n\n rayleigh.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n rayleigh.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n rayleigh.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n rayleigh.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n rayleigh.pdf: Function\n Evaluates the probability density function (PDF).\n\n rayleigh.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\n > rayleigh.sigma\n 6.0\n > rayleigh.entropy\n ~2.734\n > rayleigh.kurtosis\n ~0.245\n > rayleigh.mean\n ~7.52\n > rayleigh.median\n ~7.064\n > rayleigh.mode\n 6.0\n > rayleigh.skewness\n ~0.631\n > rayleigh.stdev\n ~3.931\n > rayleigh.variance\n ~15.451\n > rayleigh.cdf( 1.0 )\n ~0.014\n > rayleigh.logcdf( 1.0 )\n ~-4.284\n > rayleigh.logpdf( 1.5 )\n ~-3.209\n > rayleigh.mgf( -0.5 )\n ~-0.91\n > rayleigh.pdf( 1.5 )\n ~0.04\n > rayleigh.quantile( 0.5 )\n ~7.064\n\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ )\n Returns the skewness of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.rayleigh.skewness( 11.0 )\n ~0.631\n > v = base.dists.rayleigh.skewness( 4.5 )\n ~0.631\n\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ )\n Returns the standard deviation of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.rayleigh.stdev( 9.0 )\n ~5.896\n > v = base.dists.rayleigh.stdev( 4.5 )\n ~2.948\n\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ )\n Returns the variance of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.rayleigh.variance( 9.0 )\n ~34.765\n > v = base.dists.rayleigh.variance( 4.5 )\n ~8.691\n\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x, n )\n Evaluates the cumulative distribution function (CDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `x`, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.signrank.cdf( 3, 7 )\n ~0.039\n > y = base.dists.signrank.cdf( 1.8, 3 )\n ~0.375\n > y = base.dists.signrank.cdf( -1.0, 40 )\n 0.0\n > y = base.dists.signrank.cdf( NaN, 10 )\n NaN\n > y = base.dists.signrank.cdf( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.cdf.factory( n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.signrank.cdf.factory( 8 );\n > var y = myCDF( 5.7 )\n ~0.055\n > y = myCDF( 2.2 )\n ~0.012\n\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.signrank.cdf.factory( 8 );\n > var y = myCDF( 5.7 )\n ~0.055\n > y = myCDF( 2.2 )\n ~0.012","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x, n )\n Evaluates the probability density function (PDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `x`, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.signrank.pdf( 3, 7 )\n ~0.0156\n > y = base.dists.signrank.pdf( 1.8, 3 )\n 0.0\n > y = base.dists.signrank.pdf( -1.0, 40 )\n 0.0\n > y = base.dists.signrank.pdf( NaN, 10 )\n NaN\n > y = base.dists.signrank.pdf( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.pdf.factory( n )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.signrank.pdf.factory( 8 );\n > var y = myPDF( 6.0 )\n ~0.0156\n > y = myPDF( 2.0 )\n ~0.0039\n\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.signrank.pdf.factory( 8 );\n > var y = myPDF( 6.0 )\n ~0.0156\n > y = myPDF( 2.0 )\n ~0.0039","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p, n )\n Evaluates the quantile function for the Wilcoxon signed rank test statistic\n with `n` observations at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.signrank.quantile( 0.8, 5 )\n 11\n > y = base.dists.signrank.quantile( 0.5, 4 )\n 5\n\n > y = base.dists.signrank.quantile( 1.1, 5 )\n NaN\n > y = base.dists.signrank.quantile( -0.2, 5 )\n NaN\n\n > y = base.dists.signrank.quantile( NaN, 5 )\n NaN\n > y = base.dists.signrank.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.quantile.factory( n )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n > var y = myQuantile( 0.4 )\n 16\n > y = myQuantile( 1.0 )\n 36\n\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n > var y = myQuantile( 0.4 )\n 16\n > y = myQuantile( 1.0 )\n 36","base.dists.t.cdf":"\nbase.dists.t.cdf( x, v )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.t.cdf( 2.0, 0.1 )\n ~0.611\n > y = base.dists.t.cdf( 1.0, 2.0 )\n ~0.789\n > y = base.dists.t.cdf( -1.0, 4.0 )\n ~0.187\n > y = base.dists.t.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.t.cdf( 0.0, NaN )\n NaN\n > y = base.dists.t.cdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.cdf.factory( v )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.t.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n ~0.816\n > y = mycdf( 1.0 )\n ~0.699\n\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.t.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n ~0.816\n > y = mycdf( 1.0 )\n ~0.699","base.dists.t.entropy":"\nbase.dists.t.entropy( v )\n Returns the differential entropy of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.t.entropy( 11.0 )\n ~1.512\n > v = base.dists.t.entropy( 4.5 )\n ~1.652\n\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v )\n Returns the excess kurtosis of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 2`, the function returns `NaN`.\n\n If provided `2 < v <= 4`, the function returns positive infinity.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.t.kurtosis( 11.0 )\n ~0.857\n > v = base.dists.t.kurtosis( 4.5 )\n 12.0\n\n","base.dists.t.mean":"\nbase.dists.t.mean( v )\n Returns the expected value of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.t.mean( 11.0 )\n 0.0\n > v = base.dists.t.mean( 4.5 )\n 0.0\n\n","base.dists.t.median":"\nbase.dists.t.median( v )\n Returns the median of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.t.median( 11.0 )\n 0.0\n > v = base.dists.t.median( 4.5 )\n 0.0\n\n","base.dists.t.mode":"\nbase.dists.t.mode( v )\n Returns the mode of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.t.mode( 11.0 )\n 0.0\n > v = base.dists.t.mode( 4.5 )\n 0.0\n\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x, v )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.t.pdf( 0.3, 4.0 )\n ~0.355\n > y = base.dists.t.pdf( 2.0, 0.7 )\n ~0.058\n > y = base.dists.t.pdf( -1.0, 0.5 )\n ~0.118\n > y = base.dists.t.pdf( 0.0, NaN )\n NaN\n > y = base.dists.t.pdf( NaN, 2.0 )\n NaN\n > y = base.dists.t.pdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.pdf.factory( v )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.t.pdf.factory( 3.0 );\n > var y = myPDF( 1.0 )\n ~0.207\n\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.t.pdf.factory( 3.0 );\n > var y = myPDF( 1.0 )\n ~0.207","base.dists.t.quantile":"\nbase.dists.t.quantile( p, v )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.t.quantile( 0.8, 1.0 )\n ~1.376\n > y = base.dists.t.quantile( 0.1, 1.0 )\n ~-3.078\n > y = base.dists.t.quantile( 0.5, 0.1 )\n 0.0\n\n > y = base.dists.t.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.t.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.t.quantile( 0.0, NaN )\n NaN\n\n > y = base.dists.t.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.t.quantile.factory( v )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n > var y = myQuantile( 0.2 )\n ~-0.941\n > y = myQuantile( 0.9 )\n ~1.533\n\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n > var y = myQuantile( 0.2 )\n ~-0.941\n > y = myQuantile( 0.9 )\n ~1.533","base.dists.t.skewness":"\nbase.dists.t.skewness( v )\n Returns the skewness of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 3`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.t.skewness( 11.0 )\n 0.0\n > v = base.dists.t.skewness( 4.5 )\n 0.0\n\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v )\n Returns the standard deviation of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.t.stdev( 9.0 )\n ~1.134\n > v = base.dists.t.stdev( 4.5 )\n ~1.342\n\n","base.dists.t.T":"\nbase.dists.t.T( [v] )\n Returns a Student's t distribution object.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n t: Object\n Distribution instance.\n\n t.v: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n t.entropy: number\n Read-only property which returns the differential entropy.\n\n t.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n t.mean: number\n Read-only property which returns the expected value.\n\n t.median: number\n Read-only property which returns the median.\n\n t.mode: number\n Read-only property which returns the mode.\n\n t.skewness: number\n Read-only property which returns the skewness.\n\n t.stdev: number\n Read-only property which returns the standard deviation.\n\n t.variance: number\n Read-only property which returns the variance.\n\n t.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n t.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n t.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n t.pdf: Function\n Evaluates the probability density function (PDF).\n\n t.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var t = base.dists.t.T( 6.0 );\n > t.v\n 6.0\n > t.entropy\n ~1.592\n > t.kurtosis\n 3.0\n > t.mean\n 0.0\n > t.median\n 0.0\n > t.mode\n 0.0\n > t.skewness\n 0.0\n > t.stdev\n ~1.225\n > t.variance\n 1.5\n > t.cdf( 1.0 )\n ~0.822\n > t.logcdf( 1.0 )\n ~-0.196\n > t.logpdf( 1.5 )\n ~-2.075\n > t.pdf( 1.5 )\n ~0.126\n > t.quantile( 0.8 )\n ~0.906\n\n","base.dists.t.variance":"\nbase.dists.t.variance( v )\n Returns the variance of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.t.variance( 9.0 )\n ~1.286\n > v = base.dists.t.variance( 4.5 )\n ~1.8\n\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x, a, b, c )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\n 0.875\n > y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\n 0.75\n > y = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.278\n > y = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.cdf.factory( a, b, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n > var y = mycdf( 0.5 )\n 0.0125\n > y = mycdf( 8.0 )\n 0.95\n\n\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a, b, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n > var y = mycdf( 0.5 )\n 0.0125\n > y = mycdf( 8.0 )\n 0.95","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a, b, c )\n Returns the differential entropy of a triangular distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\n ~-0.193\n > v = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\n ~1.886\n > v = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n ~1.599\n\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a, b, c )\n Returns the excess kurtosis of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\n -0.6\n > v = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\n -0.6\n > v = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n -0.6\n\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x, a, b, c )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.134\n > y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\n ~-0.288\n > y = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\n ~-1.281\n > y = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logcdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n > var y = mylogcdf( 0.5 )\n ~-4.382\n > y = mylogcdf( 8.0 )\n ~-0.051\n\n\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n > var y = mylogcdf( 0.5 )\n ~-4.382\n > y = mylogcdf( 8.0 )\n ~-0.051","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x, a, b, c )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.693\n > y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\n 0.0\n > y = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\n ~-2.89\n > y = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logpdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n > var y = mylogpdf( 2.0 )\n ~-2.526\n > y = mylogpdf( 12.0 )\n -Infinity\n\n\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n > var y = mylogpdf( 2.0 )\n ~-2.526\n > y = mylogpdf( 12.0 )\n -Infinity","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a, b, c )\n Returns the expected value of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\n ~0.6\n > v = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\n 7.0\n > v = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a, b, c )\n Returns the median of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\n ~0.632\n > v = base.dists.triangular.median( 4.0, 12.0, 5.0 )\n ~6.708\n > v = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t, a, b, c )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\n ~1.021\n > y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\n ~1.111\n > y = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\n ~24.334\n > y = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\n ~1.381\n > y = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.mgf.factory( a, b, c )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n > var y = mymgf( -1.0 )\n ~0.3996\n > y = mymgf( 2.0 )\n ~10.205\n\n\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a, b, c )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n > var y = mymgf( -1.0 )\n ~0.3996\n > y = mymgf( 2.0 )\n ~10.205","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a, b, c )\n Returns the mode of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\n 0.8\n > v = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\n 5.0\n > v = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x, a, b, c )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\n 0.5\n > y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\n 1.0\n > y = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.056\n > y = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.pdf.factory( a, b, c )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n > var y = mypdf( 2.0 )\n 0.08\n > y = mypdf( 12.0 )\n 0.0\n\n\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a, b, c )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n > var y = mypdf( 2.0 )\n 0.08\n > y = mypdf( 12.0 )\n 0.0","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p, a, b, c )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\n ~0.553\n > y = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\n ~-0.452\n > y = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\n -14.0\n > y = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\n ~11.056\n\n > y = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\n NaN\n\n > y = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\n NaN\n\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.quantile.factory( a, b, c )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n > var y = myquantile( 0.4 )\n ~2.658\n > y = myquantile( 0.8 )\n ~3.225\n\n\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a, b, c )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n > var y = myquantile( 0.4 )\n ~2.658\n > y = myquantile( 0.8 )\n ~3.225","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a, b, c )\n Returns the skewness of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\n ~-0.476\n > v = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\n ~0.532\n > v = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n 0.0\n\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a, b, c )\n Returns the standard deviation of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\n ~0.216\n > v = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\n ~1.78\n > v = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n ~1.225\n\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a, b, c] )\n Returns a triangular distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b` and `c`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a` and `c`. Default: `1.0`.\n\n c: number (optional)\n Mode. Must be greater than `a` and smaller than `b`. Default: `0.5`.\n\n Returns\n -------\n triangular: Object\n Distribution instance.\n\n triangular.a: number\n Minimum support. If set, the value must be smaller or equal to `b` and\n `c`.\n\n triangular.b: number\n Maximum support. If set, the value must be greater than or equal to `a`\n and `c`.\n\n triangular.c: number\n Mode. If set, the value must be greater than or equal to `a` and smaller\n than or equal to `b`.\n\n triangular.entropy: number\n Read-only property which returns the differential entropy.\n\n triangular.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n triangular.mean: number\n Read-only property which returns the expected value.\n\n triangular.median: number\n Read-only property which returns the median.\n\n triangular.mode: number\n Read-only property which returns the mode.\n\n triangular.skewness: number\n Read-only property which returns the skewness.\n\n triangular.stdev: number\n Read-only property which returns the standard deviation.\n\n triangular.variance: number\n Read-only property which returns the variance.\n\n triangular.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n triangular.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n triangular.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n triangular.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n triangular.pdf: Function\n Evaluates the probability density function (PDF).\n\n triangular.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\n > triangular.a\n 0.0\n > triangular.b\n 1.0\n > triangular.c\n 0.5\n > triangular.entropy\n ~-0.193\n > triangular.kurtosis\n -0.6\n > triangular.mean\n 0.5\n > triangular.median\n 0.5\n > triangular.mode\n 0.5\n > triangular.skewness\n 0.0\n > triangular.stdev\n ~0.204\n > triangular.variance\n ~0.042\n > triangular.cdf( 0.8 )\n 0.92\n > triangular.logcdf( 0.8 )\n ~-0.083\n > triangular.logpdf( 0.8 )\n ~-0.223\n > triangular.mgf( 0.8 )\n ~1.512\n > triangular.pdf( 0.8 )\n ~0.8\n > triangular.quantile( 0.8 )\n ~0.684\n\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a, b, c )\n Returns the variance of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\n ~0.047\n > v = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\n ~3.167\n > v = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n ~1.5\n\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\n 0.9\n > y = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\n 0.25\n > y = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8\n\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a, b )\n Returns the differential entropy of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.uniform.entropy( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.entropy( 4.0, 12.0 )\n ~2.079\n > v = base.dists.uniform.entropy( 2.0, 8.0 )\n ~1.792\n\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a, b )\n Returns the excess kurtosis of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 4.0, 12.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 2.0, 8.0 )\n -1.2\n\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\n ~-0.105\n > y = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\n ~-1.386\n > y = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223\n\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\n ~-1.386\n > y = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\n -infinity\n > y = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\n 0.0\n > y = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -infinity\n\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -infinity","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a, b )\n Returns the expected value of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.uniform.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a, b )\n Returns the median of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.uniform.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\n ~372.495\n > y = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\n ~0.688\n > y = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\n ~3.195\n > y = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\n NaN\n > y = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.uniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n > var y = mymgf( 0.1 )\n ~1.916\n > y = mymgf( 1.1 )\n ~1339.321\n\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n > var y = mymgf( 0.1 )\n ~1.916\n > y = mymgf( 1.1 )\n ~1339.321","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x, a, b )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\n 0.25\n > y = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\n 1.0\n > y = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n 1.0\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n 1.0\n > y = myPDF( 5.0 )\n 0.0","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p, a, b )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\n 0.8\n > y = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\n 5.0\n\n > y = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n 3.2\n\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n 3.2","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a, b )\n Returns the skewness of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.uniform.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.uniform.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a, b )\n Returns the standard deviation of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.uniform.stdev( 0.0, 1.0 )\n ~0.289\n > v = base.dists.uniform.stdev( 4.0, 12.0 )\n ~2.309\n > v = base.dists.uniform.stdev( 2.0, 8.0 )\n ~1.732\n\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a, b] )\n Returns a uniform distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n uniform: Object\n Distribution instance.\n\n uniform.a: number\n Minimum support. If set, the value must be smaller than `b`.\n\n uniform.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n uniform.entropy: number\n Read-only property which returns the differential entropy.\n\n uniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n uniform.mean: number\n Read-only property which returns the expected value.\n\n uniform.median: number\n Read-only property which returns the median.\n\n uniform.skewness: number\n Read-only property which returns the skewness.\n\n uniform.stdev: number\n Read-only property which returns the standard deviation.\n\n uniform.variance: number\n Read-only property which returns the variance.\n\n uniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n uniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n uniform.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n uniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n uniform.pdf: Function\n Evaluates the probability density function (PDF).\n\n uniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\n > uniform.a\n 0.0\n > uniform.b\n 1.0\n > uniform.entropy\n 0.0\n > uniform.kurtosis\n -1.2\n > uniform.mean\n 0.5\n > uniform.median\n 0.5\n > uniform.skewness\n 0.0\n > uniform.stdev\n ~0.289\n > uniform.variance\n ~0.083\n > uniform.cdf( 0.8 )\n 0.8\n > uniform.logcdf( 0.5 )\n ~-0.693\n > uniform.logpdf( 1.0 )\n ~-0.0\n > uniform.mgf( 0.8 )\n ~1.532\n > uniform.pdf( 0.8 )\n 1.0\n > uniform.quantile( 0.8 )\n 0.8\n\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a, b )\n Returns the variance of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.uniform.variance( 0.0, 1.0 )\n ~0.083\n > v = base.dists.uniform.variance( 4.0, 12.0 )\n ~5.333\n > v = base.dists.uniform.variance( 2.0, 8.0 )\n 3.0\n\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763\n\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k, λ )\n Returns the differential entropy of a Weibull distribution (in nats).\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.weibull.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.entropy( 4.0, 12.0 )\n ~2.532\n > v = base.dists.weibull.entropy( 8.0, 2.0 )\n ~0.119\n\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k, λ )\n Returns the excess kurtosis of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.weibull.kurtosis( 4.0, 12.0 )\n ~-0.252\n > v = base.dists.weibull.kurtosis( 8.0, 2.0 )\n ~0.328\n\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x, k, λ )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\n ~-0.145\n > y = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27\n\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x, k, λ )\n Evaluates the logarithm of the probability density function (PDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\n ~-3.307\n > y = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863\n\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k, λ )\n Returns the expected value of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.weibull.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.mean( 4.0, 12.0 )\n ~10.877\n > v = base.dists.weibull.mean( 8.0, 2.0 )\n ~1.883\n\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k, λ )\n Returns the median of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.weibull.median( 1.0, 1.0 )\n ~0.693\n > v = base.dists.weibull.median( 4.0, 12.0 )\n ~10.949\n > v = base.dists.weibull.median( 8.0, 2.0 )\n ~1.91\n\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x, k, λ )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\n ~2.0\n > y = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\n ~0.019\n\n > y = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n NaN\n\n\nbase.dists.weibull.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n > var y = myMGF( 0.8 )\n ~3150.149\n > y = myMGF( 0.08 )\n ~2.137\n\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n > var y = myMGF( 0.8 )\n ~3150.149\n > y = myMGF( 0.08 )\n ~2.137","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k, λ )\n Returns the mode of a Weibull distribution.\n\n If `0 < k <= 1`, the function returns `0.0`.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.weibull.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.weibull.mode( 4.0, 12.0 )\n ~11.167\n > v = base.dists.weibull.mode( 8.0, 2.0 )\n ~1.967\n\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\n ~0.037\n > y = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n > var y = myPDF( 7.0 )\n ~0.155\n\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n > var y = myPDF( 7.0 )\n ~0.155","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p, k, λ )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\n ~1.609\n > y = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\n ~3.33\n\n > y = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n > var y = myQuantile( 0.4 )\n ~7.147\n\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n > var y = myQuantile( 0.4 )\n ~7.147","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k, λ )\n Returns the skewness of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.weibull.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.weibull.skewness( 4.0, 12.0 )\n ~-0.087\n > v = base.dists.weibull.skewness( 8.0, 2.0 )\n ~-0.534\n\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k, λ )\n Returns the standard deviation of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.weibull.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.stdev( 4.0, 12.0 )\n ~3.051\n > v = base.dists.weibull.stdev( 8.0, 2.0 )\n ~0.279\n\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k, λ )\n Returns the variance of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.weibull.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.variance( 4.0, 12.0 )\n ~9.311\n > v = base.dists.weibull.variance( 8.0, 2.0 )\n ~0.078\n\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k, λ] )\n Returns a Weibull distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n λ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n weibull: Object\n Distribution instance.\n\n weibull.k: number\n Shape parameter. If set, the value must be greater than `0`.\n\n weibull.lambda: number\n Scale parameter. If set, the value must be greater than `0`.\n\n weibull.entropy: number\n Read-only property which returns the differential entropy.\n\n weibull.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n weibull.mean: number\n Read-only property which returns the expected value.\n\n weibull.median: number\n Read-only property which returns the median.\n\n weibull.mode: number\n Read-only property which returns the mode.\n\n weibull.skewness: number\n Read-only property which returns the skewness.\n\n weibull.stdev: number\n Read-only property which returns the standard deviation.\n\n weibull.variance: number\n Read-only property which returns the variance.\n\n weibull.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n weibull.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n weibull.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n weibull.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n weibull.pdf: Function\n Evaluates the probability density function (PDF).\n\n weibull.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\n > weibull.k\n 6.0\n > weibull.lambda\n 5.0\n > weibull.entropy\n ~1.299\n > weibull.kurtosis\n ~0.035\n > weibull.mean\n ~4.639\n > weibull.median\n ~4.704\n > weibull.mode\n ~4.85\n > weibull.skewness\n ~-0.373\n > weibull.stdev\n ~0.899\n > weibull.variance\n ~0.808\n > weibull.cdf( 3.0 )\n ~0.046\n > weibull.logcdf( 3.0 )\n ~-3.088\n > weibull.logpdf( 1.0 )\n ~-7.865\n > weibull.mgf( -0.5 )\n ~0.075\n > weibull.pdf( 3.0 )\n ~0.089\n > weibull.quantile( 0.8 )\n ~5.413\n\n","base.ellipe":"\nbase.ellipe( m )\n Computes the complete elliptic integral of the second kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipe( 0.5 )\n ~1.351\n > y = base.ellipe( -1.0 )\n ~1.910\n > y = base.ellipe( 2.0 )\n NaN\n > y = base.ellipe( PINF )\n NaN\n > y = base.ellipe( NINF )\n NaN\n > y = base.ellipe( NaN )\n NaN\n\n See Also\n --------\n base.ellipj, base.ellipk\n","base.ellipj":"\nbase.ellipj( u, m )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: Array\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var v = base.ellipj( 0.3, 0.5 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > v = base.ellipj( 0.0, 0.0 )\n [ ~0.0, ~1.0, ~1.0, ~0.0 ]\n > v = base.ellipj( Infinity, 1.0 )\n [ ~1.0, ~0.0, ~0.0, ~1.571 ]\n > v = base.ellipj( 0.0, -2.0)\n [ ~0.0, ~1.0, ~1.0, NaN ]\n > v = base.ellipj( NaN, NaN )\n [ NaN, NaN, NaN, NaN ]\n\n\nbase.ellipj.assign( u, m, out, stride, offset )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var out = new Float64Array( 4 );\n > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > var bool = ( v === out )\n true\n\n\nbase.ellipj.sn( u, m )\n Computes the Jacobi elliptic function sn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function sn.\n\n Examples\n --------\n > var v = base.ellipj.sn( 0.3, 0.5 )\n ~0.293\n\n\nbase.ellipj.cn( u, m )\n Computes the Jacobi elliptic functions cn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function cn.\n\n Examples\n --------\n > var v = base.ellipj.cn( 0.3, 0.5 )\n ~0.956\n\n\nbase.ellipj.dn( u, m )\n Computes the Jacobi elliptic function dn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function dn.\n\n Examples\n --------\n > var v = base.ellipj.dn( 0.3, 0.5 )\n ~0.978\n\n\nbase.ellipj.am( u, m )\n Computes the Jacobi amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function am.\n\n Examples\n --------\n > var v = base.ellipj.am( 0.3, 0.5 )\n ~0.298\n\n See Also\n --------\n base.ellipe, base.ellipk","base.ellipj.assign":"\nbase.ellipj.assign( u, m, out, stride, offset )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var out = new Float64Array( 4 );\n > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > var bool = ( v === out )\n true","base.ellipj.sn":"\nbase.ellipj.sn( u, m )\n Computes the Jacobi elliptic function sn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function sn.\n\n Examples\n --------\n > var v = base.ellipj.sn( 0.3, 0.5 )\n ~0.293","base.ellipj.cn":"\nbase.ellipj.cn( u, m )\n Computes the Jacobi elliptic functions cn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function cn.\n\n Examples\n --------\n > var v = base.ellipj.cn( 0.3, 0.5 )\n ~0.956","base.ellipj.dn":"\nbase.ellipj.dn( u, m )\n Computes the Jacobi elliptic function dn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function dn.\n\n Examples\n --------\n > var v = base.ellipj.dn( 0.3, 0.5 )\n ~0.978","base.ellipj.am":"\nbase.ellipj.am( u, m )\n Computes the Jacobi amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function am.\n\n Examples\n --------\n > var v = base.ellipj.am( 0.3, 0.5 )\n ~0.298\n\n See Also\n --------\n base.ellipe, base.ellipk","base.ellipk":"\nbase.ellipk( m )\n Computes the complete elliptic integral of the first kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipk( 0.5 )\n ~1.854\n > y = base.ellipk( -1.0 )\n ~1.311\n > y = base.ellipk( 2.0 )\n NaN\n > y = base.ellipk( PINF )\n NaN\n > y = base.ellipk( NINF )\n NaN\n > y = base.ellipk( NaN )\n NaN\n\n See Also\n --------\n base.ellipe, base.ellipj\n","base.epsdiff":"\nbase.epsdiff( x, y[, scale] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If computing the relative difference in units of epsilon will result in\n overflow, the function returns the maximum double-precision floating-point\n number.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference in units of double-precision floating-point epsilon.\n\n Examples\n --------\n > var d = base.epsdiff( 12.15, 12.149999999999999 )\n ~0.658\n > d = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n ~64761.512\n\n // Custom scale function:\n > function scale( x, y ) { return ( x > y ) ? y : x; };\n > d = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n ~44\n\n See Also\n --------\n base.absdiff, base.reldiff\n","base.erf":"\nbase.erf( x )\n Evaluates the error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the error function is an odd function (i.e., `erf(-x) == -erf(x)`), if\n provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erf( 2.0 )\n ~0.9953\n > y = base.erf( -1.0 )\n ~-0.8427\n > y = base.erf( -0.0 )\n -0.0\n > y = base.erf( NaN )\n NaN\n\n See Also\n --------\n base.erfc, base.erfinv, base.erfcinv\n","base.erfc":"\nbase.erfc( x )\n Evaluates the complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfc( 2.0 )\n ~0.0047\n > y = base.erfc( -1.0 )\n ~1.8427\n > y = base.erfc( 0.0 )\n 1.0\n > y = base.erfc( PINF )\n 0.0\n > y = base.erfc( NINF )\n 2.0\n > y = base.erfc( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfinv, base.erfcinv, base.erfcx\n","base.erfcinv":"\nbase.erfcinv( x )\n Evaluates the inverse complementary error function.\n\n The domain of `x` is restricted to `[0,2]`. If `x` is outside this interval,\n the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcinv( 0.5 )\n ~0.4769\n > y = base.erfcinv( 0.8 )\n ~0.1791\n > y = base.erfcinv( 0.0 )\n Infinity\n > y = base.erfcinv( 2.0 )\n -Infinity\n > y = base.erfcinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfinv, base.erfcx\n","base.erfcx":"\nbase.erfcx( x )\n Evaluates the scaled complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcx( 1.0 )\n ~0.4276\n > y = base.erfcx( -1.0 )\n ~5.01\n > y = base.erfcx( 0.0 )\n 1.0\n > y = base.erfcx( NaN )\n NaN\n\n See Also\n --------\n base.erfc, base.erfcinv, base.erf, base.erfinv","base.erfinv":"\nbase.erfinv( x )\n Evaluates the inverse error function.\n\n If `|x| > 1`, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the inverse error function is an odd function (i.e., `erfinv(-x) ==\n -erfinv(x)`), if provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfinv( 0.5 )\n ~0.4769\n > y = base.erfinv( 0.8 )\n ~0.9062\n > y = base.erfinv( 0.0 )\n 0.0\n > y = base.erfinv( -0.0 )\n -0.0\n > y = base.erfinv( -1.0 )\n -Infinity\n > y = base.erfinv( 1.0 )\n Infinity\n > y = base.erfinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfcinv\n","base.eta":"\nbase.eta( s )\n Evaluates the Dirichlet eta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.eta( 0.0 )\n 0.5\n > y = base.eta( -1.0 )\n 0.25\n > y = base.eta( 1.0 )\n ~0.6931\n > y = base.eta( 3.14 )\n ~0.9096\n > y = base.eta( NaN )\n NaN\n\n","base.evalpoly":"\nbase.evalpoly( c, x )\n Evaluates a polynomial.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n out: number\n Evaluated polynomial.\n\n Examples\n --------\n > var arr = [ 3.0, 2.0, 1.0 ];\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = base.evalpoly( arr, 10.0 )\n 123.0\n\n\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var polyval = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = polyval( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = polyval( 5.0 )\n 38.0\n\n See Also\n --------\n base.evalrational\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var polyval = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = polyval( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = polyval( 5.0 )\n 38.0\n\n See Also\n --------\n base.evalrational","base.evalrational":"\nbase.evalrational( P, Q, x )\n Evaluates a rational function.\n\n A rational function `f(x)` is defined as\n\n P(x)\n f(x) = ----\n Q(x)\n\n where both `P(x)` and `Q(x)` are polynomials in `x`.\n\n The coefficients for both `P` and `Q` should be sorted in ascending degree.\n\n For polynomials of different degree, the coefficient array for the lower\n degree polynomial should be padded with zeros.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the rational function.\n\n Returns\n -------\n out: number\n Evaluated rational function.\n\n Examples\n --------\n // 2x^3 + 4x^2 - 5x^1 - 6x^0\n > var P = [ -6.0, -5.0, 4.0, 2.0 ];\n\n // 0.5x^1 + 3x^0\n > var Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n // Evaluate the rational function:\n > var v = base.evalrational( P, Q, 6.0 )\n 90.0\n\n\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var rational = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = rational( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = rational( 2.0 )\n 1.5\n\n See Also\n --------\n base.evalpoly\n","base.evalrational.factory":"\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var rational = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = rational( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = rational( 2.0 )\n 1.5\n\n See Also\n --------\n base.evalpoly","base.exp":"\nbase.exp( x )\n Evaluates the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp( 4.0 )\n ~54.5982\n > y = base.exp( -9.0 )\n ~1.234e-4\n > y = base.exp( 0.0 )\n 1.0\n > y = base.exp( NaN )\n NaN\n\n See Also\n --------\n base.exp10, base.exp2, base.expm1, base.ln\n","base.exp2":"\nbase.exp2( x )\n Evaluates the base 2 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp2( 3.0 )\n 8.0\n > y = base.exp2( -9.0 )\n ~0.002\n > y = base.exp2( 0.0 )\n 1.0\n > y = base.exp2( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp10, base.log2\n","base.exp10":"\nbase.exp10( x )\n Evaluates the base 10 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp10( 3.0 )\n 1000\n > y = base.exp10( -9.0 )\n 1.0e-9\n > y = base.exp10( 0.0 )\n 1.0\n > y = base.exp10( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp2, base.log10\n","base.expit":"\nbase.expit( x )\n Evaluates the standard logistic function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expit( 0.0 )\n 0.5\n > y = base.expit( 1.0 )\n ~0.731\n > y = base.expit( -1.0 )\n ~0.269\n > y = base.expit( Infinity )\n 1.0\n > y = base.expit( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.logit","base.expm1":"\nbase.expm1( x )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1( 0.2 )\n ~0.221\n > y = base.expm1( -9.0 )\n ~-1.0\n > y = base.expm1( 0.0 )\n 0.0\n > y = base.expm1( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.expm1rel\n","base.expm1rel":"\nbase.expm1rel( x )\n Relative error exponential.\n\n When `x` is near zero,\n\n e^x - 1\n\n can suffer catastrophic cancellation (i.e., significant loss of precision).\n This function avoids the loss of precision when `x` is near zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1rel( 0.0 )\n 1.0\n > y = base.expm1rel( 1.0 )\n ~1.718\n > y = base.expm1rel( -1.0 )\n ~0.632\n > y = base.expm1rel( NaN )\n NaN\n\t\n See Also\n --------\n base.exp, base.expm1\n","base.exponent":"\nbase.exponent( x )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponent( 3.14e-307 )\n -1019\n > exponent = base.exponent( -3.14 )\n 1\n > exponent = base.exponent( 0.0 )\n -1023\n > exponent = base.exponent( NaN )\n 1024\n\n See Also\n --------\n base.exponentf\n","base.exponentf":"\nbase.exponentf( x )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\n 114\n > exponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\n -112\n > exponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\n 1\n > exponent = base.exponentf( 0.0 )\n -127\n > exponent = base.exponentf( NaN )\n 128\n\n See Also\n --------\n base.exponent\n","base.factorial":"\nbase.factorial( x )\n Evaluates the factorial of `x`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Factorial.\n\n Examples\n --------\n > var y = base.factorial( 3.0 )\n 6.0\n > y = base.factorial( -1.5 )\n ~-3.545\n > y = base.factorial( -0.5 )\n ~1.772\n > y = base.factorial( 0.5 )\n ~0.886\n > y = base.factorial( -10.0 )\n NaN\n > y = base.factorial( 171.0 )\n Infinity\n > y = base.factorial( NaN )\n NaN\n\n See Also\n --------\n base.factorialln\n","base.factorial2":"\nbase.factorial2( n )\n Evaluates the double factorial of `n`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: number\n Input value.\n\n Returns\n -------\n y: number\n Double factorial.\n\n Examples\n --------\n > var y = base.factorial2( 3 )\n 3\n > y = base.factorial2( 5 )\n 15\n > y = base.factorial2( 6 )\n 48\n > y = base.factorial2( 301 )\n Infinity\n > y = base.factorial2( NaN )\n NaN\n\n See Also\n --------\n base.factorial\n","base.factorialln":"\nbase.factorialln( x )\n Evaluates the natural logarithm of the factorial of `x`.\n\n For input values other than negative integers, the function returns\n\n ln( x! ) = ln( Γ(x+1) )\n\n where `Γ` is the Gamma function. For negative integers, the function returns\n `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the factorial of `x`.\n\n Examples\n --------\n > var y = base.factorialln( 3.0 )\n ~1.792\n > y = base.factorialln( 2.4 )\n ~1.092\n > y = base.factorialln( -1.0 )\n NaN\n > y = base.factorialln( -1.5 )\n ~1.266\n > y = base.factorialln( NaN )\n NaN\n\n See Also\n --------\n base.factorial\n","base.fallingFactorial":"\nbase.fallingFactorial( x, n )\n Computes the falling factorial of `x` and `n`.\n\n If not provided a nonnegative integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.fallingFactorial( 0.9, 5 )\n ~0.644\n > v = base.fallingFactorial( -9.0, 3 )\n -990.0\n > v = base.fallingFactorial( 0.0, 2 )\n 0.0\n > v = base.fallingFactorial( 3.0, -2 )\n NaN\n\n See Also\n --------\n base.risingFactorial\n","base.fibonacci":"\nbase.fibonacci( n )\n Computes the nth Fibonacci number.\n\n Fibonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2}\n\n with seed values F_0 = 0 and F_1 = 1.\n\n If `n` is greater than `78`, the function returns `NaN`, as larger Fibonacci\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Fibonacci number.\n\n Examples\n --------\n > var y = base.fibonacci( 0 )\n 0\n > y = base.fibonacci( 1 )\n 1\n > y = base.fibonacci( 2 )\n 1\n > y = base.fibonacci( 3 )\n 2\n > y = base.fibonacci( 4 )\n 3\n > y = base.fibonacci( 79 )\n NaN\n > y = base.fibonacci( NaN )\n NaN\n\n See Also\n --------\n base.binet, base.fibonacciIndex, base.lucas, base.negafibonacci\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F )\n Computes the Fibonacci number index.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `F <= 1` or `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n F: integer\n Fibonacci number.\n\n Returns\n -------\n n: number\n Fibonacci number index.\n\n Examples\n --------\n > var n = base.fibonacciIndex( 2 )\n 3\n > n = base.fibonacciIndex( 3 )\n 4\n > n = base.fibonacciIndex( 5 )\n 5\n > n = base.fibonacciIndex( NaN )\n NaN\n > n = base.fibonacciIndex( 1 )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.fibpoly":"\nbase.fibpoly( n, x )\n Evaluates a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Fibonacci polynomial.\n\n Returns\n -------\n out: number\n Evaluated Fibonacci polynomial.\n\n Examples\n --------\n // 2^4 + 3*2^2 + 1\n > var v = base.fibpoly( 5, 2.0 )\n 29.0\n\n\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n See Also\n --------\n base.evalpoly, base.lucaspoly\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n See Also\n --------\n base.evalpoly, base.lucaspoly","base.firstCodePoint":"\nbase.firstCodePoint( str, n )\n Returns the first `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstCodePoint( 'beep', 1 )\n 'b'\n > out = base.firstCodePoint( 'Boop', 1 )\n 'B'\n > out = base.firstCodePoint( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodeUnit, base.firstGraphemeCluster, firstChar\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str, n )\n Returns the first `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstCodeUnit( 'beep', 1 )\n 'b'\n > out = base.firstCodeUnit( 'Boop', 1 )\n 'B'\n > out = base.firstCodeUnit( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodePoint, base.firstGraphemeCluster, firstChar\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str, n )\n Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstGraphemeCluster( 'beep', 1 )\n 'b'\n > out = base.firstGraphemeCluster( 'Boop', 1 )\n 'B'\n > out = base.firstGraphemeCluster( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodeUnit, base.firstCodePoint, firstChar\n","base.flipsign":"\nbase.flipsign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `2047`, a significand greater than `0`, and a sign bit equal to either `1`\n or `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`; otherwise, behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsign( -3.0, 10.0 )\n -3.0\n > z = base.flipsign( -3.0, -1.0 )\n 3.0\n > z = base.flipsign( 1.0, -0.0 )\n -1.0\n > z = base.flipsign( -3.0, -0.0 )\n 3.0\n > z = base.flipsign( -0.0, 1.0 )\n -0.0\n > z = base.flipsign( 0.0, -1.0 )\n -0.0\n\n See Also\n --------\n base.copysign\n","base.flipsignf":"\nbase.flipsignf( x, y )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `255`, a significand greater than `0`, and a sign bit equal to either `1` or\n `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`; otherwise, behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Single-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsignf( -3.0, 10.0 )\n -3.0\n > z = base.flipsignf( -3.0, -1.0 )\n 3.0\n > z = base.flipsignf( 1.0, -0.0 )\n -1.0\n > z = base.flipsignf( -3.0, -0.0 )\n 3.0\n > z = base.flipsignf( -0.0, 1.0 )\n -0.0\n > z = base.flipsignf( 0.0, -1.0 )\n -0.0\n\n See Also\n --------\n base.copysignf, base.flipsign\n","base.float32ToInt32":"\nbase.float32ToInt32( x )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\n 0\n > y = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\n -3\n > y = base.float32ToInt32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToInt32( FLOAT32_PINF )\n 0\n > y = base.float32ToInt32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToUint32","base.float32ToUint32":"\nbase.float32ToUint32( x )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\n 0\n > y = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\n 4294967293\n > y = base.float32ToUint32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToUint32( FLOAT32_PINF )\n 0\n > y = base.float32ToUint32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToInt32","base.float64ToFloat32":"\nbase.float64ToFloat32( x )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: float\n Nearest single-precision floating-point number.\n\n Examples\n --------\n > var y = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n","base.float64ToInt32":"\nbase.float64ToInt32( x )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToInt32( 4294967295.0 )\n -1\n > y = base.float64ToInt32( 3.14 )\n 3\n > y = base.float64ToInt32( -3.14 )\n -3\n > y = base.float64ToInt32( NaN )\n 0\n > y = base.float64ToInt32( PINF )\n 0\n > y = base.float64ToInt32( NINF )\n 0\n\n See Also\n --------\n base.float64ToUint32","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness).\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n Returns\n -------\n out: Uint8Array\n Byte array.\n\n Examples\n --------\n > var y = base.float64ToInt64Bytes( 4294967297.0 )\n \n\n\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Uint8Array( 16 );\n > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n \n\n See Also\n --------\n base.float64ToInt32","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Uint8Array( 16 );\n > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n \n\n See Also\n --------\n base.float64ToInt32","base.float64ToUint32":"\nbase.float64ToUint32( x )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToUint32( 4294967297.0 )\n 1\n > y = base.float64ToUint32( 3.14 )\n 3\n > y = base.float64ToUint32( -3.14 )\n 4294967293\n > y = base.float64ToUint32( NaN )\n 0\n > y = base.float64ToUint32( PINF )\n 0\n > y = base.float64ToUint32( NINF )\n 0\n\n See Also\n --------\n base.float64ToInt32","base.floor":"\nbase.floor( x )\n Rounds a double-precision floating-point number toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor( 3.14 )\n 3.0\n > y = base.floor( -4.2 )\n -5.0\n > y = base.floor( -4.6 )\n -5.0\n > y = base.floor( 9.5 )\n 9.0\n > y = base.floor( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.round\n","base.floor2":"\nbase.floor2( x )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor2( 3.14 )\n 2.0\n > y = base.floor2( -4.2 )\n -8.0\n > y = base.floor2( -4.6 )\n -8.0\n > y = base.floor2( 9.5 )\n 8.0\n > y = base.floor2( 13.0 )\n 8.0\n > y = base.floor2( -13.0 )\n -16.0\n > y = base.floor2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor, base.floor10, base.round2\n","base.floor10":"\nbase.floor10( x )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor10( 3.14 )\n 1.0\n > y = base.floor10( -4.2 )\n -10.0\n > y = base.floor10( -4.6 )\n -10.0\n > y = base.floor10( 9.5 )\n 1.0\n > y = base.floor10( 13.0 )\n 10.0\n > y = base.floor10( -13.0 )\n -100.0\n > y = base.floor10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor, base.floor2, base.round10\n","base.floorb":"\nbase.floorb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.floorb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward negative infinity:\n > y = base.floorb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floor, base.floorn, base.roundb\n","base.floorf":"\nbase.floorf( x )\n Rounds a single-precision floating-point number toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorf( 3.14 )\n 3.0\n > y = base.floorf( -4.2 )\n -5.0\n > y = base.floorf( -4.6 )\n -5.0\n > y = base.floorf( 9.5 )\n 9.0\n > y = base.floorf( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceilf, base.floor\n","base.floorn":"\nbase.floorn( x, n )\n Rounds a double-precision floating-point number to the nearest multiple of\n `10^n` toward negative infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round toward negative infinity behavior:\n > y = base.floorn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.floorn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floor, base.floorb, base.roundn\n","base.floorsd":"\nbase.floorsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorsd( 3.14159, 5 )\n 3.1415\n > y = base.floorsd( 3.14159, 1 )\n 3.0\n > y = base.floorsd( 12368.0, 2 )\n 12000.0\n > y = base.floorsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floor, base.roundsd, base.truncsd\n","base.forEachChar":"\nbase.forEachChar( str, clbk[, thisArg] )\n Invokes a function for each UTF-16 code unit in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character\n - index: character index\n - str: input string\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each UTF-16 code unit in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachChar( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachCodePoint, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str, clbk[, thisArg] )\n Invokes a function for each Unicode code point in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: code point\n - index: starting code point index\n - str: input string\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each Unicode code point in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachCodePoint( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachGraphemeCluster, forEachChar\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str, clbk[, thisArg] )\n Invokes a function for each grapheme cluster (i.e., user-perceived\n character) in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: grapheme cluster\n - index: starting grapheme cluster index\n - str: input string\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each grapheme cluster in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachGraphemeCluster( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachCodePoint, forEachChar\n","base.fresnel":"\nbase.fresnel( x )\n Computes the Fresnel integrals S(x) and C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: Array\n S(x) and C(x).\n\n Examples\n --------\n > var y = base.fresnel( 0.0 )\n [ ~0.0, ~0.0 ]\n > y = base.fresnel( 1.0 )\n [ ~0.438, ~0.780 ]\n > y = base.fresnel( PINF )\n [ ~0.5, ~0.5 ]\n > y = base.fresnel( NINF )\n [ ~-0.5, ~-0.5 ]\n > y = base.fresnel( NaN )\n [ NaN, NaN ]\n\n\nbase.fresnel.assign( x, out, stride, offset )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n S(x) and C(x).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.fresnelc, base.fresnels","base.fresnel.assign":"\nbase.fresnel.assign( x, out, stride, offset )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n S(x) and C(x).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.fresnelc, base.fresnels","base.fresnelc":"\nbase.fresnelc( x )\n Computes the Fresnel integral C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n C(x).\n\n Examples\n --------\n > var y = base.fresnelc( 0.0 )\n ~0.0\n > y = base.fresnelc( 1.0 )\n ~0.780\n > y = base.fresnelc( PINF )\n ~0.5\n > y = base.fresnelc( NINF )\n ~-0.5\n > y = base.fresnelc( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnels\n","base.fresnels":"\nbase.fresnels( x )\n Computes the Fresnel integral S(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n S(x).\n\n Examples\n --------\n > var y = base.fresnels( 0.0 )\n ~0.0\n > y = base.fresnels( 1.0 )\n ~0.438\n > y = base.fresnels( PINF )\n ~0.5\n > y = base.fresnels( NINF )\n ~-0.5\n > y = base.fresnels( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnelc\n","base.frexp":"\nbase.frexp( x )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = base.frexp( 4.0 )\n [ 0.5, 3 ]\n > out = base.frexp( 0.0 )\n [ 0.0, 0 ]\n > out = base.frexp( -0.0 )\n [ -0.0, 0 ]\n > out = base.frexp( NaN )\n [ NaN, 0 ]\n > out = base.frexp( PINF )\n [ Infinity, 0 ]\n > out = base.frexp( NINF )\n [ -Infinity, 0 ]\n\n\nbase.frexp.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.frexp.assign( 4.0, out, 1, 0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.ldexp\n","base.frexp.assign":"\nbase.frexp.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.frexp.assign( 4.0, out, 1, 0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.ldexp","base.fromBinaryString":"\nbase.fromBinaryString( bstr )\n Creates a double-precision floating-point number from a literal bit\n representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var bstr;\n > bstr = '0100000000010000000000000000000000000000000000000000000000000000';\n > var val = base.fromBinaryString( bstr )\n 4.0\n > bstr = '0100000000001001001000011111101101010100010001000010110100011000';\n > val = base.fromBinaryString( bstr )\n 3.141592653589793\n > bstr = '1111111111100001110011001111001110000101111010111100100010100000';\n > val = base.fromBinaryString( bstr )\n -1.0e308\n\n // The function handles subnormals:\n > bstr = '1000000000000000000000000000000000000000000000000001100011010011';\n > val = base.fromBinaryString( bstr )\n -3.14e-320\n > bstr = '0000000000000000000000000000000000000000000000000000000000000001';\n > val = base.fromBinaryString( bstr )\n 5.0e-324\n\n // The function handles special values:\n > bstr = '0000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n 0.0\n > bstr = '1000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -0.0\n > bstr = '0111111111111000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n NaN\n > bstr = '0111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n Infinity\n > bstr = '1111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -Infinity\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var bstr = '01000000100000000000000000000000';\n > var val = base.fromBinaryStringf( bstr )\n 4.0\n > bstr = '01000000010010010000111111011011';\n > val = base.fromBinaryStringf( bstr )\n ~3.14\n > bstr = '11111111011011000011101000110011';\n > val = base.fromBinaryStringf( bstr )\n ~-3.14e+38\n\n // The function handles subnormals:\n > bstr = '10000000000000000000000000010110';\n > val = base.fromBinaryStringf( bstr )\n ~-3.08e-44\n > bstr = '00000000000000000000000000000001';\n > val = base.fromBinaryStringf( bstr )\n ~1.40e-45\n\n // The function handles special values:\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n 0.0\n > bstr = '10000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -0.0\n > bstr = '01111111110000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n NaN\n > bstr = '01111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n Infinity\n > bstr = '11111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -Infinity\n\n See Also\n --------\n base.toBinaryStringf, base.fromBinaryString\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr )\n Creates an unsigned 8-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 8-bit integer.\n\n Examples\n --------\n > var bstr = '01010101';\n > var val = base.fromBinaryStringUint8( bstr )\n 85\n > bstr = '00000000';\n > val = base.fromBinaryStringUint8( bstr )\n 0\n > bstr = '00000010';\n > val = base.fromBinaryStringUint8( bstr )\n 2\n > bstr = '11111111';\n > val = base.fromBinaryStringUint8( bstr )\n 255\n\n See Also\n --------\n base.fromBinaryStringUint16, base.fromBinaryStringUint32, base.toBinaryStringUint8\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr )\n Creates an unsigned 16-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 16-bit integer.\n\n Examples\n --------\n > var bstr = '0101010101010101';\n > var val = base.fromBinaryStringUint16( bstr )\n 21845\n > bstr = '0000000000000000';\n > val = base.fromBinaryStringUint16( bstr )\n 0\n > bstr = '0000000000000010';\n > val = base.fromBinaryStringUint16( bstr )\n 2\n > bstr = '1111111111111111';\n > val = base.fromBinaryStringUint16( bstr )\n 65535\n\n See Also\n --------\n base.toBinaryStringUint16, base.fromBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr )\n Creates an unsigned 32-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var bstr = '01010101010101010101010101010101';\n > var val = base.fromBinaryStringUint32( bstr )\n 1431655765\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringUint32( bstr )\n 0\n > bstr = '00000000000000000000000000000010';\n > val = base.fromBinaryStringUint32( bstr )\n 2\n > bstr = '11111111111111111111111111111111';\n > val = base.fromBinaryStringUint32( bstr )\n 4294967295\n\n See Also\n --------\n base.fromBinaryStringUint16, base.toBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes, stride, offset )\n Converts a signed 64-bit integer byte array to a double-precision floating-\n point number.\n\n The function assumes host byte order (endianness).\n\n Parameters\n ----------\n bytes: Array|TypedArray|Object\n Byte array.\n\n stride: integer\n Index stride.\n\n offset: integer\n Index offset.\n\n Returns\n -------\n out: number\n Number.\n\n Examples\n --------\n > var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\n > var y = base.fromInt64Bytes( bytes, 1, 0 )\n -1.0\n\n See Also\n --------\n base.float64ToInt64Bytes","base.fromWordf":"\nbase.fromWordf( word )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n\n Parameters\n ----------\n word: integer\n Unsigned integer.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var word = 1068180177; // => 0 01111111 01010110010001011010001\n > var f32 = base.fromWordf( word ) // when printed, promoted to float64\n 1.3370000123977661\n\n See Also\n --------\n base.fromWords\n","base.fromWords":"\nbase.fromWords( high, low )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n Parameters\n ----------\n high: integer\n Higher order word (unsigned 32-bit integer).\n\n low: integer\n Lower order word (unsigned 32-bit integer).\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var v = base.fromWords( 1774486211, 2479577218 )\n 3.14e201\n > v = base.fromWords( 3221823995, 1413754136 )\n -3.141592653589793\n > v = base.fromWords( 0, 0 )\n 0.0\n > v = base.fromWords( 2147483648, 0 )\n -0.0\n > v = base.fromWords( 2146959360, 0 )\n NaN\n > v = base.fromWords( 2146435072, 0 )\n Infinity\n > v = base.fromWords( 4293918720, 0 )\n -Infinity\n\n See Also\n --------\n base.fromWordf\n","base.gamma":"\nbase.gamma( x )\n Evaluates the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma( 4.0 )\n 6.0\n > y = base.gamma( -1.5 )\n ~2.363\n > y = base.gamma( -0.5 )\n ~-3.545\n > y = base.gamma( 0.5 )\n ~1.772\n > y = base.gamma( 0.0 )\n Infinity\n > y = base.gamma( -0.0 )\n -Infinity\n > y = base.gamma( NaN )\n NaN\n\n See Also\n --------\n base.gamma1pm1, base.gammainc, base.gammaincinv, base.gammaln\n","base.gamma1pm1":"\nbase.gamma1pm1( x )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma1pm1( 0.2 )\n ~-0.082\n > y = base.gamma1pm1( -6.7 )\n ~-0.991\n > y = base.gamma1pm1( 0.0 )\n 0.0\n > y = base.gamma1pm1( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv, base.gammaln\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z, delta )\n Computes the ratio of two gamma functions.\n\n The ratio is defined as: Γ(z) / Γ(z+Δ).\n\n Parameters\n ----------\n z: number\n First gamma parameter.\n\n delta: number\n Difference.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaDeltaRatio( 2.0, 3.0 )\n ~0.042\n > y = base.gammaDeltaRatio( 4.0, 0.5 )\n ~0.516\n > y = base.gammaDeltaRatio( 100.0, 0.0 )\n 1.0\n > y = base.gammaDeltaRatio( NaN, 3.0 )\n NaN\n > y = base.gammaDeltaRatio( 5.0, NaN )\n NaN\n > y = base.gammaDeltaRatio( NaN, NaN )\n NaN\n\n See Also\n --------\n base.gamma\n","base.gammainc":"\nbase.gammainc( x, s[, regularized[, upper]] )\n Computes the regularized incomplete gamma function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete gamma functions, respectively.\n\n If provided `x < 0` or `s <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n s: number\n Second function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete gamma function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete gamma function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammainc( 6.0, 2.0 )\n ~0.9826\n > y = base.gammainc( 1.0, 2.0, true, true )\n ~0.7358\n > y = base.gammainc( 7.0, 5.0 )\n ~0.8270\n > y = base.gammainc( 7.0, 5.0, false )\n ~19.8482\n > y = base.gammainc( NaN, 2.0 )\n NaN\n > y = base.gammainc( 6.0, NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammaincinv, base.gammaln\n","base.gammaincinv":"\nbase.gammaincinv( p, a[, upper] )\n Computes the inverse of the lower incomplete gamma function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second argument is the scale factor `a`.\n\n By default, the function inverts the lower regularized incomplete gamma\n function, `P(x,a)`. To invert the upper function `Q(x,a)`, set the `upper`\n argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Scale parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete gamma function; i.e., compute `xr` such that `Q(a,xr) = p`.\n Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaincinv( 0.5, 2.0 )\n ~1.678\n > y = base.gammaincinv( 0.1, 10.0 )\n ~6.221\n > y = base.gammaincinv( 0.75, 3.0 )\n ~3.92\n > y = base.gammaincinv( 0.75, 3.0, true )\n ~1.727\n > y = base.gammaincinv( 0.75, NaN )\n NaN\n > y = base.gammaincinv( NaN, 3.0 )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammainc, base.gammaln\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x )\n Calculates the Lanczos sum for the approximation of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSum( 4.0 )\n ~950.366\n > y = base.gammaLanczosSum( -1.5 )\n ~1373366.245\n > y = base.gammaLanczosSum( -0.5 )\n ~-699841.735\n > y = base.gammaLanczosSum( 0.5 )\n ~96074.186\n > y = base.gammaLanczosSum( 0.0 )\n Infinity\n > y = base.gammaLanczosSum( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSumExpGScaled\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Scaled Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSumExpGScaled( 4.0 )\n ~0.018\n > y = base.gammaLanczosSumExpGScaled( -1.5 )\n ~25.337\n > y = base.gammaLanczosSumExpGScaled( -0.5 )\n ~-12.911\n > y = base.gammaLanczosSumExpGScaled( 0.5 )\n ~1.772\n > y = base.gammaLanczosSumExpGScaled( 0.0 )\n Infinity\n > y = base.gammaLanczosSumExpGScaled( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSum\n","base.gammaln":"\nbase.gammaln( x )\n Evaluates the natural logarithm of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the gamma function.\n\n Examples\n --------\n > var y = base.gammaln( 1.0 )\n 0.0\n > y = base.gammaln( 2.0 )\n 0.0\n > y = base.gammaln( 4.0 )\n ~1.792\n > y = base.gammaln( -0.5 )\n ~1.266\n > y = base.gammaln( 0.5 )\n ~0.572\n > y = base.gammaln( 0.0 )\n Infinity\n > y = base.gammaln( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv\n","base.gcd":"\nbase.gcd( a, b )\n Computes the greatest common divisor (gcd).\n\n If both `a` and `b` are `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Greatest common divisor.\n\n Examples\n --------\n > var v = base.gcd( 48, 18 )\n 6\n\n See Also\n --------\n base.lcm\n","base.getHighWord":"\nbase.getHighWord( x )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Higher order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getHighWord( 3.14e201 )\n 1774486211\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n","base.getLowWord":"\nbase.getLowWord( x )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Lower order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getLowWord( 3.14e201 )\n 2479577218\n\n See Also\n --------\n base.getHighWord, base.setHighWord\n","base.hacovercos":"\nbase.hacovercos( x )\n Computes the half-value coversed cosine.\n\n The half-value coversed cosine is defined as `(1 + sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed cosine.\n\n Examples\n --------\n > var y = base.hacovercos( 3.14 )\n ~0.5008\n > y = base.hacovercos( -4.2 )\n ~0.9358\n > y = base.hacovercos( -4.6 )\n ~0.9968\n > y = base.hacovercos( 9.5 )\n ~0.4624\n > y = base.hacovercos( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacoversin, base.havercos\n","base.hacoversin":"\nbase.hacoversin( x )\n Computes the half-value coversed sine.\n\n The half-value coversed sine is defined as `(1 - sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed sine.\n\n Examples\n --------\n > var y = base.hacoversin( 3.14 )\n ~0.4992\n > y = base.hacoversin( -4.2 )\n ~0.0642\n > y = base.hacoversin( -4.6 )\n ~0.0032\n > y = base.hacoversin( 9.5 )\n ~0.538\n > y = base.hacoversin( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacovercos, base.haversin\n","base.havercos":"\nbase.havercos( x )\n Computes the half-value versed cosine.\n\n The half-value versed cosine is defined as `(1 + cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed cosine.\n\n Examples\n --------\n > var y = base.havercos( 3.14 )\n ~0.0\n > y = base.havercos( -4.2 )\n ~0.2549\n > y = base.havercos( -4.6 )\n ~0.4439\n > y = base.havercos( 9.5 )\n ~0.0014\n > y = base.havercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.haversin, base.vercos\n","base.haversin":"\nbase.haversin( x )\n Computes the half-value versed sine.\n\n The half-value versed sine is defined as `(1 - cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed sine.\n\n Examples\n --------\n > var y = base.haversin( 3.14 )\n ~1.0\n > y = base.haversin( -4.2 )\n ~0.7451\n > y = base.haversin( -4.6 )\n ~0.5561\n > y = base.haversin( 9.5 )\n ~0.9986\n > y = base.haversin( -0.0 )\n 0.0\n\n See Also\n --------\n base.havercos, base.versin\n","base.heaviside":"\nbase.heaviside( x[, continuity] )\n Evaluates the Heaviside function.\n\n The `continuity` parameter may be one of the following:\n\n - 'half-maximum': if `x == 0`, the function returns `0.5`.\n - 'left-continuous': if `x == 0`, the function returns `0`.\n - 'right-continuous': if `x == 0`, the function returns `1`.\n\n By default, if `x == 0`, the function returns `NaN` (i.e., the function is\n discontinuous).\n\n Parameters\n ----------\n x: number\n Input value.\n\n continuity: string (optional)\n Specifies how to handle `x == 0`. By default, if `x == 0`, the function\n returns `NaN`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.heaviside( 3.14 )\n 1.0\n > y = base.heaviside( -3.14 )\n 0.0\n > y = base.heaviside( 0.0 )\n NaN\n > y = base.heaviside( 0.0, 'half-maximum' )\n 0.5\n > y = base.heaviside( 0.0, 'left-continuous' )\n 0.0\n > y = base.heaviside( 0.0, 'right-continuous' )\n 1.0\n\n See Also\n --------\n base.ramp\n","base.hermitepoly":"\nbase.hermitepoly( n, x )\n Evaluates a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.hermitepoly( 1, 0.5 )\n 1.0\n > y = base.hermitepoly( -1, 0.5 )\n NaN\n > y = base.hermitepoly( 0, 0.5 )\n 1.0\n > y = base.hermitepoly( 2, 0.5 )\n -1.0\n\n\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n See Also\n --------\n base.evalpoly, base.normhermitepoly\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n See Also\n --------\n base.evalpoly, base.normhermitepoly","base.hypot":"\nbase.hypot( x, y )\n Computes the hypotenuse avoiding overflow and underflow.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypot( -5.0, 12.0 )\n 13.0\n > h = base.hypot( NaN, 12.0 )\n NaN\n > h = base.hypot( -0.0, -0.0 )\n 0.0\n\n","base.hypotf":"\nbase.hypotf( x, y )\n Computes the hypotenuse avoiding overflow and underflow (single-precision).\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypotf( -5.0, 12.0 )\n 13.0\n > h = base.hypotf( NaN, 12.0 )\n NaN\n > h = base.hypotf( -0.0, -0.0 )\n 0.0\n\n See Also\n --------\n base.hypot\n","base.identity":"\nbase.identity( x )\n Evaluates the identity function for a double-precision floating-point number\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Input value.\n\n Examples\n --------\n > var y = base.identity( -1.0 )\n -1.0\n > y = base.identity( 2.0 )\n 2.0\n > y = base.identity( 0.0 )\n 0.0\n > y = base.identity( -0.0 )\n -0.0\n > y = base.identity( NaN )\n NaN\n\n","base.identityf":"\nbase.identityf( x )\n Evaluates the identity function for a single-precision floating-point number\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Input value.\n\n Examples\n --------\n > var y = base.identityf( -1.0 )\n -1.0\n > y = base.identityf( 2.0 )\n 2.0\n > y = base.identityf( 0.0 )\n 0.0\n > y = base.identityf( -0.0 )\n -0.0\n > y = base.identityf( NaN )\n NaN\n\n See Also\n --------\n base.identityf\n","base.imul":"\nbase.imul( a, b )\n Performs C-like multiplication of two signed 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.imul( -10|0, 4|0 )\n -40\n\n See Also\n --------\n base.imuldw\n","base.imuldw":"\nbase.imuldw( a, b )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: Array\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.imuldw( 1, 10 )\n [ 0, 10 ]\n\n\nbase.imuldw.assign( a, b, out, stride, offset )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imul","base.imuldw.assign":"\nbase.imuldw.assign( a, b, out, stride, offset )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imul","base.int32ToUint32":"\nbase.int32ToUint32( x )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\n 4294967264\n > y = base.int32ToUint32( base.float64ToInt32( 3 ) )\n 3\n\n See Also\n --------\n base.uint32ToInt32\n","base.inv":"\nbase.inv( x )\n Computes the multiplicative inverse of a double-precision floating-point\n number `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.inv( -1.0 )\n -1.0\n > y = base.inv( 2.0 )\n 0.5\n > y = base.inv( 0.0 )\n Infinity\n > y = base.inv( -0.0 )\n -Infinity\n > y = base.inv( NaN )\n NaN\n\n See Also\n --------\n base.pow\n","base.invf":"\nbase.invf( x )\n Computes the multiplicative inverse of a single-precision floating-point\n number `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.invf( -1.0 )\n -1.0\n > y = base.invf( 2.0 )\n 0.5\n > y = base.invf( 0.0 )\n Infinity\n > y = base.invf( -0.0 )\n -Infinity\n > y = base.invf( NaN )\n NaN\n\n See Also\n --------\n base.inv\n","base.isComposite":"\nbase.isComposite( x )\n Tests if a number is composite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a composite number.\n\n Examples\n --------\n > var bool = base.isComposite( 10.0 )\n true\n > bool = base.isComposite( 11.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isPrime\n","base.isCoprime":"\nbase.isCoprime( a, b )\n Tests if two numbers are coprime.\n\n Parameters\n ----------\n a: number\n First value.\n\n b: number\n Second value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the values are coprime.\n\n Examples\n --------\n > var bool = base.isCoprime( 14.0, 15.0 )\n true\n > bool = base.isCoprime( 14.0, 21.0 )\n false\n\n See Also\n --------\n base.isComposite, base.isPrime, base.gcd\n","base.isEven":"\nbase.isEven( x )\n Tests if a finite numeric value is an even number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEven( 5.0 )\n false\n > bool = base.isEven( -2.0 )\n true\n > bool = base.isEven( 0.0 )\n true\n > bool = base.isEven( NaN )\n false\n\n See Also\n --------\n base.isOdd\n","base.isEvenInt32":"\nbase.isEvenInt32( x )\n Tests if a 32-bit integer is even.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEvenInt32( 5 )\n false\n > bool = base.isEvenInt32( -2 )\n true\n > bool = base.isEvenInt32( 0 )\n true\n\n See Also\n --------\n base.isEven, base.isOddInt32\n","base.isFinite":"\nbase.isFinite( x )\n Tests if a double-precision floating-point numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinite( 5.0 )\n true\n > bool = base.isFinite( -2.0e64 )\n true\n > bool = base.isFinite( PINF )\n false\n > bool = base.isFinite( NINF )\n false\n\n See Also\n --------\n base.isInfinite\n","base.isFinitef":"\nbase.isFinitef( x )\n Tests if a single-precision floating-point numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinitef( 5.0 )\n true\n > bool = base.isFinitef( -1.0e38 )\n true\n > bool = base.isFinitef( FLOAT32_PINF )\n false\n > bool = base.isFinitef( FLOAT32_NINF )\n false\n\n See Also\n --------\n base.isInfinitef\n","base.isInfinite":"\nbase.isInfinite( x )\n Tests if a double-precision floating-point numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinite( PINF )\n true\n > bool = base.isInfinite( NINF )\n true\n > bool = base.isInfinite( 5.0 )\n false\n > bool = base.isInfinite( NaN )\n false\n\n See Also\n --------\n base.isFinite\n","base.isInfinitef":"\nbase.isInfinitef( x )\n Tests if a single-precision floating-point numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinitef( FLOAT32_PINF )\n true\n > bool = base.isInfinitef( FLOAT32_NINF )\n true\n > bool = base.isInfinitef( 5.0 )\n false\n > bool = base.isInfinitef( NaN )\n false\n\n See Also\n --------\n base.isFinitef\n","base.isInteger":"\nbase.isInteger( x )\n Tests if a finite double-precision floating-point number is an integer.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an integer.\n\n Examples\n --------\n > var bool = base.isInteger( 1.0 )\n true\n > bool = base.isInteger( 3.14 )\n false\n\n","base.isnan":"\nbase.isnan( x )\n Tests if a double-precision floating-point numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnan( NaN )\n true\n > bool = base.isnan( 7.0 )\n false\n\n See Also\n --------\n base.isnanf\n","base.isnanf":"\nbase.isnanf( x )\n Tests if a single-precision floating-point numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnanf( NaN )\n true\n > bool = base.isnanf( 7.0 )\n false\n\n See Also\n --------\n base.isnan\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a negative integer.\n\n Examples\n --------\n > var bool = base.isNegativeInteger( -1.0 )\n true\n > bool = base.isNegativeInteger( 0.0 )\n false\n > bool = base.isNegativeInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNonNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNegativeZero":"\nbase.isNegativeZero( x )\n Tests if a double-precision floating-point numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZero( -0.0 )\n true\n > bool = base.isNegativeZero( 0.0 )\n false\n\n See Also\n --------\n base.isPositiveZero\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x )\n Tests if a single-precision floating-point numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZerof( -0.0 )\n true\n > bool = base.isNegativeZerof( 0.0 )\n false\n\n See Also\n --------\n base.isNegativeZero, base.isPositiveZerof\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonnegative integer.\n\n Examples\n --------\n > var bool = base.isNonNegativeInteger( 1.0 )\n true\n > bool = base.isNonNegativeInteger( 0.0 )\n true\n > bool = base.isNonNegativeInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonpositive integer.\n\n Examples\n --------\n > var bool = base.isNonPositiveInteger( -1.0 )\n true\n > bool = base.isNonPositiveInteger( 0.0 )\n true\n > bool = base.isNonPositiveInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isPositiveInteger\n","base.isOdd":"\nbase.isOdd( x )\n Tests if a finite numeric value is an odd number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOdd( 5.0 )\n true\n > bool = base.isOdd( -2.0 )\n false\n > bool = base.isOdd( 0.0 )\n false\n > bool = base.isOdd( NaN )\n false\n\n See Also\n --------\n base.isEven\n","base.isOddInt32":"\nbase.isOddInt32( x )\n Tests if a 32-bit integer is odd.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOddInt32( 5 )\n true\n > bool = base.isOddInt32( -2 )\n false\n > bool = base.isOddInt32( 0 )\n false\n\n See Also\n --------\n base.isEvenInt32, base.isOdd\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a positive integer.\n\n Examples\n --------\n > var bool = base.isPositiveInteger( 1.0 )\n true\n > bool = base.isPositiveInteger( 0.0 )\n false\n > bool = base.isPositiveInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isNonPositiveInteger\n","base.isPositiveZero":"\nbase.isPositiveZero( x )\n Tests if a double-precision floating-point numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZero( 0.0 )\n true\n > bool = base.isPositiveZero( -0.0 )\n false\n\n See Also\n --------\n base.isNegativeZero\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x )\n Tests if a single-precision floating-point numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZerof( 0.0 )\n true\n > bool = base.isPositiveZerof( -0.0 )\n false\n\n See Also\n --------\n base.isNegativeZerof, base.isPositiveZero\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x )\n Tests whether an unsigned integer is a power of 2.\n\n Parameters\n ----------\n x: integer\n Unsigned integer.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a power of 2.\n\n Examples\n --------\n > var bool = base.isPow2Uint32( 2 )\n true\n > bool = base.isPow2Uint32( 5 )\n false\n\n","base.isPrime":"\nbase.isPrime( x )\n Tests if a number is prime.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a prime number.\n\n Examples\n --------\n > var bool = base.isPrime( 11.0 )\n true\n > bool = base.isPrime( 3.14 )\n false\n\n See Also\n --------\n base.isComposite, base.isInteger\n","base.isProbability":"\nbase.isProbability( x )\n Tests if a double-precision floating-point number value is a probability.\n\n A probability is defined as a number on the closed interval [0,1].\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a probability.\n\n Examples\n --------\n > var bool = base.isProbability( 0.5 )\n true\n > bool = base.isProbability( 3.14 )\n false\n > bool = base.isProbability( NaN )\n false\n\n","base.isSafeInteger":"\nbase.isSafeInteger( x )\n Tests if a finite double-precision floating-point number is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a safe integer.\n\n Examples\n --------\n > var bool = base.isSafeInteger( 1.0 )\n true\n > bool = base.isSafeInteger( 2.0e200 )\n false\n > bool = base.isSafeInteger( 3.14 )\n false\n\n","base.kernelBetainc":"\nbase.kernelBetainc( x, a, b, regularized, upper )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\n [ ~1.277, ~0.926 ]\n > out = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n [ 0.36, 1.6 ]\n\n\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.betainc\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.betainc","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a, b, p, q )\n Computes the inverse of the lower incomplete beta function.\n\n Probabilities `p` and `q` must satisfy `p = 1 - q`.\n\n Parameters\n ----------\n a: number\n First function parameter (a positive number).\n\n b: number\n Second function parameter (a positive number).\n\n p: number\n Probability.\n\n q: number\n Probability equal to `1-p`.\n\n Returns\n -------\n out: Array\n Two-element array holding function value `y` and `1-y`.\n\n Examples\n --------\n > var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\n [ ~0.327, ~0.673 ]\n > y = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\n [ ~0.446, ~0.554 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\n [ ~0.082, ~0.918 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n [ ~0.235, ~0.765 ]\n\n See Also\n --------\n base.betaincinv\n","base.kernelCos":"\nbase.kernelCos( x, y )\n Computes the cosine of a double-precision floating-point number on the\n interval [-π/4, π/4].\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Cosine.\n\n Examples\n --------\n > var out = base.kernelCos( 0.0, 0.0 )\n ~1.0\n > out = base.kernelCos( PI/6.0, 0.0 )\n ~0.866\n > out = base.kernelCos( 0.785, -1.144e-17 )\n ~0.707\n > out = base.kernelCos( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.kernelSin, base.kernelTan\n","base.kernelSin":"\nbase.kernelSin( x, y )\n Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Sine.\n\n Examples\n --------\n > var y = base.kernelSin( 0.0, 0.0 )\n ~0.0\n > y = base.kernelSin( PI/6.0, 0.0 )\n ~0.5\n > y = base.kernelSin( 0.619, 9.279e-18 )\n ~0.58\n\n > y = base.kernelSin( NaN, 0.0 )\n NaN\n > y = base.kernelSin( 2.0, NaN )\n NaN\n > y = base.kernelSin( NaN, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelTan, base.sin\n","base.kernelTan":"\nbase.kernelTan( x, y, k )\n Computes the tangent of a double-precision floating-point number on the\n interval [-π/4, π/4].\n\n For increased accuracy, the number for which the tangent should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The numbers `x` and `y` must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either `x` or `y` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n k: integer\n If `k=1`, the function returns `tan(x+y)`. If `k=-1`, the function\n returns the negative inverse `-1/tan(x+y)`.\n\n Returns\n -------\n out: number\n Tangent.\n\n Examples\n --------\n > var out = base.kernelTan( PI/4.0, 0.0, 1 )\n ~1.0\n > out = base.kernelTan( PI/4.0, 0.0, -1 )\n ~-1.0\n > out = base.kernelTan( PI/6.0, 0.0, 1 )\n ~0.577\n > out = base.kernelTan( 0.664, 5.288e-17, 1 )\n ~0.783\n\n > out = base.kernelTan( NaN, 0.0, 1 )\n NaN\n > out = base.kernelTan( 3.0, NaN, 1 )\n NaN\n > out = base.kernelTan( 3.0, 0.0, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelSin, base.tan\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i, j )\n Evaluates the Kronecker delta.\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDelta( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDelta( 3.14, 3.14 )\n 1.0\n\n See Also\n --------\n base.diracDelta\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i, j )\n Evaluates the Kronecker delta (single-precision).\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDeltaf( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDeltaf( 3.14, 3.14 )\n 1.0\n\n See Also\n --------\n base.kroneckerDelta\n","base.labs":"\nbase.labs( x )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Absolute value.\n\n Examples\n --------\n > var v = base.labs( -1|0 )\n 1\n > v = base.labs( 2|0 )\n 2\n > v = base.labs( 0|0 )\n 0\n\n See Also\n --------\n base.abs\n","base.lcm":"\nbase.lcm( a, b )\n Computes the least common multiple (lcm).\n\n If either `a` or `b` is `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Least common multiple.\n\n Examples\n --------\n > var v = base.lcm( 21, 6 )\n 42\n\n See Also\n --------\n base.gcd\n","base.ldexp":"\nbase.ldexp( frac, exp )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n\n If `frac` equals positive or negative `zero`, `NaN`, or positive or negative\n infinity, the function returns a value equal to `frac`.\n\n Parameters\n ----------\n frac: number\n Fraction.\n\n exp: number\n Exponent.\n\n Returns\n -------\n out: number\n Double-precision floating-point number equal to `frac * 2^exp`.\n\n Examples\n --------\n > var x = base.ldexp( 0.5, 3 )\n 4.0\n > x = base.ldexp( 4.0, -2 )\n 1.0\n > x = base.ldexp( 0.0, 20 )\n 0.0\n > x = base.ldexp( -0.0, 39 )\n -0.0\n > x = base.ldexp( NaN, -101 )\n NaN\n > x = base.ldexp( PINF, 11 )\n Infinity\n > x = base.ldexp( NINF, -118 )\n -Infinity\n\n See Also\n --------\n base.frexp\n","base.ln":"\nbase.ln( x )\n Evaluates the natural logarithm of a double-precision floating-point number.\n\n For negative numbers, the natural logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ln( 4.0 )\n ~1.386\n > y = base.ln( 0.0 )\n -Infinity\n > y = base.ln( PINF )\n Infinity\n > y = base.ln( NaN )\n NaN\n > y = base.ln( -4.0 )\n NaN\n\n See Also\n --------\n base.exp, base.log10, base.log1p, base.log2\n","base.log":"\nbase.log( x, b )\n Computes the base `b` logarithm of `x`.\n\n For negative `b` or `x`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n b: number\n Base.\n\n Returns\n -------\n y: number\n Logarithm (base `b`).\n\n Examples\n --------\n > var y = base.log( 100.0, 10.0 )\n 2.0\n > y = base.log( 16.0, 2.0 )\n 4.0\n > y = base.log( 5.0, 1.0 )\n Infinity\n > y = base.log( NaN, 2.0 )\n NaN\n > y = base.log( 1.0, NaN )\n NaN\n > y = base.log( -4.0, 2.0 )\n NaN\n > y = base.log( 4.0, -2.0 )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log10, base.log1p, base.log2\n","base.log1mexp":"\nbase.log1mexp( x )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1mexp( -10.0 )\n ~-0.00005\n > y = base.log1mexp( 0.0 )\n -Infinity\n > y = base.log1mexp( 5.0 )\n ~-0.00676\n > y = base.log1mexp( 10.0 )\n ~-0.00005\n > y = base.log1mexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1p, base.log1pexp","base.log1p":"\nbase.log1p( x )\n Evaluates the natural logarithm of `1+x`.\n\n For `x < -1`, the function returns `NaN`, as the natural logarithm is not\n defined for negative numbers.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1p( 4.0 )\n ~1.609\n > y = base.log1p( -1.0 )\n -Infinity\n > y = base.log1p( 0.0 )\n 0.0\n > y = base.log1p( -0.0 )\n -0.0\n > y = base.log1p( -2.0 )\n NaN\n > y = base.log1p( NaN )\n NaN\n\n See Also\n --------\n base.ln, base.log\n","base.log1pexp":"\nbase.log1pexp( x )\n Evaluates the natural logarithm of `1+exp(x)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1pexp( -10.0 )\n ~0.000045\n > y = base.log1pexp( 0.0 )\n ~0.693147\n > y = base.log1pexp( 5.0 )\n ~5.006715\n > y = base.log1pexp( 34.0 )\n 34.0\n > y = base.log1pexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1mexp, base.log1p","base.log1pmx":"\nbase.log1pmx( x )\n Evaluates `ln(1+x) - x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > base.log1pmx( 1.1 )\n ~-0.358\n > base.log1pmx( 0.99 )\n ~-0.302\n > base.log1pmx( -0.99 )\n ~-3.615\n > base.log1pmx( -1.1 )\n NaN\n > base.log1pmx( NaN )\n NaN\n\n See Also\n --------\n base.ln, base.log1p","base.log2":"\nbase.log2( x )\n Evaluates the binary logarithm (base two).\n\n For negative numbers, the binary logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log2( 4.0 )\n 2.0\n > y = base.log2( 8.0 )\n 3.0\n > y = base.log2( 0.0 )\n -Infinity\n > y = base.log2( PINF )\n Infinity\n > y = base.log2( NaN )\n NaN\n > y = base.log2( -4.0 )\n NaN\n\n See Also\n --------\n base.exp2, base.ln, base.log\n","base.log10":"\nbase.log10( x )\n Evaluates the common logarithm (base 10).\n\n For negative numbers, the common logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log10( 100.0 )\n 2.0\n > y = base.log10( 8.0 )\n ~0.903\n > y = base.log10( 0.0 )\n -Infinity\n > y = base.log10( PINF )\n Infinity\n > y = base.log10( NaN )\n NaN\n > y = base.log10( -4.0 )\n NaN\n\n See Also\n --------\n base.exp10, base.ln, base.log\n","base.logaddexp":"\nbase.logaddexp( x, y )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.logaddexp( 90.0, 90.0 )\n ~90.6931\n > v = base.logaddexp( -20.0, 90.0 )\n 90.0\n > v = base.logaddexp( 0.0, -100.0 )\n ~3.7201e-44\n > v = base.logaddexp( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln\n","base.logit":"\nbase.logit( p )\n Evaluates the logit function.\n\n Let `p` be the probability of some event. The logit function is defined as\n the logarithm of the odds `p / (1-p)`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.logit( 0.2 )\n ~-1.386\n > y = base.logit( 0.9 )\n ~2.197\n > y = base.logit( -4.0 )\n NaN\n > y = base.logit( 1.5 )\n NaN\n > y = base.logit( NaN )\n NaN\n\n","base.lucas":"\nbase.lucas( n )\n Computes the nth Lucas number.\n\n Lucas numbers follow the recurrence relation\n\n L_n = L_{n-1} + L_{n-2}\n\n with seed values L_0 = 2 and L_1 = 1.\n\n If `n` is greater than `76`, the function returns `NaN`, as larger Lucas\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Lucas number.\n\n Examples\n --------\n > var y = base.lucas( 0 )\n 2\n > y = base.lucas( 1 )\n 1\n > y = base.lucas( 2 )\n 3\n > y = base.lucas( 3 )\n 4\n > y = base.lucas( 4 )\n 7\n > y = base.lucas( 77 )\n NaN\n > y = base.lucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n","base.lucaspoly":"\nbase.lucaspoly( n, x )\n Evaluates a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Lucas polynomial.\n\n Returns\n -------\n out: number\n Evaluated Lucas polynomial.\n\n Examples\n --------\n // 2^5 + 5*2^3 + 5*2\n > var v = base.lucaspoly( 5, 2.0 )\n 82.0\n\n\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n See Also\n --------\n base.evalpoly, base.fibpoly\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n See Also\n --------\n base.evalpoly, base.fibpoly","base.max":"\nbase.max( x, y )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.max( 3.14, 4.2 )\n 4.2\n > v = base.max( 3.14, NaN )\n NaN\n > v = base.max( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.maxn, base.min\n","base.maxabs":"\nbase.maxabs( x, y )\n Returns the maximum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n > var v = base.maxabs( 3.14, -4.2 )\n 4.2\n > v = base.maxabs( 3.14, NaN )\n NaN\n > v = base.maxabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.max, base.minabs\n","base.maxn":"\nbase.maxn( [x[, y[, ...args]]] )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns negative infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.maxn( 3.14, 4.2 )\n 4.2\n > v = base.maxn( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.maxn( 3.14, NaN )\n NaN\n > v = base.maxn( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.max, base.minn\n","base.min":"\nbase.min( x, y )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.min( 3.14, 4.2 )\n 3.14\n > v = base.min( 3.14, NaN )\n NaN\n > v = base.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max, base.minabs, base.minn\n","base.minabs":"\nbase.minabs( x, y )\n Returns the minimum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest upper bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n > var v = base.minabs( 3.14, -4.2 )\n 3.14\n > v = base.minabs( 3.14, NaN )\n NaN\n > v = base.minabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.min\n","base.minmax":"\nbase.minmax( x, y )\n Returns the minimum and maximum values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: Array\n Minimum and maximum values.\n\n Examples\n --------\n > var v = base.minmax( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmax( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmax( +0.0, -0.0 )\n [ -0.0, +0.0 ]\n\n\nbase.minmax.assign( x, y, out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.max, base.min, base.minmaxabs","base.minmax.assign":"\nbase.minmax.assign( x, y, out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.max, base.min, base.minmaxabs","base.minmaxabs":"\nbase.minmaxabs( x, y )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: Array\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var v = base.minmaxabs( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxabs( -5.9, 3.14)\n [ 3.14, 5.9 ]\n > v = base.minmaxabs( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxabs( +0.0, -0.0 )\n [ 0.0, 0.0 ]\n\n\nbase.minmaxabs.assign( x, y, out, stride, offset )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabs, base.minabs, base.minmax\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x, y, out, stride, offset )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabs, base.minabs, base.minmax","base.minn":"\nbase.minn( [x[, y[, ...args]]] )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.minn( 3.14, 4.2 )\n 3.14\n > v = base.minn( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.minn( 3.14, NaN )\n NaN\n > v = base.minn( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.maxn, base.min\n","base.modf":"\nbase.modf( x )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n Integral and fractional parts.\n\n Examples\n --------\n > var parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( +0.0 )\n [ +0.0, +0.0 ]\n > parts = base.modf( -0.0 )\n [ -0.0, -0.0 ]\n > parts = base.modf( PINF )\n [ Infinity, +0.0 ]\n > parts = base.modf( NINF )\n [ -Infinity, -0.0 ]\n > parts = base.modf( NaN )\n [ NaN, NaN ]\n\n\nbase.modf.assign( x, out, stride, offset )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var parts = base.modf.assign( 3.14, out, 1, 0 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true\n","base.modf.assign":"\nbase.modf.assign( x, out, stride, offset )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var parts = base.modf.assign( 3.14, out, 1, 0 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true","base.mul":"\nbase.mul( x, y )\n Multiplies two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.mul( -1.0, 5.0 )\n -5.0\n > v = base.mul( 2.0, 5.0 )\n 10.0\n > v = base.mul( 0.0, 5.0 )\n 0.0\n > v = base.mul( -0.0, 0.0 )\n -0.0\n > v = base.mul( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.div, base.sub\n","base.mulf":"\nbase.mulf( x, y )\n Multiplies two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.mulf( -1.0, 5.0 )\n -5.0\n > v = base.mulf( 2.0, 5.0 )\n 10.0\n > v = base.mulf( 0.0, 5.0 )\n 0.0\n > v = base.mulf( -0.0, 0.0 )\n -0.0\n > v = base.mulf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.divf, base.mul, base.subf\n","base.ndarray":"\nbase.ndarray( dtype, buffer, shape, strides, offset, order )\n Returns an ndarray.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n Returns\n -------\n ndarray: ndarray\n ndarray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.ndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nbase.ndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nbase.ndarray.prototype.order: string\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nbase.ndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nbase.ndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nbase.ndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nbase.ndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nbase.ndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays, fcn )\n Applies a unary callback to elements in an input ndarray and assigns results\n to elements in an output ndarray.\n\n Each provided \"ndarray\" should be an `object` with the following properties:\n\n - dtype: data type.\n - data: data buffer.\n - shape: dimensions.\n - strides: stride lengths.\n - offset: index offset.\n - order: specifies whether an ndarray is row-major (C-style) or column-major\n (Fortran-style).\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one input ndarray and one output ndarray.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n // Define ndarray data and meta data...\n > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dtype = 'float64';\n > var shape = [ 2, 2 ];\n > var sx = [ 2, 1 ];\n > var sy = [ 2, 1 ];\n > var ox = 0;\n > var oy = 0;\n > var order = 'row-major';\n\n // Using ndarrays...\n > var x = ndarray( dtype, xbuf, shape, sx, ox, order );\n > var y = ndarray( dtype, ybuf, shape, sy, oy, order );\n > base.ndarrayUnary( [ x, y ], base.abs );\n > y.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using minimal ndarray-like objects...\n > x = {\n ... 'dtype': dtype,\n ... 'data': xbuf,\n ... 'shape': shape,\n ... 'strides': sx,\n ... 'offset': ox,\n ... 'order': order\n ... };\n > y = {\n ... 'dtype': dtype,\n ... 'data': ybuf,\n ... 'shape': shape,\n ... 'strides': sy,\n ... 'offset': oy,\n ... 'order': order\n ... };\n > base.ndarrayUnary( [ x, y ], base.abs );\n > y.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n ndarrayDispatch\n","base.ndzeros":"\nbase.ndzeros( dtype, shape, order )\n Returns a zero-filled ndarray having a specified shape and data type.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n shape: ArrayLikeObject\n Array shape.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n \n > var sh = arr.shape\n [ 2, 2 ]\n > var dt = arr.dtype\n 'float64'\n\n See Also\n --------\n base.ndarray, base.ndzerosLike\n","base.ndzerosLike":"\nbase.ndzerosLike( x )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n\n Along with data type, shape, and order, the function infers the \"class\" of\n the returned ndarray from the provided ndarray. For example, if provided a\n \"base\" ndarray, the function returns a base ndarray. If provided a non-base\n ndarray, the function returns a non-base ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var dt = x.dtype\n 'float64'\n > var y = base.ndzerosLike( x )\n \n > sh = y.shape\n [ 2, 2 ]\n > dt = y.dtype\n 'float64'\n\n See Also\n --------\n base.ndarray, base.ndzeros\n","base.negafibonacci":"\nbase.negafibonacci( n )\n Computes the nth negaFibonacci number.\n\n The negaFibonacci numbers follow the recurrence relation\n\n F_{n-2} = F_{n} - F_{n-1}\n\n with seed values F_0 = 0 and F_{-1} = 1.\n\n If `|n|` is greater than `78`, the function returns `NaN` as larger\n negaFibonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaFibonacci number.\n\n Examples\n --------\n > var y = base.negafibonacci( 0 )\n 0\n > y = base.negafibonacci( -1 )\n 1\n > y = base.negafibonacci( -2 )\n -1\n > y = base.negafibonacci( -3 )\n 2\n > y = base.negafibonacci( -4 )\n -3\n > y = base.negafibonacci( -79 )\n NaN\n > y = base.negafibonacci( -80 )\n NaN\n > y = base.negafibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n","base.negalucas":"\nbase.negalucas( n )\n Computes the nth negaLucas number.\n\n The negaLucas numbers follow the recurrence relation\n\n L_{n-2} = L_{n} - L_{n-1}\n\n with seed values L_0 = 2 and L_{-1} = -1.\n\n If `|n|` is greater than `76`, the function returns `NaN` as larger\n negaLucas numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaLucas number.\n\n Examples\n --------\n > var y = base.negalucas( 0 )\n 2\n > y = base.negalucas( -1 )\n -1\n > y = base.negalucas( -2 )\n 3\n > y = base.negalucas( -3 )\n -4\n > y = base.negalucas( -4 )\n 7\n > y = base.negalucas( -77 )\n NaN\n > y = base.negalucas( -78 )\n NaN\n > y = base.negalucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.lucas, base.negafibonacci\n","base.nonfibonacci":"\nbase.nonfibonacci( n )\n Computes the nth non-Fibonacci number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Non-Fibonacci number.\n\n Examples\n --------\n > var v = base.nonfibonacci( 1 )\n 4\n > v = base.nonfibonacci( 2 )\n 6\n > v = base.nonfibonacci( 3 )\n 7\n > v = base.nonfibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.normalize":"\nbase.normalize( x )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalize( 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > var y = out[ 0 ];\n > var exponent = out[ 1 ];\n > var bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\n true\n\n // Special cases:\n > out = base.normalize( 0.0 )\n [ 0.0, 0 ];\n > out = base.normalize( PINF )\n [ Infinity, 0 ]\n > out = base.normalize( NINF )\n [ -Infinity, 0 ]\n > out = base.normalize( NaN )\n [ NaN, 0 ]\n\n\nbase.normalize.assign( x, out, stride, offset )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 )\n > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n [ 1.4141234400356668e-303, -52 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.normalizef\n","base.normalize.assign":"\nbase.normalize.assign( x, out, stride, offset )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 )\n > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n [ 1.4141234400356668e-303, -52 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.normalizef","base.normalizef":"\nbase.normalizef( x )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: Array\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23 ]\n > var y = out[ 0 ];\n > var exp = out[ 1 ];\n > var bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\n true\n\n // Special cases:\n > out = base.normalizef( FLOAT32_PINF )\n [ Infinity, 0 ]\n > out = base.normalizef( FLOAT32_NINF )\n [ -Infinity, 0 ]\n > out = base.normalizef( NaN )\n [ NaN, 0 ]\n\n\nbase.normalizef.assign( x, out, stride, offset )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n assigns results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > out = new Float32Array( 2 );\n > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalize","base.normalizef.assign":"\nbase.normalizef.assign( x, out, stride, offset )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n assigns results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > out = new Float32Array( 2 );\n > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalize","base.normhermitepoly":"\nbase.normhermitepoly( n, x )\n Evaluates a normalized Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.normhermitepoly( 1, 0.5 )\n 0.5\n > y = base.normhermitepoly( -1, 0.5 )\n NaN\n > y = base.normhermitepoly( 0, 0.5 )\n 1.0\n > y = base.normhermitepoly( 2, 0.5 )\n -0.75\n\n\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.normhermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -0.75\n\n See Also\n --------\n base.evalpoly, base.hermitepoly\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.normhermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -0.75\n\n See Also\n --------\n base.evalpoly, base.hermitepoly","base.pdiff":"\nbase.pdiff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdiff( 5.9, 3.14 )\n 2.76\n > v = base.pdiff( 3.14, 4.2 )\n 0.0\n > v = base.pdiff( 3.14, NaN )\n NaN\n > v = base.pdiff( -0.0, +0.0 )\n +0.0\n\n","base.pdifff":"\nbase.pdifff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdifff( 5.9, 3.15 )\n 2.75\n > v = base.pdifff( 3.14, 4.2 )\n 0.0\n > v = base.pdifff( 3.14, NaN )\n NaN\n > v = base.pdifff( -0.0, +0.0 )\n +0.0\n\n See Also\n --------\n base.pdiff\n","base.polygamma":"\nbase.polygamma( n, x )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n\n If `n` is not a nonnegative integer, the function returns `NaN`.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN` as either parameter, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Derivative order.\n\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.polygamma( 3, 1.2 )\n ~3.245\n > v = base.polygamma( 5, 1.2 )\n ~41.39\n > v = base.polygamma( 3, -4.9 )\n ~60014.239\n > v = base.polygamma( -1, 5.3 )\n NaN\n > v = base.polygamma( 2, -1.0 )\n Infinity\n\n See Also\n --------\n base.trigamma, base.digamma, base.gamma\n","base.pow":"\nbase.pow( b, x )\n Evaluates the exponential function `bˣ`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.pow( 2.0, 3.0 )\n 8.0\n > y = base.pow( 4.0, 0.5 )\n 2.0\n > y = base.pow( 100.0, 0.0 )\n 1.0\n > y = base.pow( PI, 5.0 )\n ~306.0197\n > y = base.pow( PI, -0.2 )\n ~0.7954\n > y = base.pow( NaN, 3.0 )\n NaN\n > y = base.pow( 5.0, NaN )\n NaN\n > y = base.pow( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.powm1\n","base.powm1":"\nbase.powm1( b, x )\n Evaluates `bˣ - 1`.\n\n When `b` is close to `1` and/or `x` is small, this function is more accurate\n than naively computing `bˣ` and subtracting `1`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.powm1( 2.0, 3.0 )\n 7.0\n > y = base.powm1( 4.0, 0.5 )\n 1.0\n > y = base.powm1( 0.0, 100.0 )\n -1.0\n > y = base.powm1( 100.0, 0.0 )\n 0.0\n > y = base.powm1( 0.0, 0.0 )\n 0.0\n > y = base.powm1( PI, 5.0 )\n ~305.0197\n > y = base.powm1( NaN, 3.0 )\n NaN\n > y = base.powm1( 5.0, NaN )\n NaN\n\n See Also\n --------\n base.pow\n","base.rad2deg":"\nbase.rad2deg( x )\n Converts an angle from radians to degrees.\n\n Parameters\n ----------\n x: number\n Angle in radians.\n\n Returns\n -------\n d: number\n Angle in degrees.\n\n Examples\n --------\n > var d = base.rad2deg( PI/2.0 )\n 90.0\n > d = base.rad2deg( -PI/4.0 )\n -45.0\n > d = base.rad2deg( NaN )\n NaN\n\n // Due to finite precision, canonical values may not be returned:\n > d = base.rad2deg( PI/6.0 )\n 29.999999999999996\n\n See Also\n --------\n base.deg2rad\n","base.ramp":"\nbase.ramp( x )\n Evaluates the ramp function.\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ramp( 3.14 )\n 3.14\n > y = base.ramp( -3.14 )\n 0.0\n\n See Also\n --------\n base.heaviside\n","base.rampf":"\nbase.rampf( x )\n Evaluates the ramp function (single-precision).\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.rampf( 3.14 )\n 3.14\n > y = base.rampf( -3.14 )\n 0.0\n\n See Also\n --------\n base.ramp\n","base.random.arcsine":"\nbase.random.arcsine( a, b )\n Returns a pseudorandom number drawn from an arcsine distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 5.0 )\n \n\n\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n \n\n\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'\n\n\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;\n\n\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;\n\n\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;\n\n\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;\n\n\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;\n\n\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, base.random.beta\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n ","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;","base.random.arcsine.state":"\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n ","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, base.random.beta","base.random.bernoulli":"\nbase.random.bernoulli( p )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.8 );\n\n\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'\n\n\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;\n\n\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;\n\n\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;\n\n\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;\n\n\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;\n\n\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, base.random.binomial\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n ","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, base.random.binomial","base.random.beta":"\nbase.random.beta( α, β )\n Returns a pseudorandom number drawn from a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 );\n\n\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'\n\n\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;\n\n\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;\n\n\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;\n\n\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;\n\n\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;\n\n\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.beta, random.iterators.beta, random.streams.beta\n","base.random.beta.factory":"\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.beta.NAME":"\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;","base.random.beta.seed":"\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;","base.random.beta.state":"\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n ","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.beta, random.iterators.beta, random.streams.beta","base.random.betaprime":"\nbase.random.betaprime( α, β )\n Returns a pseudorandom number drawn from a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 );\n\n\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'\n\n\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;\n\n\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;\n\n\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;\n\n\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;\n\n\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;\n\n\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.betaprime, random.iterators.betaprime, random.streams.betaprime\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;","base.random.betaprime.state":"\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n ","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.betaprime, random.iterators.betaprime, random.streams.betaprime","base.random.binomial":"\nbase.random.binomial( n, p )\n Returns a pseudorandom number drawn from a binomial distribution.\n\n If `n` is not a positive integer or `p` is not a probability, the function\n returns `NaN`.\n\n If `n` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 );\n\n\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'\n\n\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;\n\n\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;\n\n\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;\n\n\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;\n\n\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;\n\n\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.binomial, random.iterators.binomial, random.streams.binomial\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;","base.random.binomial.seed":"\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;","base.random.binomial.state":"\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n ","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.binomial, random.iterators.binomial, random.streams.binomial","base.random.boxMuller":"\nbase.random.boxMuller()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.boxMuller();\n\n\nbase.random.boxMuller.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.boxMuller.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.boxMuller.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.boxMuller.NAME\n 'box-muller'\n\n\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.boxMuller.PRNG;\n\n\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.boxMuller.seed;\n\n\nbase.random.boxMuller.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.boxMuller.seedLength;\n\n\nbase.random.boxMuller.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Get a copy of the current state:\n > var state = base.random.boxMuller.state\n \n\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Set the state:\n > base.random.boxMuller.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n\nbase.random.boxMuller.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.boxMuller.stateLength;\n\n\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.boxMuller.byteLength;\n\n\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.boxMuller.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.boxMuller, random.streams.boxMuller\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.boxMuller.factory();\n > r = rand();\n > r = rand();","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.boxMuller.NAME\n 'box-muller'","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.boxMuller.PRNG;","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.boxMuller.seed;","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.boxMuller.seedLength;","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Get a copy of the current state:\n > var state = base.random.boxMuller.state\n \n\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Set the state:\n > base.random.boxMuller.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n ","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.boxMuller.stateLength;","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.boxMuller.byteLength;","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.boxMuller.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.boxMuller, random.streams.boxMuller","base.random.cauchy":"\nbase.random.cauchy( x0, Ɣ )\n Returns a pseudorandom number drawn from a Cauchy distribution.\n\n If `x0` or `Ɣ` is `NaN` or `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 );\n\n\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n `Ɣ` be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n Ɣ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cauchy.factory();\n > var r = rand( 0.0, 1.5 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `x0` and `Ɣ`:\n > rand = base.random.cauchy.factory( 0.0, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cauchy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cauchy.NAME\n 'cauchy'\n\n\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cauchy.PRNG;\n\n\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cauchy.seed;\n\n\nbase.random.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cauchy.seedLength;\n\n\nbase.random.cauchy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cauchy.state\n \n\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cauchy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n\nbase.random.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cauchy.stateLength;\n\n\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cauchy.byteLength;\n\n\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cauchy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cauchy, random.iterators.cauchy, random.streams.cauchy\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n `Ɣ` be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n Ɣ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cauchy.factory();\n > var r = rand( 0.0, 1.5 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `x0` and `Ɣ`:\n > rand = base.random.cauchy.factory( 0.0, 1.5 );\n > r = rand();\n > r = rand();","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cauchy.NAME\n 'cauchy'","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cauchy.PRNG;","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cauchy.seed;","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cauchy.seedLength;","base.random.cauchy.state":"\nbase.random.cauchy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cauchy.state\n \n\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cauchy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n ","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cauchy.stateLength;","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cauchy.byteLength;","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cauchy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cauchy, random.iterators.cauchy, random.streams.cauchy","base.random.chi":"\nbase.random.chi( k )\n Returns a pseudorandom number drawn from a chi distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chi( 2 );\n\n\nbase.random.chi.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chi.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chi.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chi.NAME\n 'chi'\n\n\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chi.PRNG;\n\n\nbase.random.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chi.seed;\n\n\nbase.random.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chi.seedLength;\n\n\nbase.random.chi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chi.state\n \n\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Set the state:\n > base.random.chi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n\nbase.random.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chi.stateLength;\n\n\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chi.byteLength;\n\n\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chi, random.iterators.chi, random.streams.chi\n","base.random.chi.factory":"\nbase.random.chi.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chi.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chi.factory( 3 );\n > r = rand();\n > r = rand();","base.random.chi.NAME":"\nbase.random.chi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chi.NAME\n 'chi'","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chi.PRNG;","base.random.chi.seed":"\nbase.random.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chi.seed;","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chi.seedLength;","base.random.chi.state":"\nbase.random.chi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chi.state\n \n\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Set the state:\n > base.random.chi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n ","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chi.stateLength;","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chi.byteLength;","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chi, random.iterators.chi, random.streams.chi","base.random.chisquare":"\nbase.random.chisquare( k )\n Returns a pseudorandom number drawn from a chi-square distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 );\n\n\nbase.random.chisquare.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chisquare.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chisquare.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chisquare.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chisquare.NAME\n 'chisquare'\n\n\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chisquare.PRNG;\n\n\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chisquare.seed;\n\n\nbase.random.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chisquare.seedLength;\n\n\nbase.random.chisquare.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chisquare.state\n \n\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Set the state:\n > base.random.chisquare.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n\nbase.random.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chisquare.stateLength;\n\n\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chisquare.byteLength;\n\n\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chisquare.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chisquare, random.iterators.chisquare, random.streams.chisquare\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chisquare.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chisquare.factory( 3 );\n > r = rand();\n > r = rand();","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chisquare.NAME\n 'chisquare'","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chisquare.PRNG;","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chisquare.seed;","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chisquare.seedLength;","base.random.chisquare.state":"\nbase.random.chisquare.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chisquare.state\n \n\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Set the state:\n > base.random.chisquare.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n ","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chisquare.stateLength;","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chisquare.byteLength;","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chisquare.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chisquare, random.iterators.chisquare, random.streams.chisquare","base.random.cosine":"\nbase.random.cosine( μ, s )\n Returns a pseudorandom number drawn from a raised cosine distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 );\n\n\nbase.random.cosine.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cosine.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.cosine.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cosine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cosine.NAME\n 'cosine'\n\n\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cosine.PRNG;\n\n\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cosine.seed;\n\n\nbase.random.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cosine.seedLength;\n\n\nbase.random.cosine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cosine.state\n \n\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cosine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n\nbase.random.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cosine.stateLength;\n\n\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cosine.byteLength;\n\n\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cosine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cosine, random.iterators.cosine, random.streams.cosine\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cosine.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.cosine.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cosine.NAME\n 'cosine'","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cosine.PRNG;","base.random.cosine.seed":"\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cosine.seed;","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cosine.seedLength;","base.random.cosine.state":"\nbase.random.cosine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cosine.state\n \n\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cosine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n ","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cosine.stateLength;","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cosine.byteLength;","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cosine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cosine, random.iterators.cosine, random.streams.cosine","base.random.discreteUniform":"\nbase.random.discreteUniform( a, b )\n Returns a pseudorandom number drawn from a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 );\n\n\nbase.random.discreteUniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.discreteUniform.factory();\n > var r = rand( 0, 10 );\n > r = rand( -20, 20 );\n\n // Provide `a` and `b`:\n > rand = base.random.discreteUniform.factory( 0, 10 );\n > r = rand();\n > r = rand();\n\n\nbase.random.discreteUniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.discreteUniform.NAME\n 'discrete-uniform'\n\n\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.discreteUniform.PRNG;\n\n\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.discreteUniform.seed;\n\n\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.discreteUniform.seedLength;\n\n\nbase.random.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Get a copy of the current state:\n > var state = base.random.discreteUniform.state\n \n\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Set the state:\n > base.random.discreteUniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n\nbase.random.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.discreteUniform.stateLength;\n\n\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.discreteUniform.byteLength;\n\n\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.discreteUniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.discreteUniform.factory();\n > var r = rand( 0, 10 );\n > r = rand( -20, 20 );\n\n // Provide `a` and `b`:\n > rand = base.random.discreteUniform.factory( 0, 10 );\n > r = rand();\n > r = rand();","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.discreteUniform.NAME\n 'discrete-uniform'","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.discreteUniform.PRNG;","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.discreteUniform.seed;","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.discreteUniform.seedLength;","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Get a copy of the current state:\n > var state = base.random.discreteUniform.state\n \n\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Set the state:\n > base.random.discreteUniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n ","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.discreteUniform.stateLength;","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.discreteUniform.byteLength;","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.discreteUniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform","base.random.erlang":"\nbase.random.erlang( k, λ )\n Returns a pseudorandom number drawn from an Erlang distribution.\n\n If `k` is not a positive integer or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 );\n\n\nbase.random.erlang.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: integer (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.erlang.factory();\n > var r = rand( 2, 1.0 );\n > r = rand( 4, 3.14 );\n\n // Provide `k` and `λ`:\n > rand = base.random.erlang.factory( 2, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.erlang.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.erlang.NAME\n 'erlang'\n\n\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.erlang.PRNG;\n\n\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.erlang.seed;\n\n\nbase.random.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.erlang.seedLength;\n\n\nbase.random.erlang.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.erlang.state\n \n\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Set the state:\n > base.random.erlang.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n\nbase.random.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.erlang.stateLength;\n\n\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.erlang.byteLength;\n\n\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.erlang.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.erlang, random.iterators.erlang, random.streams.erlang\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: integer (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.erlang.factory();\n > var r = rand( 2, 1.0 );\n > r = rand( 4, 3.14 );\n\n // Provide `k` and `λ`:\n > rand = base.random.erlang.factory( 2, 1.5 );\n > r = rand();\n > r = rand();","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.erlang.NAME\n 'erlang'","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.erlang.PRNG;","base.random.erlang.seed":"\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.erlang.seed;","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.erlang.seedLength;","base.random.erlang.state":"\nbase.random.erlang.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.erlang.state\n \n\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Set the state:\n > base.random.erlang.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n ","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.erlang.stateLength;","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.erlang.byteLength;","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.erlang.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.erlang, random.iterators.erlang, random.streams.erlang","base.random.exponential":"\nbase.random.exponential( λ )\n Returns a pseudorandom number drawn from an exponential distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 );\n\n\nbase.random.exponential.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.exponential.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.exponential.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.exponential.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.exponential.NAME\n 'exponential'\n\n\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.exponential.PRNG;\n\n\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.exponential.seed;\n\n\nbase.random.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.exponential.seedLength;\n\n\nbase.random.exponential.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Get a copy of the current state:\n > var state = base.random.exponential.state\n \n\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Set the state:\n > base.random.exponential.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n\nbase.random.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.exponential.stateLength;\n\n\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.exponential.byteLength;\n\n\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.exponential.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.exponential, random.iterators.exponential, random.streams.exponential\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.exponential.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.exponential.factory( 10.0 );\n > r = rand();\n > r = rand();","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.exponential.NAME\n 'exponential'","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.exponential.PRNG;","base.random.exponential.seed":"\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.exponential.seed;","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.exponential.seedLength;","base.random.exponential.state":"\nbase.random.exponential.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Get a copy of the current state:\n > var state = base.random.exponential.state\n \n\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Set the state:\n > base.random.exponential.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n ","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.exponential.stateLength;","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.exponential.byteLength;","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.exponential.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.exponential, random.iterators.exponential, random.streams.exponential","base.random.f":"\nbase.random.f( d1, d2 )\n Returns a pseudorandom number drawn from an F distribution.\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.f( 2.0, 5.0 );\n\n\nbase.random.f.factory( [d1, d2, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n\n If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n `d2` be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.f.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.0, 3.14 );\n\n // Provide `d1` and `d2`:\n > rand = base.random.f.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.f.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.f.NAME\n 'f'\n\n\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.f.PRNG;\n\n\nbase.random.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.f.seed;\n\n\nbase.random.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.f.seedLength;\n\n\nbase.random.f.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.f.state\n \n\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.f.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n\nbase.random.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.f.stateLength;\n\n\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.f.byteLength;\n\n\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.f.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.f, random.iterators.f, random.streams.f\n","base.random.f.factory":"\nbase.random.f.factory( [d1, d2, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n\n If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n `d2` be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.f.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.0, 3.14 );\n\n // Provide `d1` and `d2`:\n > rand = base.random.f.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.f.NAME":"\nbase.random.f.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.f.NAME\n 'f'","base.random.f.PRNG":"\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.f.PRNG;","base.random.f.seed":"\nbase.random.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.f.seed;","base.random.f.seedLength":"\nbase.random.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.f.seedLength;","base.random.f.state":"\nbase.random.f.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.f.state\n \n\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.f.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n ","base.random.f.stateLength":"\nbase.random.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.f.stateLength;","base.random.f.byteLength":"\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.f.byteLength;","base.random.f.toJSON":"\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.f.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.f, random.iterators.f, random.streams.f","base.random.frechet":"\nbase.random.frechet( α, s, m )\n Returns a pseudorandom number drawn from a Fréchet distribution.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n If either `α`, `s`, or `m` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.frechet( 2.0, 5.0, 3.33 );\n\n\nbase.random.frechet.factory( [α, s, m, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n and `m` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.frechet.factory();\n > var r = rand( 1.0, 1.0, 0.5 );\n > r = rand( 2.0, 2.0, 1.0 );\n\n // Provide `α`, `s`, and `m`:\n > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.frechet.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.frechet.NAME\n 'frechet'\n\n\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.frechet.PRNG;\n\n\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.frechet.seed;\n\n\nbase.random.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.frechet.seedLength;\n\n\nbase.random.frechet.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.frechet.state\n \n\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.frechet.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n\nbase.random.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.frechet.stateLength;\n\n\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.frechet.byteLength;\n\n\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.frechet.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.frechet, random.iterators.frechet, random.streams.frechet\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α, s, m, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n and `m` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.frechet.factory();\n > var r = rand( 1.0, 1.0, 0.5 );\n > r = rand( 2.0, 2.0, 1.0 );\n\n // Provide `α`, `s`, and `m`:\n > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.frechet.NAME\n 'frechet'","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.frechet.PRNG;","base.random.frechet.seed":"\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.frechet.seed;","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.frechet.seedLength;","base.random.frechet.state":"\nbase.random.frechet.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.frechet.state\n \n\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.frechet.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n ","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.frechet.stateLength;","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.frechet.byteLength;","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.frechet.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.frechet, random.iterators.frechet, random.streams.frechet","base.random.gamma":"\nbase.random.gamma( α, β )\n Returns a pseudorandom number drawn from a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 );\n\n\nbase.random.gamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.gamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gamma.NAME\n 'gamma'\n\n\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gamma.PRNG;\n\n\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gamma.seed;\n\n\nbase.random.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gamma.seedLength;\n\n\nbase.random.gamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gamma.state\n \n\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n\nbase.random.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gamma.stateLength;\n\n\nbase.random.gamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.gamma.byteLength;\n\n\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gamma, random.iterators.gamma, random.streams.gamma\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.gamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gamma.NAME\n 'gamma'","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gamma.PRNG;","base.random.gamma.seed":"\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gamma.seed;","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gamma.seedLength;","base.random.gamma.state":"\nbase.random.gamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gamma.state\n \n\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n ","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gamma.stateLength;","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.gamma.byteLength;","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gamma, random.iterators.gamma, random.streams.gamma","base.random.geometric":"\nbase.random.geometric( p )\n Returns a pseudorandom number drawn from a geometric distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.geometric( 0.8 );\n\n\nbase.random.geometric.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.geometric.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.geometric.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.geometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.geometric.NAME\n 'geometric'\n\n\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.geometric.PRNG;\n\n\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.geometric.seed;\n\n\nbase.random.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.geometric.seedLength;\n\n\nbase.random.geometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.geometric.state\n \n\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Set the state:\n > base.random.geometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n\nbase.random.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.geometric.stateLength;\n\n\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.geometric.byteLength;\n\n\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.geometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.geometric, random.iterators.geometric, random.streams.geometric\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.geometric.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.geometric.factory( 0.3 );\n > r = rand();\n > r = rand();","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.geometric.NAME\n 'geometric'","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.geometric.PRNG;","base.random.geometric.seed":"\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.geometric.seed;","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.geometric.seedLength;","base.random.geometric.state":"\nbase.random.geometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.geometric.state\n \n\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Set the state:\n > base.random.geometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n ","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.geometric.stateLength;","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.geometric.byteLength;","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.geometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.geometric, random.iterators.geometric, random.streams.geometric","base.random.gumbel":"\nbase.random.gumbel( μ, β )\n Returns a pseudorandom number drawn from a Gumbel distribution.\n\n If `μ` or `β` is `NaN` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 );\n\n\nbase.random.gumbel.factory( [μ, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided `μ` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gumbel.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `β`:\n > rand = base.random.gumbel.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gumbel.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gumbel.NAME\n 'gumbel'\n\n\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gumbel.PRNG;\n\n\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gumbel.seed;\n\n\nbase.random.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gumbel.seedLength;\n\n\nbase.random.gumbel.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gumbel.state\n \n\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gumbel.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n\nbase.random.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gumbel.stateLength;\n\n\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.gumbel.byteLength;\n\n\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gumbel.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gumbel, random.iterators.gumbel, random.streams.gumbel\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided `μ` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gumbel.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `β`:\n > rand = base.random.gumbel.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gumbel.NAME\n 'gumbel'","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gumbel.PRNG;","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gumbel.seed;","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gumbel.seedLength;","base.random.gumbel.state":"\nbase.random.gumbel.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gumbel.state\n \n\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gumbel.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n ","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gumbel.stateLength;","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.gumbel.byteLength;","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gumbel.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gumbel, random.iterators.gumbel, random.streams.gumbel","base.random.hypergeometric":"\nbase.random.hypergeometric( N, K, n )\n Returns a pseudorandom number drawn from a hypergeometric distribution.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n returns `NaN`.\n\n If `n > N` or `K > N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 7 );\n\n\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n and `n` be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.hypergeometric.factory();\n > var r = rand( 20, 10, 15 );\n > r = rand( 20, 10, 7 );\n\n // Provide `N`, `K`, and `n`:\n > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n > r = rand();\n > r = rand();\n\n\nbase.random.hypergeometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.hypergeometric.NAME\n 'hypergeometric'\n\n\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.hypergeometric.PRNG;\n\n\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.hypergeometric.seed;\n\n\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.hypergeometric.seedLength;\n\n\nbase.random.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Get a copy of the current state:\n > var state = base.random.hypergeometric.state\n \n\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Set the state:\n > base.random.hypergeometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n\nbase.random.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.hypergeometric.stateLength;\n\n\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.hypergeometric.byteLength;\n\n\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.hypergeometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n and `n` be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.hypergeometric.factory();\n > var r = rand( 20, 10, 15 );\n > r = rand( 20, 10, 7 );\n\n // Provide `N`, `K`, and `n`:\n > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n > r = rand();\n > r = rand();","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.hypergeometric.NAME\n 'hypergeometric'","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.hypergeometric.PRNG;","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.hypergeometric.seed;","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.hypergeometric.seedLength;","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Get a copy of the current state:\n > var state = base.random.hypergeometric.state\n \n\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Set the state:\n > base.random.hypergeometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n ","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.hypergeometric.stateLength;","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.hypergeometric.byteLength;","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.hypergeometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat();\n\n\nbase.random.improvedZiggurat.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.improvedZiggurat.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.improvedZiggurat.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.improvedZiggurat.NAME\n 'improved-ziggurat'\n\n\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.improvedZiggurat.PRNG;\n\n\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.improvedZiggurat.seed;\n\n\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.seedLength;\n\n\nbase.random.improvedZiggurat.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Get a copy of the current state:\n > var state = base.random.improvedZiggurat.state\n \n\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Set the state:\n > base.random.improvedZiggurat.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.stateLength;\n\n\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.improvedZiggurat.byteLength;\n\n\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.improvedZiggurat.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.improvedZiggurat, random.streams.improvedZiggurat\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.improvedZiggurat.factory();\n > r = rand();\n > r = rand();","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.improvedZiggurat.NAME\n 'improved-ziggurat'","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.improvedZiggurat.PRNG;","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.improvedZiggurat.seed;","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.seedLength;","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Get a copy of the current state:\n > var state = base.random.improvedZiggurat.state\n \n\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Set the state:\n > base.random.improvedZiggurat.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n ","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.stateLength;","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.improvedZiggurat.byteLength;","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.improvedZiggurat.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.improvedZiggurat, random.streams.improvedZiggurat","base.random.invgamma":"\nbase.random.invgamma( α, β )\n Returns a pseudorandom number drawn from an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 );\n\n\nbase.random.invgamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.invgamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.invgamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.invgamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.invgamma.NAME\n 'invgamma'\n\n\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.invgamma.PRNG;\n\n\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.invgamma.seed;\n\n\nbase.random.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.invgamma.seedLength;\n\n\nbase.random.invgamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.invgamma.state\n \n\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.invgamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n\nbase.random.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.invgamma.stateLength;\n\n\nbase.random.invgamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.invgamma.byteLength;\n\n\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.invgamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.invgamma, random.iterators.invgamma, random.streams.invgamma\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.invgamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.invgamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.invgamma.NAME\n 'invgamma'","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.invgamma.PRNG;","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.invgamma.seed;","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.invgamma.seedLength;","base.random.invgamma.state":"\nbase.random.invgamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.invgamma.state\n \n\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.invgamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n ","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.invgamma.stateLength;","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.invgamma.byteLength;","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.invgamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.invgamma, random.iterators.invgamma, random.streams.invgamma","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a, b )\n Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n distribution.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 2.0, 5.0 );\n\n\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.kumaraswamy.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `a` and `b`:\n > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.kumaraswamy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.kumaraswamy.NAME\n 'kumaraswamy'\n\n\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.kumaraswamy.PRNG;\n\n\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.kumaraswamy.seed;\n\n\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.seedLength;\n\n\nbase.random.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.kumaraswamy.state\n \n\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.kumaraswamy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.stateLength;\n\n\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.kumaraswamy.byteLength;\n\n\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.kumaraswamy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.kumaraswamy.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `a` and `b`:\n > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.kumaraswamy.NAME\n 'kumaraswamy'","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.kumaraswamy.PRNG;","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.kumaraswamy.seed;","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.seedLength;","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.kumaraswamy.state\n \n\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.kumaraswamy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n ","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.stateLength;","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.kumaraswamy.byteLength;","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.kumaraswamy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy","base.random.laplace":"\nbase.random.laplace( μ, b )\n Returns a pseudorandom number drawn from a Laplace distribution.\n\n If `μ` or `b` is `NaN` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 );\n\n\nbase.random.laplace.factory( [μ, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n\n If provided `μ` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.laplace.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.laplace.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.laplace.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.laplace.NAME\n 'laplace'\n\n\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.laplace.PRNG;\n\n\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.laplace.seed;\n\n\nbase.random.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.laplace.seedLength;\n\n\nbase.random.laplace.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.laplace.state\n \n\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.laplace.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n\nbase.random.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.laplace.stateLength;\n\n\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.laplace.byteLength;\n\n\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.laplace.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.laplace, random.iterators.laplace, random.streams.laplace\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n\n If provided `μ` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.laplace.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.laplace.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.laplace.NAME\n 'laplace'","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.laplace.PRNG;","base.random.laplace.seed":"\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.laplace.seed;","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.laplace.seedLength;","base.random.laplace.state":"\nbase.random.laplace.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.laplace.state\n \n\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.laplace.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n ","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.laplace.stateLength;","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.laplace.byteLength;","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.laplace.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.laplace, random.iterators.laplace, random.streams.laplace","base.random.levy":"\nbase.random.levy( μ, c )\n Returns a pseudorandom number drawn from a Lévy distribution.\n\n If `μ` or `c` is `NaN` or `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 );\n\n\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'\n\n\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;\n\n\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;\n\n\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;\n\n\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;\n\n\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;\n\n\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.levy, random.iterators.levy, random.streams.levy\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.levy.NAME":"\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;","base.random.levy.seed":"\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;","base.random.levy.state":"\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n ","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.levy, random.iterators.levy, random.streams.levy","base.random.logistic":"\nbase.random.logistic( μ, s )\n Returns a pseudorandom number drawn from a logistic distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 );\n\n\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'\n\n\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;\n\n\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;\n\n\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;\n\n\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;\n\n\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;\n\n\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.logistic, random.iterators.logistic, random.streams.logistic\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;","base.random.logistic.seed":"\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;","base.random.logistic.state":"\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n ","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.logistic, random.iterators.logistic, random.streams.logistic","base.random.lognormal":"\nbase.random.lognormal( μ, σ )\n Returns a pseudorandom number drawn from a lognormal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 );\n\n\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'\n\n\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;\n\n\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;\n\n\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;\n\n\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;\n\n\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;\n\n\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.lognormal, random.iterators.lognormal, random.streams.lognormal\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;","base.random.lognormal.state":"\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n ","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.lognormal, random.iterators.lognormal, random.streams.lognormal","base.random.minstd":"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd();\n\n\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();\n\n\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838\n\n\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'\n\n\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1\n\n\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646\n\n\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;\n\n\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;\n\n\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;\n\n\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;\n\n\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();","base.random.minstd.factory":"\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646","base.random.minstd.seed":"\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;","base.random.minstd.state":"\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n ","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle();\n\n\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();\n\n\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654\n\n\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'\n\n\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1\n\n\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646\n\n\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;\n\n\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;\n\n\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;\n\n\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;\n\n\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n ","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi","base.random.mt19937":"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937();\n\n\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();\n\n\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775\n\n\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'\n\n\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 0\n\n\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295\n\n\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;\n\n\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;\n\n\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;\n\n\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;\n\n\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 0","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;","base.random.mt19937.state":"\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n ","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r, p )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n\n If `p` is not in the interval `(0,1)`, the function returns `NaN`.\n\n If `r` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.8 );\n\n\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'\n\n\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;\n\n\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;\n\n\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;\n\n\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;\n\n\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;\n\n\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n ","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial","base.random.normal":"\nbase.random.normal( μ, σ )\n Returns a pseudorandom number drawn from a normal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 );\n\n\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'\n\n\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;\n\n\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;\n\n\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;\n\n\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;\n\n\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;\n\n\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.normal, random.iterators.normal, random.streams.normal\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.normal.NAME":"\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;","base.random.normal.seed":"\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;","base.random.normal.state":"\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n ","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.normal, random.iterators.normal, random.streams.normal","base.random.pareto1":"\nbase.random.pareto1( α, β )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 );\n\n\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'\n\n\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;\n\n\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;\n\n\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;\n\n\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;\n\n\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;\n\n\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.pareto1, random.iterators.pareto1, random.streams.pareto1\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;","base.random.pareto1.state":"\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n ","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.pareto1, random.iterators.pareto1, random.streams.pareto1","base.random.poisson":"\nbase.random.poisson( λ )\n Returns a pseudorandom number drawn from a Poisson distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.poisson( 7.9 );\n\n\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'\n\n\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;\n\n\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;\n\n\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;\n\n\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;\n\n\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;\n\n\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.poisson, random.iterators.poisson, random.streams.poisson\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;","base.random.poisson.seed":"\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;","base.random.poisson.state":"\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n ","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.poisson, random.iterators.poisson, random.streams.poisson","base.random.randi":"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randi();\n\n\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();\n\n\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'\n\n\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;\n\n\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;\n\n\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;\n\n\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;\n\n\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;\n\n\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;\n\n\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;\n\n\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937\n","base.random.randi.factory":"\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();","base.random.randi.NAME":"\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;","base.random.randi.MIN":"\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;","base.random.randi.MAX":"\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;","base.random.randi.seed":"\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;","base.random.randi.state":"\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n ","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937","base.random.randn":"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randn();\n\n\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'\n\n\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;\n\n\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;\n\n\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;\n\n\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;\n\n\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;\n\n\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu\n","base.random.randn.factory":"\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();","base.random.randn.NAME":"\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;","base.random.randn.seed":"\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;","base.random.randn.state":"\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n ","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu","base.random.randu":"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number on the interval `[0,1)`.\n\n Examples\n --------\n > var r = base.random.randu();\n\n\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'\n\n\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;\n\n\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;\n\n\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;\n\n\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;\n\n\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;\n\n\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;\n\n\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;\n\n\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn\n","base.random.randu.factory":"\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();","base.random.randu.NAME":"\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;","base.random.randu.MIN":"\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;","base.random.randu.MAX":"\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;","base.random.randu.seed":"\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;","base.random.randu.state":"\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n ","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn","base.random.rayleigh":"\nbase.random.rayleigh( σ )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n\n If `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.rayleigh( 2.5 );\n\n\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'\n\n\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;\n\n\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;\n\n\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;\n\n\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;\n\n\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;\n\n\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n ","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh","base.random.t":"\nbase.random.t( v )\n Returns a pseudorandom number drawn from a Student's t distribution.\n\n If `v <= 0` or `v` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.t( 2.0 );\n\n\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'\n\n\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;\n\n\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;\n\n\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;\n\n\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;\n\n\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;\n\n\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.t, random.iterators.t, random.streams.t\n","base.random.t.factory":"\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();","base.random.t.NAME":"\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'","base.random.t.PRNG":"\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;","base.random.t.seed":"\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;","base.random.t.seedLength":"\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;","base.random.t.state":"\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n ","base.random.t.stateLength":"\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;","base.random.t.byteLength":"\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;","base.random.t.toJSON":"\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.t, random.iterators.t, random.streams.t","base.random.triangular":"\nbase.random.triangular( a, b, c )\n Returns a pseudorandom number drawn from a triangular distribution.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.triangular( 2.0, 5.0, 3.33 );\n\n\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'\n\n\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;\n\n\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;\n\n\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;\n\n\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;\n\n\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;\n\n\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.triangular, random.iterators.triangular, random.streams.triangular\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;","base.random.triangular.seed":"\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;","base.random.triangular.state":"\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n ","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.triangular, random.iterators.triangular, random.streams.triangular","base.random.uniform":"\nbase.random.uniform( a, b )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support (inclusive).\n\n b: number\n Maximum support (exclusive).\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 );\n\n\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'\n\n\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;\n\n\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;\n\n\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;\n\n\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;\n\n\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;\n\n\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.uniform, random.iterators.uniform, random.streams.uniform, base.random.discreteUniform, base.random.randu\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;","base.random.uniform.seed":"\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;","base.random.uniform.state":"\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n ","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.uniform, random.iterators.uniform, random.streams.uniform, base.random.discreteUniform, base.random.randu","base.random.weibull":"\nbase.random.weibull( k, λ )\n Returns a pseudorandom number drawn from a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If either `λ` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 );\n\n\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'\n\n\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;\n\n\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;\n\n\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;\n\n\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;\n\n\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;\n\n\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.weibull, random.iterators.weibull, random.streams.weibull\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;","base.random.weibull.seed":"\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;","base.random.weibull.state":"\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n ","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.weibull, random.iterators.weibull, random.streams.weibull","base.reldiff":"\nbase.reldiff( x, y[, scale] )\n Computes the relative difference of two real numbers.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference.\n\n Examples\n --------\n > var d = base.reldiff( 2.0, 5.0 )\n 0.6\n > d = base.reldiff( -1.0, 3.14 )\n ~1.318\n > d = base.reldiff( -2.0, 5.0, 'max-abs' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'max' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'min-abs' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'min' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'mean-abs' )\n 2.0\n > d = base.reldiff( -2.0, 5.0, 'mean' )\n ~4.667\n > d = base.reldiff( -2.0, 5.0, 'x' )\n 3.5\n > d = base.reldiff( 5.0, -2.0, 'x' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'y' )\n 1.4\n > d = base.reldiff( 5.0, -2.0, 'y' )\n 3.5\n\n // Custom scale function:\n > function scale( x, y ) {\n ... var s;\n ...\n ... x = base.abs( x );\n ... y = base.abs( y );\n ...\n ... // Maximum absolute value:\n ... s = (x < y ) ? y : x;\n ...\n ... // Scale in units of epsilon:\n ... return s * EPS;\n ... };\n > d = base.reldiff( 12.15, 12.149999999999999, scale )\n ~0.658\n\n See Also\n --------\n base.absdiff, base.epsdiff\n","base.rempio2":"\nbase.rempio2( x, y )\n Computes `x - nπ/2 = r`.\n\n The function returns `n` and stores the remainder `r` as the two numbers\n `y[0]` and `y[1]`, such that `y[0] + y[1] = r`.\n\n For input values larger than `2^20 * π/2` in magnitude, the function only\n returns the last three binary digits of `n` and not the full result.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: Array|TypedArray|Object\n Remainder elements.\n\n Returns\n -------\n n: integer\n Factor of `π/2`.\n\n Examples\n --------\n > var y = [ 0.0, 0.0 ];\n > var n = base.rempio2( 128.0, y )\n 81\n > var y1 = y[ 0 ]\n ~0.765\n > var y2 = y[ 1 ]\n ~3.618e-17\n\n\n","base.risingFactorial":"\nbase.risingFactorial( x, n )\n Computes the rising factorial of `x` and `n`.\n\n If provided a non-integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.risingFactorial( 0.9, 5 )\n ~94.766\n > v = base.risingFactorial( -9.0, 3 )\n -504.0\n > v = base.risingFactorial( 0.0, 2 )\n 0.0\n > v = base.risingFactorial( 3.0, -2 )\n 0.5\n\n See Also\n --------\n base.fallingFactorial\n","base.rotl32":"\nbase.rotl32( x, shift )\n Performs a bitwise rotation to the left.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 2147483649;\n > var bStr = base.toBinaryStringUint32( x )\n '10000000000000000000000000000001'\n > var y = base.rotl32( x, 10 )\n 1536\n > bstr = base.toBinaryStringUint32( y )\n '00000000000000000000011000000000'\n\n See Also\n --------\n base.rotr32\n","base.rotr32":"\nbase.rotr32( x, shift )\n Performs a bitwise rotation to the right.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 1;\n > var bStr = base.toBinaryStringUint32( x )\n '00000000000000000000000000000001'\n > var y = base.rotr32( x, 10 )\n 4194304\n > bstr = base.toBinaryStringUint32( y )\n '00000000010000000000000000000000'\n\n See Also\n --------\n base.rotl32\n","base.round":"\nbase.round( x )\n Rounds a numeric value to the nearest integer.\n\n Ties are rounded toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round( 3.14 )\n 3.0\n > y = base.round( -4.2 )\n -4.0\n > y = base.round( -4.6 )\n -5.0\n > y = base.round( 9.5 )\n 10.0\n > y = base.round( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.roundn, base.trunc\n","base.round2":"\nbase.round2( x )\n Rounds a numeric value to the nearest power of two on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round2( 3.14 )\n 4.0\n > y = base.round2( -4.2 )\n -4.0\n > y = base.round2( -4.6 )\n -4.0\n > y = base.round2( 9.5 )\n 8.0\n > y = base.round2( 13.0 )\n 16.0\n > y = base.round2( -13.0 )\n -16.0\n > y = base.round2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round, base.round10\n","base.round10":"\nbase.round10( x )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round10( 3.14 )\n 1.0\n > y = base.round10( -4.2 )\n -1.0\n > y = base.round10( -4.6 )\n -1.0\n > y = base.round10( 9.5 )\n 10.0\n > y = base.round10( 13.0 )\n 10.0\n > y = base.round10( -13.0 )\n -10.0\n > y = base.round10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round, base.round2\n","base.roundb":"\nbase.roundb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundb( 3.14159, -2, 10 )\n 3.14\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.roundb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two:\n > y = base.roundb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.round, base.roundn\n","base.roundn":"\nbase.roundn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundn( 3.14159, -2 )\n 3.14\n\n // If `n = 0`, standard round behavior:\n > y = base.roundn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.roundn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.round, base.roundb\n","base.roundsd":"\nbase.roundsd( x, n[, b] )\n Rounds a numeric value to the nearest number with `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.roundsd( 3.14159, 3 )\n 3.14\n > y = base.roundsd( 3.14159, 1 )\n 3.0\n > y = base.roundsd( 12368.0, 2 )\n 12000.0\n > y = base.roundsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.round, base.truncsd\n","base.rsqrt":"\nbase.rsqrt( x )\n Computes the reciprocal square root of a double-precision floating-point\n number.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrt( 4.0 )\n 0.5\n > y = base.rsqrt( 100.0 )\n 0.1\n > y = base.rsqrt( 0.0 )\n Infinity\n > y = base.rsqrt( Infinity )\n 0.0\n > y = base.rsqrt( -4.0 )\n NaN\n > y = base.rsqrt( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n","base.rsqrtf":"\nbase.rsqrtf( x )\n Computes the reciprocal square root of a single-precision floating-point\n number.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrtf( 4.0 )\n 0.5\n > y = base.rsqrtf( 0.0 )\n Infinity\n > y = base.rsqrtf( Infinity )\n 0.0\n > y = base.rsqrtf( -4.0 )\n NaN\n > y = base.rsqrtf( NaN )\n NaN\n\n See Also\n --------\n base.rsqrt, base.sqrtf\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value, dtype, order )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n\n If `value` is a number and `dtype` is a complex number data type, the\n function returns a zero-dimensional ndarray containing a complex number\n whose real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n dtype: string\n Data type.\n\n order: string\n Memory layout (either 'row-major' or 'column-major').\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\n \n > var sh = x.shape\n []\n > var dt = x.dtype\n 'float64'\n > var v = x.get()\n 1.0\n\n See Also\n --------\n array, base.ndarray, ndarray\n","base.setHighWord":"\nbase.setHighWord( x, high )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n high: integer\n Unsigned 32-bit integer to replace the higher order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same lower order word as `x`.\n\n Examples\n --------\n // Set the higher order bits of `+infinity` to return `1`:\n > var high = 1072693248 >>> 0;\n > var y = base.setHighWord( PINF, high )\n 1.0\n\n See Also\n --------\n base.getHighWord, base.setLowWord\n","base.setLowWord":"\nbase.setLowWord( x, low )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n\n Setting the lower order bits of `NaN` or positive or negative infinity will\n return `NaN`, as `NaN` is defined as a double whose exponent bit sequence is\n all ones and whose fraction can be any bit sequence except all zeros.\n Positive and negative infinity are defined as doubles with an exponent bit\n sequence equal to all ones and a fraction equal to all zeros. Hence,\n changing the less significant bits of positive and negative infinity\n converts each value to `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n low: integer\n Unsigned 32-bit integer to replace the lower order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same higher order word as `x`.\n\n Examples\n --------\n > var low = 5 >>> 0;\n > var x = 3.14e201;\n > var y = base.setLowWord( x, low )\n 3.139998651394392e+201\n\n // Special cases:\n > var low = 12345678;\n > var y = base.setLowWord( PINF, low )\n NaN\n > y = base.setLowWord( NINF, low )\n NaN\n > y = base.setLowWord( NaN, low )\n NaN\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n","base.sici":"\nbase.sici( x )\n Computes the sine and cosine integrals.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n Sine and cosine integrals.\n\n Examples\n --------\n > var y = base.sici( 3.0 )\n [ ~1.849, ~0.12 ]\n > y = base.sici( 0.0 )\n [ 0.0, -Infinity ]\n > y = base.sici( -9.0 )\n [ ~-1.665, ~0.055 ]\n > y = base.sici( NaN )\n [ NaN, NaN ]\n\n\nbase.sici.assign( x, out, stride, offset )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.sici.assign( 3.0, out, 1, 0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true\n","base.sici.assign":"\nbase.sici.assign( x, out, stride, offset )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.sici.assign( 3.0, out, 1, 0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true","base.signbit":"\nbase.signbit( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbit( 4.0 )\n false\n > bool = base.signbit( -9.14e-34 )\n true\n > bool = base.signbit( 0.0 )\n false\n > bool = base.signbit( -0.0 )\n true\n\n See Also\n --------\n base.signbitf\n","base.signbitf":"\nbase.signbitf( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\n false\n > bool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\n true\n > bool = base.signbitf( 0.0 )\n false\n > bool = base.signbitf( -0.0 )\n true\n\n See Also\n --------\n base.signbit\n","base.significandf":"\nbase.significandf( x )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Significand.\n\n Examples\n --------\n > var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\n 4293751\n > s = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\n 5288021\n > s = base.significandf( base.float64ToFloat32( -3.14 ) )\n 4781507\n > s = base.significandf( 0.0 )\n 0\n > s = base.significandf( NaN )\n 4194304\n\n","base.signum":"\nbase.signum( x )\n Evaluates the signum function for a double-precision floating-point number.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signum( -5.0 )\n -1.0\n > sign = base.signum( 5.0 )\n 1.0\n > sign = base.signum( -0.0 )\n -0.0\n > sign = base.signum( 0.0 )\n 0.0\n > sign = base.signum( NaN )\n NaN\n\n","base.signumf":"\nbase.signumf( x )\n Evaluates the signum function for a single-precision floating-point number.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signumf( -5.0 )\n -1.0\n > sign = base.signumf( 5.0 )\n 1.0\n > sign = base.signumf( -0.0 )\n -0.0\n > sign = base.signumf( 0.0 )\n 0.0\n > sign = base.signumf( NaN )\n NaN\n\n See Also\n --------\n base.signum\n","base.sin":"\nbase.sin( x )\n Computes the sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Sine.\n\n Examples\n --------\n > var y = base.sin( 0.0 )\n ~0.0\n > y = base.sin( PI/2.0 )\n ~1.0\n > y = base.sin( -PI/6.0 )\n ~-0.5\n > y = base.sin( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinpi, base.tan\n","base.sinc":"\nbase.sinc( x )\n Computes the normalized cardinal sine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cardinal sine.\n\n Examples\n --------\n > var y = base.sinc( 0.5 )\n ~0.637\n > y = base.sinc( -1.2 )\n ~-0.156\n > y = base.sinc( 0.0 )\n 1.0\n > y = base.sinc( NaN )\n NaN\n\n See Also\n --------\n base.sin\n","base.sincos":"\nbase.sincos( x )\n Simultaneously computes the sine and cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: Array\n Sine and cosine.\n\n Examples\n --------\n > var y = base.sincos( 0.0 )\n [ ~0.0, ~1.0 ]\n > y = base.sincos( PI/2.0 )\n [ ~1.0, ~0.0 ]\n > y = base.sincos( -PI/6.0 )\n [ ~-0.5, ~0.866 ]\n > y = base.sincos( NaN )\n [ NaN, NaN ]\n\n\nbase.sincos( x, out, stride, offset )\n Simultaneously computes the sine and cosine of a number and assigns\n results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Sine and cosine.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincos.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cos, base.sin, base.sincospi","base.sincospi":"\nbase.sincospi( x )\n Simultaneously computes the sine and cosine of a number times π.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: Array\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var y = base.sincospi( 0.0 )\n [ 0.0, 1.0 ]\n > y = base.sincospi( 0.5 )\n [ 1.0, 0.0 ]\n > y = base.sincospi( 0.1 )\n [ ~0.309, ~0.951 ]\n > y = base.sincospi( NaN )\n [ NaN, NaN ]\n\n\nbase.sincospi.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cospi, base.sincos, base.sinpi","base.sincospi.assign":"\nbase.sincospi.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cospi, base.sincos, base.sinpi","base.sinh":"\nbase.sinh( x )\n Computes the hyperbolic sine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic sine.\n\n Examples\n --------\n > var y = base.sinh( 0.0 )\n 0.0\n > y = base.sinh( 2.0 )\n ~3.627\n > y = base.sinh( -2.0 )\n ~-3.627\n > y = base.sinh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sin, base.tanh\n","base.sinpi":"\nbase.sinpi( x )\n Computes the value of `sin(πx)`.\n\n The function computes `sin(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.sinpi( 0.0 )\n 0.0\n > y = base.sinpi( 0.5 )\n 1.0\n > y = base.sinpi( 0.9 )\n ~0.309\n > y = base.sinpi( NaN )\n NaN\n\n See Also\n --------\n base.sin\n","base.spence":"\nbase.spence( x )\n Evaluates Spence’s function, which is also known as the dilogarithm.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.spence( 3.0 )\n ~-1.437\n > y = base.spence( 0.0 )\n ~1.645\n > y = base.spence( -9.0 )\n NaN\n > y = base.spence( NaN )\n NaN\n\n","base.sqrt":"\nbase.sqrt( x )\n Computes the principal square root of a double-precision floating-point\n number.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrt( 4.0 )\n 2.0\n > y = base.sqrt( 9.0 )\n 3.0\n > y = base.sqrt( 0.0 )\n 0.0\n > y = base.sqrt( -4.0 )\n NaN\n > y = base.sqrt( NaN )\n NaN\n\n See Also\n --------\n base.cbrt, base.rsqrt\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x )\n Computes the principal square root of `1+x` minus one.\n\n This function is more accurate than the obvious approach for small `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Square root of `1+x` minus one.\n\n Examples\n --------\n > var y = base.sqrt1pm1( 3.0 )\n 1.0\n > y = base.sqrt1pm1( 0.5 )\n ~0.225\n > y = base.sqrt1pm1( 0.02 )\n ~0.01\n > y = base.sqrt1pm1( -0.5 )\n ~-0.293\n > y = base.sqrt1pm1( -1.1 )\n NaN\n > y = base.sqrt1pm1( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n","base.sqrtf":"\nbase.sqrtf( x )\n Computes the principal square root of a single-precision floating-point\n number.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrtf( 4.0 )\n 2.0\n > y = base.sqrtf( 9.0 )\n 3.0\n > y = base.sqrtf( 0.0 )\n 0.0\n > y = base.sqrtf( -4.0 )\n NaN\n > y = base.sqrtf( NaN )\n NaN\n\n See Also\n --------\n base.cbrtf, base.rsqrtf, base.sqrt\n","base.sqrtpi":"\nbase.sqrtpi( x )\n Computes the principal square root of the product of π and a positive\n double-precision floating-point number.\n\n For `x < 0`, the square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root of the product of π and the input value.\n\n Examples\n --------\n > var y = base.sqrtpi( 4.0 )\n ~3.5449\n > y = base.sqrtpi( 10.0 )\n ~5.60499\n > y = base.sqrtpi( 0.0 )\n 0.0\n > y = base.sqrtpi( -4.0 )\n NaN\n > y = base.sqrtpi( NaN )\n NaN\n\n See Also\n --------\n base.sqrt","base.strided.binary":"\nbase.strided.binary( arrays, shape, strides, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary( [ x, y, z ], shape, strides, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1, dtypes2, dtypes3[, options] )\n Generates a list of binary interface signatures from strided array data\n types.\n\n The function returns a strided array having a stride length of `3` (i.e.,\n every `3` elements define a binary interface signature).\n\n For each signature (i.e., set of three consecutive non-overlapping strided\n array elements), the first two elements are the input data types and the\n third element is the return data type.\n\n All signatures follow type promotion rules.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the first input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the second input argument.\n\n dtypes3: ArrayLike\n List of supported data types for the output value.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing binary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n [...]\n\n See Also\n --------\n base.strided.binarySignatureCallbacks\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table, signatures )\n Assigns callbacks to binary interfaces according to type promotion rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing binary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\n > var t = {\n ... 'default': base.add,\n ... 'complex64': base.caddf,\n ... 'complex128': base.cadd\n ... };\n > var out = base.strided.binarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.binaryDtypeSignatures\n","base.strided.ccopy":"\nbase.strided.ccopy( N, x, strideX, y, strideY )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy( x.length, x, 1, y, 1 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imag( z )\n 2.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy( 2, x, -2, y, 1 );\n > z = y.get( 0 );\n > re = realf( z )\n 5.0\n > im = imag( z )\n 6.0\n\n // Using typed array views:\n > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.ccopy( 2, x1, -2, y1, 1 );\n > z = y0.get( 2 );\n > re = realf( z )\n 7.0\n > im = imag( z )\n 8.0\n\n\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imag( z )\n 2.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > z = y.get( y.length-1 );\n > re = realf( z )\n 3.0\n > im = imag( z )\n 4.0\n\n See Also\n --------\n base.strided.cswap\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imag( z )\n 2.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > z = y.get( y.length-1 );\n > re = realf( z )\n 3.0\n > im = imag( z )\n 4.0\n\n See Also\n --------\n base.strided.cswap","base.strided.cmap":"\nbase.strided.cmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap( x.length, x, 1, y, 1, base.cidentityf );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Using `N` and stride parameters:\n > y = new Complex64Array( x.length );\n > base.strided.cmap( 2, x, 2, y, -1, base.cidentityf );\n > v = y.get( 0 )\n \n > re = real( v )\n 5.0\n > im = imag( v )\n 6.0\n\n // Using view offsets:\n > var x0 = new Complex64Array( xbuf );\n > var y0 = new Complex64Array( x0.length );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf );\n > v = y1.get( 0 )\n \n > re = real( v )\n 7.0\n > im = imag( v )\n 8.0\n\n\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Advanced indexing:\n > x = new Complex64Array( xbuf );\n > y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\n > v = y.get( y.length-1 )\n \n > re = real( v )\n 3.0\n > im = imag( v )\n 4.0\n\n See Also\n --------\n base.strided.zmap, base.strided.unary\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Advanced indexing:\n > x = new Complex64Array( xbuf );\n > y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\n > v = y.get( y.length-1 )\n \n > re = real( v )\n 3.0\n > im = imag( v )\n 4.0\n\n See Also\n --------\n base.strided.zmap, base.strided.unary","base.strided.cswap":"\nbase.strided.cswap( N, x, strideX, y, strideY )\n Interchanges two complex single-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped with\n values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap( x.length, x, 1, y, 1 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 2.0\n > z = x.get( 0 );\n > re = realf( z )\n 6.0\n > im = imagf( z )\n 7.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap( 2, x, -2, y, 1 );\n > z = y.get( 0 );\n > re = realf( z )\n 5.0\n > im = imagf( z )\n 6.0\n > z = x.get( 0 );\n > re = realf( z )\n 0.0\n > im = imagf( z )\n 0.0\n\n // Using typed array views:\n > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.cswap( 2, x1, -2, y1, 1 );\n > z = y0.get( 2 );\n > re = realf( z )\n 7.0\n > im = imagf( z )\n 8.0\n > z = x0.get( 1 );\n > re = realf( z )\n 0.0\n > im = imagf( z )\n 0.0\n\n\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two complex single-precision floating-point vectors using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 2.0\n > z = x.get( 0 );\n > re = realf( z )\n 6.0\n > im = imagf( z )\n 7.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > z = y.get( y.length-1 );\n > re = realf( z )\n 3.0\n > im = imagf( z )\n 4.0\n > z = x.get( 1 );\n > re = realf( z )\n 0.0\n > im = imagf( z )\n 0.0\n\n See Also\n --------\n base.strided.ccopy\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two complex single-precision floating-point vectors using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 2.0\n > z = x.get( 0 );\n > re = realf( z )\n 6.0\n > im = imagf( z )\n 7.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > z = y.get( y.length-1 );\n > re = realf( z )\n 3.0\n > im = imagf( z )\n 4.0\n > z = x.get( 1 );\n > re = realf( z )\n 0.0\n > im = imagf( z )\n 0.0\n\n See Also\n --------\n base.strided.ccopy","base.strided.cumax":"\nbase.strided.cumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumax( N, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.cumax( N, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumax\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumax","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumaxabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.cumaxabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs","base.strided.cumin":"\nbase.strided.cumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumin( N, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.cumin( N, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumin\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumin","base.strided.cuminabs":"\nbase.strided.cuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cuminabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.cuminabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs","base.strided.dabs":"\nbase.strided.dabs( N, x, strideX, y, strideY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs( N, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dabs( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs","base.strided.dabs2":"\nbase.strided.dabs2( N, x, strideX, y, strideY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2( x.length, x, 1, y, 1 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2( N, x, 2, y, -1 )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dabs2( N, x1, -2, y1, 1 )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs2\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs2","base.strided.dapx":"\nbase.strided.dapx( N, alpha, x, stride )\n Adds a constant to each element in a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns the strided array unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx( 3, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.dapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gapx, base.strided.sapx\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gapx, base.strided.sapx","base.strided.dapxsum":"\nbase.strided.dapxsum( N, alpha, x, stride )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dapxsum( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dapxsum( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.dapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N, alpha, x, stride )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided \n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumkbn( 3, 5.0, x1, 2)\n 14.0\n\n\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N, alpha, x, stride )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dapxsumkbn2( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dapxsumkbn2( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N, alpha, x, stride )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dapxsumors( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dapxsumors( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.dapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N, alpha, x, stride )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dapxsumpw( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dapxsumpw( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.dapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw","base.strided.dasum":"\nbase.strided.dasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum( x.length, x, 1 )\n 15.0\n\n // Sum every other value:\n > s = base.strided.dasum( 3, x, 2 )\n 9.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.dasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum","base.strided.dasumpw":"\nbase.strided.dasumpw( N, x, stride )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dasumpw( N, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dasumpw( N, x1, stride )\n 5.0\n\nbase.strided.dasumpw.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dasumpw.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dasumpw.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw","base.strided.daxpy":"\nbase.strided.daxpy( N, alpha, x, strideX, y, strideY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.strided.daxpy( 3, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.dasum, base.strided.gaxpy, base.strided.saxpy\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.dasum, base.strided.gaxpy, base.strided.saxpy","base.strided.dcbrt":"\nbase.strided.dcbrt( N, x, strideX, y, strideY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt( x.length, x, 1, y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt( N, x, 2, y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcbrt( N, x1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, base.strided.scbrt\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, base.strided.scbrt","base.strided.dceil":"\nbase.strided.dceil( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil( x.length, x, 1, y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil( N, x, 2, y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dceil( N, x1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil","base.strided.dcopy":"\nbase.strided.dcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.scopy\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.scopy","base.strided.dcumax":"\nbase.strided.dcumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumax( N, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcumax( N, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumax\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumax","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumaxabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcumaxabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs","base.strided.dcumin":"\nbase.strided.dcumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumin( N, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcumin( N, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumin\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumin","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcuminabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcuminabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs","base.strided.dcusum":"\nbase.strided.dcusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements.\n\n The `N` and `stride` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumkbn( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcusumkbn( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumkbn2( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcusumkbn2( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2","base.strided.dcusumors":"\nbase.strided.dcusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumors( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcusumors( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumpw( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcusumpw( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N, x, strideX, y, strideY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad( x.length, x, 1, y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad( N, x, 2, y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ddeg2rad( N, x1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n strided.deg2rad, base.strided.sdeg2rad\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n strided.deg2rad, base.strided.sdeg2rad","base.strided.ddot":"\nbase.strided.ddot( N, x, strideX, y, strideY )\n Computes the dot product of two double-precision floating-point vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.ddot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot","base.strided.dfill":"\nbase.strided.dfill( N, alpha, x, stride )\n Fills a double-precision floating-point strided array with a specified\n scalar value.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill( 3, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dfill( 3, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.dfill.ndarray( N, alpha, x, stride, offset )\n Fills a double-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill, base.strided.sfill\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N, alpha, x, stride, offset )\n Fills a double-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill, base.strided.sfill","base.strided.dfloor":"\nbase.strided.dfloor( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor( x.length, x, 1, y, 1 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor( N, x, 2, y, -1 )\n [ 3.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dfloor( N, x1, -2, y1, 1 )\n [ 4.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor","base.strided.dinv":"\nbase.strided.dinv( N, x, strideX, y, strideY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv( x.length, x, 1, y, 1 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv( N, x, 2, y, -1 )\n [ 0.5, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dinv( N, x1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n strided.inv, base.strided.sinv\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n strided.inv, base.strided.sinv","base.strided.dmap":"\nbase.strided.dmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap( x.length, x, 1, y, 1, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap( 2, x, 2, y, -1, base.identity )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmap( 2, x1, -2, y1, 1, base.identity )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.smap, base.strided.unary\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.smap, base.strided.unary","base.strided.dmap2":"\nbase.strided.dmap2( N, x, sx, y, sy, z, sz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays and assigns results to a double-precision floating-point strided\n output array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\n [ 3.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\n [ 7.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.smap2, base.strided.binary\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.smap2, base.strided.binary","base.strided.dmax":"\nbase.strided.dmax( N, x, stride )\n Computes the maximum value of a double-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmax( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmax( N, x1, stride )\n 2.0\n\nbase.strided.dmax.ndarray( N, x, stride, offset )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N, x, stride, offset )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N, x, stride )\n Computes the maximum absolute value of a double-precision floating-point\n strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmaxabs( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmaxabs( N, x1, stride )\n 2.0\n\nbase.strided.dmaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs","base.strided.dmaxabssorted":"\nbase.strided.dmaxabssorted( N, x, stride )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmaxabssorted( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmaxabssorted( N, x1, stride )\n 3.0\n\nbase.strided.dmaxabssorted.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmaxabssorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted\n","base.strided.dmaxabssorted.ndarray":"\nbase.strided.dmaxabssorted.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmaxabssorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted","base.strided.dmaxsorted":"\nbase.strided.dmaxsorted( N, x, stride )\n Computes the maximum value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmaxsorted( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmaxsorted( N, x1, stride )\n 3.0\n\nbase.strided.dmaxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmaxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted\n","base.strided.dmaxsorted.ndarray":"\nbase.strided.dmaxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmaxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted","base.strided.dmean":"\nbase.strided.dmean( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.smean\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.smean","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeankbn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeankbn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn, base.strided.smeankbn\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn, base.strided.smeankbn","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeankbn2( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeankbn2( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2","base.strided.dmeanli":"\nbase.strided.dmeanli( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanli( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanli( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanli.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanli.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanli.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanlipw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanlipw( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanlipw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw\n","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw","base.strided.dmeanors":"\nbase.strided.dmeanors( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanpw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanpw( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N, c, x, strideX, out, strideOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and standard deviation equal to\n `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanstdev( N, 1, x, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev( N, 1, x1, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N, c, x, strideX, out, strideOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and standard deviation equal to\n `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanstdevpn( N, 1, x, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( N, 1, x1, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N, c, x, strideX, out, strideOut )\n Computes the mean and variance of a double-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanvar( N, 1, x, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar( N, 1, x1, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dvariance\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dvariance","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N, c, x, strideX, out, strideOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanvarpn( N, 1, x, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( N, 1, x1, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N, x, stride )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmediansorted( N, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dmediansorted( N, x1, 2 )\n 2.0\n\nbase.strided.dmediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted","base.strided.dmidrange":"\nbase.strided.dmidrange( N, x, stride )\n Computes the mid-range of a double-precision floating-point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmidrange( N, x, stride )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmidrange( N, x1, stride )\n 0.0\n\nbase.strided.dmidrange.ndarray( N, x, stride, offset )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmidrange.ndarray( N, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N, x, stride, offset )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmidrange.ndarray( N, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange","base.strided.dmin":"\nbase.strided.dmin( N, x, stride )\n Computes the minimum value of a double-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmin( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmin( N, x1, stride )\n -2.0\n\nbase.strided.dmin.ndarray( N, x, stride, offset )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N, x, stride, offset )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin","base.strided.dminabs":"\nbase.strided.dminabs( N, x, stride )\n Computes the minimum absolute value of a double-precision floating-point\n strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dminabs( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dminabs( N, x1, stride )\n 1.0\n\nbase.strided.dminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs","base.strided.dminsorted":"\nbase.strided.dminsorted( N, x, stride )\n Computes the minimum value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dminsorted( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dminsorted( N, x1, stride )\n -2.0\n\nbase.strided.dminsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dminsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dminsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted","base.strided.dmskabs":"\nbase.strided.dmskabs( N, x, sx, m, sm, y, sy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\n [ 5.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N, x, sx, m, sm, y, sy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N, x, sx, m, sm, y, sy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt","base.strided.dmskceil":"\nbase.strided.dmskceil( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N, x, sx, m, sm, y, sy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.dmskdeg2rad, base.strided.smskdeg2rad\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.dmskdeg2rad, base.strided.smskdeg2rad","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor","base.strided.dmskinv":"\nbase.strided.dmskinv( N, x, sx, m, sm, y, sy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\n [ 0.0, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.smskinv\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.smskinv","base.strided.dmskmap":"\nbase.strided.dmskmap( N, x, sx, m, sm, y, sy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n [ 0.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\n [ 0.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\n [ 0.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2","base.strided.dmskmax":"\nbase.strided.dmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dmskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax","base.strided.dmskmin":"\nbase.strided.dmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dmskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin","base.strided.dmskramp":"\nbase.strided.dmskramp( N, x, sx, m, sm, y, sy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.smskramp\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.smskramp","base.strided.dmskrange":"\nbase.strided.dmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dmskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N, x, sx, m, sm, y, sy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N, x, sx, m, sm, y, sy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc","base.strided.dnanasum":"\nbase.strided.dnanasum( N, x, stride )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum( x.length, x, 1 )\n 5.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanasum( N, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanasum( N, x1, stride )\n 5.0\n\nbase.strided.dnanasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanasum.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dasumpw\n","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanasum.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dasumpw","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N, x, stride )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors( x.length, x, 1 )\n 5.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanasumors( N, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanasumors( N, x1, stride )\n 5.0\n\nbase.strided.dnanasumors.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanasumors.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dnanasum\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanasumors.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dnanasum","base.strided.dnanmax":"\nbase.strided.dnanmax( N, x, stride )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmax( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmax( N, x1, stride )\n 2.0\n\nbase.strided.dnanmax.ndarray( N, x, stride, offset )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N, x, stride, offset )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N, x, stride )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmaxabs( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmaxabs( N, x1, stride )\n 2.0\n\nbase.strided.dnanmaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs","base.strided.dnanmean":"\nbase.strided.dnanmean( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.snanmean\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.snanmean","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmeanpw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmeanpw( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dnanmean\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dnanmean","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, using Welford's algorithm and ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd","base.strided.dnanmin":"\nbase.strided.dnanmin( N, x, stride )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmin( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmin( N, x1, stride )\n -2.0\n\nbase.strided.dnanmin.ndarray( N, x, stride, offset )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N, x, stride, offset )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N, x, stride )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanminabs( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanminabs( N, x1, stride )\n 1.0\n\nbase.strided.dnanminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dnanmskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dnanmskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dnanmskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange","base.strided.dnannsum":"\nbase.strided.dnannsum( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` .`stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnannsum( N, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnansum, base.strided.dsum\n","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnansum, base.strided.dsum","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnannsumkbn( N, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnannsumkbn2( N, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnannsumors( N, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnannsumpw( N, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw","base.strided.dnanrange":"\nbase.strided.dnanrange( N, x, stride )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanrange( N, x, stride )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanrange( N, x1, stride )\n 4.0\n\nbase.strided.dnanrange.ndarray( N, x, stride, offset )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanrange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N, x, stride, offset )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanrange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc","base.strided.dnansum":"\nbase.strided.dnansum( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansum.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnansumkbn( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnansumkbn( N, x1, stride )\n -1.0\n\nbase.strided.dnansumkbn.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnansumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnansumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnansumkbn2( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnansumkbn2( N, x1, stride )\n -1.0\n\nbase.strided.dnansumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnansumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnansumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2","base.strided.dnansumors":"\nbase.strided.dnansumors( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnansumors( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnansumors( N, x1, stride )\n -1.0\n\nbase.strided.dnansumors.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnansumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnansumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnansumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnansumpw( N, x1, stride )\n -1.0\n\nbase.strided.dnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvariancech( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvariancech( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvariancetk( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvariancetk( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvariancewd( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvariancewd( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvarianceyc( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvarianceyc( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc","base.strided.dnrm2":"\nbase.strided.dnrm2( N, x, stride )\n Computes the L2-norm of a double-precision floating-point vector.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` or `stride <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dnrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.gnrm2, base.strided.snrm2\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.gnrm2, base.strided.snrm2","base.strided.dramp":"\nbase.strided.dramp( N, x, strideX, y, strideY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp( x.length, x, 1, y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp( N, x, 2, y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dramp( N, x1, -2, y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n strided.ramp, base.strided.sramp\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n strided.ramp, base.strided.sramp","base.strided.drange":"\nbase.strided.drange( N, x, stride )\n Computes the range of a double-precision floating-point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange( x.length, x, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.drange( N, x, stride )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.drange( N, x1, stride )\n 4.0\n\nbase.strided.drange.ndarray( N, x, stride, offset )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N, x, stride, offset )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange","base.strided.drev":"\nbase.strided.drev( N, x, stride )\n Reverses a double-precision floating-point strided array in-place.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.drev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.drev.ndarray( N, x, stride, offset )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.drev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.grev, base.strided.srev\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N, x, stride, offset )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.drev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.grev, base.strided.srev","base.strided.drsqrt":"\nbase.strided.drsqrt( N, x, strideX, y, strideY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt( x.length, x, 1, y, 1 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt( N, x, 2, y, -1 )\n [ ~0.333, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.drsqrt( N, x1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dsapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsapxsumpw( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsapxsumpw( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw","base.strided.dscal":"\nbase.strided.dscal( N, alpha, x, stride )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `stride <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal( x.length, 5.0, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy","base.strided.dsdot":"\nbase.strided.dsdot( N, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation and result.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > dot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, base.strided.sdsdot\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, base.strided.sdsdot","base.strided.dsem":"\nbase.strided.dsem( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsem( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsem( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsem.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsem.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dstdev\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsem.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dstdev","base.strided.dsemch":"\nbase.strided.dsemch( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsemch( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsemch( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsemch.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevch\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevch","base.strided.dsempn":"\nbase.strided.dsempn( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsempn( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsempn( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsempn.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevpn\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevpn","base.strided.dsemtk":"\nbase.strided.dsemtk( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsemtk( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsemtk( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsemtk.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevtk\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevtk","base.strided.dsemwd":"\nbase.strided.dsemwd( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsemwd( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsemwd( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsemwd.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevwd\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevwd","base.strided.dsemyc":"\nbase.strided.dsemyc( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsemyc( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsemyc( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsemyc.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevyc\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevyc","base.strided.dsmean":"\nbase.strided.dsmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and returning an extended precision\n result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsmeanpw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsmeanpw( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using ordinary recursive summation with\n extended accumulation, and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using a two-pass error correction algorithm\n with extended accumulation, and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnanmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnanmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsnanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using Welford's algorithm with extended\n accumulation, and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnanmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnanmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsnanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N, x, strideX, out, strideOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnannsumors( N, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors","base.strided.dsnansum":"\nbase.strided.dsnansum( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnansum( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnansum( N, x1, stride )\n -1.0\n\nbase.strided.dsnansum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnansum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnansum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnansumors( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnansumors( N, x1, stride )\n -1.0\n\nbase.strided.dsnansumors.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnansumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnansumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation,\n and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnansumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnansumpw( N, x1, stride )\n -1.0\n\nbase.strided.dsnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2ins( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsort2ins( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh","base.strided.dsorthp":"\nbase.strided.dsorthp( N, order, x, stride )\n Sorts a double-precision floating-point strided array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsorthp( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsorthp( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsorthp.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp","base.strided.dsortins":"\nbase.strided.dsortins( N, order, x, stride )\n Sorts a double-precision floating-point strided array using insertion sort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortins( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsortins( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsortins.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins","base.strided.dsortsh":"\nbase.strided.dsortsh( N, order, x, stride )\n Sorts a double-precision floating-point strided array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsortsh( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh","base.strided.dsqrt":"\nbase.strided.dsqrt( N, x, strideX, y, strideY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt( x.length, x, 1, y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt( N, x, 2, y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsqrt( N, x1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt","base.strided.dssum":"\nbase.strided.dssum( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dssum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dssum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dssum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssum.ndarray(3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssum.ndarray(3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean","base.strided.dssumors":"\nbase.strided.dssumors( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and returning\n an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dssumors( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dssumors( N, x1, stride )\n -1.0\n\nbase.strided.dssumors.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dssumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dssumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors","base.strided.dssumpw":"\nbase.strided.dssumpw( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dssumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dssumpw( N, x1, stride )\n -1.0\n\nbase.strided.dssumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dssumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dssumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw","base.strided.dstdev":"\nbase.strided.dstdev( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev","base.strided.dstdevch":"\nbase.strided.dstdevch( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc","base.strided.dsum":"\nbase.strided.dsum( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsum.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsumkbn( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsumkbn( N, x1, stride )\n -1.0\n\nbase.strided.dsumkbn.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsumkbn2( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsumkbn2( N, x1, stride )\n -1.0\n\nbase.strided.dsumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2","base.strided.dsumors":"\nbase.strided.dsumors( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsumors( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsumors( N, x1, stride )\n -1.0\n\nbase.strided.dsumors.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors","base.strided.dsumpw":"\nbase.strided.dsumpw( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsumpw( N, x1, stride )\n -1.0\n\nbase.strided.dsumpw.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw","base.strided.dsvariance":"\nbase.strided.dsvariance( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsvariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsvariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dsvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.variance, base.strided.svariance\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.variance, base.strided.svariance","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsvariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsvariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dsvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn","base.strided.dswap":"\nbase.strided.dswap( N, x, strideX, y, strideY )\n Interchanges two double-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped\n with values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap","base.strided.dtrunc":"\nbase.strided.dtrunc( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc( N, x, 2, y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dtrunc( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc","base.strided.dvariance":"\nbase.strided.dvariance( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance","base.strided.dvariancech":"\nbase.strided.dvariancech( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariancech( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariancech( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariancetk( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariancetk( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariancewd( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariancewd( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvarianceyc( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvarianceyc( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc","base.strided.dvarm":"\nbase.strided.dvarm( N, mean, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm( x.length, 1.0/3.0, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarm( N, 1.0/3.0, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dvarm( N, 1.0/3.0, 1, x1, 2 )\n ~4.3333\n\nbase.strided.dvarm.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N, mean, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn( x.length, 1.0/3.0, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmpn( N, 1.0/3.0, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dvarmpn( N, 1.0/3.0, 1, x1, 2 )\n ~4.3333\n\nbase.strided.dvarmpn.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N, mean, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk( x.length, 1.0/3.0, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmtk( N, 1.0/3.0, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dvarmtk( N, 1.0/3.0, 1, x1, 2 )\n ~4.3333\n\nbase.strided.dvarmtk.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm","base.strided.gapx":"\nbase.strided.gapx( N, alpha, x, stride )\n Adds a constant to each element in a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var alpha = 5.0;\n > base.strided.gapx( x.length, alpha, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.gapx( N, alpha, x, stride )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > alpha = 5.0;\n > stride = 2;\n > base.strided.gapx( N, alpha, x1, stride )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\nbase.strided.gapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var alpha = 5.0;\n > base.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.sapx\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var alpha = 5.0;\n > base.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.sapx","base.strided.gapxsum":"\nbase.strided.gapxsum( N, alpha, x, stride )\n Adds a constant to each strided array element and computes the sum.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gapxsum( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gapxsum( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.gapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N, alpha, x, stride )\n Adds a constant to each strided array element and computes the sum using an\n improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gapxsumkbn( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gapxsumkbn( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using an\n improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using an\n improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N, alpha, x, stride )\n Adds a constant to each strided array element and computes the sum using a\n second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gapxsumkbn2( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gapxsumkbn2( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using a\n second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using a\n second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N, alpha, x, stride )\n Adds a constant to each strided array element and computes the sum using\n ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gapxsumors( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gapxsumors( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.gapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N, alpha, x, stride )\n Adds a constant to each strided array element and computes the sum using\n pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gapxsumpw( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gapxsumpw( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.gapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw","base.strided.gasum":"\nbase.strided.gasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > s = base.strided.gasum( 3, x, 2 )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.gasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.sasum\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.sasum","base.strided.gasumpw":"\nbase.strided.gasumpw( N, x, stride )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gasumpw( N, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gasumpw( N, x1, stride )\n 5.0\n\nbase.strided.gasumpw.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.gasumpw.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.gasumpw.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw","base.strided.gaxpy":"\nbase.strided.gaxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.saxpy\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.saxpy","base.strided.gcopy":"\nbase.strided.gcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.scopy\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.scopy","base.strided.gcusum":"\nbase.strided.gcusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusum( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gcusum( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gcusumkbn( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn2( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gcusumkbn2( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2","base.strided.gcusumors":"\nbase.strided.gcusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumors( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gcusumors( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using pairwise\n summation.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumpw( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gcusumpw( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw","base.strided.gdot":"\nbase.strided.gdot( N, x, strideX, y, strideY )\n Computes the dot product of two vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.gdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, gdot\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, gdot","base.strided.gfill":"\nbase.strided.gfill( N, alpha, x, stride )\n Fills a strided array with a specified scalar value.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Constant.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfill( N, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gfill( N, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfill.ndarray( N, alpha, x, stride, offset )\n Fills a strided array with a specified scalar value using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Constant.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.sfill\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N, alpha, x, stride, offset )\n Fills a strided array with a specified scalar value using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Constant.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.sfill","base.strided.gfillBy":"\nbase.strided.gfillBy( N, x, stride, clbk[, thisArg] )\n Fills a strided array according to a provided callback function.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element\n - aidx: array index\n - sidx: strided index (offset + aidx*stride)\n - array: the input array\n\n The callback return value is used as the fill value for the current array\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy( x.length, x, 1, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfillBy( N, x, 2, fill )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gfillBy( N, x1, 2, fill )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfillBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N, x, strideX, out, strideOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnannsumkbn( N, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumkbn\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumkbn","base.strided.gnansum":"\nbase.strided.gnansum( N, x, stride )\n Computes the sum of strided array elements, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gnansum( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gnansum( N, x1, stride )\n -1.0\n\nbase.strided.gnansum.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N, x, stride )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gnansumkbn( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gnansumkbn( N, x1, stride )\n -1.0\n\nbase.strided.gnansumkbn.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N, x, stride )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gnansumkbn2( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gnansumkbn2( N, x1, stride )\n -1.0\n\nbase.strided.gnansumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2","base.strided.gnansumors":"\nbase.strided.gnansumors( N, x, stride )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gnansumors( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gnansumors( N, x1, stride )\n -1.0\n\nbase.strided.gnansumors.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N, x, stride )\n Computes the sum of strided array elements, ignoring `NaN` values and\n pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gnansumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gnansumpw( N, x1, stride )\n -1.0\n\nbase.strided.gnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw","base.strided.gnrm2":"\nbase.strided.gnrm2( N, x, stride )\n Computes the L2-norm of a vector.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` or `stride <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gnrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a vector using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.snrm2\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a vector using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.snrm2","base.strided.grev":"\nbase.strided.grev( N, x, stride )\n Reverses a strided array in-place.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.grev( N, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.grev( N, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.grev.ndarray( N, x, stride, offset )\n Reverses a strided array in-place using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.grev.ndarray( N, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.srev\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N, x, stride, offset )\n Reverses a strided array in-place using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.grev.ndarray( N, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.srev","base.strided.gscal":"\nbase.strided.gscal( N, alpha, x, stride )\n Multiplies a vector `x` by a constant `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `stride <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var alpha = 5.0;\n > base.strided.gscal( x.length, alpha, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.gscal.ndarray( N, alpha, x, stride, offset )\n Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.dscal, base.strided.gaxpy, base.strided.sscal\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N, alpha, x, stride, offset )\n Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.dscal, base.strided.gaxpy, base.strided.sscal","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2hp( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsort2hp( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2ins( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsort2ins( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2sh( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsort2sh( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.gsorthp":"\nbase.strided.gsorthp( N, order, x, stride )\n Sorts a strided array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsorthp( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsorthp( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsorthp.ndarray( N, order, x, stride, offset )\n Sorts a strided array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N, order, x, stride, offset )\n Sorts a strided array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.gsortins":"\nbase.strided.gsortins( N, order, x, stride )\n Sorts a strided array using insertion sort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortins( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsortins( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsortins.ndarray( N, order, x, stride, offset )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N, order, x, stride, offset )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins","base.strided.gsortsh":"\nbase.strided.gsortsh( N, order, x, stride )\n Sorts a strided array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortsh( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsortsh( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsortsh.ndarray( N, order, x, stride, offset )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N, order, x, stride, offset )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.gsum":"\nbase.strided.gsum( N, x, stride )\n Computes the sum of strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gsum( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gsum( N, x1, stride )\n -1.0\n\nbase.strided.gsum.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N, x, stride )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gsumkbn( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gsumkbn( N, x1, stride )\n -1.0\n\nbase.strided.gsumkbn.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N, x, stride )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gsumkbn2( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gsumkbn2( N, x1, stride )\n -1.0\n\nbase.strided.gsumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2","base.strided.gsumors":"\nbase.strided.gsumors( N, x, stride )\n Computes the sum of strided array elements using ordinary recursive\n summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gsumors( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gsumors( N, x1, stride )\n -1.0\n\nbase.strided.gsumors.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors","base.strided.gsumpw":"\nbase.strided.gsumpw( N, x, stride )\n Computes the sum of strided array elements using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gsumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gsumpw( N, x1, stride )\n -1.0\n\nbase.strided.gsumpw.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw","base.strided.gswap":"\nbase.strided.gswap( N, x, strideX, y, strideY )\n Interchanges vectors `x` and `y`.\n\n The `N` and stride parameters determine how values from `x` are swapped with\n values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap","base.strided.mapBy":"\nbase.strided.mapBy( N, x, sx, y, sy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element\n - idx: iteration index\n - indices: strided indices (offset + idx*stride)\n - arrays: input and output arrays\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy2, base.strided.unary\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy2, base.strided.unary","base.strided.mapBy2":"\nbase.strided.mapBy2( N, x, sx, y, sy, z, sz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements\n - idx: iteration index\n - indices: strided array indices (offset + idx*stride)\n - arrays: input and output arrays\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\n [ 8.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\n [ -4.0, 0.0 ]\n > z0\n [ 0.0, 0.0, -4.0, 0.0 ]\n\n\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 1.0, 1.0, 2.0, 2.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n [ 0.0, -4.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.binary\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 1.0, 1.0, 2.0, 2.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n [ 0.0, -4.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.binary","base.strided.max":"\nbase.strided.max( N, x, stride )\n Computes the maximum value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.max( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.max( N, x1, stride )\n 2.0\n\nbase.strided.max.ndarray( N, x, stride, offset )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.max.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N, x, stride, offset )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.max.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax","base.strided.maxabs":"\nbase.strided.maxabs( N, x, stride )\n Computes the maximum absolute value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.maxabs( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.maxabs( N, x1, stride )\n 2.0\n\nbase.strided.maxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs","base.strided.maxBy":"\nbase.strided.maxBy( N, x, stride, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element\n - aidx: array index\n - sidx: strided index (offset + aidx*stride)\n - array: the input array\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy( x.length, x, 1, accessor )\n 8.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxBy( N, x, 2, accessor )\n 8.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.maxBy( N, x1, 2, accessor )\n -4.0\n\nbase.strided.maxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax","base.strided.maxsorted":"\nbase.strided.maxsorted( N, x, stride )\n Computes the maximum value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.maxsorted( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.maxsorted( N, x1, stride )\n 3.0\n\nbase.strided.maxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted","base.strided.mean":"\nbase.strided.mean( N, x, stride )\n Computes the arithmetic mean of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.mean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.mean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.mean( N, x1, stride )\n ~-0.3333\n\nbase.strided.mean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.mean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.smean\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.mean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.smean","base.strided.meankbn":"\nbase.strided.meankbn( N, x, stride )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meankbn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meankbn( N, x1, stride )\n ~-0.3333\n\nbase.strided.meankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn","base.strided.meankbn2":"\nbase.strided.meankbn2( N, x, stride )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meankbn2( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meankbn2( N, x1, stride )\n ~-0.3333\n\nbase.strided.meankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2","base.strided.meanors":"\nbase.strided.meanors( N, x, stride )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.meanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors","base.strided.meanpn":"\nbase.strided.meanpn( N, x, stride )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.meanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn","base.strided.meanpw":"\nbase.strided.meanpw( N, x, stride )\n Computes the arithmetic mean of a strided array using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meanpw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meanpw( N, x1, stride )\n ~-0.3333\n\nbase.strided.meanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw","base.strided.meanwd":"\nbase.strided.meanwd( N, x, stride )\n Computes the arithmetic mean of a strided array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.meanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd","base.strided.mediansorted":"\nbase.strided.mediansorted( N, x, stride )\n Computes the median value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mediansorted( N, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.mediansorted( N, x1, 2 )\n 2.0\n\nbase.strided.mediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted","base.strided.min":"\nbase.strided.min( N, x, stride )\n Computes the minimum value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min( x.length, x, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.min( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.min( N, x1, stride )\n -2.0\n\nbase.strided.min.ndarray( N, x, stride, offset )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.min.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N, x, stride, offset )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.min.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin","base.strided.minabs":"\nbase.strided.minabs( N, x, stride )\n Computes the minimum absolute value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.minabs( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.minabs( N, x1, stride )\n 1.0\n\nbase.strided.minabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs","base.strided.minBy":"\nbase.strided.minBy( N, x, stride, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element\n - aidx: array index\n - sidx: strided index (offset + aidx*stride)\n - array: the input array\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy( x.length, x, 1, accessor )\n -10.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minBy( N, x, 2, accessor )\n -4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.minBy( N, x1, 2, accessor )\n -12.0\n\nbase.strided.minBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minBy.ndarray( N, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minBy.ndarray( N, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin","base.strided.minsorted":"\nbase.strided.minsorted( N, x, stride )\n Computes the minimum value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.minsorted( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.minsorted( N, x1, stride )\n -2.0\n\nbase.strided.minsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted","base.strided.mskmax":"\nbase.strided.mskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a strided array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.mskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax","base.strided.mskmin":"\nbase.strided.mskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a strided array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, -4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.mskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin","base.strided.mskrange":"\nbase.strided.mskrange( N, x, strideX, mask, strideMask )\n Computes the range of a strided array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.mskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange","base.strided.mskunary":"\nbase.strided.mskunary( arrays, shape, strides, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array and assigns results to elements in a\n strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > base.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.smskmap, base.strided.unary\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.smskmap, base.strided.unary","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1, dtypes2[, options] )\n Generates a list of masked unary interface signatures from strided array\n data types.\n\n The function returns a strided array having a stride length of three (i.e.,\n every three elements define a masked unary interface signature).\n\n For each signature (i.e., set of three consecutive non-overlapping strided\n array elements), the first element is the input data type, the second\n element is the mask data type, and the last element is the return data type.\n\n All signatures follow type promotion rules.\n\n The mask array data type is always `uint8`.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the output argument.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing masked unary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.mskunaryDtypeSignatures( dt, dt )\n [...]\n\n See Also\n --------\n base.strided.mskunarySignatureCallbacks\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table, signatures )\n Assigns callbacks to masked unary interfaces according to type promotion\n rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing masked unary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\n > var t = {\n ... 'default': base.identity,\n ... 'complex64': base.cidentityf,\n ... 'complex128': base.cidentity\n ... };\n > var out = base.strided.mskunarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.mskunaryDtypeSignatures\n","base.strided.nanmax":"\nbase.strided.nanmax( N, x, stride )\n Computes the maximum value of a strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmax( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmax( N, x1, stride )\n 2.0\n\nbase.strided.nanmax.ndarray( N, x, stride, offset )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N, x, stride, offset )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N, x, stride )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmaxabs( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmaxabs( N, x1, stride )\n 2.0\n\nbase.strided.nanmaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N, x, stride, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function,\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element\n - aidx: array index\n - sidx: strided index (offset + aidx*stride)\n - array: the input array\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy( x.length, x, 1, accessor )\n 8.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmaxBy( N, x, 2, accessor )\n 8.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanmaxBy( N, x1, 2, accessor )\n -4.0\n\nbase.strided.nanmaxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax","base.strided.nanmean":"\nbase.strided.nanmean( N, x, stride )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.nanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.snanmean\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.snanmean","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N, x, stride )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.nanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N, x, stride )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.nanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N, x, stride )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.nanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd","base.strided.nanmin":"\nbase.strided.nanmin( N, x, stride )\n Computes the minimum value of a strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmin( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmin( N, x1, stride )\n -2.0\n\nbase.strided.nanmin.ndarray( N, x, stride, offset )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N, x, stride, offset )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin","base.strided.nanminabs":"\nbase.strided.nanminabs( N, x, stride )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanminabs( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanminabs( N, x1, stride )\n 1.0\n\nbase.strided.nanminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs","base.strided.nanminBy":"\nbase.strided.nanminBy( N, x, stride, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function,\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element\n - aidx: array index\n - sidx: strided index (offset + aidx*stride)\n - array: the input array\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy( x.length, x, 1, accessor )\n -10.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanminBy( N, x, 2, accessor )\n -4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanminBy( N, x1, 2, accessor )\n -12.0\n\nbase.strided.nanminBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a strided array according to a mask and\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanmskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a strided array according to a mask and\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanmskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a strided array according to a mask and ignoring `NaN`\n values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanmskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange","base.strided.nanrange":"\nbase.strided.nanrange( N, x, stride )\n Computes the range of a strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanrange( N, x, stride )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanrange( N, x1, stride )\n 4.0\n\nbase.strided.nanrange.ndarray( N, x, stride, offset )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanrange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N, x, stride, offset )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanrange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N, x, stride, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element\n - aidx: array index\n - sidx: strided index (offset + aidx*stride)\n - array: the input array\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy( x.length, x, 1, accessor )\n 18.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanrangeBy( N, x, 2, accessor )\n 14.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanrangeBy( N, x1, 2, accessor )\n 8.0\n\nbase.strided.nanrangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange","base.strided.nanstdev":"\nbase.strided.nanstdev( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdev( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdev( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevch( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdevch( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevpn( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdevpn( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevtk( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdevtk( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevwd( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdevwd( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevyc( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdevyc( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc","base.strided.nanvariance":"\nbase.strided.nanvariance( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvariancech( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvariancech( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvariancetk( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvariancetk( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvariancewd( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvariancewd( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvarianceyc( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvarianceyc( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc","base.strided.nullary":"\nbase.strided.nullary( arrays, shape, strides, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n output array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary( [ x ], shape, strides, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting index (i.e., index offset) for\n the strided output array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1 ];\n > var offsets = [ 0 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting index (i.e., index offset) for\n the strided output array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1 ];\n > var offsets = [ 0 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.quaternary":"\nbase.strided.quaternary( arrays, shape, strides, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.quinary":"\nbase.strided.quinary( arrays, shape, strides, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary","base.strided.range":"\nbase.strided.range( N, x, stride )\n Computes the range of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range( x.length, x, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.range( N, x, stride )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.range( N, x1, stride )\n 4.0\n\nbase.strided.range.ndarray( N, x, stride, offset )\n Computes the range of a strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.range.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange\n","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N, x, stride, offset )\n Computes the range of a strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.range.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange","base.strided.rangeBy":"\nbase.strided.rangeBy( N, x, stride, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element\n - aidx: array index\n - sidx: strided index (offset + aidx*stride)\n - array: the input array\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy( x.length, x, 1, accessor )\n 18.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.rangeBy( N, x, 2, accessor )\n 12.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.rangeBy( N, x1, 2, accessor )\n 8.0\n\nbase.strided.rangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange","base.strided.sabs":"\nbase.strided.sabs( N, x, strideX, y, strideY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs( N, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sabs( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs, base.strided.sabs2\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs, base.strided.sabs2","base.strided.sabs2":"\nbase.strided.sabs2( N, x, strideX, y, strideY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2( x.length, x, 1, y, 1 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2( N, x, 2, y, -1 )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sabs2( N, x1, -2, y1, 1 )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs2, base.strided.sabs\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs2, base.strided.sabs","base.strided.sapx":"\nbase.strided.sapx( N, alpha, x, stride )\n Adds a constant to each element in a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns the strided array unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx( 3, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.sapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx","base.strided.sapxsum":"\nbase.strided.sapxsum( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sapxsumkbn2( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sapxsumkbn2( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sapxsumors( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sapxsumors( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.sapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var stride = 2;\n > base.strided.sapxsumpw( 3, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.sapxsumpw( 3, 5.0, x1, stride )\n 14.0\n\n\nbase.strided.sapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw","base.strided.sasum":"\nbase.strided.sasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and stride parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum( x.length, x, 1 )\n 15.0\n\n // Sum every other value:\n > s = base.strided.sasum( 3, x, 2 )\n 9.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.sasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.gasum\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.gasum","base.strided.sasumpw":"\nbase.strided.sasumpw( N, x, stride )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sasumpw( N, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sasumpw( N, x1, stride )\n 5.0\n\nbase.strided.sasumpw.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sasumpw.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sasumpw.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw","base.strided.saxpy":"\nbase.strided.saxpy( N, alpha, x, strideX, y, strideY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.strided.saxpy( 3, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gaxpy\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gaxpy","base.strided.scbrt":"\nbase.strided.scbrt( N, x, strideX, y, strideY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt( x.length, x, 1, y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt( N, x, 2, y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scbrt( N, x1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, strided.cbrt, base.strided.ssqrt\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, strided.cbrt, base.strided.ssqrt","base.strided.sceil":"\nbase.strided.sceil( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil( x.length, x, 1, y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil( N, x, 2, y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sceil( N, x1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc","base.strided.scopy":"\nbase.strided.scopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gcopy, base.strided.sswap\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gcopy, base.strided.sswap","base.strided.scumax":"\nbase.strided.scumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumax( N, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scumax( N, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumax, base.strided.scumin\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumax, base.strided.scumin","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumaxabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scumaxabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs","base.strided.scumin":"\nbase.strided.scumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumin( N, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scumin( N, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumin, base.strided.scumax\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumin, base.strided.scumax","base.strided.scuminabs":"\nbase.strided.scuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scuminabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scuminabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin","base.strided.scusum":"\nbase.strided.scusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements.\n\n The `N` and `stride` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scusumkbn( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided \n array elements using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use \n a typed array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scusumkbn2( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameter supports indexing semantics\n based on starting indices.\n\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameter supports indexing semantics\n based on starting indices.\n\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn","base.strided.scusumors":"\nbase.strided.scusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum","base.strided.scusumpw":"\nbase.strided.scusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N, x, strideX, y, strideY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad( x.length, x, 1, y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad( N, x, 2, y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sdeg2rad( N, x1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, strided.deg2rad\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, strided.deg2rad","base.strided.sdot":"\nbase.strided.sdot( N, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.sdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sdsapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsdot":"\nbase.strided.sdsdot( N, scalar, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns the provided scalar constant.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdot\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdot","base.strided.sdsmean":"\nbase.strided.sdsmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmean, base.strided.sdsnanmeanors\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmean, base.strided.sdsnanmeanors","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsnanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsnanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsnanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsnanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmeanors, base.strided.sdsnanmean\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmeanors, base.strided.sdsnanmean","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsnansum( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsnansum( N, x1, stride )\n -1.0\n\nbase.strided.sdsnansum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnansum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnansum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsnansumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsnansumpw( N, x1, stride )\n -1.0\n\nbase.strided.sdsnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw","base.strided.sdssum":"\nbase.strided.sdssum( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdssum( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdssum( N, x1, stride )\n -1.0\n\nbase.strided.sdssum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdssum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdssum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdssumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdssumpw( N, x1, stride )\n -1.0\n\nbase.strided.sdssumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdssumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdssumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw","base.strided.sfill":"\nbase.strided.sfill( N, alpha, x, stride )\n Fills a single-precision floating-point strided array with a specified\n scalar value.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfill( N, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sfill( N, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\nbase.strided.sfill.ndarray( N, alpha, x, stride, offset )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfill.ndarray( N, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.gfill\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N, alpha, x, stride, offset )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfill.ndarray( N, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.gfill","base.strided.sfloor":"\nbase.strided.sfloor( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor( x.length, x, 1, y, 1 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor( N, x, 2, y, -1 )\n [ 3.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sfloor( N, x1, -2, y1, 1 )\n [ 4.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc","base.strided.sinv":"\nbase.strided.sinv( N, x, strideX, y, strideY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv( x.length, x, 1, y, 1 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv( N, x, 2, y, -1 )\n [ 0.5, ~-0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sinv( N, x1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, strided.inv\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, strided.inv","base.strided.smap":"\nbase.strided.smap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap( x.length, x, 1, y, 1, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap( 2, x, 2, y, -1, base.identityf )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smap( 2, x1, -2, y1, 1, base.identityf )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.unary\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.unary","base.strided.smap2":"\nbase.strided.smap2( N, x, sx, y, sy, z, sz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\n [ 3.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\n [ 7.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.binary\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.binary","base.strided.smax":"\nbase.strided.smax( N, x, stride )\n Computes the maximum value of a single-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smax( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smax( N, x1, stride )\n 2.0\n\nbase.strided.smax.ndarray( N, x, stride, offset )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N, x, stride, offset )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax","base.strided.smaxabs":"\nbase.strided.smaxabs( N, x, stride )\n Computes the maximum absolute value of a single-precision floating-point\n strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smaxabs( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smaxabs( N, x1, stride )\n 2.0\n\nbase.strided.smaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N, x, stride )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smaxabssorted( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smaxabssorted( N, x1, stride )\n 3.0\n\nbase.strided.smaxabssorted.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smaxabssorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smaxabssorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N, x, stride )\n Computes the maximum value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smaxsorted( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smaxsorted( N, x1, stride )\n 3.0\n\nbase.strided.smaxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smaxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smaxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted","base.strided.smean":"\nbase.strided.smean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smean( N, x1, stride )\n ~-0.3333\n\nbase.strided.smean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean","base.strided.smeankbn":"\nbase.strided.smeankbn( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeankbn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeankbn( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.meankbn, base.strided.smean\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.meankbn, base.strided.smean","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeankbn2( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeankbn2( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean","base.strided.smeanli":"\nbase.strided.smeanli( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanli( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanli( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanli.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanli.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanli.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanlipw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanlipw( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanlipw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanlipw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanlipw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli","base.strided.smeanors":"\nbase.strided.smeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors","base.strided.smeanpn":"\nbase.strided.smeanpn( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn","base.strided.smeanpw":"\nbase.strided.smeanpw( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanpw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanpw( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.meanpw, base.strided.smean\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.meanpw, base.strided.smean","base.strided.smeanwd":"\nbase.strided.smeanwd( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd","base.strided.smediansorted":"\nbase.strided.smediansorted( N, x, stride )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smediansorted( N, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.smediansorted( N, x1, 2 )\n 2.0\n\nbase.strided.smediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean","base.strided.smidrange":"\nbase.strided.smidrange( N, x, stride )\n Computes the mid-range of a single-precision floating-point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smidrange( N, x, stride )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smidrange( N, x1, stride )\n 0.0\n\nbase.strided.smidrange.ndarray( N, x, stride, offset )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smidrange.ndarray( N, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N, x, stride, offset )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smidrange.ndarray( N, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange","base.strided.smin":"\nbase.strided.smin( N, x, stride )\n Computes the minimum value of a single-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin( x.length, x, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smin( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smin( N, x1, stride )\n -2.0\n\nbase.strided.smin.ndarray( N, x, stride, offset )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N, x, stride, offset )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin","base.strided.sminabs":"\nbase.strided.sminabs( N, x, stride )\n Computes the minimum absolute value of a single-precision floating-point\n strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sminabs( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sminabs( N, x1, stride )\n 1.0\n\nbase.strided.sminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs","base.strided.sminsorted":"\nbase.strided.sminsorted( N, x, stride )\n Computes the minimum value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sminsorted( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sminsorted( N, x1, stride )\n -2.0\n\nbase.strided.sminsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sminsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sminsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin","base.strided.smskabs":"\nbase.strided.smskabs( N, x, sx, m, sm, y, sy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\n [ 5.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2","base.strided.smskabs2":"\nbase.strided.smskabs2( N, x, sx, m, sm, y, sy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N, x, sx, m, sm, y, sy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt","base.strided.smskceil":"\nbase.strided.smskceil( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N, x, sx, m, sm, y, sy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.dmskdeg2rad, base.strided.sdeg2rad\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.dmskdeg2rad, base.strided.sdeg2rad","base.strided.smskfloor":"\nbase.strided.smskfloor( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc","base.strided.smskinv":"\nbase.strided.smskinv( N, x, sx, m, sm, y, sy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv( 2, x, 2, m, 2, y, -1 )\n [ 0.0, ~-0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.dmskinv\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.dmskinv","base.strided.smskmap":"\nbase.strided.smskmap( N, x, sx, m, sm, y, sy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n [ 0.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2","base.strided.smskmap2":"\nbase.strided.smskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\n [ 0.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\n [ 0.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap","base.strided.smskmax":"\nbase.strided.smskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.smskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax","base.strided.smskmin":"\nbase.strided.smskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.smskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin","base.strided.smskramp":"\nbase.strided.smskramp( N, x, sx, m, sm, y, sy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskramp, base.strided.sramp\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskramp, base.strided.sramp","base.strided.smskrange":"\nbase.strided.smskrange( N, x, strideX, mask, strideMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.smskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N, x, sx, m, sm, y, sy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N, x, sx, m, sm, y, sy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc","base.strided.snanmax":"\nbase.strided.snanmax( N, x, stride )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmax( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmax( N, x1, stride )\n 2.0\n\nbase.strided.snanmax.ndarray( N, x, stride, offset )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N, x, stride, offset )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N, x, stride )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmaxabs( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmaxabs( N, x1, stride )\n 2.0\n\nbase.strided.snanmaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs","base.strided.snanmean":"\nbase.strided.snanmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.snanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.smean, base.strided.nanmean\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.smean, base.strided.nanmean","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.snanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.snanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.snanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean\n","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean","base.strided.snanmin":"\nbase.strided.snanmin( N, x, stride )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmin( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmin( N, x1, stride )\n -2.0\n\nbase.strided.snanmin.ndarray( N, x, stride, offset )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N, x, stride, offset )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax","base.strided.snanminabs":"\nbase.strided.snanminabs( N, x, stride )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanminabs( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanminabs( N, x1, stride )\n 1.0\n\nbase.strided.snanminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanmskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanmskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanmskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin","base.strided.snanrange":"\nbase.strided.snanrange( N, x, stride )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanrange( N, x, stride )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanrange( N, x1, stride )\n 4.0\n\nbase.strided.snanrange.ndarray( N, x, stride, offset )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanrange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N, x, stride, offset )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanrange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange","base.strided.snanstdev":"\nbase.strided.snanstdev( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc","base.strided.snansum":"\nbase.strided.snansum( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snansum( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snansum( N, x1, stride )\n -1.0\n\nbase.strided.snansum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snansum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snansum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snansumkbn( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snansumkbn( N, x1, stride )\n -1.0\n\nbase.strided.snansumkbn.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snansumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snansumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snansumkbn2( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snansumkbn2( N, x1, stride )\n -1.0\n\nbase.strided.snansumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snansumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snansumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2","base.strided.snansumors":"\nbase.strided.snansumors( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snansumors( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snansumors( N, x1, stride )\n -1.0\n\nbase.strided.snansumors.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snansumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snansumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors","base.strided.snansumpw":"\nbase.strided.snansumpw( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snansumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snansumpw( N, x1, stride )\n -1.0\n\nbase.strided.snansumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw","base.strided.snanvariance":"\nbase.strided.snanvariance( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariance( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancech( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancepn( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancetk( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancewd( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvarianceyc( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc","base.strided.snrm2":"\nbase.strided.snrm2( N, x, stride )\n Computes the L2-norm of a single-precision floating-point vector.\n\n The `N` and `stride` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` or `stride <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.snrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.gnrm2\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.gnrm2","base.strided.sramp":"\nbase.strided.sramp( N, x, strideX, y, strideY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp( N, x, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sramp( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dramp, strided.ramp\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dramp, strided.ramp","base.strided.srange":"\nbase.strided.srange( N, x, stride )\n Computes the range of a single-precision floating-point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange( x.length, x, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.srange( N, x, stride )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.srange( N, x1, stride )\n 4.0\n\nbase.strided.srange.ndarray( N, x, stride, offset )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.srange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N, x, stride, offset )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.srange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range","base.strided.srev":"\nbase.strided.srev( N, x, stride )\n Reverses a single-precision floating-point strided array in-place.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.srev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.srev.ndarray( N, x, stride, offset )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.srev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.grev\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N, x, stride, offset )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.srev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.grev","base.strided.srsqrt":"\nbase.strided.srsqrt( N, x, strideX, y, strideY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt( x.length, x, 1, y, 1 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt( N, x, 2, y, -1 )\n [ ~0.333, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.srsqrt( N, x1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt","base.strided.sscal":"\nbase.strided.sscal( N, alpha, x, stride )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `stride <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal( x.length, 5.0, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssort2hp( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ssort2hp( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssort2ins( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ssort2ins( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssort2sh( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ssort2sh( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.ssorthp":"\nbase.strided.ssorthp( N, order, x, stride )\n Sorts a single-precision floating-point strided array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssorthp( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ssorthp( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.ssorthp.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssorthp.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssorthp.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.ssortins":"\nbase.strided.ssortins( N, order, x, stride )\n Sorts a single-precision floating-point strided array using insertion sort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssortins( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ssortins( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssortins.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssortins.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins","base.strided.ssortsh":"\nbase.strided.ssortsh( N, order, x, stride )\n Sorts a single-precision floating-point strided array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssortsh( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ssortsh( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.ssqrt":"\nbase.strided.ssqrt( N, x, strideX, y, strideY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt( x.length, x, 1, y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt( N, x, 2, y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ssqrt( N, x1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt","base.strided.sstdev":"\nbase.strided.sstdev( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance","base.strided.sstdevch":"\nbase.strided.sstdevch( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc","base.strided.ssum":"\nbase.strided.ssum( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.ssum( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.ssum( N, x1, stride )\n -1.0\n\nbase.strided.ssum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumkbn.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumkbn2( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumkbn2( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumors":"\nbase.strided.ssumors( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumors.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw","base.strided.ssumpw":"\nbase.strided.ssumpw( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors","base.strided.sswap":"\nbase.strided.sswap( N, x, strideX, y, strideY )\n Interchanges two single-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped\n with values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.sswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap","base.strided.stdev":"\nbase.strided.stdev( N, correction, x, stride )\n Computes the standard deviation of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance","base.strided.stdevch":"\nbase.strided.stdevch( N, correction, x, stride )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech","base.strided.stdevpn":"\nbase.strided.stdevpn( N, correction, x, stride )\n Computes the standard deviation of a strided array using a two-pass\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn","base.strided.stdevtk":"\nbase.strided.stdevtk( N, correction, x, stride )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk","base.strided.stdevwd":"\nbase.strided.stdevwd( N, correction, x, stride )\n Computes the standard deviation of a strided array using Welford's\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd","base.strided.stdevyc":"\nbase.strided.stdevyc( N, correction, x, stride )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc","base.strided.strunc":"\nbase.strided.strunc( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc( N, x, 2, y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.strunc( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc","base.strided.svariance":"\nbase.strided.svariance( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance","base.strided.svariancech":"\nbase.strided.svariancech( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariancech( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariancech( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech","base.strided.svariancepn":"\nbase.strided.svariancepn( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn","base.strided.svariancetk":"\nbase.strided.svariancetk( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariancetk( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariancetk( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk","base.strided.svariancewd":"\nbase.strided.svariancewd( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariancewd( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariancewd( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svarianceyc( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svarianceyc( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc\n","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc","base.strided.ternary":"\nbase.strided.ternary( arrays, shape, strides, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary( [ x, y, z, w ], shape, strides, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary","base.strided.unary":"\nbase.strided.unary( arrays, shape, strides, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > base.strided.unary( [ x, y ], shape, strides, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var offsets = [ 0, 0 ];\n > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.unary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var offsets = [ 0, 0 ];\n > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.unary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays, shape, strides, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n\n The shape and stride parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element\n - idx: iteration index\n - indices: strided indices (offset + idx*stride)\n - arrays: input and output arrays\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using shape and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n > y\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > sh = [ 2 ];\n > st = [ -2, 1 ];\n > base.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\n > y1\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > var o = [ 0, 0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > o = [ 1, y.length-1 ];\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.unary\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > var o = [ 0, 0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > o = [ 1, y.length-1 ];\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.unary","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1, dtypes2[, options] )\n Generates a list of unary interface signatures from strided array data\n types.\n\n The function returns a strided array having a stride length of two (i.e.,\n every two elements define a unary interface signature).\n\n For each signature (i.e., set of two consecutive non-overlapping strided\n array elements), the first element is the input data type and the second\n element is the return data type.\n\n All signatures follow type promotion rules.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the output argument.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing unary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.unaryDtypeSignatures( dt, dt )\n [...]\n\n See Also\n --------\n base.strided.unarySignatureCallbacks\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table, signatures )\n Assigns callbacks to unary interfaces according to type promotion rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing unary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.unaryDtypeSignatures( dt, dt );\n > var t = {\n ... 'default': base.identity,\n ... 'complex64': base.cidentityf,\n ... 'complex128': base.cidentity\n ... };\n > var out = base.strided.unarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.unaryDtypeSignatures\n","base.strided.variance":"\nbase.strided.variance( N, correction, x, stride )\n Computes the variance of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.variance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.variance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.variance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance","base.strided.variancech":"\nbase.strided.variancech( N, correction, x, stride )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.variancech( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.variancech( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.variancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance","base.strided.variancepn":"\nbase.strided.variancepn( N, correction, x, stride )\n Computes the variance of a strided array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.variancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.variancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.variancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance","base.strided.variancetk":"\nbase.strided.variancetk( N, correction, x, stride )\n Computes the variance of a strided array using a one-pass textbook\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.variancetk( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.variancetk( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.variancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance","base.strided.variancewd":"\nbase.strided.variancewd( N, correction, x, stride )\n Computes the variance of a strided array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.variancewd( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.variancewd( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.variancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance","base.strided.varianceyc":"\nbase.strided.varianceyc( N, correction, x, stride )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.varianceyc( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.varianceyc( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.varianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance","base.strided.zmap":"\nbase.strided.zmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap( x.length, x, 1, y, 1, base.cidentity );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Using `N` and stride parameters:\n > y = new Complex128Array( x.length );\n > base.strided.zmap( 2, x, 2, y, -1, base.cidentity );\n > v = y.get( 0 )\n \n > re = real( v )\n 5.0\n > im = imag( v )\n 6.0\n\n // Using view offsets:\n > var x0 = new Complex128Array( xbuf );\n > var y0 = new Complex128Array( x0.length );\n > var x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.zmap( 2, x1, -2, y1, 1, base.cidentity );\n > v = y1.get( 0 )\n \n > re = real( v )\n 7.0\n > im = imag( v )\n 8.0\n\n\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Advanced indexing:\n > x = new Complex128Array( xbuf );\n > y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\n > v = y.get( y.length-1 )\n \n > re = real( v )\n 3.0\n > im = imag( v )\n 4.0\n\n See Also\n --------\n base.strided.cmap, base.strided.unary\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Advanced indexing:\n > x = new Complex128Array( xbuf );\n > y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\n > v = y.get( y.length-1 )\n \n > re = real( v )\n 3.0\n > im = imag( v )\n 4.0\n\n See Also\n --------\n base.strided.cmap, base.strided.unary","base.sub":"\nbase.sub( x, y )\n Subtracts two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.sub( -1.0, 5.0 )\n -6.0\n > v = base.sub( 2.0, 5.0 )\n -3.0\n > v = base.sub( 0.0, 5.0 )\n -5.0\n > v = base.sub( -0.0, 0.0 )\n -0.0\n > v = base.sub( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.div, base.mul\n","base.subf":"\nbase.subf( x, y )\n Subtracts two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.subf( -1.0, 5.0 )\n -6.0\n > v = base.subf( 2.0, 5.0 )\n -3.0\n > v = base.subf( 0.0, 5.0 )\n -5.0\n > v = base.subf( -0.0, 0.0 )\n -0.0\n > v = base.subf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.divf, base.mulf, base.sub\n","base.sumSeries":"\nbase.sumSeries( generator[, options] )\n Sum the elements of the series given by the supplied function.\n\n Parameters\n ----------\n generator: Function\n Series function.\n\n options: Object (optional)\n Options.\n\n options.maxTerms: integer (optional)\n Maximum number of terms to be added. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n the current term times the tolerance. Default: `2.22e-16`.\n\n options.initialValue: number (optional)\n Initial value of the resulting sum. Default: `0`.\n\n Returns\n -------\n out: number\n Sum of series terms.\n\n Examples\n --------\n // Using an ES6 generator function:\n > function* geometricSeriesGenerator( x ) {\n ... var exponent = 0;\n ... while ( true ) {\n ... yield Math.pow( x, exponent );\n ... exponent += 1;\n ... }\n ... };\n > var gen = geometricSeriesGenerator( 0.9 );\n > var out = base.sumSeries( gen )\n 10\n\n // Using a closure:\n > function geometricSeriesClosure( x ) {\n ... var exponent = -1;\n ... return function() {\n ... exponent += 1;\n ... return Math.pow( x, exponent );\n ... };\n ... };\n > gen = geometricSeriesClosure( 0.9 );\n > out = base.sumSeries( gen )\n 10\n\n // Setting an initial value for the sum:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\n 3\n // Changing the maximum number of terms to be summed:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\n ~1.998 // Infinite sum is 2\n\n // Adjusting the used tolerance:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n ~1.998\n\n","base.tan":"\nbase.tan( x )\n Computes the tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Tangent.\n\n Examples\n --------\n > var y = base.tan( 0.0 )\n ~0.0\n > y = base.tan( -PI/4.0 )\n ~-1.0\n > y = base.tan( PI/4.0 )\n ~1.0\n > y = base.tan( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sin\n","base.tanh":"\nbase.tanh( x )\n Computes the hyperbolic tangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic tangent.\n\n Examples\n --------\n > var y = base.tanh( 0.0 )\n 0.0\n > var y = base.tanh( -0.0 )\n -0.0\n > y = base.tanh( 2.0 )\n ~0.964\n > y = base.tanh( -2.0 )\n ~-0.964\n > y = base.tanh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sinh, base.tan\n","base.toBinaryString":"\nbase.toBinaryString( x )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bstr: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryString( 4.0 )\n '0100000000010000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PI )\n '0100000000001001001000011111101101010100010001000010110100011000'\n > str = base.toBinaryString( -1.0e308 )\n '1111111111100001110011001111001110000101111010111100100010100000'\n > str = base.toBinaryString( -3.14e-320 )\n '1000000000000000000000000000000000000000000000000001100011010011'\n > str = base.toBinaryString( 5.0e-324 )\n '0000000000000000000000000000000000000000000000000000000000000001'\n > str = base.toBinaryString( 0.0 )\n '0000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( -0.0 )\n '1000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NaN )\n '0111111111111000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PINF )\n '0111111111110000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NINF )\n '1111111111110000000000000000000000000000000000000000000000000000'\n\n See Also\n --------\n base.fromBinaryString, base.toBinaryStringf\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\n '01000000100000000000000000000000'\n > str = base.toBinaryStringf( base.float64ToFloat32( PI ) )\n '01000000010010010000111111011011'\n > str = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\n '11111110100101100111011010011001'\n > str = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\n '10000000001000100011000100001011'\n > str = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringf( 0.0 )\n '00000000000000000000000000000000'\n > str = base.toBinaryStringf( -0.0 )\n '10000000000000000000000000000000'\n > str = base.toBinaryStringf( NaN )\n '01111111110000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_PINF )\n '01111111100000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_NINF )\n '11111111100000000000000000000000'\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 8-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 8-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned 8-bit\n integers. Accordingly, care should be taken to ensure that only nonnegative\n integer values less than `256` (`2^8`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint8Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint8( a[ 0 ] )\n '00000001'\n > str = base.toBinaryStringUint8( a[ 1 ] )\n '00000100'\n > str = base.toBinaryStringUint8( a[ 2 ] )\n '00001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 16-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 16-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 16-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `65536` (`2^16`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint16Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint16( a[ 0 ] )\n '0000000000000001'\n > str = base.toBinaryStringUint16( a[ 1 ] )\n '0000000000000100'\n > str = base.toBinaryStringUint16( a[ 2 ] )\n '0000000000001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 32-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 32-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 32-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `4,294,967,296` (`2^32`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint32Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint32( a[ 0 ] )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringUint32( a[ 1 ] )\n '00000000000000000000000000000100'\n > str = base.toBinaryStringUint32( a[ 2 ] )\n '00000000000000000000000000001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toWordf":"\nbase.toWordf( x )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var f32 = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n > var w = base.toWordf( f32 )\n 1068180177\n\n See Also\n --------\n base.fromWordf, base.toWords\n","base.toWords":"\nbase.toWords( x )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array\n Higher and lower order words.\n\n Examples\n --------\n > var w = base.toWords( 3.14e201 )\n [ 1774486211, 2479577218 ]\n\n\nbase.toWords.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var out = new Uint32Array( 2 );\n > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n\n See Also\n --------\n base.fromWords, base.toWordf","base.toWords.assign":"\nbase.toWords.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var out = new Uint32Array( 2 );\n > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n\n See Also\n --------\n base.fromWords, base.toWordf","base.transpose":"\nbase.transpose( x )\n Transposes a matrix (or a stack of matrices).\n\n The returned ndarray is a *view* of the input ndarray. Accordingly, writing\n to the original ndarray will mutate the returned ndarray and vice versa.\n While powerful, this can lead to subtle bugs. In general, one should handle\n the returned ndarray as read-only.\n\n If provided an ndarray with fewer than two dimensions, the function raises\n an exception.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n \n > var sh = x.shape\n [ 2, 3 ]\n > var y = base.transpose( x )\n \n > sh = y.shape\n [ 3, 2 ]\n > var bool = ( x.data === y.data )\n true\n > bool = ( x.get( 0, 1 ) === y.get( 1, 0 ) )\n true\n\n See Also\n --------\n ndarray\n","base.tribonacci":"\nbase.tribonacci( n )\n Computes the nth Tribonacci number.\n\n Tribonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2} + F_{n-3}\n\n with seed values F_0 = 0, F_1 = 0, and F_2 = 1.\n\n If `n` is greater than `63`, the function returns `NaN`, as larger\n Tribonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Tribonacci number.\n\n Examples\n --------\n > var y = base.tribonacci( 0 )\n 0\n > y = base.tribonacci( 1 )\n 0\n > y = base.tribonacci( 2 )\n 1\n > y = base.tribonacci( 3 )\n 1\n > y = base.tribonacci( 4 )\n 2\n > y = base.tribonacci( 64 )\n NaN\n > y = base.tribonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.trigamma":"\nbase.trigamma( x )\n Evaluates the trigamma function.\n\n If `x` is `0` or a negative `integer`, the `function` returns `NaN`.\n\n If provided `NaN`, the `function` returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.trigamma( -2.5 )\n ~9.539\n > y = base.trigamma( 1.0 )\n ~1.645\n > y = base.trigamma( 10.0 )\n ~0.105\n > y = base.trigamma( NaN )\n NaN\n > y = base.trigamma( -1.0 )\n NaN\n\n See Also\n --------\n base.digamma, base.gamma\n","base.trunc":"\nbase.trunc( x )\n Rounds a double-precision floating-point number toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc( 3.14 )\n 3.0\n > y = base.trunc( -4.2 )\n -4.0\n > y = base.trunc( -4.6 )\n -4.0\n > y = base.trunc( 9.5 )\n 9.0\n > y = base.trunc( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.round\n","base.trunc2":"\nbase.trunc2( x )\n Rounds a numeric value to the nearest power of two toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc2( 3.14 )\n 2.0\n > y = base.trunc2( -4.2 )\n -4.0\n > y = base.trunc2( -4.6 )\n -4.0\n > y = base.trunc2( 9.5 )\n 8.0\n > y = base.trunc2( 13.0 )\n 8.0\n > y = base.trunc2( -13.0 )\n -8.0\n > y = base.trunc2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round2, base.trunc, base.trunc10\n","base.trunc10":"\nbase.trunc10( x )\n Rounds a numeric value to the nearest power of ten toward zero.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc10( 3.14 )\n 1.0\n > y = base.trunc10( -4.2 )\n -1.0\n > y = base.trunc10( -4.6 )\n -1.0\n > y = base.trunc10( 9.5 )\n 1.0\n > y = base.trunc10( 13.0 )\n 10.0\n > y = base.trunc10( -13.0 )\n -10.0\n > y = base.trunc10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round10, base.trunc, base.trunc2\n","base.truncb":"\nbase.truncb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.truncb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward zero:\n > y = base.truncb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.roundb, base.trunc, base.truncn\n","base.truncf":"\nbase.truncf( x )\n Rounds a single-precision floating-point number toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncf( 3.14 )\n 3.0\n > y = base.truncf( -4.2 )\n -4.0\n > y = base.truncf( -4.6 )\n -4.0\n > y = base.truncf( 9.5 )\n 9.0\n > y = base.truncf( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceilf, base.floorf, base.trunc\n","base.truncn":"\nbase.truncn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round behavior:\n > y = base.truncn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.truncn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.roundn, base.trunc, base.truncb\n","base.truncsd":"\nbase.truncsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncsd( 3.14159, 5 )\n 3.1415\n > y = base.truncsd( 3.14159, 1 )\n 3.0\n > y = base.truncsd( 12368.0, 2 )\n 12000.0\n > y = base.truncsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.roundsd, base.trunc\n","base.umul":"\nbase.umul( a, b )\n Performs C-like multiplication of two unsigned 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.umul( 10>>>0, 4>>>0 )\n 40\n\n See Also\n --------\n base.imul\n","base.umuldw":"\nbase.umuldw( a, b )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: Array\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.umuldw( 1, 10 )\n [ 0, 10 ]\n\n\nbase.umuldw.assign( a, b, out, stride, offset )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imuldw, base.umul\n","base.umuldw.assign":"\nbase.umuldw.assign( a, b, out, stride, offset )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imuldw, base.umul","base.uint32ToInt32":"\nbase.uint32ToInt32( x )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\n -1\n > y = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n 3\n\n","base.vercos":"\nbase.vercos( x )\n Computes the versed cosine.\n\n The versed cosine is defined as `1 + cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed cosine.\n\n Examples\n --------\n > var y = base.vercos( 3.14 )\n ~0.0\n > y = base.vercos( -4.2 )\n ~0.5097\n > y = base.vercos( -4.6 )\n ~0.8878\n > y = base.vercos( 9.5 )\n ~0.0028\n > y = base.vercos( -0.0 )\n 2.0\n\n See Also\n --------\n base.cos, base.versin\n","base.versin":"\nbase.versin( x )\n Computes the versed sine.\n\n The versed sine is defined as `1 - cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed sine.\n\n Examples\n --------\n > var y = base.versin( 3.14 )\n ~2.0\n > y = base.versin( -4.2 )\n ~1.490\n > y = base.versin( -4.6 )\n ~1.112\n > y = base.versin( 9.5 )\n ~1.997\n > y = base.versin( -0.0 )\n 0.0\n\n See Also\n --------\n base.cos, base.sin, base.vercos\n","base.wrap":"\nbase.wrap( v, min, max )\n Wraps a value on the half-open interval `[min,max)`.\n\n The function does not distinguish between positive and negative zero. Where\n appropriate, the function returns positive zero.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to wrap.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Wrapped value.\n\n Examples\n --------\n > var y = base.wrap( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.wrap( -3.14, 0.0, 5.0 )\n ~1.86\n > y = base.wrap( 3.14, 0.0, 3.0 )\n ~0.14\n > y = base.wrap( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.wrap( 0.0, -3.14, -0.0 )\n -3.14\n > y = base.wrap( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clamp\n","base.xlog1py":"\nbase.xlog1py( x, y )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlog1py( 3.0, 2.0 )\n ~3.296\n > out = base.xlog1py( 1.5, 5.9 )\n ~2.897\n > out = base.xlog1py( 0.9, 1.0 )\n ~0.624\n > out = base.xlog1py( 1.0, 0.0 )\n 0.0\n > out = base.xlog1py( 0.0, -2.0 )\n 0.0\n > out = base.xlog1py( 1.5, NaN )\n NaN\n > out = base.xlog1py( 0.0, NaN )\n NaN\n > out = base.xlog1py( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.log1p, base.xlogy\n","base.xlogy":"\nbase.xlogy( x, y )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlogy( 3.0, 2.0 )\n ~2.079\n > out = base.xlogy( 1.5, 5.9 )\n ~2.662\n > out = base.xlogy( 0.9, 1.0 )\n 0.0\n > out = base.xlogy( 0.0, -2.0 )\n 0.0\n > out = base.xlogy( 1.5, NaN )\n NaN\n > out = base.xlogy( 0.0, NaN )\n NaN\n > out = base.xlogy( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.ln, base.xlog1py\n","base.zeta":"\nbase.zeta( s )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.zeta( 1.1 )\n ~10.584\n > y = base.zeta( -4.0 )\n 0.0\n > y = base.zeta( 70.0 )\n 1.0\n > y = base.zeta( 0.5 )\n ~-1.46\n > y = base.zeta( NaN )\n NaN\n\n // Evaluate at a pole:\n > y = base.zeta( 1.0 )\n NaN\n\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and and other characteristics.\n\n Each array element has the following eleven fields:\n\n - education: number of years of education.\n - south: indicator variable for southern region (1 if a person lives in the\n South; 0 if a person does not live in the South).\n - gender: gender of the person.\n - experience: number of years of work experience.\n - union: indicator variable for union membership (1 if union member; 0 if\n not a union member).\n - wage: wage (in dollars per hour).\n - age: age (in years).\n - race: ethnicity/race (white, hispanic, and other).\n - occupation: occupational category (management, sales, clerical, service,\n professional, and other).\n - sector: sector (other, manufacturing, or construction).\n - married: marital status (0 if unmarried; 1 if married).\n\n Based on residual plots, wages were log-transformed to stabilize the\n variance.\n\n Returns\n -------\n out: Array\n CPS data.\n\n Examples\n --------\n > var data = BERNDT_CPS_WAGES_1985()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Berndt, Ernst R. 1991. _The Practice of Econometrics_. Addison Wesley\n Longman Publishing Co.\n\n","bifurcate":"\nbifurcate( collection, [options,] filter )\n Splits values into two groups.\n\n If an element in `filter` is truthy, then the corresponding element in the\n input collection belongs to the first group; otherwise, the collection\n element belongs to the second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n filter: Array|TypedArray|Object\n A collection indicating which group an element in the input collection\n belongs to. If an element in `filter` is truthy, the corresponding\n element in `collection` belongs to the first group; otherwise, the\n collection element belongs to the second group. If provided an object,\n the object must be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var f = [ true, true, false, true ];\n > var out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n > f = [ 1, 1, 0, 1 ];\n > out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > f = [ true, true, false, true ];\n > var opts = { 'returns': 'indices' };\n > out = bifurcate( collection, opts, f )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = bifurcate( collection, opts, f )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo'] ] ]\n\n See Also\n --------\n bifurcateBy, bifurcateOwn, group\n","bifurcateBy":"\nbifurcateBy( collection, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If a predicate function returns a truthy value, a collection value is\n placed in the first group; otherwise, a collection value is placed in the\n second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = bifurcateBy( collection, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, groupBy\n","bifurcateByAsync":"\nbifurcateByAsync( collection, [options,] predicate, done )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an predicate function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If a predicate function calls the `next` callback with a truthy group value,\n a collection value is placed in the first group; otherwise, a collection\n value is placed in the second group.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n [ [ 1000, 3000 ], [ 2500 ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ 2, 0 ], [ 1 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ [ 2, 1000 ], [ 0, 3000 ] ], [ [ 1, 2500 ] ] ]\n\n // Limit number of concurrent invocations:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n // Process sequentially:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n See Also\n --------\n bifurcateBy, groupByAsync\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n See Also\n --------\n bifurcateBy, groupByAsync","bifurcateIn":"\nbifurcateIn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object with no prototype, the function returns an empty\n array.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var out = bifurcateIn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateOwn, groupIn\n","bifurcateOwn":"\nbifurcateOwn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object, the function returns an empty array.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = bifurcateOwn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateIn, groupOwn\n","BigInt":"\nBigInt( value )\n Returns a BigInt.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support BigInts.\n\n Parameters\n ----------\n value: integer|string\n Value of the BigInt.\n\n Returns\n -------\n out: BigInt\n BigInt.\n\n Examples\n --------\n > var v = ( BigInt ) ? BigInt( '1' ) : null\n\n\nTODO: document properties/methods\n\n","binomialTest":"\nbinomialTest( x[, n][, options] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: (number|Array)\n Number of successes or two-element array with successes and failures.\n\n n: Array (optional)\n Total number of observations.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.p: number (optional)\n Hypothesized probability under the null hypothesis. Default: `0.5`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Sample proportion.\n\n out.ci: Array\n 1-alpha confidence interval for the success probability.\n\n out.nullValue: number\n Assumed success probability under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var out = binomialTest( 682, 925 )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( [ 682, 925 - 682 ] )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( 21, 40, {\n ... 'p': 0.4,\n ... 'alternative': 'greater'\n ... })\n {\n 'pValue': ~0.074,\n 'statistic': 0.525\n // ...\n }\n\n","Boolean":"\nBoolean( value )\n Returns a boolean.\n\n When invoked without `new`,\n\n - if provided `false`, `null`, `undefined`, `-0`, `0`, `NaN`, or an empty\n string, the function returns `false`.\n - if provided any other value, including an empty object, an empty array,\n the string `'false'`, or a `Boolean` object (including a `Boolean` object\n whose value is `false`), the function returns `true`.\n\n When invoked with `new`, the constructor returns a `Boolean` object, which\n is an object wrapper for a primitive boolean value. The value of the\n returned `Boolean` object follows the same conversion semantics as when the\n constructor is invoked without `new`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: boolean|Boolean\n Boolean primitive or object.\n\n Examples\n --------\n > var b = new Boolean( null )\n \n > b = Boolean( null )\n false\n > b = Boolean( [] )\n true\n\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n\n Returns\n -------\n out: string\n String representation.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.toString()\n 'true'\n\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n\n Returns\n -------\n out: boolean\n Boolean primitive.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.valueOf()\n true\n\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n\n Returns\n -------\n out: string\n String representation.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.toString()\n 'true'","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n\n Returns\n -------\n out: boolean\n Boolean primitive.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.valueOf()\n true","broadcastArray":"\nbroadcastArray( x, shape )\n Broadcasts an ndarray to a specified shape.\n\n The returned array is a read-only view on the input array data buffer. The\n view is typically *not* contiguous. As more than one element of a returned\n view may refer to the same memory location, writing to the input array may\n affect multiple elements. If you need to write to the input array, copy the\n input array before broadcasting.\n\n The function throws an error if a provided ndarray is incompatible with a\n provided shape.\n\n The function always returns a new ndarray instance even if the input ndarray\n shape and the desired shape are the same.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n shape: ArrayLikeObject\n Desired shape.\n\n Returns\n -------\n out: ndarray\n Broadcasted array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = broadcastArray( x, [ 3, 2, 2 ] )\n \n > sh = y.shape\n [ 3, 2, 2 ]\n > var v = y.get( 0, 0, 0 )\n 1\n > v = y.get( 0, 0, 1 )\n 2\n > v = y.get( 0, 1, 0 )\n 3\n > v = y.get( 0, 1, 1 )\n 4\n > v = y.get( 1, 0, 0 )\n 1\n > v = y.get( 1, 1, 0 )\n 3\n > v = y.get( 2, 0, 0 )\n 1\n > v = y.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, broadcastArrays, ndarray, maybeBroadcastArray\n","broadcastArrays":"\nbroadcastArrays( ...arrays )\n Broadcasts ndarrays to a common shape.\n\n The function supports two (mutually exclusive) means of providing ndarray\n arguments:\n\n 1. Providing a single array containing ndarray arguments.\n 2. Providing ndarray arguments as separate arguments.\n\n The returned arrays are read-only views on their respective underlying\n array data buffers. The views are typically **not** contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to a view may affect multiple elements. If you need to write to an\n input array, copy the array before broadcasting.\n\n The function throws an error if provided broadcast-incompatible ndarrays.\n\n The function always returns new ndarray instances even if an input ndarray\n and the broadcasted shape are the same.\n\n Parameters\n ----------\n arrays: ...ndarray|ArrayLikeObject\n Array arguments.\n\n Returns\n -------\n out: Array\n Broadcasted arrays.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = ndzeros( [ 3, 2, 2 ] )\n \n > var out = broadcastArrays( [ x, y ] )\n [ , ]\n\n // Retrieve the broadcasted \"x\" array:\n > var bx = out[ 0 ]\n \n > sh = bx.shape\n [ 3, 2, 2 ]\n\n // Retrieve broadcasted elements...\n > var v = bx.get( 0, 0, 0 )\n 1\n > v = bx.get( 0, 0, 1 )\n 2\n > v = bx.get( 0, 1, 0 )\n 3\n > v = bx.get( 0, 1, 1 )\n 4\n > v = bx.get( 1, 0, 0 )\n 1\n > v = bx.get( 1, 1, 0 )\n 3\n > v = bx.get( 2, 0, 0 )\n 1\n > v = bx.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, broadcastArray, ndarray, maybeBroadcastArrays\n","Buffer":"\nBuffer\n Buffer constructor.\n\n\nBuffer( size )\n Allocates a buffer having a specified number of bytes.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 4 )\n \n\n\nBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = new Buffer( [ 1, 2, 3, 4 ] );\n > var b2 = new Buffer( b1 )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( array )\n Allocates a buffer using an array of octets.\n\n Parameters\n ----------\n array: Array\n Array of octets.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 'beep boop' )\n \n\n\nTODO: add methods and properties\n\n\n See Also\n --------\n ArrayBuffer\n","buffer2json":"\nbuffer2json( buffer )\n Returns a JSON representation of a buffer.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n out.type: string\n Value type. The assigned value is always \"Buffer\".\n\n out.data: Array\n Buffer data.\n\n Examples\n --------\n > var buf = new allocUnsafe( 2 );\n > buf[ 0 ] = 1;\n > buf[ 1 ] = 2;\n > var json = buffer2json( buf )\n { 'type': 'Buffer', 'data': [ 1, 2 ] }\n\n See Also\n --------\n typedarray2json, reviveBuffer\n","BYTE_ORDER":"\nBYTE_ORDER\n Platform byte order.\n\n Possible values:\n\n - 'little-endian'\n - 'big-endian'\n - 'mixed-endian'\n - 'unknown'\n\n Examples\n --------\n > BYTE_ORDER\n \n\n See Also\n --------\n IS_BIG_ENDIAN, IS_LITTLE_ENDIAN\n","camelcase":"\ncamelcase( str )\n Converts a string to camel case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Camel-cased string.\n\n Examples\n --------\n > var out = camelcase( 'Hello World!' )\n 'helloWorld'\n > out = camelcase( 'beep boop' )\n 'beepBoop'\n\n See Also\n --------\n constantcase, kebabcase, pascalcase, snakecase","capitalize":"\ncapitalize( str )\n Capitalizes the first character in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Capitalized string.\n\n Examples\n --------\n > var out = capitalize( 'beep' )\n 'Beep'\n > out = capitalize( 'Boop' )\n 'Boop'\n\n See Also\n --------\n uncapitalize, uppercase\n","capitalizeKeys":"\ncapitalizeKeys( obj )\n Converts the first letter of each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'aa': 1, 'bb': 2 };\n > var out = capitalizeKeys( obj )\n { 'Aa': 1, 'Bb': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n","CATALAN":"\nCATALAN\n Catalan's constant.\n\n Examples\n --------\n > CATALAN\n 0.915965594177219\n\n","CBRT_EPS":"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n\n Examples\n --------\n > CBRT_EPS\n 0.0000060554544523933395\n\n See Also\n --------\n EPS, SQRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n Returns US birth data from 1969 to 1988, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_BIRTHS_1969_1988()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1994_2003, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n Returns US birth data from 1994 to 2003, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_BIRTHS_1994_2003()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1969_1988, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n the Center for Disease Control and Prevention's National Center for Health\n Statistics.\n\n All birth data by race before 1980 are based on race of the child. Starting\n in 1980, birth data by race are based on race of the mother. Birth data are\n used to calculate infant mortality rate.\n\n Returns\n -------\n out: Array\n Infant mortality data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n { 'black': [...], 'white': [...] }\n\n","chdir":"\nchdir( path )\n Changes the current working directory.\n\n If unable to set the current working directory (e.g., due to a non-existent\n path), the function returns an error; otherwise, the function returns\n `null`.\n\n Parameters\n ----------\n path: string\n Desired working directory.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = chdir( '/path/to/current/working/directory' )\n\n See Also\n --------\n cwd\n","chi2gof":"\nchi2gof( x, y[, ...args][, options] )\n Performs a chi-square goodness-of-fit test.\n\n A chi-square goodness-of-fit test is computed for the null hypothesis that\n the values of `x` come from the discrete probability distribution specified\n by `y`.\n\n The second argument can either be expected frequencies, population\n probabilities summing to one, or a discrete probability distribution name to\n test against.\n\n When providing a discrete probability distribution name, distribution\n parameters *must* be supplied as additional arguments.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n By default, the p-value is computed using a chi-square distribution with\n `k-1` degrees of freedom, where `k` is the length of `x`.\n\n If provided distribution arguments are estimated (e.g., via maximum\n likelihood estimation), the degrees of freedom should be corrected. Set the\n `ddof` option to use `k-1-n` degrees of freedom, where `n` is the degrees of\n freedom adjustment.\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five.\n\n Instead of relying on chi-square approximation to calculate the p-value, one\n can use Monte Carlo simulation. When the `simulate` option is `true`, the\n simulation is performed by re-sampling from the discrete probability\n distribution specified by `y`.\n\n Parameters\n ----------\n x: ndarray|Array|TypedArray\n Observation frequencies.\n\n y: ndarray|Array|TypedArray|string\n Expected frequencies, population probabilities, or a discrete\n probability distribution name.\n\n args: ...number (optional)\n Distribution parameters. Distribution parameters will be passed to a\n probability mass function (PMF) as arguments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.ddof: number (optional)\n Delta degrees of freedom adjustment. Default: 0.\n\n options.simulate: boolean (optional)\n Boolean indicating whether to calculate p-values by Monte Carlo\n simulation. The simulation is performed by re-sampling from the discrete\n distribution specified by `y`. Default: false.\n\n options.iterations: number (optional)\n Number of Monte Carlo iterations. Default: 500.\n\n Returns\n -------\n out: Object\n Test results object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number|null\n Degrees of freedom.\n\n out.method: string\n Test name.\n\n out.toString: Function\n Serializes results as formatted output.\n\n out.toJSON: Function\n Serializes results as JSON.\n\n Examples\n --------\n // Provide expected probabilities...\n > var x = [ 89, 37, 30, 28, 2 ];\n > var p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > var out = chi2gof( x, p );\n > var o = out.toJSON()\n { 'pValue': ~0.0406, 'statistic': ~9.9901, ... }\n > out.toString()\n\n // Set significance level...\n > var opts = { 'alpha': 0.01 };\n > out = chi2gof( x, p, opts );\n > out.toString()\n\n // Calculate the test p-value via Monte Carlo simulation...\n > x = [ 89, 37, 30, 28, 2 ];\n > p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > opts = { 'simulate': true, 'iterations': 1000 };\n > out = chi2gof( x, p, opts );\n > out.toString()\n\n // Verify that data comes from Poisson distribution...\n > var lambda = 3.0;\n > var rpois = base.random.poisson.factory( lambda );\n > var len = 400;\n > x = [];\n > for ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n // Generate a frequency table...\n > var freqs = new Int32Array( len );\n > for ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\n > out = chi2gof( freqs, 'poisson', lambda );\n > out.toString()\n\n","chi2test":"\nchi2test( x[, options] )\n Performs a chi-square independence test.\n\n For a two-way contingency table, the function computes a chi-square\n independence test for the null hypothesis that the joint distribution of the\n cell counts is the product of the row and column marginals (i.e. that the\n row and column variables are independent).\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five. The Yates' continuity correction is enabled\n by default for 2x2 tables to account for this, although it tends to\n over-correct.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n Parameters\n ----------\n x: ndarray|Array>\n Two-way table of observed frequencies.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.correct: boolean (optional)\n Boolean indicating whether to use Yates' continuity correction when\n provided a 2x2 contingency table. Default: true.\n\n Returns\n -------\n out: Object\n Test results object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number\n Degrees of freedom.\n\n out.expected: ndarray\n Expected frequencies.\n\n out.method: string\n Test name.\n\n out.toString: Function\n Serializes results as formatted output.\n\n out.toJSON: Function\n Serializes results as JSON.\n\n Examples\n --------\n > var x = [ [ 20, 30 ], [ 30, 20 ] ];\n > var out = chi2test( x );\n > var o = out.toJSON()\n { 'rejected': false, 'pValue': ~0.072, 'statistic': 3.24, ... }\n > out.toString()\n\n // Set significance level...\n > var opts = { 'alpha': 0.1 };\n > out = chi2test( x, opts );\n > o = out.toJSON()\n { 'rejected': true, 'pValue': ~0.072, 'statistic': 3.24, ... }\n > out.toString()\n\n // Disable Yates' continuity correction (primarily used with small counts):\n > opts = { 'correct': false };\n > out = chi2test( x, opts );\n > out.toString()\n\n","circarray2iterator":"\ncircarray2iterator( src[, options][, mapFcn[, thisArg]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, an iterator iterates over elements\n from right-to-left. Default: 1.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = circarray2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n array2iterator, stridedarray2iterator\n","circularArrayStream":"\ncircularArrayStream( src[, options] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );\n\n\ncircularArrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream, stridedArrayStream\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream, stridedArrayStream","CircularBuffer":"\nCircularBuffer( buffer )\n Circular buffer constructor.\n\n Parameters\n ----------\n buffer: integer|ArrayLike\n Buffer size or an array-like object to use as the underlying buffer.\n\n Returns\n -------\n buf: Object\n Circular buffer data structure.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.length\n 3\n > b.count\n 3\n > b.push( 'boop' )\n 'foo'\n\n\nCircularBuffer.prototype.clear()\n Clears a buffer.\n\n Returns\n -------\n out: Object\n Circular buffer instance.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.count\n 3\n > b.clear();\n > b.count\n 0\n\n\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n\n Returns\n -------\n out: integer\n Number of elements currently in the buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.count\n 0\n > b.push( 'foo' );\n > b.count\n 1\n > b.push( 'bar' );\n > b.count\n 2\n\n\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a circular buffer is full.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.full\n false\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.full\n true\n\n\nCircularBuffer.prototype.iterator( [niters] )\n Returns an iterator for iterating over a circular buffer.\n\n A returned iterator does not iterate over partially full buffers.\n\n Parameters\n ----------\n niters: integer (optional)\n Number of iterations. Default: infinity.\n\n Returns\n -------\n out: Iterator\n Iterator.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var it = b.iterator( b.length );\n > var v = it.next().value\n 'bar'\n > v = it.next().value\n 'beep'\n > v = it.next().value\n 'boop'\n > var bool = it.next().done\n true\n\n\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n\n Returns\n -------\n out: integer\n Buffer length.\n\n Examples\n --------\n > var b = CircularBuffer( [ 0, 0, 0 ] );\n > var len = b.length\n 3\n\n\nCircularBuffer.prototype.push( value )\n Adds a value to a circular buffer.\n\n Parameters\n ----------\n value: any\n Value to add.\n\n Returns\n -------\n out: any\n Removed element (or undefined).\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' )\n undefined\n > b.push( 'bar' )\n undefined\n > b.push( 'beep' )\n undefined\n > b.push( 'boop' )\n 'foo'\n\n\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n\n Returns\n -------\n out: Array\n Circular buffer values.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var vals = b.toArray()\n [ 'bar', 'beep', 'boop' ]\n\n\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n\n Returns\n -------\n out: Object\n Serialized circular buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var o = b.toJSON()\n {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n See Also\n --------\n FIFO, Stack\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n Clears a buffer.\n\n Returns\n -------\n out: Object\n Circular buffer instance.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.count\n 3\n > b.clear();\n > b.count\n 0","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n\n Returns\n -------\n out: integer\n Number of elements currently in the buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.count\n 0\n > b.push( 'foo' );\n > b.count\n 1\n > b.push( 'bar' );\n > b.count\n 2","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a circular buffer is full.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.full\n false\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.full\n true","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters] )\n Returns an iterator for iterating over a circular buffer.\n\n A returned iterator does not iterate over partially full buffers.\n\n Parameters\n ----------\n niters: integer (optional)\n Number of iterations. Default: infinity.\n\n Returns\n -------\n out: Iterator\n Iterator.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var it = b.iterator( b.length );\n > var v = it.next().value\n 'bar'\n > v = it.next().value\n 'beep'\n > v = it.next().value\n 'boop'\n > var bool = it.next().done\n true","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n\n Returns\n -------\n out: integer\n Buffer length.\n\n Examples\n --------\n > var b = CircularBuffer( [ 0, 0, 0 ] );\n > var len = b.length\n 3","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value )\n Adds a value to a circular buffer.\n\n Parameters\n ----------\n value: any\n Value to add.\n\n Returns\n -------\n out: any\n Removed element (or undefined).\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' )\n undefined\n > b.push( 'bar' )\n undefined\n > b.push( 'beep' )\n undefined\n > b.push( 'boop' )\n 'foo'","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n\n Returns\n -------\n out: Array\n Circular buffer values.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var vals = b.toArray()\n [ 'bar', 'beep', 'boop' ]","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n\n Returns\n -------\n out: Object\n Serialized circular buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var o = b.toJSON()\n {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n See Also\n --------\n FIFO, Stack","close":"\nclose( fd, clbk )\n Asynchronously closes a file descriptor, so that the file descriptor no\n longer refers to any file and may be reused.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n clbk: Function\n Callback to invoke upon closing a file descriptor.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close( fd, done ); };\n\n\nclose.sync( fd )\n Synchronously closes a file descriptor.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n Returns\n -------\n out: Error|void\n If an error occurs, an error object; otherwise, undefined.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n exists, open, readFile\n","close.sync":"\nclose.sync( fd )\n Synchronously closes a file descriptor.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n Returns\n -------\n out: Error|void\n If an error occurs, an error object; otherwise, undefined.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n exists, open, readFile","CMUDICT":"\nCMUDICT( [options] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n\n Data includes the following:\n\n - dict: the main pronouncing dictionary\n - phones: manners of articulation for each sound\n - symbols: complete list of ARPABET symbols used by the dictionary\n - vp: verbal pronunciations of punctuation marks\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n CMUdict dataset.\n\n Examples\n --------\n > var data = CMUDICT();\n > var dict = data.dict\n {...}\n > var phones = data.phones\n {...}\n > var symbols = data.symbols\n [...]\n > var vp = data.vp\n {...}\n\n","codePointAt":"\ncodePointAt( str, idx[, backward] )\n Returns a Unicode code point from a string at a specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n idx: integer\n Position. If less than `0`, the string position is determined relative\n to the end of the input string.\n\n backward: boolean (optional)\n Backward iteration for low surrogates. Default: false.\n\n Returns\n -------\n out: integer\n Unicode code point.\n\n Examples\n --------\n > var out = codePointAt( 'last man standing', 4 )\n 32\n > out = codePointAt( 'presidential election', 8, true )\n 116\n > out = codePointAt( 'अनुच्छेद', 2 )\n 2369\n > out = codePointAt( '🌷', 1, true )\n 127799\n\n See Also\n --------\n fromCodePoint","commonKeys":"\ncommonKeys( obj1, obj2[, ...obj] )\n Returns the common own property names of two or more objects.\n\n Parameters\n ----------\n obj1: any\n First object.\n\n obj2: any\n Second object.\n\n obj: ...any (optional)\n Additional objects.\n\n Returns\n -------\n out: Array\n Common keys of objects.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > var keys = commonKeys( obj1, obj2 )\n [ 'a', 'b' ]\n\n See Also\n --------\n commonKeysIn, objectKeys","commonKeysIn":"\ncommonKeysIn( obj1, obj2[, ...obj] )\n Returns the common own and inherited property names of two or more objects.\n\n Parameters\n ----------\n obj1: any\n First object.\n\n obj2: any\n Second object.\n\n obj: ...any (optional)\n Additional objects.\n\n Returns\n -------\n out: Array\n Common keys.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > var keys = commonKeysIn( obj1, obj2 )\n [ 'a', 'b' ]\n\n See Also\n --------\n commonKeys, keysIn","complex":"\ncomplex( real, imag[, dtype] )\n Creates a complex number.\n\n The function supports the following data types:\n\n - float64\n - float32\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n z: Complex\n Complex number.\n\n Examples\n --------\n > var z = complex( 5.0, 3.0, 'float64' )\n \n > z = complex( 5.0, 3.0, 'float32' )\n \n\n See Also\n --------\n Complex128, Complex64\n","Complex64":"\nComplex64( real, imag )\n 64-bit complex number constructor.\n\n Both the real and imaginary components are stored as single-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex64\n 64-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n z.BYTES_PER_ELEMENT\n Size (in bytes) of each component. Value: 4.\n\n z.byteLength\n Length (in bytes) of a complex number. Value: 8.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n See Also\n --------\n complex, Complex128\n","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n Canonical single-precision complex floating-point NaN.\n\n Examples\n --------\n > COMPLEX64_NAN\n \n\n See Also\n --------\n COMPLEX128_NAN\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n\n Examples\n --------\n > COMPLEX64_NUM_BYTES\n 8\n\n See Also\n --------\n COMPLEX128_NUM_BYTES, FLOAT32_NUM_BYTES\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n Single-precision complex floating-point zero.\n\n Examples\n --------\n > COMPLEX64_ZERO\n \n\n See Also\n --------\n COMPLEX128_ZERO\n","Complex128":"\nComplex128( real, imag )\n 128-bit complex number constructor.\n\n Both the real and imaginary components are stored as double-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex128\n 128-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n z.BYTES_PER_ELEMENT\n Size (in bytes) of each component. Value: 8.\n\n z.byteLength\n Length (in bytes) of a complex number. Value: 16.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n See Also\n --------\n complex, Complex64\n","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n Canonical double-precision complex floating-point NaN.\n\n Examples\n --------\n > COMPLEX128_NAN\n \n\n See Also\n --------\n COMPLEX64_NAN\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n\n Examples\n --------\n > COMPLEX128_NUM_BYTES\n 16\n\n See Also\n --------\n COMPLEX64_NUM_BYTES, FLOAT64_NUM_BYTES\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n Double-precision complex floating-point zero.\n\n Examples\n --------\n > COMPLEX128_ZERO\n \n\n See Also\n --------\n COMPLEX64_ZERO\n","complexarray":"\ncomplexarray( [dtype] )\n Creates a complex typed array.\n\n The function supports the following data types:\n\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n\n The default typed array data type is `complex128`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr = complexarray()\n \n > arr = complexarray( 'complex64' )\n \n\n\ncomplexarray( length[, dtype] )\n Returns a complex number typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr = complexarray( 5 )\n \n > arr = complexarray( 5, 'complex64' )\n \n\n\ncomplexarray( complexarray[, dtype] )\n Creates a complex number typed array from another complex number typed\n array.\n\n Parameters\n ----------\n complexarray: ComplexArray\n Complex number typed array from which to generate another complex number\n typed array.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\n > var arr2 = complexarray( arr1, 'complex64' )\n \n\n\ncomplexarray( obj[, dtype] )\n Creates a complex number typed array from an array-like object or iterable.\n\n If an array-like object contains interleaved real and imaginary components,\n the array-like object must have a length which is a multiple of two.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\n > var arr2 = complexarray( arr1, 'complex64' )\n \n\n\ncomplexarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a complex number typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first array element.\n Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 64 );\n > var arr = complexarray( buf, 0, 8, 'complex64' )\n \n\n See Also\n --------\n typedarray, realarray\n","complexarrayCtors":"\ncomplexarrayCtors( dtype )\n Returns a complex typed array constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Complex typed array constructor.\n\n Examples\n --------\n > var ctor = complexarrayCtors( 'complex64' )\n \n > ctor = complexarrayCtors( 'float32' )\n null\n\n See Also\n --------\n arrayCtors, typedarrayCtors, realarrayCtors\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n Returns a list of complex typed array data types.\n\n Returns\n -------\n out: Array\n List of complex typed array data types.\n\n Examples\n --------\n > var out = complexarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, typedarrayDataTypes, realarrayDataTypes, ndarrayDataTypes\n","complexCtors":"\ncomplexCtors( dtype )\n Returns a complex number constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = complexCtors( 'complex128' )\n \n > ctor = complexCtors( 'complex' )\n null\n\n See Also\n --------\n complexarrayCtors\n","complexDataType":"\ncomplexDataType( value )\n Returns the data type of a complex number object.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var v = new Complex128( 1.0, 2.0 );\n > var dt = complexDataType( v )\n 'complex128'\n > dt = complexDataType( 'beep' )\n null\n\n See Also\n --------\n arrayDataType\n","complexDataTypes":"\ncomplexDataTypes()\n Returns a list of complex number data types.\n\n The output array contains the following data types:\n\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n\n Returns\n -------\n out: Array\n List of complex number data types.\n\n Examples\n --------\n > var out = complexDataTypes()\n \n\n See Also\n --------\n complexarrayDataTypes\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1, dtype2] )\n Returns the complex number data type with the smallest size and closest\n \"kind\" to which data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n Data type.\n\n dtype2: string (optional)\n Data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = complexPromotionRules( 'complex128', 'complex64' )\n 'complex128'\n\n See Also\n --------\n arrayPromotionRules, ndarrayPromotionRules\n","compose":"\ncompose( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as an argument\n to the next function. The result of the leftmost function is the result\n of the whole.\n\n Notes:\n\n - Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n - The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x ) {\n ... return 2 * x;\n ... }\n > function b( x ) {\n ... return x + 3;\n ... }\n > function c( x ) {\n ... return x / 5;\n ... }\n > var f = compose( c, b, a );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n composeAsync\n","composeAsync":"\ncomposeAsync( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as the first argument\n of the next function. The result of the leftmost function is the result\n of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a composed function calls the `next` callback with a truthy `error`\n argument, the composite function suspends execution and immediately calls\n the `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = composeAsync( c, b, a );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n compose\n","configdir":"\nconfigdir( [p] )\n Returns a directory for user-specific configuration files.\n\n On Windows platforms, the function first checks for a `LOCALAPPDATA`\n environment variable before checking for an `APPDATA` environment variable.\n This means that machine specific user configuration files have precedence\n over roaming user configuration files.\n\n On non-Windows platforms, if the function is unable to locate the current\n user's `home` directory, the function returns `null`. Similarly, on Windows\n platforms, if the function is unable to locate an application data\n directory, the function also returns `null`.\n\n Parameters\n ----------\n p: string (optional)\n Path to append to a base directory.\n\n Returns\n -------\n out: string|null\n Directory.\n\n Examples\n --------\n > var dir = configdir()\n e.g., '/Users//Library/Preferences'\n > dir = configdir( 'appname/config' )\n e.g., '/Users//Library/Preferences/appname/config'\n\n See Also\n --------\n homedir, tmpdir\n","conj":"\nconj( z )\n Returns the complex conjugate of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex conjugate.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conj( z );\n > v.toString()\n '5 - 3i'\n\n See Also\n --------\n imag, real, reim\n","conjf":"\nconjf( z )\n Returns the complex conjugate of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Complex conjugate.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conjf( z );\n > v.toString()\n '5 - 3i'\n\n See Also\n --------\n conj, imagf, realf, reimf\n","constantcase":"\nconstantcase( str )\n Converts a string to constant case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Constant-cased string.\n\n Examples\n --------\n > var out = constantcase( 'Hello World!' )\n 'HELLO_WORLD'\n > out = constantcase( 'I am a tiny little teapot' )\n 'I_AM_A_TINY_LITTLE_TEAPOT'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","constantFunction":"\nconstantFunction( val )\n Creates a function which always returns the same value.\n\n Notes:\n\n - When provided an object reference, the returned `function` always returns\n the same reference.\n\n Parameters\n ----------\n val: any\n Value to always return.\n\n Returns\n -------\n out: Function\n Constant function.\n\n Examples\n --------\n > var fcn = constantFunction( 3.14 );\n > var v = fcn()\n 3.14\n > v = fcn()\n 3.14\n > v = fcn()\n 3.14\n\n See Also\n --------\n argumentFunction, identity\n","constantStream":"\nconstantStream( value[, options] )\n Returns a readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream( 'beep', opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );\n\n\nconstantStream.objectMode( value[, options] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream\n","constantStream.factory":"\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );","constantStream.objectMode":"\nconstantStream.objectMode( value[, options] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream","constructorName":"\nconstructorName( val )\n Determines the name of a value's constructor.\n\n Parameters\n ----------\n val: any\n Input value.\n\n Returns\n -------\n out: string\n Name of a value's constructor.\n\n Examples\n --------\n > var v = constructorName( 'a' )\n 'String'\n > v = constructorName( {} )\n 'Object'\n > v = constructorName( true )\n 'Boolean'\n\n See Also\n --------\n functionName\n","contains":"\ncontains( val, searchValue[, position] )\n Tests if an array-like value contains a search value.\n\n When `val` is a string, the function checks whether the characters of the\n search string are found in the input string. The search is case-sensitive.\n\n When `val` is an array-like object, the function checks whether the input\n array contains an element strictly equal to the specified search value.\n\n For strings, this function is modeled after `String.prototype.includes`,\n part of the ECMAScript 6 specification. This function is different from a\n call to `String.prototype.includes.call` insofar as type-checking is\n performed for all arguments.\n\n The function does not distinguish between positive and negative zero.\n\n If `position < 0`, the search is performed for the entire input array or\n string.\n\n\n Parameters\n ----------\n val: ArrayLike\n Input value.\n\n searchValue: any\n Value to search for.\n\n position: integer (optional)\n Position at which to start searching for `searchValue`. Default: `0`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input value contains another value.\n\n Examples\n --------\n > var bool = contains( 'Hello World', 'World' )\n true\n > bool = contains( 'Hello World', 'world' )\n false\n > bool = contains( [ 1, 2, 3, 4 ], 2 )\n true\n > bool = contains( [ NaN, 2, 3, 4 ], NaN )\n true\n\n // Supply a position:\n > bool = contains( 'Hello World', 'Hello', 6 )\n false\n > bool = contains( [ true, NaN, false ], true, 1 )\n false\n\n","convertArray":"\nconvertArray( arr, dtype )\n Converts an input array to an array of a different data type.\n\n The function supports the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Array to convert.\n\n dtype: string\n Output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var arr = [ 1.0, 2.0, 3.0, 4.0 ];\n > var out = convertArray( arr, 'float32' )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArraySame\n","convertArraySame":"\nconvertArraySame( x, y )\n Converts an input array to the same data type as a second input array.\n\n The function supports input arrays having the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Array to convert.\n\n y: Array|TypedArray\n Array having desired output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = new Float32Array( 0 );\n > var out = convertArraySame( x, y )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArray\n","convertPath":"\nconvertPath( from, to )\n Converts between POSIX and Windows paths.\n\n Parameters\n ----------\n from: string\n Input path.\n\n to: string\n Output path convention: 'win32', 'mixed', or 'posix'.\n\n Returns\n -------\n out: string\n Converted path.\n\n Examples\n --------\n > var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\n 'c:\\\\foo\\\\bar\\\\beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'mixed' )\n 'c:/foo/bar/beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\n 'C:\\\\\\\\foo\\\\bar\\\\beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\n 'C:/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n\n","copy":"\ncopy( value[, level] )\n Copy or deep clone a value to an arbitrary depth.\n\n The implementation can handle circular references.\n\n If a `Number`, `String`, or `Boolean` object is encountered, the value is\n cloned as a primitive. This behavior is intentional.\n\n For objects, the implementation only copies enumerable keys and their\n associated property descriptors.\n\n The implementation only checks whether basic `Objects`, `Arrays`, and class\n instances are extensible, sealed, and/or frozen.\n\n Functions are not cloned; their reference is copied.\n\n The implementation supports custom error types which are `Error` instances\n (e.g., ES2015 subclasses).\n\n Support for copying class instances is inherently fragile. Any instances\n with privileged access to variables (e.g., within closures) cannot be\n cloned. This stated, basic copying of class instances is supported. Provided\n an environment which supports ES5, the implementation is greedy and performs\n a deep clone of any arbitrary class instance and its properties. The\n implementation assumes that the concept of `level` applies only to the class\n instance reference, but not to its internal state.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n level: integer (optional)\n Copy depth. Default: Infinity.\n\n Returns\n -------\n out: any\n Value copy.\n\n Examples\n --------\n > var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > var out = copy( value )\n [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ]\n > var bool = ( value[ 0 ].c === out[ 0 ].c )\n false\n\n // Set the `level` option to limit the copy depth:\n > value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > out = copy( value, 1 );\n > bool = ( value[ 0 ] === out[ 0 ] )\n true\n > bool = ( value[ 0 ].c === out[ 0 ].c )\n true\n\n\n See Also\n --------\n merge\n","copyBuffer":"\ncopyBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = array2buffer( [ 1, 2, 3, 4 ] );\n > var b2 = copyBuffer( b1 )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n allocUnsafe, Buffer\n","countBy":"\ncountBy( collection, [options,] indicator )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: collection value\n - index: collection index\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = countBy( collection, indicator )\n { 'b': 3, 'other': 1 }\n\n See Also\n --------\n group, groupBy\n","countByAsync":"\ncountByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"even\": 2, \"odd\": 1 }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { \"even\": 2, \"odd\": 2 }\n\n See Also\n --------\n countBy, groupByAsync, tabulateByAsync\n","countByAsync.factory":"\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { \"even\": 2, \"odd\": 2 }\n\n See Also\n --------\n countBy, groupByAsync, tabulateByAsync","currentYear":"\ncurrentYear()\n Returns the current year.\n\n Returns\n -------\n out: integer\n Current year.\n\n Examples\n --------\n > var y = currentYear()\n \n\n","curry":"\ncurry( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curry( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curry( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curry( obj.greet, obj );\n > var str = f( 'Hello' )( 'there' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curryRight, uncurry, uncurryRight\n","curryRight":"\ncurryRight( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n This function applies arguments starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curryRight( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curryRight( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curryRight( obj.greet, obj );\n > var str = f( 'there' )( 'Hello' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curry, uncurry, uncurryRight\n","cwd":"\ncwd()\n Returns the current working directory.\n\n Returns\n -------\n path: string\n Current working directory of the process.\n\n Examples\n --------\n > var dir = cwd()\n '/path/to/current/working/directory'\n\n See Also\n --------\n chdir\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n Returns a list of familiar English words.\n\n Returns\n -------\n out: Array\n List of familiar English words.\n\n Examples\n --------\n > var list = DALE_CHALL_NEW()\n [ 'a', 'able', 'aboard', 'about', 'above', ... ]\n\n References\n ----------\n - Chall, Jeanne Sternlicht, and Edgar Dale. 1995. *Readability revisited:\n the new Dale-Chall readability formula*. Brookline Books.\n .\n\n","datasets":"\ndatasets( name[, options] )\n Returns a dataset.\n\n The function forwards provided options to the dataset interface specified\n by `name`.\n\n Parameters\n ----------\n name: string\n Dataset name.\n\n options: Object (optional)\n Function options.\n\n Returns\n -------\n out: any\n Dataset.\n\n Examples\n --------\n > var out = datasets( 'MONTH_NAMES_EN' )\n [ 'January', 'February', ... ]\n > var opts = { 'data': 'cities' };\n > out = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n [ {...}, {...}, ... ]\n\n","DataView":"\nDataView( buffer[, byteOffset[, byteLength]] )\n Returns a data view representing a provided array buffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer|SharedArrayBuffer\n Array buffer.\n\n byteOffset: integer (optional)\n Offset (in bytes) to the first byte in the array buffer for the new view\n to reference. Default: 0.\n\n byteLength: integer (optional)\n Number of elements in the byte array. If not provided, the view's length\n will equal the buffer's length.\n\n Returns\n -------\n out: DataView\n A data view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n > var dv = new DataView( buf )\n \n\n\nDataView.prototype.buffer\n Read-only property which returns the underyling array buffer.\n\n Examples\n --------\n > var buf1 = new ArrayBuffer( 5 );\n > var dv = new DataView( buf1 );\n > var buf2 = dv.buffer\n \n > var b = ( buf1 === buf2 )\n true\n\n\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf );\n > dv.byteLength\n 5\n\n\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf, 2 );\n > dv.byteLength\n 3\n > dv.byteOffset\n 2\n\n\nTODO: document properties/methods\n\n\n See Also\n --------\n ArrayBuffer, typedarray\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n Read-only property which returns the underyling array buffer.\n\n Examples\n --------\n > var buf1 = new ArrayBuffer( 5 );\n > var dv = new DataView( buf1 );\n > var buf2 = dv.buffer\n \n > var b = ( buf1 === buf2 )\n true","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf );\n > dv.byteLength\n 5","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf, 2 );\n > dv.byteLength\n 3\n > dv.byteOffset\n 2","datespace":"\ndatespace( start, stop[, length][ , options] )\n Generates an array of linearly spaced dates.\n\n Parameters\n ----------\n start: number\n Start time as either a `Date` object, Unix timestamp, JavaScript\n timestamp, or date string.\n\n stop: number\n Stop time as either a `Date` object, Unix timestamp, JavaScript\n timestamp, or date string.\n\n length: integer (optional)\n Length of output array. Default: `100`.\n\n options: Object (optional)\n Options.\n\n options.round: string (optional)\n Specifies how sub-millisecond times should be rounded:\n [ 'floor', 'ceil', 'round' ]. Default: 'floor'.\n\n Returns\n -------\n arr: Array\n Array of dates.\n\n Examples\n --------\n > var stop = '2014-12-02T07:00:54.973Z';\n > var start = new Date( stop ) - 60000;\n > var arr = datespace( start, stop, 6 )\n [...]\n\n // Equivalent of Math.ceil():\n > var opts = { 'round': 'ceil' };\n > arr = datespace( 1417503655000, 1417503655001, 3, opts )\n [...]\n\n See Also\n --------\n linspace, logspace\n","dayOfQuarter":"\ndayOfQuarter( [month[, day, year]] )\n Returns the day of the quarter.\n\n By default, the function returns the day of the quarter for the current date\n (according to local time). To determine the day of the quarter for a\n particular day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the quarter.\n\n Examples\n --------\n > var day = dayOfQuarter()\n \n > day = dayOfQuarter( new Date() )\n \n > day = dayOfQuarter( 12, 31, 2017 )\n 92\n\n // Other ways to supply month:\n > day = dayOfQuarter( 'dec', 31, 2017 )\n 92\n > day = dayOfQuarter( 'december', 31, 2017 )\n 92\n\n See Also\n --------\n dayOfYear\n","dayOfYear":"\ndayOfYear( [month[, day, year]] )\n Returns the day of the year.\n\n By default, the function returns the day of the year for the current date\n (according to local time). To determine the day of the year for a particular\n day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the year.\n\n Examples\n --------\n > var day = dayOfYear()\n \n > day = dayOfYear( new Date() )\n \n > day = dayOfYear( 12, 31, 2016 )\n 366\n\n // Other ways to supply month:\n > day = dayOfYear( 'dec', 31, 2016 )\n 366\n > day = dayOfYear( 'december', 31, 2016 )\n 366\n\n See Also\n --------\n dayOfQuarter\n","daysInMonth":"\ndaysInMonth( [month[, year]] )\n Returns the number of days in a month.\n\n By default, the function returns the number of days in the current month\n of the current year (according to local time). To determine the number of\n days for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Days in a month.\n\n Examples\n --------\n > var num = daysInMonth()\n \n > num = daysInMonth( 2 )\n \n > num = daysInMonth( 2, 2016 )\n 29\n > num = daysInMonth( 2, 2017 )\n 28\n\n // Other ways to supply month:\n > num = daysInMonth( 'feb', 2016 )\n 29\n > num = daysInMonth( 'february', 2016 )\n 29\n\n See Also\n --------\n daysInYear\n","daysInYear":"\ndaysInYear( [value] )\n Returns the number of days in a year according to the Gregorian calendar.\n\n By default, the function returns the number of days in the current year\n (according to local time). To determine the number of days for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of days in a year.\n\n Examples\n --------\n > var num = daysInYear()\n \n > num = daysInYear( 2016 )\n 366\n > num = daysInYear( 2017 )\n 365\n\n See Also\n --------\n daysInMonth\n","ddot":"\nddot( x, y )\n Computes the dot product of two double-precision floating-point vectors.\n\n If provided empty vectors, the function returns `0.0`.\n\n Parameters\n ----------\n x: ndarray\n First input array whose underlying data type is 'float64'.\n\n y: ndarray\n Second input array whose underlying data type is 'float64'.\n\n Returns\n -------\n dot: number\n The dot product.\n\n Examples\n --------\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > ddot( x, y )\n -5.0\n\n See Also\n --------\n base.strided.ddot, gdot, sdot\n","debugSinkStream":"\ndebugSinkStream( [options,] [clbk] )\n Returns a writable stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > var s = debugSinkStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );\n\n\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream, inspectSinkStream\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream, inspectSinkStream","debugStream":"\ndebugStream( [options,] [clbk] )\n Returns a transform stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = debugStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );\n\n\ndebugStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n","debugStream.factory":"\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );","debugStream.objectMode":"\ndebugStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream","decorateAfter":"\ndecorateAfter( fcn, arity, after[, thisArg] )\n Decorates a provided function such that the function's return value is\n provided as an argument to another function.\n\n Decorators are intended to be transparent, meaning that, when interfacing\n with an API, the decorated API should have the same signature (i.e., number\n of parameters) as the decorated function.\n\n Thus, a typical value for `arity` is `fcn.length`. This function does not\n require equality, however, and the `arity` argument is allowed to diverge\n from that of the decorated function. Specifying a differing `arity` does\n *not* affect function evaluation behavior, as the returned function passes\n all provided arguments to the decorated function.\n\n If the `after` function returns `undefined`, the returned decorator returns\n the return value of the decorated function `fcn`; otherwise, the returned\n decorator returns the return value of `after`.\n\n The returned decorator supports an `arity` less than or equal to `10` (i.e.,\n the maximum arity of the returned function is `10`). For an arity greater\n than `10`, the returned function has an arity equal to `0`. While this\n violates strict notions of a decorator, for all practical purposes, this is\n unlikely to be an issue, as the vast majority of functions have fewer than\n `10` parameters and the need for explicitly checking function length is\n relatively uncommon.\n\n Common use cases for decorating a function with additional actions *after*\n invocation include logging, capturing invocation statistics, and validating\n return values.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5\n\n\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n\n Code generation may be problematic in browser contexts enforcing a strict\n content security policy] (CSP). If running in or targeting an environment\n with a CSP, avoid using code generation.\n\n For non-native functions, the function supports returning a decorator whose\n API exactly matches the API of the decorated function, including function\n length and parameter names.\n\n For native functions, due to how native functions serialize to strings, the\n function generates placeholder parameter names, which are unlikely to match\n the canonical parameter names. Using placeholder parameter names ensures\n that the length of the decorator (i.e., number of parameters) matches the\n decorated function and, except in scenarios involving function source code\n inspection, will not affect runtime behavior.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter.factory( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5\n\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n\n Code generation may be problematic in browser contexts enforcing a strict\n content security policy] (CSP). If running in or targeting an environment\n with a CSP, avoid using code generation.\n\n For non-native functions, the function supports returning a decorator whose\n API exactly matches the API of the decorated function, including function\n length and parameter names.\n\n For native functions, due to how native functions serialize to strings, the\n function generates placeholder parameter names, which are unlikely to match\n the canonical parameter names. Using placeholder parameter names ensures\n that the length of the decorator (i.e., number of parameters) matches the\n decorated function and, except in scenarios involving function source code\n inspection, will not affect runtime behavior.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter.factory( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5","deepEqual":"\ndeepEqual( a, b )\n Tests for deep equality between two values.\n\n Parameters\n ----------\n a: any\n First comparison value.\n\n b: any\n Second comparison value.\n\n Returns\n -------\n out: boolean\n Boolean indicating if `a` is deep equal to `b`.\n\n Examples\n --------\n > var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\n true\n\n > bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\n false\n\n > bool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n false\n\n See Also\n --------\n isStrictEqual, isSameValue\n","deepGet":"\ndeepGet( obj, path[, options] )\n Returns a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: any\n Nested property value.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a.b.c' )\n 'd'\n\n // Specify a custom separator via the `sep` option:\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n 'd'\n\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n See Also\n --------\n deepPluck, deepSet\n","deepGet.factory":"\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n See Also\n --------\n deepPluck, deepSet","deepHasOwnProp":"\ndeepHasOwnProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path.\n\n The function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepHasOwnProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet","deepHasProp":"\ndeepHasProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var obj = { 'a': new Foo() };\n > var bool = deepHasProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > bool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasProp.factory":"\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet","deepPluck":"\ndeepPluck( arr, path[, options] )\n Extracts a nested property value from each element of an object array.\n\n If a key path does not exist, the function sets the plucked value as\n `undefined`.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. Default:\n true.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': { 'b': { 'c': 1 } } },\n ... { 'a': { 'b': { 'c': 2 } } }\n ... ];\n > var out = deepPluck( arr, 'a.b.c' )\n [ 1, 2 ]\n > arr = [\n ... { 'a': [ 0, 1, 2 ] },\n ... { 'a': [ 3, 4, 5 ] }\n ... ];\n > out = deepPluck( arr, [ 'a', 1 ] )\n [ 1, 4 ]\n\n See Also\n --------\n deepGet, deepSet\n","deepSet":"\ndeepSet( obj, path, value[, options] )\n Sets a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n value: any\n Value to set.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if the property was successfully set.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepSet( obj, 'a.b.c', 'beep' )\n true\n\n // Specify an alternative separator via the sep option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n // To create a key path which does not exist, set the create option to true:\n > bool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\n > obj\n { 'a': { 'b': { 'c': 'beep' }, 'e': { 'c': 'boop' } } }\n\n\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n See Also\n --------\n deepGet, deepPluck\n","deepSet.factory":"\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n See Also\n --------\n deepGet, deepPluck","defineMemoizedProperty":"\ndefineMemoizedProperty( obj, prop, descriptor )\n Defines a memoized object property.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() {\n ... return 'bar';\n ... };\n > defineMemoizedProperty( obj, 'foo', {\n ... 'configurable': false,\n ... 'enumerable': true,\n ... 'writable': false,\n ... 'value': foo\n ... });\n > obj.foo\n 'bar'\n\n See Also\n --------\n setMemoizedReadOnly, defineProperty\n","defineProperties":"\ndefineProperties( obj, properties )\n Defines (and/or modifies) object properties.\n\n The second argument is an object whose own enumerable property values are\n descriptors for the properties to be defined or modified.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n A property descriptor has the following optional properties:\n\n - configurable: boolean indicating if property descriptor can be changed and\n if the property can be deleted from the provided object. Default: false.\n\n - enumerable: boolean indicating if the property shows up when enumerating\n object properties. Default: false.\n\n - writable: boolean indicating if the value associated with the property can\n be changed with an assignment operator. Default: false.\n\n - value: property value.\n\n - get: function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used as\n the property value. Default: undefined.\n\n - set: function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called with\n one argument (the value being assigned to the property) and with the `this`\n context set to the object through which the property is assigned. Default: undefined.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the properties.\n\n properties: Object\n Object with property descriptors.\n\n Returns\n -------\n obj: Object\n Object on which properties were defined (and/or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperties( obj, {\n ... 'foo': {\n ... 'value': 'bar',\n ... 'writable': false,\n ... 'configurable': false,\n ... 'enumerable': true\n ... },\n ... 'baz': {\n ... 'value': 13\n ... }\n ... });\n > obj.foo\n 'bar'\n > obj.baz\n 13\n\n See Also\n --------\n defineProperty, setReadOnly\n","defineProperty":"\ndefineProperty( obj, prop, descriptor )\n Defines (or modifies) an object property.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: any (optional)\n Property value.\n\n descriptor.get: Function|void (optional)\n Function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used\n as the property value. Default: undefined.\n\n descriptor.set: Function|void (optional)\n Function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called\n with one argument (the value being assigned to the property) and with\n the `this` context set to the object through which the property is\n assigned. Default: undefined.\n\n Returns\n -------\n obj: Object\n Object on which the property was defined (or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperty( obj, 'foo', {\n ... 'value': 'bar',\n ... 'enumerable': true,\n ... 'writable': false\n ... });\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n defineProperties, setReadOnly\n","dirname":"\ndirname( path )\n Returns a directory name.\n\n Parameters\n ----------\n path: string\n Path.\n\n Returns\n -------\n out: string\n Directory name.\n\n Examples\n --------\n > var dir = dirname( './foo/bar/index.js' )\n './foo/bar'\n\n See Also\n --------\n extname\n","dotcase":"\ndotcase( str )\n Converts a string to dot case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Dot-cased string.\n\n Examples\n --------\n > var out = dotcase( 'Hello World!' )\n 'hello.world'\n > out = dotcase( 'beep boop' )\n 'beep.boop'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","DoublyLinkedList":"\nDoublyLinkedList()\n Doubly linked list constructor.\n\n Returns\n -------\n list: Object\n Doubly linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the first list node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node. For its third argument, the\n method accepts a location: 'before' or 'after'. Default: 'after'.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation. For its sole argument, the method accepts a\n direction: 'forward' or 'reverse'. Default: 'forward'.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = DoublyLinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n LinkedList, Stack\n","doUntil":"\ndoUntil( fcn, predicate[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doUntil( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntilAsync, doUntilEach, doWhile, until, whilst\n","doUntilAsync":"\ndoUntilAsync( fcn, predicate, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from one)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is falsy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doUntilAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, untilAsync, whileAsync\n","doUntilEach":"\ndoUntilEach( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doUntilEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, untilEach\n","doUntilEachRight":"\ndoUntilEachRight( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doUntilEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, untilEachRight\n","doWhile":"\ndoWhile( fcn, predicate[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doWhile( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, doWhileEach, until, whilst\n","doWhileAsync":"\ndoWhileAsync( fcn, predicate, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from one)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is truthy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doWhileAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhile, untilAsync, whileAsync\n","doWhileEach":"\ndoWhileEach( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doWhileEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, whileEach\n","doWhileEachRight":"\ndoWhileEachRight( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doWhileEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, whileEachRight\n","dswap":"\ndswap( x, y )\n Interchanges two double-precision floating-point vectors.\n\n Parameters\n ----------\n x: ndarray\n First input array whose underlying data type is 'float64'.\n\n y: ndarray\n Second input array whose underlying data type is 'float64'.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > dswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dswap, gswap, sswap\n","E":"\nE\n Euler's number.\n\n Examples\n --------\n > E\n 2.718281828459045\n\n","EMOJI":"\nEMOJI()\n Returns an emoji database.\n\n Returns\n -------\n out: Array\n Emoji database.\n\n Examples\n --------\n > var data = EMOJI()\n [ {...}, ... ]\n\n See Also\n --------\n EMOJI_CODE_PICTO, EMOJI_PICTO_CODE\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n Returns an object mapping emoji codes to pictographs.\n\n Returns\n -------\n out: Object\n An object mapping emoji codes to pictographs.\n\n Examples\n --------\n > var out = EMOJI_CODE_PICTO()\n\n See Also\n --------\n EMOJI, EMOJI_PICTO_CODE\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n Returns an object mapping emoji pictographs to codes.\n\n Returns\n -------\n out: Object\n An object mapping emoji pictographs to codes.\n\n Examples\n --------\n > var out = EMOJI_PICTO_CODE()\n\n See Also\n --------\n EMOJI, EMOJI_CODE_PICTO\n","emptyStream":"\nemptyStream( [options] )\n Returns an \"empty\" readable stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = emptyStream();\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );\n\n\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n constantStream\n","emptyStream.factory":"\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );","emptyStream.objectMode":"\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n constantStream","endsWith":"\nendsWith( str, search[, len] )\n Tests if a string ends with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n len: integer (optional)\n Substring length. Restricts the search to a substring within the input\n string beginning from the leftmost character. If provided a negative\n value, `len` indicates to ignore the last `len` characters, returning\n the same output as `str.length + len`. Default: `str.length`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string ends with the characters of another\n string.\n\n Examples\n --------\n > var bool = endsWith( 'beep', 'ep' )\n true\n > bool = endsWith( 'Beep', 'op' )\n false\n > bool = endsWith( 'Beep', 'ee', 3 )\n true\n > bool = endsWith( 'Beep', 'ee', -1 )\n true\n > bool = endsWith( 'beep', '' )\n true\n\n See Also\n --------\n startsWith\n","enumerableProperties":"\nenumerableProperties( value )\n Returns an array of an object's own enumerable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = enumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerablePropertiesIn, enumerablePropertySymbols, inheritedEnumerableProperties, objectKeys, nonEnumerableProperties, properties\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = enumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbolsIn, inheritedEnumerableProperties, keysIn, nonEnumerablePropertiesIn, propertiesIn\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value )\n Returns an array of an object's own enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedEnumerablePropertySymbols, objectKeys, nonEnumerablePropertySymbols, propertySymbols\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedEnumerablePropertySymbols, keysIn, nonEnumerablePropertySymbolsIn, propertySymbolsIn\n","ENV":"\nENV\n An object containing the user environment.\n\n Examples\n --------\n > var user = ENV.USER\n \n\n See Also\n --------\n ARGV\n","EPS":"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n\n Examples\n --------\n > EPS\n 2.220446049250313e-16\n\n See Also\n --------\n FLOAT32_EPS\n","error2json":"\nerror2json( error )\n Returns a JSON representation of an error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n The JSON object is guaranteed to have the following properties:\n\n - type: error type.\n - message: error message.\n\n The only standardized cross-platform property is `message`. Depending on the\n platform, the following properties *may* be present:\n\n - name: error name.\n - stack: stack trace.\n - code: error code (Node.js system errors).\n - errno: error code string (Node.js system errors).\n - syscall: string representing the failed system call (Node.js system\n errors).\n\n The function also serializes all enumerable properties.\n\n The implementation supports custom error types and sets the `type` field to\n the closest built-in error type.\n\n Parameters\n ----------\n error: Error\n Error to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var err = new Error( 'beep' );\n > var json = error2json( err )\n \n\n See Also\n --------\n reviveError\n","EULERGAMMA":"\nEULERGAMMA\n The Euler-Mascheroni constant.\n\n Examples\n --------\n > EULERGAMMA\n 0.5772156649015329\n\n","every":"\nevery( collection )\n Tests whether all elements in a collection are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 1, 1, 1, 1, 1 ];\n > var bool = every( arr )\n true\n\n See Also\n --------\n any, everyBy, forEach, none, some\n","everyBy":"\neveryBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyBy( arr, positive )\n true\n\n See Also\n --------\n anyBy, everyByRight, forEach, noneBy, someBy\n","everyByAsync":"\neveryByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync\n","everyByAsync.factory":"\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync","everyByRight":"\neveryByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyByRight( arr, positive )\n true\n\n See Also\n --------\n anyBy, every, everyBy, forEachRight, noneByRight, someByRight\n","everyByRightAsync":"\neveryByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync","evil":"\nevil( str )\n Alias for `eval` global.\n\n A reference to `eval` is treated differently by the compiler. For example,\n when evaluating code containing block-scoped declarations (e.g., `let`,\n `const`, `function`, `class`), the compiler may throw an `error` complaining\n that block-scoped declarations are not yet supported outside of\n `strict mode`. One possible workaround is to include `\"use strict\";` in the\n evaluated code.\n\n Parameters\n ----------\n str: string\n Code to evaluate.\n\n Returns\n -------\n out: any\n Returned value if applicable.\n\n Examples\n --------\n > var v = evil( '5*4*3*2*1' )\n 120\n\n","EXEC_PATH":"\nEXEC_PATH\n Absolute pathname of the executable which started the current Node.js\n process.\n\n Examples\n --------\n > EXEC_PATH\n \n\n","exists":"\nexists( path, clbk )\n Asynchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n clbk: Function\n Callback to invoke after testing for path existence. A callback may\n accept a single argument, a boolean indicating whether a path exists, or\n two arguments, an error argument and a boolean, matching the error-first\n callback convention used in most asynchronous Node.js APIs.\n\n Examples\n --------\n > function done( error, bool ) { console.log( bool ); };\n > exists( './beep/boop', done );\n\n\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n See Also\n --------\n readFile, readDir\n","exists.sync":"\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n See Also\n --------\n readFile, readDir","expandAcronyms":"\nexpandAcronyms( str )\n Expands acronyms in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded acronyms.\n\n Examples\n --------\n > var str = 'LOL, this is fun. I am ROFL.';\n > var out = expandAcronyms( str )\n 'laughing out loud, this is fun. I am rolling on the floor laughing.'\n\n > str = 'brb, I need to check my mail. thx!';\n > out = expandAcronyms( str )\n 'be right back, I need to check my mail. thanks!'\n\n See Also\n --------\n expandContractions\n","expandContractions":"\nexpandContractions( str )\n Expands all contractions to their formal equivalents.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded contractions.\n\n Examples\n --------\n > var str = 'I won\\'t be able to get y\\'all out of this one.';\n > var out = expandContractions( str )\n 'I will not be able to get you all out of this one.'\n\n > str = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\n > out = expandContractions( str )\n 'It ought not to be my fault, because, you know, I did not know'\n\n","extname":"\nextname( filename )\n Returns a filename extension.\n\n Parameters\n ----------\n filename: string\n Filename.\n\n Returns\n -------\n ext: string\n Filename extension.\n\n Examples\n --------\n > var ext = extname( 'index.js' )\n '.js'\n\n See Also\n --------\n dirname\n","FancyArray":"\nFancyArray( dtype, buffer, shape, strides, offset, order[, options] )\n Returns a FancyArray instance.\n\n A FancyArray is an ndarray which supports slicing via indexing expressions.\n\n A FancyArray is an ndarray instance and supports all ndarray options,\n attributes, and methods. A FancyArray can be consumed by any API which\n supports ndarray instances.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on ndarray views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use and\n scripting. For performance critical applications, prefer equivalent\n functional APIs supporting ndarray instances.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n ndarray: FancyArray\n FancyArray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nFancyArray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nFancyArray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nFancyArray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nFancyArray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nFancyArray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nFancyArray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nFancyArray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nFancyArray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","FancyArray.prototype.data":"\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","FancyArray.prototype.length":"\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","FancyArray.prototype.order":"\nFancyArray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray","fastmath.abs":"\nfastmath.abs( x )\n Computes an absolute value.\n\n This implementation is not IEEE 754 compliant. If provided `-0`, the\n function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Absolute value.\n\n Examples\n --------\n > var v = fastmath.abs( -1.0 )\n 1.0\n > v = fastmath.abs( 2.0 )\n 2.0\n > v = fastmath.abs( 0.0 )\n 0.0\n > v = fastmath.abs( -0.0 )\n -0.0\n > v = fastmath.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs\n","fastmath.acosh":"\nfastmath.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n The domain of `x` is restricted to `[1,+infinity)`. If `x < 1`, the function\n will return `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var v = fastmath.acosh( 1.0 )\n 0.0\n > v = fastmath.acosh( 2.0 )\n ~1.317\n > v = fastmath.acosh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.acosh( 1.0e308 )\n Infinity\n\n See Also\n --------\n base.acosh\n","fastmath.ampbm":"\nfastmath.ampbm( x, y )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n\n The algorithm computes only an approximation.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.ampbm( 5.0, 12.0 )\n ~13.514\n\n\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n See Also\n --------\n base.hypot\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n See Also\n --------\n base.hypot","fastmath.asinh":"\nfastmath.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var v = fastmath.asinh( 0.0 )\n 0.0\n > v = fastmath.asinh( 2.0 )\n ~1.444\n > v = fastmath.asinh( -2.0 )\n ~-1.444\n > v = fastmath.asinh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.asinh( 1.0e200 )\n Infinity\n\n // The function underflows for small `x`:\n > v = fastmath.asinh( 1.0e-50 )\n 0.0\n\n See Also\n --------\n base.asinh\n","fastmath.atanh":"\nfastmath.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n The domain of `x` is restricted to `[-1,1]`. If `|x| > 1`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var v = fastmath.atanh( 0.0 )\n 0.0\n > v = fastmath.atanh( 0.9 )\n ~1.472\n > v = fastmath.atanh( 1.0 )\n Infinity\n > v = fastmath.atanh( -1.0 )\n -Infinity\n > v = fastmath.atanh( NaN )\n NaN\n\n // The function underflows for small `x`:\n > v = fastmath.atanh( 1.0e-17 )\n 0.0\n\n See Also\n --------\n base.atanh\n","fastmath.hypot":"\nfastmath.hypot( x, y )\n Computes the hypotenuse.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.hypot( -5.0, 12.0 )\n 13.0\n\n // For a sufficiently large `x` and/or `y`, the function overflows:\n > h = fastmath.hypot( 1.0e154, 1.0e154 )\n Infinity\n\n // For sufficiently small `x` and/or `y`, the function underflows:\n > h = fastmath.hypot( 1e-200, 1.0e-200 )\n 0.0\n\n See Also\n --------\n base.hypot\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n\n This function provides a performance boost when requiring only approximate\n computations for integer arguments.\n\n For high-precision applications, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer binary logarithm (base two).\n\n Examples\n --------\n > var v = fastmath.log2Uint32( 4 >>> 0 )\n 2\n > v = fastmath.log2Uint32( 8 >>> 0 )\n 3\n > v = fastmath.log2Uint32( 9 >>> 0 )\n 3\n\n See Also\n --------\n base.log2\n","fastmath.max":"\nfastmath.max( x, y )\n Returns the maximum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = fastmath.max( 3.14, 4.2 )\n 4.2\n > v = fastmath.max( 3.14, NaN )\n NaN\n > v = fastmath.max( NaN, 3.14 )\n 3.14\n > v = fastmath.max( -0.0, +0.0 )\n +0.0\n > v = fastmath.max( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max\n","fastmath.min":"\nfastmath.min( x, y )\n Returns the minimum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = fastmath.min( 3.14, 4.2 )\n 3.14\n > v = fastmath.min( 3.14, NaN )\n NaN\n > v = fastmath.min( NaN, 3.14 )\n 3.14\n > v = fastmath.min( -0.0, +0.0 )\n +0.0\n > v = fastmath.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.min\n","fastmath.powint":"\nfastmath.powint( x, y )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n\n This function is not recommended for high-precision applications due to\n error accumulation.\n\n If provided a negative exponent, the function first computes the reciprocal\n of the base and then evaluates the exponential function. This can introduce\n significant error.\n\n Parameters\n ----------\n x: number\n Base.\n\n y: integer\n Signed 32-bit integer exponent.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = fastmath.powint( 2.0, 3 )\n 8.0\n > v = fastmath.powint( 3.14, 0 )\n 1.0\n > v = fastmath.powint( 2.0, -2 )\n 0.25\n > v = fastmath.powint( 0.0, 0 )\n 1.0\n > v = fastmath.powint( -3.14, 1 )\n -3.14\n > v = fastmath.powint( NaN, 0 )\n NaN\n\n See Also\n --------\n base.pow\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n\n Prefer hardware `sqrt` over a software implementation.\n\n When using a software `sqrt`, this function provides a performance boost\n when an application requires only approximate computations for integer\n arguments.\n\n For applications requiring high-precision, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer square root.\n\n Examples\n --------\n > var v = fastmath.sqrtUint32( 9 >>> 0 )\n 3\n > v = fastmath.sqrtUint32( 2 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 3 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 0 >>> 0 )\n 0\n\n See Also\n --------\n base.sqrt\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common female first names.\n\n Examples\n --------\n > var list = FEMALE_FIRST_NAMES_EN()\n [ 'Aaren', 'Aarika', 'Abagael', 'Abagail', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. \"Moby Word II.\" .\n\n See Also\n --------\n MALE_FIRST_NAMES_EN\n","FIFO":"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n\n Returns\n -------\n queue: Object\n First-in-first-out queue.\n\n queue.clear: Function\n Clears the queue.\n\n queue.first: Function\n Returns the \"oldest\" queue value (i.e., the value which is \"first-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.iterator: Function\n Returns an iterator for iterating over a queue. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from queue mutation during\n iteration, a returned iterator **always** iterates over a queue\n \"snapshot\", which is defined as the list of queue elements at the time\n of the method's invocation.\n\n queue.last: Function\n Returns the \"newest\" queue value (i.e., the value which is \"last-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.length: integer\n Queue length.\n\n queue.pop: Function\n Removes and returns the current \"first-out\" value from the queue. If the\n queue is empty, the returned value is `undefined`.\n\n queue.push: Function\n Adds a value to the queue.\n\n queue.toArray: Function\n Returns an array of queue values.\n\n queue.toJSON: Function\n Serializes a queue as JSON.\n\n Examples\n --------\n > var q = FIFO();\n > q.push( 'foo' ).push( 'bar' );\n > q.length\n 2\n > q.pop()\n 'foo'\n > q.length\n 1\n > q.pop()\n 'bar'\n > q.length\n 0\n\n See Also\n --------\n Stack\n","filledarray":"\nfilledarray( [dtype] )\n Creates a filled array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarray()\n \n > arr = filledarray( 'float32' )\n \n\n\nfilledarray( value, length[, dtype] )\n Returns a filled array having a specified length.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarray( 1.0, 5 )\n [ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n > arr = filledarray( 1, 5, 'int32' )\n [ 1, 1, 1, 1, 1 ]\n\n\nfilledarray( value, array[, dtype] )\n Creates a filled array from another array (or array-like object).\n\n Parameters\n ----------\n value: any\n Fill value.\n\n array: ArrayLikeObject\n Array from which to generate another array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\n [ 2.0, 2.0, 2.0 ]\n > var arr2 = filledarray( 1.0, arr1, 'float32' )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, iterable[, dtype] )\n Creates a filled array from an iterable.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n iterable: Iterable\n Iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = iterConstant( 3.0, {'iter': 3} );\n > var arr2 = filledarray( 1.0, arr1, 'float32' )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, buffer[, byteOffset[, length]][, dtype] )\n Returns a filled typed array view of an ArrayBuffer.\n\n The 'generic' array data type is *not* supported.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n [ 1.0, 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n filledarrayBy, typedarray\n","filledarrayBy":"\nfilledarrayBy( [dtype] )\n Creates a filled array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarrayBy()\n \n > arr = filledarrayBy( 'float32' )\n \n\n\nfilledarrayBy( length[, dtype], clbk[, thisArg] )\n Returns a filled array according to a provided callback function and having\n a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var arr = filledarrayBy( 5, clbk )\n [ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n > arr = filledarrayBy( 5, 'int32', clbk )\n [ 1, 1, 1, 1, 1 ]\n\n\nfilledarrayBy( array[, dtype], clbk[, thisArg] )\n Creates a filled array from another array (or array-like object) according\n to a provided callback function.\n\n Parameters\n ----------\n array: ArrayLikeObject\n Array from which to generate another array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\n [ 2.0, 2.0, 2.0 ]\n > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( iterable[, dtype], clbk[, thisArg] )\n Creates a filled array from an iterable according to a provided callback\n function.\n\n Parameters\n ----------\n iterable: Iterable\n Iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = iterConstant( 3.0, {'iter': 3} );\n > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( buffer[, byteOffset[, length]][, dtype], clbk[, thisArg] )\n Returns a filled typed array view of an ArrayBuffer according to a provided\n callback function.\n\n The 'generic' array data type is *not* supported.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n filledarray, typedarray\n","filterArguments":"\nfilterArguments( fcn, predicate[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n\n Only those arguments in which the predicate function returns a truthy value\n are applied to a provided function.\n\n The predicate function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > function predicate( v ) { return ( v !== 2 ); };\n > var bar = filterArguments( foo, predicate );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n maskArguments, rejectArguments, reorderArguments, reverseArguments\n","find":"\nfind( arr, [options,] clbk )\n Finds elements in an array-like object that satisfy a test condition.\n\n Parameters\n ----------\n arr: Array|TypedArray|string\n Object from which elements will be tested.\n\n options: Object (optional)\n Options.\n\n options.k: integer (optional)\n Limits the number of returned elements. The sign determines the\n direction in which to search. If set to a negative integer, the function\n searches from last element to first element. Default: arr.length.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'indices'.\n\n clbk: Function\n Function invoked for each array element. If the return value is truthy,\n the value is considered to have satisfied the test condition.\n\n Returns\n -------\n out: Array\n Array of indices, element values, or arrays of index-value pairs.\n\n Examples\n --------\n > var data = [ 30, 20, 50, 60, 10 ];\n > function condition( val ) { return val > 20; };\n > var vals = find( data, condition )\n [ 0, 2, 3 ]\n\n // Limit number of results:\n > data = [ 30, 20, 50, 60, 10 ];\n > var opts = { 'k': 2, 'returns': 'values' };\n > vals = find( data, opts, condition )\n [ 30, 50 ]\n\n // Return both indices and values as index-value pairs:\n > data = [ 30, 20, 50, 60, 10 ];\n > opts = { 'k': -2, 'returns': '*' };\n > vals = find( data, opts, condition )\n [ [ 3, 60 ], [ 2, 50 ] ]\n\n","firstChar":"\nfirstChar( str[, n][, options] )\n Returns the first character(s) of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to return. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = firstChar( 'beep' )\n 'b'\n > out = firstChar( 'Boop', 1 )\n 'B'\n > out = firstChar( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n removeFirst\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n Returns FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n\n Returns\n -------\n out: Array\n FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n\n Examples\n --------\n > var data = FIVETHIRTYEIGHT_FFQ()\n [ {...}, ... ]\n\n References\n ----------\n - Aschwanden, Christie. 2016. \"You Can't Trust What You Read About\n Nutrition.\" .\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n","flattenArray":"\nflattenArray( arr[, options] )\n Flattens an array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > var out = flattenArray( arr )\n [ 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Set the maximum depth:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2 } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > var bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n true\n\n // Deep copy:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2, 'copy': true } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n false\n\n\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: ArrayLike\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n See Also\n --------\n flattenObject\n","flattenArray.factory":"\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: ArrayLike\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n See Also\n --------\n flattenObject","flattenObject":"\nflattenObject( obj[, options] )\n Flattens an object.\n\n Parameters\n ----------\n obj: ObjectLike\n Object to flatten.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n out: ObjectLike\n Flattened object.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flattenObject( obj )\n { 'a.b.c': 'd' }\n\n // Set the `depth` option to flatten to a specified depth:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'depth': 1 } )\n { 'a.b': { 'c': 'd' } }\n > var bool = ( obj.a.b === out[ 'a.b' ] )\n true\n\n // Set the `delimiter` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'delimiter': '-|-' } )\n { 'a-|-b-|-c': 'd' }\n\n // Flatten arrays:\n > obj = { 'a': { 'b': [ 1, 2, 3 ] } };\n > out = flattenObject( obj, { 'flattenArrays': true } )\n { 'a.b.0': 1, 'a.b.1': 2, 'a.b.2': 3 }\n\n\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n See Also\n --------\n flattenArray\n","flattenObject.factory":"\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n See Also\n --------\n flattenArray","flignerTest":"\nflignerTest( ...x[, options] )\n Computes the Fligner-Killeen test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = flignerTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = flignerTest( arr, { 'groups': groups } )\n\n See Also\n --------\n bartlettTest\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n Platform float word order.\n\n Possible values:\n\n - 'little-endian'\n - 'big-endian'\n - 'unknown'\n\n Examples\n --------\n > FLOAT_WORD_ORDER\n \n\n See Also\n --------\n BYTE_ORDER\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_CBRT_EPS\n 0.09921256574801247\n\n See Also\n --------\n FLOAT16_EPS, FLOAT16_SQRT_EPS, FLOAT32_CBRT_EPS, CBRT_EPS\n","FLOAT16_EPS":"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_EPS\n 0.0009765625\n\n See Also\n --------\n FLOAT32_EPS, EPS\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT16_EXPONENT_BIAS\n 15\n\n See Also\n --------\n FLOAT32_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT16_MAX":"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_MAX\n 65504.0\n\n See Also\n --------\n FLOAT32_MAX, FLOAT64_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n\n The maximum safe half-precision floating-point integer is given by\n `2^11 - 1`.\n\n Examples\n --------\n > FLOAT16_MAX_SAFE_INTEGER\n 2047\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n\n The minimum safe half-precision floating-point integer is given by\n `-(2^11 - 1)`.\n\n Examples\n --------\n > FLOAT16_MIN_SAFE_INTEGER\n -2047\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT16_NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_PINF, FLOAT32_NINF, NINF\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_NUM_BYTES\n 2\n\n See Also\n --------\n FLOAT32_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT16_PINF":"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT16_PINF\n Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_PINF, PINF\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n\n The effective number of bits is `10` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT16_PRECISION\n 11\n\n See Also\n --------\n FLOAT32_PRECISION, FLOAT64_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_NORMAL\n 6.103515625e-5\n\n See Also\n --------\n FLOAT16_SMALLEST_SUBNORMAL, FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_SUBNORMAL\n 5.960464477539063e-8\n\n See Also\n --------\n FLOAT16_SMALLEST_NORMAL, FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_SQRT_EPS\n 0.03125\n\n See Also\n --------\n FLOAT16_EPS, FLOAT32_SQRT_EPS, SQRT_EPS\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_CBRT_EPS\n 0.004921566694974899\n\n See Also\n --------\n FLOAT32_EPS, FLOAT32_SQRT_EPS, CBRT_EPS\n","FLOAT32_EPS":"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_EPS\n 1.1920928955078125e-7\n\n See Also\n --------\n EPS\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT32_EXPONENT_BIAS\n 127\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT32_MAX":"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX\n 3.4028234663852886e+38\n\n See Also\n --------\n FLOAT16_MAX, FLOAT64_MAX\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n\n The maximum safe single-precision floating-point integer is given by\n `2^24 - 1`.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_INTEGER\n 16777215\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n\n The minimum safe single-precision floating-point integer is given by\n `-(2^24 - 1)`.\n\n Examples\n --------\n > FLOAT32_MIN_SAFE_INTEGER\n -16777215\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"\nFLOAT32_NAN\n Single-precision floating-point NaN.\n\n Examples\n --------\n > FLOAT32_NAN\n NaN\n\n See Also\n --------\n NAN\n","FLOAT32_NINF":"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT32_NINF\n -Infinity\n\n See Also\n --------\n FLOAT32_PINF, NINF\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_NUM_BYTES\n 4\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT32_PINF":"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT32_PINF\n Infinity\n\n See Also\n --------\n FLOAT32_NINF, PINF\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n\n The effective number of bits is `23` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT32_PRECISION\n 24\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT64_PRECISION\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_NORMAL\n 1.1754943508222875e-38\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_SUBNORMAL\n 1.401298464324817e-45\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_SQRT_EPS\n 0.0003452669770922512\n\n See Also\n --------\n FLOAT32_EPS, SQRT_EPS\n","Float32Array":"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array()\n \n\n\nFloat32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Float32Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'\n\n\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n \n\n\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20\n\n\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5\n\n\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float32Array.from":"\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]","Float32Array.of":"\nFloat32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4","Float32Array.name":"\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n ","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT64_EXPONENT_BIAS\n 1023\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT32_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_EXPONENT_MASK\n 2146435072\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n '01111111111100000000000000000000'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n 1048575\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n '00000000000011111111111111111111'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_EXPONENT_MASK\n","FLOAT64_MAX":"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX\n 1.7976931348623157e+308\n\n See Also\n --------\n FLOAT16_MAX, FLOAT32_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT\n 1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n -1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT\n 308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_LN\n 709.782712893384\n\n See Also\n --------\n FLOAT64_MIN_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_FIBONACCI\n 8944394323791464\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n\n The maximum safe double-precision floating-point integer is given by\n `2^53 - 1`.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_INTEGER\n 9007199254740991\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_LUCAS\n 7639424778862807\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI, FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_FIBONACCI\n 78\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_LUCAS\n 76\n\n See Also\n --------\n FLOAT64_MAX_SAFE_LUCAS, FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT\n -1022\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n -1074\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n -324\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MIN_LN\n -708.3964185322641\n\n See Also\n --------\n FLOAT64_MAX_LN\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n\n The minimum safe double-precision floating-point integer is given by\n `-(2^53 - 1)`.\n\n Examples\n --------\n > FLOAT64_MIN_SAFE_INTEGER\n -9007199254740991\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_NUM_BYTES\n 8\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT32_NUM_BYTES\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n\n The effective number of bits is `52` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT64_PRECISION\n 53\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT32_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_NORMAL\n 2.2250738585072014e-308\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_SUBNORMAL\n 4.940656458412465e-324\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","Float64Array":"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array()\n \n\n\nFloat64Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = new Float64Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'\n\n\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n \n\n\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40\n\n\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5\n\n\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float64Array.from":"\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]","Float64Array.of":"\nFloat64Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8","Float64Array.name":"\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n ","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","forEach":"\nforEach( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEach( arr, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n forEachAsync, forEachRight\n","forEachAsync":"\nforEachAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEach, forEachRightAsync\n","forEachAsync.factory":"\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEach, forEachRightAsync","forEachChar":"\nforEachChar( str, [options,] clbk[, thisArg] )\n Invokes a function for each character in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character\n - index: starting character index\n - str: input string\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters over which to iterate. The following modes are\n supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n clbk: Function\n The function to invoke for each character in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > forEachChar( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n forEach\n","forEachRight":"\nforEachRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEachRight( arr, logger )\n 3: 4\n 2: 3\n 1: 2\n 0: 1\n\n See Also\n --------\n forEach, forEachRightAsync\n","forEachRightAsync":"\nforEachRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEachAsync, forEachRight\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEachAsync, forEachRight","forIn":"\nforIn( obj, fcn[, thisArg] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n\n When invoked, the function is provided three arguments:\n\n - `value`: object property value\n - `key`: object property\n - `obj`: the input object\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > function Foo() { return this; };\n > Foo.prototype.beep = 'boop';\n > var obj = new Foo();\n > forIn( obj, logger )\n beep: boop\n\n See Also\n --------\n forEach, forOwn\n","forOwn":"\nforOwn( obj, fcn[, thisArg] )\n Invokes a function for each own enumerable property of an object.\n\n When invoked, the function is provided three arguments:\n\n - `value`: object property value\n - `key`: object property\n - `obj`: the input object\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n The function determines the list of own enumerable properties *before*\n invoking the provided function. Hence, any modifications made to the input\n object *after* calling this function (such as adding and removing\n properties) will *not* affect the list of visited properties.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > forOwn( obj, logger )\n a: 1\n b: 2\n c: 3\n d: 4\n\n See Also\n --------\n forEach, forIn\n","FOURTH_PI":"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n\n Examples\n --------\n > FOURTH_PI\n 7.85398163397448309616e-1\n\n See Also\n --------\n PI\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n\n Examples\n --------\n > FOURTH_ROOT_EPS\n 0.0001220703125\n\n See Also\n --------\n EPS\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n\n Each array element has the following fields:\n\n - date: collection date (month/day/year; e.g., 01/01/1980).\n - all_workers: wage rates for hourly and non-hourly workers.\n - hourly_workers: wage rates for hourly workers.\n - non_hourly_workers: wage rates for non-hourly workers.\n - less_than_high_school: wage rates for workers with less than a high school\n education.\n - high_school: wage rates for workers with a high school education.\n - some_college: wage rates for workers with some college education.\n - college: wage rates for workers with a college education.\n - construction: wage rates for workers in the construction industry.\n - finance: wage rates for workers in the finance industry.\n - manufacturing: wage rates for workers in the manufacturing industry.\n\n Returns\n -------\n out: Array\n Wage rates.\n\n Examples\n --------\n > var data = FRB_SF_WAGE_RIGIDITY()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Federal Reserve Bank of San Francisco. 2017. \"Wage Rigidity.\" .\n\n","fromCodePoint":"\nfromCodePoint( ...pt )\n Creates a string from a sequence of Unicode code points.\n\n In addition to multiple arguments, the function also supports providing an\n array-like object as a single argument containing a sequence of Unicode code\n points.\n\n Parameters\n ----------\n pt: ...integer\n Sequence of Unicode code points.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = fromCodePoint( 9731 )\n '☃'\n > out = fromCodePoint( [ 9731 ] )\n '☃'\n > out = fromCodePoint( 97, 98, 99 )\n 'abc'\n > out = fromCodePoint( [ 97, 98, 99 ] )\n 'abc'\n\n See Also\n --------\n codePointAt\n","Function":"\nFunction( [...argNames,] body )\n Returns a Function object.\n\n Argument names must be strings corresponding to valid JavaScript parameters\n (i.e., a plain identifier, or, in environments supporting such parameters, a\n rest parameter or destructured parameter, optionally with a default).\n\n Parameters\n ----------\n argNames: ...any (optional)\n Parameter names.\n\n body: string\n Function body.\n\n Returns\n -------\n fcn: Function\n Function object.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f( 1, 2 )\n 3\n\n\nFunction.prototype.apply( thisArg, args )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: Array\n Array of arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.apply( null, [ 1, 2 ] )\n 3\n\nFunction.prototype.call( thisArg, ...args )\n Calls a function with a given `this` value and arguments provided\n individually.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.call( null, 1, 2 )\n 3\n\nFunction.prototype.bind( thisArg, ...args )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n fcn: Function\n Bound function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > var g = f.bind( null, 1 );\n > g( 2 )\n 3\n\nFunction.prototype.toString()\n Returns a string representation of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.toString()\n 'function anonymous( x, y ) { return x + y; }'\n\nFunction.prototype.length\n The number of arguments expected by the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.length\n 2\n\nFunction.prototype.name\n The name of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name\n 'anonymous'\n\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name = 'add';\n > f.name\n 'add'\n\nFunction.prototype.prototype\n The prototype of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.prototype\n {}\n\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg, args )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: Array\n Array of arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.apply( null, [ 1, 2 ] )\n 3","Function.prototype.call":"\nFunction.prototype.call( thisArg, ...args )\n Calls a function with a given `this` value and arguments provided\n individually.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.call( null, 1, 2 )\n 3","Function.prototype.bind":"\nFunction.prototype.bind( thisArg, ...args )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n fcn: Function\n Bound function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > var g = f.bind( null, 1 );\n > g( 2 )\n 3","Function.prototype.toString":"\nFunction.prototype.toString()\n Returns a string representation of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.toString()\n 'function anonymous( x, y ) { return x + y; }'","Function.prototype.length":"\nFunction.prototype.length\n The number of arguments expected by the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.length\n 2","Function.prototype.name":"\nFunction.prototype.name\n The name of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name\n 'anonymous'\n\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name = 'add';\n > f.name\n 'add'","Function.prototype.prototype":"\nFunction.prototype.prototype\n The prototype of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.prototype\n {}","function2string":"\nfunction2string( fcn )\n Returns a string representing the source code of a provided function.\n\n If called on built-in functions, functions created by `Function#bind()`, or\n other non-JavaScript functions, the function returns a \"native\" function\n string similar to the following:\n\n \"function foo() { [native code] }\"\n\n For intrinsic object methods and functions, `foo` is the initial name of the\n function.\n\n If called on a function created by the `Function` constructor, the function\n returns the source code of a synthesized function declaration having the\n name \"anonymous\" and using the provided parameters and function body.\n\n Starting in ES2018, the ECMAScript specification requires that the returned\n string contain the exact same source code as it was declared, including any\n whitespace and/or comments. If the host is unable to access the source code,\n the specification requires that the returned string be the native function\n string.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n String representing the function's source code.\n\n Examples\n --------\n > function2string( base.erf )\n \n\n See Also\n --------\n Function\n","functionName":"\nfunctionName( fcn )\n Returns the name of a function.\n\n If provided an anonymous function, the function returns an empty `string` or\n the string `\"anonymous\"`.\n\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n Function name.\n\n Examples\n --------\n > var v = functionName( String )\n 'String'\n > v = functionName( function foo(){} )\n 'foo'\n > v = functionName( function(){} )\n '' || 'anonymous'\n\n See Also\n --------\n constructorName\n","functionSequence":"\nfunctionSequence( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as an argument to the next function. The result of the\n rightmost function is the result of the whole.\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x ) { return 2 * x; };\n > function b( x ) { return x + 3; };\n > function c( x ) { return x / 5; };\n > var f = functionSequence( a, b, c );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n compose, functionSequenceAsync\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as the first argument of the next function. The result of\n the rightmost function is the result of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the pipeline function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = functionSequenceAsync( a, b, c );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n composeAsync, functionSequence\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n\n Examples\n --------\n > GAMMA_LANCZOS_G\n 10.900511\n\n","gdot":"\ngdot( x, y )\n Computes the dot product of two vectors.\n\n In general, for best performance, especially for large vectors, provide\n 1-dimensional ndarrays whose underlying data type is either 'float64' or\n 'float32'.\n\n If provided empty vectors, the function returns `0.0`.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n First input array.\n\n y: ndarray|ArrayLikeObject\n Second input array.\n\n Returns\n -------\n dot: number\n The dot product.\n\n Examples\n --------\n // Using ndarrays...\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > gdot( x, y )\n -5.0\n\n // Using array-like objects...\n > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > gdot( x, y )\n -5.0\n\n See Also\n --------\n base.strided.gdot, ddot, sdot\n","getegid":"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n\n The function only returns an effective group identity on POSIX platforms.\n For all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric group identity.\n\n Examples\n --------\n > var gid = getegid()\n\n See Also\n --------\n geteuid, getgid, getuid\n","geteuid":"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n\n The function only returns an effective user identity on POSIX platforms. For\n all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric user identity.\n\n Examples\n --------\n > var uid = geteuid()\n\n See Also\n --------\n getegid, getgid, getuid\n","getgid":"\ngetgid()\n Returns the numeric group identity of the calling process.\n\n The function only returns a group identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric group identity.\n\n Examples\n --------\n > var gid = getgid()\n\n See Also\n --------\n getegid, geteuid, getuid\n","getGlobal":"\ngetGlobal( [codegen] )\n Returns the global object.\n\n Parameters\n ----------\n codegen: boolean (optional)\n Boolean indicating whether to use code generation to resolve the global\n object. Code generation is the *most* reliable means for resolving the\n global object; however, using code generation may violate content\n security policies (CSPs). Default: false.\n\n Returns\n -------\n global: Object\n Global object.\n\n Examples\n --------\n > var g = getGlobal()\n {...}\n\n","getPrototypeOf":"\ngetPrototypeOf( value )\n Returns the prototype of a provided object.\n\n In contrast to the native `Object.getPrototypeOf`, this function does not\n throw when provided `null` or `undefined`. Instead, similar to when provided\n any value with *no* inherited properties, the function returns `null`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object|null\n Prototype.\n\n Examples\n --------\n > var proto = getPrototypeOf( {} )\n {}\n\n See Also\n --------\n isPrototypeOf\n","getuid":"\ngetuid()\n Returns the numeric user identity of the calling process.\n\n The function only returns a user identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric user identity.\n\n Examples\n --------\n > var uid = getuid()\n\n See Also\n --------\n getegid, geteuid, getgid\n","GLAISHER":"\nGLAISHER\n Glaisher-Kinkelin constant.\n\n Examples\n --------\n > GLAISHER\n 1.2824271291006226\n\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over each grapheme cluster in a string.\n\n When invoked, an input function is provided three arguments:\n\n - value: grapheme cluster\n - index: iterated value index\n - src: source string\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke a string's `@@iterator` method, regardless of whether this method is\n defined. To convert a string to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: string\n String from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = graphemeClusters2iterator( '🌷🍕' );\n > var v = it.next().value\n '🌷'\n > v = it.next().value\n '🍕'\n > var bool = it.next().done\n true\n\n See Also\n --------\n array2iterator, graphemeClusters2iteratorRight\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over each grapheme\n cluster in a string.\n\n When invoked, an input function is provided three arguments:\n\n - value: grapheme cluster\n - index: iterated value index\n - src: source string\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke a string's `@@iterator` method, regardless of whether this method is\n defined. To convert a string to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: string\n String from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = graphemeClusters2iteratorRight( '🌷🍕' );\n > var v = it.next().value\n '🍕'\n > v = it.next().value\n '🌷'\n > var bool = it.next().done\n true\n\n See Also\n --------\n array2iteratorRight, graphemeClusters2iterator\n","group":"\ngroup( collection, [options,] groups )\n Groups values as arrays associated with distinct keys.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n groups: Array|TypedArray|Object\n A collection defining which group an element in the input collection\n belongs to. Each value in `groups` should resolve to a value which can\n be serialized as an object key. If provided an object, the object must\n be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var groups = [ 'b', 'b', 'f', 'b' ];\n > var out = group( collection, groups )\n { 'b': [ 'beep', 'boop', 'bar' ], 'f': [ 'foo' ] }\n > groups = [ 1, 1, 2, 1 ];\n > out = group( collection, groups )\n { '1': [ 'beep', 'boop', 'bar' ], '2': [ 'foo' ] }\n\n // Output group results as indices:\n > groups = [ 'b', 'b', 'f', 'b' ];\n > var opts = { 'returns': 'indices' };\n > out = group( collection, opts, groups )\n { 'b': [ 0, 1, 3 ], 'f': [ 2 ] }\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = group( collection, opts, groups )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'f': [ [2, 'foo'] ] }\n\n See Also\n --------\n bifurcate, countBy, groupBy\n","groupBy":"\ngroupBy( collection, [options,] indicator )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = groupBy( collection, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ 0, 1, 3 ], 'other': [ 2 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'other': [ [2, 'foo' ] ] }\n\n See Also\n --------\n bifurcateBy, countBy, group\n","groupByAsync":"\ngroupByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 1000, 3000 ], \"false\": [ 2500 ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 2, 0 ], \"false\": [ 1 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ [ 2, 1000 ], [ 0, 3000 ] ], \"false\": [ [ 1, 2500 ] ] }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n See Also\n --------\n bifurcateByAsync, countByAsync, groupBy\n","groupByAsync.factory":"\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n See Also\n --------\n bifurcateByAsync, countByAsync, groupBy","groupIn":"\ngroupIn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object with no prototype, the function returns an empty\n object.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > var out = groupIn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateIn, groupBy, groupOwn\n","groupOwn":"\ngroupOwn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object, the function returns an empty object.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = groupOwn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateOwn, group, groupBy\n","gswap":"\ngswap( x, y )\n Interchanges two vectors.\n\n In general, for best performance, especially for large vectors, provide\n 1-dimensional ndarrays whose underlying data type is either 'float64' or\n 'float32'.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n First input array.\n\n y: ndarray|ArrayLikeObject\n Second input array.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n // Using ndarrays...\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > gswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n // Using array-like objects...\n > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > gswap( x, y );\n > x\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gswap, dswap, sswap\n","HALF_LN2":"\nHALF_LN2\n One half times the natural logarithm of `2`.\n\n Examples\n --------\n > HALF_LN2\n 3.46573590279972654709e-01\n\n See Also\n --------\n LN2\n","HALF_PI":"\nHALF_PI\n One half times the mathematical constant `π`.\n\n Examples\n --------\n > HALF_PI\n 1.5707963267948966\n\n See Also\n --------\n PI\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 14 attributes:\n\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n - medv: median value of owner-occupied homes in $1000's\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n Additionally, as documented by Gilley and Pace (1996), the dataset contains\n eight miscoded median values.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES_CORRECTED, PACE_BOSTON_HOUSE_PRICES\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 15 attributes:\n\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n - medv: median value of owner-occupied homes in $1000's\n - cmedv: corrected median value of owner-occupied homes in $1000's\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, PACE_BOSTON_HOUSE_PRICES\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `ArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasArrayBufferSupport()\n \n\n See Also\n --------\n hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasSharedArrayBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `async`/`await` support.\n\n Examples\n --------\n > var bool = hasAsyncAwaitSupport()\n \n\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.asyncIterator`\n support.\n\n Examples\n --------\n > var bool = hasAsyncIteratorSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport, hasSymbolSupport\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n Tests for native `BigInt64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `BigInt64Array` support.\n\n Examples\n --------\n > var bool = hasBigInt64ArraySupport()\n \n\n See Also\n --------\n hasBigIntSupport, hasBigUint64ArraySupport\n","hasBigIntSupport":"\nhasBigIntSupport()\n Tests for native `BigInt` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `BigInt` support.\n\n Examples\n --------\n > var bool = hasBigIntSupport()\n \n\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n Tests for native `BigUint64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `BigUint64Array` support.\n\n Examples\n --------\n > var bool = hasBigUint64ArraySupport()\n \n\n See Also\n --------\n hasBigIntSupport, hasBigInt64ArraySupport\n","hasClassSupport":"\nhasClassSupport()\n Tests for native `class` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `class` support.\n\n Examples\n --------\n > var bool = hasClassSupport()\n \n\n","hasDataViewSupport":"\nhasDataViewSupport()\n Tests for native `DataView` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `DataView` support.\n\n Examples\n --------\n > var bool = hasDataViewSupport()\n \n\n See Also\n --------\n hasArrayBufferSupport\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperties`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertiesSupport()\n \n\n See Also\n --------\n hasDefinePropertySupport\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperty`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertySupport()\n \n\n See Also\n --------\n hasDefinePropertiesSupport\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float32Array` support.\n\n Examples\n --------\n > var bool = hasFloat32ArraySupport()\n \n\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float64Array` support.\n\n Examples\n --------\n > var bool = hasFloat64ArraySupport()\n \n\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n Tests for native function `name` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has function `name` support.\n\n Examples\n --------\n > var bool = hasFunctionNameSupport()\n \n\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n Tests whether an environment supports native generator functions.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment support generator functions.\n\n Examples\n --------\n > var bool = hasGeneratorSupport()\n \n\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n Tests for `globalThis` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `globalThis` support.\n\n Examples\n --------\n > var bool = hasGlobalThisSupport()\n \n\n See Also\n --------\n getGlobal\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int8Array` support.\n\n Examples\n --------\n > var bool = hasInt8ArraySupport()\n \n\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int16Array` support.\n\n Examples\n --------\n > var bool = hasInt16ArraySupport()\n \n\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int32Array` support.\n\n Examples\n --------\n > var bool = hasInt32ArraySupport()\n \n\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.iterator`\n support.\n\n Examples\n --------\n > var bool = hasIteratorSymbolSupport()\n \n\n See Also\n --------\n hasAsyncIteratorSymbolSupport, hasSymbolSupport\n","hasMapSupport":"\nhasMapSupport()\n Tests for native `Map` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Map` support.\n\n Examples\n --------\n > var bool = hasMapSupport()\n \n\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Buffer` support.\n\n Examples\n --------\n > var bool = hasNodeBufferSupport()\n \n\n","hasOwnProp":"\nhasOwnProp( value, property )\n Tests if an object has a specified property.\n\n In contrast to the native `Object.prototype.hasOwnProperty`, this function\n does not throw when provided `null` or `undefined`. Instead, the function\n returns `false`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasOwnProp( beep, 'boop' )\n true\n > bool = hasOwnProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp\n","hasProp":"\nhasProp( value, property )\n Tests if an object has a specified property, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasProp( beep, 'boop' )\n true\n > bool = hasProp( beep, 'toString' )\n true\n > bool = hasProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp\n","hasProxySupport":"\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Proxy` support.\n\n Examples\n --------\n > var bool = hasProxySupport()\n \n\n","hasSetSupport":"\nhasSetSupport()\n Tests for native `Set` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Set` support.\n\n Examples\n --------\n > var bool = hasSetSupport()\n \n\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `SharedArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasSharedArrayBufferSupport()\n \n\n See Also\n --------\n hasArrayBufferSupport, hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasSymbolSupport":"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol` support.\n\n Examples\n --------\n > var bool = hasSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n Tests for native `toStringTag` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `toStringTag` support.\n\n Examples\n --------\n > var bool = hasToStringTagSupport()\n \n\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8Array` support.\n\n Examples\n --------\n > var bool = hasUint8ArraySupport()\n \n\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8ClampedArray` support.\n\n Examples\n --------\n > var bool = hasUint8ClampedArraySupport()\n \n\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n Tests for native `Uint16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint16Array` support.\n\n Examples\n --------\n > var bool = hasUint16ArraySupport()\n \n\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n Tests for native `Uint32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint32Array` support.\n\n Examples\n --------\n > var bool = hasUint32ArraySupport()\n \n\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str, pos )\n Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n\n Parameters\n ----------\n str: string\n Input string.\n\n pos: integer\n Position.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether surrogate pair exists at specified position.\n\n Examples\n --------\n > var out = hasUTF16SurrogatePairAt( '🌷', 0 )\n true\n > out = hasUTF16SurrogatePairAt( '🌷', 1 )\n false\n\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakMap` support.\n\n Examples\n --------\n > var bool = hasWeakMapSupport()\n \n\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakSet` support.\n\n Examples\n --------\n > var bool = hasWeakSetSupport()\n \n\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native WebAssembly support.\n\n Examples\n --------\n > var bool = hasWebAssemblySupport()\n \n\n","headercase":"\nheadercase( str )\n Converts a string to HTTP header case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n HTTP header-cased string.\n\n Examples\n --------\n > var out = headercase( 'Hello World!' )\n 'Hello-World'\n > out = headercase( 'beep boop' )\n 'Beep-Boop'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n\n This dataset is a classic dataset commonly used in examples demonstrating\n outlier detection.\n\n Returns\n -------\n out: Array\n Observations.\n\n Examples\n --------\n > var d = HERNDON_VENUS_SEMIDIAMETERS()\n [ -0.30, -0.44, ..., 0.39, 0.10 ]\n\n References\n ----------\n - Chauvenet, William. 1868. _A Manual of Spherical and Practical Astronomy_.\n 5th ed. Vol. 5. London, England: Trübner & Co.\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n - Tietjen, Gary L., and Roger H. Moore. 1972. \"Some Grubbs-Type Statistics\n for the Detection of Several Outliers.\" _Technometrics_ 14 (3). Taylor &\n Francis: 583–97. doi:10.1080/00401706.1972.10488948.\n\n","homedir":"\nhomedir()\n Returns the current user's home directory.\n\n If unable to locate a home directory, the function returns `null`.\n\n Returns\n -------\n out: string|null\n Home directory.\n\n Examples\n --------\n > var home = homedir()\n e.g., '/Users/'\n\n See Also\n --------\n configdir, tmpdir\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n Number of hours in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var hrs = days * HOURS_IN_DAY\n 75.36\n\n See Also\n --------\n HOURS_IN_WEEK\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n Number of hours in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var hrs = wks * HOURS_IN_WEEK\n 527.52\n\n See Also\n --------\n HOURS_IN_DAY\n","hoursInMonth":"\nhoursInMonth( [month[, year]] )\n Returns the number of hours in a month.\n\n By default, the function returns the number of hours in the current month of\n the current year (according to local time). To determine the number of hours\n for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Hours in a month.\n\n Examples\n --------\n > var num = hoursInMonth()\n \n > num = hoursInMonth( 2 )\n \n > num = hoursInMonth( 2, 2016 )\n 696\n > num = hoursInMonth( 2, 2017 )\n 672\n\n // Other ways to supply month:\n > num = hoursInMonth( 'feb', 2016 )\n 696\n > num = hoursInMonth( 'february', 2016 )\n 696\n\n See Also\n --------\n hoursInYear\n","hoursInYear":"\nhoursInYear( [value] )\n Returns the number of hours in a year according to the Gregorian calendar.\n\n By default, the function returns the number of hours in the current year\n (according to local time). To determine the number of hours for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of hours in a year.\n\n Examples\n --------\n > var num = hoursInYear()\n \n > num = hoursInYear( 2016 )\n 8784\n > num = hoursInYear( 2017 )\n 8760\n\n See Also\n --------\n hoursInMonth\n","httpServer":"\nhttpServer( [options,] [requestListener] )\n Returns a function to create an HTTP server.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.port: integer (optional)\n Server port. Default: `0` (i.e., randomly assigned).\n\n options.maxport: integer (optional)\n Max server port when port hunting. Default: `maxport = port`.\n\n options.hostname: string (optional)\n Server hostname.\n\n options.address: string (optional)\n Server address. Default: `'127.0.0.1'`.\n\n requestListener: Function (optional)\n Request callback.\n\n Returns\n -------\n createServer: Function\n Function to create an HTTP server.\n\n Examples\n --------\n // Basic usage:\n > var createServer = httpServer()\n \n\n // Provide a request callback:\n > function onRequest( request, response ) {\n ... console.log( request.url );\n ... response.end( 'OK' );\n ... };\n > createServer = httpServer( onRequest )\n \n\n // Specify a specific port:\n > var opts = { 'port': 7331 };\n > createServer = httpServer( opts )\n \n\n\ncreateServer( done )\n Creates an HTTP server.\n\n Parameters\n ----------\n done: Function\n Callback to invoke after creating a server.\n\n Examples\n --------\n > function done( error, server ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Success!' );\n ... server.close();\n ... };\n > var createServer = httpServer();\n > createServer( done );\n\n","identity":"\nidentity( x )\n Identity function.\n\n Parameters\n ----------\n x: any\n Input value.\n\n Returns\n -------\n out: any\n Input value.\n\n Examples\n --------\n > var v = identity( 3.14 )\n 3.14\n\n See Also\n --------\n constantFunction\n","ifelse":"\nifelse( bool, x, y )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n Returns\n -------\n z: any\n Either `x` or `y`.\n\n Examples\n --------\n > var z = ifelse( true, 1.0, -1.0 )\n 1.0\n > z = ifelse( false, 1.0, -1.0 )\n -1.0\n\n See Also\n --------\n ifelseAsync, ifthen\n","ifelseAsync":"\nifelseAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n\n A predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate completion\n\n The callback function accepts two arguments:\n\n - error: error object\n - bool: condition used to determine whether to invoke `x` or `y`\n\n The `done` callback is invoked upon function completion and is provided at\n most two arguments:\n\n - error: error object\n - result: either `x` or `y`\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, true );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifelseAsync( predicate, 'beep', 'boop', done )\n 'beep'\n\n See Also\n --------\n ifthenAsync, ifelse\n","ifthen":"\nifthen( bool, x, y )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n Returns\n -------\n z: any\n Return value of either `x` or `y`.\n\n Examples\n --------\n > function x() { return 1.0; };\n > function y() { return -1.0; };\n > var z = ifthen( true, x, y )\n 1.0\n > z = ifthen( false, x, y )\n -1.0\n\n See Also\n --------\n ifthenAsync, ifelse\n","ifthenAsync":"\nifthenAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n\n The predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate function completion\n\n The predicate function callback accepts two arguments:\n\n - error: error object\n - bool: condition used to determine whether to invoke `x` or `y`\n\n Both `x` and `y` are provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the `done` callback is invoked with only an\n error argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, false );\n ... }\n ... };\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'beep' );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifthenAsync( predicate, x, y, done )\n 'boop'\n\n See Also\n --------\n ifelseAsync, ifthen\n","imag":"\nimag( z )\n Returns the imaginary component of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var im = imag( z )\n 3.0\n\n See Also\n --------\n real, reim\n","imagf":"\nimagf( z )\n Returns the imaginary component of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var im = imagf( z )\n 3.0\n\n See Also\n --------\n imag, realf, reimf\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ACANTHUS_MOLLIS()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Acanthus mollis*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ALLIUM_OREOPHILUM\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_AIRPLANE_FROM_ABOVE()\n \n\n References\n ----------\n - Azari, Fédèle. 1929. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium ostrowskianum*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ALLIUM_OREOPHILUM()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Allium ostrowskianum*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ACANTHUS_MOLLIS\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_BLACK_CANYON()\n \n\n References\n ----------\n - O'Sullivan, Timothy H. 1871. *Black Cañon, Colorado River, From Camp 8,\n Looking Above*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_DUST_BOWL_HOME()\n \n\n References\n ----------\n - Lange, Dorothea. 1940. *Abandoned Dust Bowl Home*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n \n\n References\n ----------\n - Braun, Adolphe. 1870. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_HOUSE_CAT()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_NUDE_MALE\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_NUDE_MALE()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_HOUSE_CAT\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_MARCH_PASTORAL()\n \n\n References\n ----------\n - Emerson, Peter Henry. 1888. *A March Pastoral*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_NAGASAKI_BOATS()\n \n\n References\n ----------\n - Beato, Felice. 1865. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","incrapcorr":"\nincrapcorr( [mx, my] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrapcorr();\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator()\n ~1.0\n\n See Also\n --------\n incrmapcorr, incrpcorr, incrpcorr2\n","incrBinaryClassification":"\nincrBinaryClassification( N[, options] )\n Returns an accumulator function which incrementally performs binary\n classification using stochastic gradient descent (SGD).\n\n If provided a feature vector and response value, the accumulator function\n updates a binary classification model and returns updated model\n coefficients.\n\n If not provided a feature vector and response value, the accumulator\n function returns the current model coefficients.\n\n Stochastic gradient descent is sensitive to the scaling of the features. One\n is advised to either scale each feature to `[0,1]` or `[-1,1]` or to\n transform the features into z-scores with zero mean and unit variance. One\n should keep in mind that the same scaling has to be applied to training data\n in order to obtain accurate predictions.\n\n In general, the more data provided to an accumulator, the more reliable the\n model predictions.\n\n Parameters\n ----------\n N: integer\n Number of features.\n\n options: Object (optional)\n Function options.\n\n options.intercept: boolean (optional)\n Boolean indicating whether to include an intercept. Default: true.\n\n options.lambda: number (optional)\n Regularization parameter. Default: 1.0e-4.\n\n options.learningRate: ArrayLike (optional)\n Learning rate function and associated (optional) parameters. The first\n array element specifies the learning rate function and must be one of\n the following:\n\n - ['constant', ...]: constant learning rate function. To set the\n learning rate, provide a second array element. By default, when the\n learn rate function is 'constant', the learning rate is set to 0.02.\n\n - ['basic']: basic learning rate function according to the formula\n `10/(10+t)` where `t` is the current iteration.\n\n - ['invscaling', ...]: inverse scaling learning rate function according\n to the formula `eta0/pow(t, power_t)` where `eta0` is the initial\n learning rate and `power_t` is the exponent controlling how quickly the\n learning rate decreases. To set the initial learning rate, provide a\n second array element. By default, the initial learning rate is 0.02. To\n set the exponent, provide a third array element. By default, the\n exponent is 0.5.\n\n - ['pegasos']: Pegasos learning rate function according to the formula\n `1/(lambda*t)` where `t` is the current iteration and `lambda` is the\n regularization parameter.\n\n Default: ['basic'].\n\n options.loss: string (optional)\n Loss function. Must be one of the following:\n\n - hinge: hinge loss function. Corresponds to a soft-margin linear\n Support Vector Machine (SVM), which can handle non-linearly separable\n data.\n\n - log: logistic loss function. Corresponds to Logistic Regression.\n\n - modifiedHuber: Huber loss function variant for classification.\n\n - perceptron: hinge loss function without a margin. Corresponds to the\n original Perceptron by Rosenblatt.\n\n - squaredHinge: squared hinge loss function SVM (L2-SVM).\n\n Default: 'log'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts response values for one ore more observation vectors. Provide a\n second argument to specify the prediction type. Must be one of the\n following: 'label', 'probability', or 'linear'. Default: 'label'.\n\n Note that the probability prediction type is only compatible with 'log'\n and 'modifiedHuber' loss functions.\n\n Examples\n --------\n // Create an accumulator:\n > var opts = {};\n > opts.intercept = true;\n > opts.lambda = 1.0e-5;\n > var acc = incrBinaryClassification( 3, opts );\n\n // Update the model:\n > var buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\n > var x = array( buf );\n > var coefs = acc( x, 1 )\n \n\n // Create a new observation vector:\n > buf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\n > x = array( buf );\n\n // Predict the response value:\n > var yhat = acc.predict( x )\n \n\n See Also\n --------\n incrSGDRegression\n","incrcount":"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n See Also\n --------\n incrmean, incrsum, incrsummary\n","incrcovariance":"\nincrcovariance( [mx, my] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n\n If provided values, the accumulator function returns an updated unbiased\n sample covariance. If not provided values, the accumulator function returns\n the current unbiased sample covariance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovariance();\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator()\n ~-7.49\n\n See Also\n --------\n incrmcovariance, incrpcorr, incrvariance\n","incrcovmat":"\nincrcovmat( out[, means] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n unbiased sample covariance matrix. If not provided a data vector, the\n accumulator function returns the current unbiased sample covariance matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the covariance matrix or a square 2-dimensional ndarray for\n storing the covariance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovariance, incrpcorrmat\n","incrcv":"\nincrcv( [mean] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcv();\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator()\n ~0.47\n\n See Also\n --------\n incrmean, incrmcv, incrstdev, incrvmr\n","increwmean":"\nincrewmean( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwmean( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -1.5\n > v = accumulator()\n -1.5\n\n See Also\n --------\n increwvariance, incrmean, incrmmean, incrwmean\n","increwstdev":"\nincrewstdev( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n\n If provided a value, the accumulator function returns an updated standard\n deviation. If not provided a value, the accumulator function returns the\n current standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwstdev( 0.5 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n 3.5\n > s = accumulator()\n 3.5\n\n See Also\n --------\n increwvariance, incrmstdev, incrstdev\n","increwvariance":"\nincrewvariance( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n\n If provided a value, the accumulator function returns an updated variance.\n If not provided a value, the accumulator function returns the current\n variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwvariance( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 0.0\n > v = accumulator( -5.0 )\n 12.25\n > v = accumulator()\n 12.25\n\n See Also\n --------\n increwmean, increwstdev, incrvariance, incrmvariance\n","incrgmean":"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n\n If provided a value, the accumulator function returns an updated geometric\n mean. If not provided a value, the accumulator function returns the current\n geometric mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n If provided a negative value, the accumulated value is `NaN` for all future\n invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrgmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator()\n ~3.16\n\n See Also\n --------\n incrhmean, incrmean, incrmgmean, incrsummary\n","incrgrubbs":"\nincrgrubbs( [options] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the test statistic is `NaN` for all future invocations.\n\n The accumulator must be provided *at least* three data points before\n performing Grubbs' test. Until at least three data points are provided, the\n accumulator returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n options.init: integer (optional)\n Number of data points the accumulator should use to compute initial\n statistics *before* testing for an outlier. Until the accumulator is\n provided the number of data points specified by this option, the\n accumulator returns `null`. Default: 100.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrgrubbs();\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrmgrubbs\n","incrhmean":"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n\n If provided a value, the accumulator function returns an updated harmonic\n mean. If not provided a value, the accumulator function returns the current\n harmonic mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrhmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator()\n ~2.86\n\n See Also\n --------\n incrgmean, incrmean, incrmhmean, incrsummary\n","incrkmeans":"\nincrkmeans( k[, ndims][, options] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n\n If not provided initial centroids, the accumulator caches data vectors for\n subsequent centroid initialization. Until an accumulator computes initial\n centroids, an accumulator returns `null`.\n\n Once an accumulator has initial centroids (either provided or computed), if\n provided a data vector, the accumulator function returns updated cluster\n results. If not provided a data vector, the accumulator function returns the\n current cluster results.\n\n Cluster results are comprised of the following:\n\n - centroids: a `k x ndims` matrix containing centroid locations. Each\n centroid is the component-wise mean of the data points assigned to a\n centroid's corresponding cluster.\n - stats: a `k x 4` matrix containing cluster statistics.\n\n Cluster statistics consists of the following columns:\n\n - 0: number of data points assigned to a cluster.\n - 1: total within-cluster sum of squared distances.\n - 2: arithmetic mean of squared distances.\n - 3: corrected sample standard deviation of squared distances.\n\n Because an accumulator incrementally partitions data, one should *not*\n expect cluster statistics to match similar statistics had provided data been\n analyzed via a batch algorithm. In an incremental context, data points which\n would not be considered part of a particular cluster when analyzed via a\n batch algorithm may contribute to that cluster's statistics when analyzed\n incrementally.\n\n In general, the more data provided to an accumulator, the more reliable the\n cluster statistics.\n\n Parameters\n ----------\n k: integer|ndarray\n Number of clusters or a `k x ndims` matrix containing initial centroids.\n\n ndims: integer (optional)\n Number of dimensions. This argument must accompany an integer-valued\n first argument.\n\n options: Object (optional)\n Function options.\n\n options.metric: string (optional)\n Distance metric. Must be one of the following: 'euclidean', 'cosine', or\n 'correlation'. Default: 'euclidean'.\n\n options.init: ArrayLike (optional)\n Centroid initialization method and associated (optional) parameters. The\n first array element specifies the initialization method and must be one\n of the following: 'kmeans++', 'sample', or 'forgy'. The second array\n element specifies the number of data points to use when calculating\n initial centroids. When performing kmeans++ initialization, the third\n array element specifies the number of trials to perform when randomly\n selecting candidate centroids. Typically, more trials is correlated with\n initial centroids which lead to better clustering; however, a greater\n number of trials increases computational overhead. Default: ['kmeans++',\n k, 2+⌊ln(k)⌋ ].\n\n options.normalize: boolean (optional)\n Boolean indicating whether to normalize incoming data. This option is\n only relevant for non-Euclidean distance metrics. If set to `true`, an\n accumulator partitioning data based on cosine distance normalizes\n provided data to unit Euclidean length. If set to `true`, an accumulator\n partitioning data based on correlation distance first centers provided\n data and then normalizes data dimensions to have zero mean and unit\n variance. If this option is set to `false` and the metric is either\n cosine or correlation distance, then incoming data *must* already be\n normalized. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy incoming data to prevent mutation\n during normalization. Default: true.\n\n options.seed: any (optional)\n PRNG seed. Setting this option is useful when wanting reproducible\n initial centroids.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts centroid assignment for each data point in a provided matrix.\n To specify an output vector, provide a 1-dimensional ndarray as the\n first argument. Each element in the returned vector corresponds to a\n predicted cluster index for a respective data point.\n\n Examples\n --------\n > var accumulator = incrkmeans( 5, 2 );\n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v );\n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v );\n\n","incrkurtosis":"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n\n If provided a value, the accumulator function returns an updated corrected\n sample excess kurtosis. If not provided a value, the accumulator function\n returns the current corrected sample excess kurtosis.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrkurtosis();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( 2.0 )\n null\n > v = accumulator( -4.0 )\n null\n > v = accumulator( -4.0 )\n -6.0\n\n See Also\n --------\n incrmean, incrskewness, incrstdev, incrsummary, incrvariance\n","incrmaape":"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n\n If provided input values, the accumulator function returns an updated mean\n arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current mean arctangent absolute percentage\n error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.3218\n > m = accumulator( 5.0, 2.0 )\n ~0.6523\n > m = accumulator()\n ~0.6523\n\n See Also\n --------\n incrmae, incrmape, incrmean, incrmmaape\n","incrmae":"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute error. If not provided input values, the accumulator function\n returns the current mean absolute error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmae();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmape, incrme, incrmean, incrmmae\n","incrmapcorr":"\nincrmapcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample absolute correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample absolute correlation coefficient. If not provided values, the\n accumulator function returns the current moving sample absolute correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmapcorr( 3 );\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator( 3.0, -1.0 )\n ~0.925\n > ar = accumulator( 5.0, -9.5 )\n ~0.863\n > ar = accumulator()\n ~0.863\n\n See Also\n --------\n incrapcorr, incrmpcorr, incrmpcorr2\n","incrmape":"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute percentage error. If not provided input values, the accumulator\n function returns the current mean absolute percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator()\n ~91.67\n\n See Also\n --------\n incrmaape, incrmae, incrmean, incrmmape\n","incrmax":"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n\n If provided a value, the accumulator function returns an updated maximum\n value. If not provided a value, the accumulator function returns the current\n maximum value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmax();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmidrange, incrmin, incrmmax, incrrange, incrsummary\n","incrmaxabs":"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n\n If provided a value, the accumulator function returns an updated maximum\n absolute value. If not provided a value, the accumulator function returns\n the current maximum absolute value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaxabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmax, incrminabs, incrmmaxabs\n","incrmcovariance":"\nincrmcovariance( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample covariance.\n\n If provided values, the accumulator function returns an updated moving\n unbiased sample covariance. If not provided values, the accumulator function\n returns the current moving unbiased sample covariance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcovariance( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator( 3.0, -1.0 )\n -8.35\n > v = accumulator( 5.0, -9.5 )\n -29.42\n > v = accumulator()\n -29.42\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrmvariance\n","incrmcv":"\nincrmcv( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n\n The `W` parameter defines the number of values over which to compute the\n moving coefficient of variation.\n\n If provided a value, the accumulator function returns an updated moving\n coefficient of variation. If not provided a value, the accumulator function\n returns the current moving coefficient of variation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcv( 3 );\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator( 3.0 )\n 0.5\n > cv = accumulator( 7.0 )\n ~0.83\n > cv = accumulator()\n ~0.83\n\n See Also\n --------\n incrcv, incrmmean, incrmstdev, incrmvmr\n","incrmda":"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n\n If provided input values, the accumulator function returns an updated mean\n directional accuracy. If not provided input values, the accumulator function\n returns the current mean directional accuracy.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmda();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 4.0 )\n 0.5\n > m = accumulator()\n 0.5\n\n See Also\n --------\n incrmape, incrmmda\n","incrme":"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n\n If provided input values, the accumulator function returns an updated mean\n error. If not provided input values, the accumulator function returns the\n current mean error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrme();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmae, incrmean, incrmme\n","incrmean":"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator()\n -1.5\n\n See Also\n --------\n incrmidrange, incrmmean, incrstdev, incrsum, incrsummary, incrvariance\n","incrmeanabs":"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator()\n 3.5\n\n See Also\n --------\n incrmean, incrmmeanabs, incrsumabs\n","incrmeanabs2":"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs2();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 4.0\n > mu = accumulator( -5.0 )\n 14.5\n > mu = accumulator()\n 14.5\n\n See Also\n --------\n incrmean, incrmeanabs, incrmmeanabs2, incrsumabs2\n","incrmeanstdev":"\nincrmeanstdev( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanstdev();\n > var ms = accumulator()\n null\n > ms = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > ms = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > ms = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > ms = accumulator( 5.0 )\n [ 1.25, ~4.35 ]\n > ms = accumulator()\n [ 1.25, ~4.35 ]\n\n See Also\n --------\n incrmean, incrmeanvar, incrmmeanstdev, incrstdev\n","incrmeanvar":"\nincrmeanvar( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanvar();\n > var mv = accumulator()\n null\n > mv = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > mv = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > mv = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > mv = accumulator( 5.0 )\n [ 1.25, ~18.92 ]\n > mv = accumulator()\n [ 1.25, ~18.92 ]\n\n See Also\n --------\n incrmean, incrmeanstdev, incrmmeanvar, incrvariance\n","incrmgmean":"\nincrmgmean( W )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving geometric mean.\n\n If provided a value, the accumulator function returns an updated moving\n geometric mean. If not provided a value, the accumulator function returns\n the current moving geometric mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmgmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator( 3.0 )\n ~3.11\n > v = accumulator( 5.0 )\n ~4.22\n > v = accumulator()\n ~4.22\n\n See Also\n --------\n incrgmean, incrmhmean, incrmmean\n","incrmgrubbs":"\nincrmgrubbs( W[, options] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n The `W` parameter defines the number of values over which to perform Grubbs'\n test. The minimum window size is 3.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n Until provided `W` values, the accumulator function returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrmgrubbs( 20 );\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrgrubbs\n","incrmhmean":"\nincrmhmean( W )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving harmonic mean.\n\n If provided a value, the accumulator function returns an updated moving\n harmonic mean. If not provided a value, the accumulator function returns the\n current moving harmonic mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmhmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator( 3.0 )\n ~2.90\n > v = accumulator( 5.0 )\n ~4.09\n > v = accumulator()\n ~4.09\n\n See Also\n --------\n incrhmean, incrmgmean, incrmmean\n","incrmidrange":"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If provided a value, the accumulator function returns an updated mid-range.\n If not provided a value, the accumulator function returns the current mid-\n range.\n\n If provided `NaN`, the mid-range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmidrange();\n > var v = accumulator()\n null\n > v = accumulator( 3.14 )\n 3.14\n > v = accumulator( -5.0 )\n ~-0.93\n > v = accumulator( 10.1 )\n 2.55\n > v = accumulator()\n 2.55\n\n See Also\n --------\n incrmean, incrmax, incrmin, incrrange, incrsummary\n","incrmin":"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n\n If provided a value, the accumulator function returns an updated minimum\n value. If not provided a value, the accumulator function returns the current\n minimum value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmin();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 10.1 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmax, incrmidrange, incrmmin, incrrange, incrsummary\n","incrminabs":"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n\n If provided a value, the accumulator function returns an updated minimum\n absolute value. If not provided a value, the accumulator function returns\n the current minimum absolute value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 3.14\n > m = accumulator()\n 3.14\n\n See Also\n --------\n incrmaxabs, incrmin, incrmminabs\n","incrminmax":"\nincrminmax( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmax();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmminmax, incrrange\n","incrminmaxabs":"\nincrminmaxabs( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmaxabs();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator()\n [ 2.0, 5.0 ]\n\n See Also\n --------\n incrmaxabs, incrminabs, incrminmax, incrmminmaxabs\n","incrmmaape":"\nincrmmaape( W )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean arctangent absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean arctangent absolute\n percentage error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.32\n > m = accumulator( 5.0, 2.0 )\n ~0.65\n > m = accumulator( 3.0, 2.0 )\n ~0.59\n > m = accumulator( 2.0, 5.0 )\n ~0.66\n > m = accumulator()\n ~0.66\n\n See Also\n --------\n incrmaape, incrmmape, incrmmpe, incrmmean\n","incrmmae":"\nincrmmae( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute error.\n\n If provided a value, the accumulator function returns an updated moving\n mean absolute error. If not provided a value, the accumulator function\n returns the current moving mean absolute error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmae( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n 3.0\n > m = accumulator( 5.0, -2.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmae, incrmme, incrmmean\n","incrmmape":"\nincrmmape( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean absolute percentage\n error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator( 3.0, 2.0 )\n ~77.78\n > m = accumulator( 2.0, 5.0 )\n ~86.67\n > m = accumulator()\n ~86.67\n\n See Also\n --------\n incrmape, incrmmaape, incrmmpe, incrmmean\n","incrmmax":"\nincrmmax( W )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum.\n\n If provided a value, the accumulator function returns an updated moving\n maximum. If not provided a value, the accumulator function returns the\n current moving maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmax( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 3.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmmidrange, incrmmin, incrmrange, incrmsummary\n","incrmmaxabs":"\nincrmmaxabs( W )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n maximum absolute value. If not provided a value, the accumulator function\n returns the current moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaxabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 3.0 )\n 5.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmaxabs, incrmmax, incrmminabs\n","incrmmda":"\nincrmmda( W )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean directional accuracy.\n\n If provided input values, the accumulator function returns an updated moving\n mean directional accuracy. If not provided input values, the accumulator\n function returns the current moving mean directional accuracy.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmda( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( 5.0, 2.0 )\n 0.5\n > m = accumulator( 3.0, 2.0 )\n ~0.33\n > m = accumulator( 4.0, 5.0 )\n ~0.33\n > m = accumulator()\n ~0.33\n\n See Also\n --------\n incrmda, incrmmape\n","incrmme":"\nincrmme( W )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean error.\n\n If provided a value, the accumulator function returns an updated moving\n mean error. If not provided a value, the accumulator function returns the\n current moving mean error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmme( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n ~2.33\n > m = accumulator( 5.0, -2.0 )\n ~-0.33\n > m = accumulator()\n ~-0.33\n\n See Also\n --------\n incrme, incrmmae, incrmmean\n","incrmmean":"\nincrmmean( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmean( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator( 3.0 )\n 0.0\n > mu = accumulator( 5.0 )\n 1.0\n > mu = accumulator()\n 1.0\n\n See Also\n --------\n incrmean, incrmsum, incrmstdev, incrmsummary, incrmvariance\n","incrmmeanabs":"\nincrmmeanabs( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator( 3.0 )\n ~3.33\n > mu = accumulator( 5.0 )\n ~4.33\n > mu = accumulator()\n ~4.33\n\n See Also\n --------\n incrmeanabs, incrmmean, incrmsumabs\n","incrmmeanabs2":"\nincrmmeanabs2( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs2( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 4.0\n > m = accumulator( -5.0 )\n 14.5\n > m = accumulator( 3.0 )\n ~12.67\n > m = accumulator( 5.0 )\n ~19.67\n > m = accumulator()\n ~19.67\n\n See Also\n --------\n incrmeanabs2, incrmmeanabs, incrmsumabs2\n","incrmmeanstdev":"\nincrmmeanstdev( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanstdev( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > v = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > v = accumulator( 5.0 )\n [ 1.0, ~5.29 ]\n > v = accumulator()\n [ 1.0, ~5.29 ]\n\n See Also\n --------\n incrmeanstdev, incrmmean, incrmmeanvar, incrmstdev\n","incrmmeanvar":"\nincrmmeanvar( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanvar( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > v = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > v = accumulator( 5.0 )\n [ 1.0, 28.0 ]\n > v = accumulator()\n [ 1.0, 28.0 ]\n\n See Also\n --------\n incrmeanvar, incrmmean, incrmmeanstdev, incrmvariance\n","incrmmidrange":"\nincrmmidrange( W )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of values over which to compute\n the moving mid-range.\n\n If provided a value, the accumulator function returns an updated moving mid-\n range. If not provided a value, the accumulator function returns the current\n moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmidrange( 3 );\n > var mr = accumulator()\n null\n > mr = accumulator( 2.0 )\n 2.0\n > mr = accumulator( -5.0 )\n -1.5\n > mr = accumulator( 3.0 )\n -1.0\n > mr = accumulator( 5.0 )\n 0.0\n > mr = accumulator()\n 0.0\n\n See Also\n --------\n incrmmean, incrmmax, incrmmin, incrmrange\n","incrmmin":"\nincrmmin( W )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum. If not provided a value, the accumulator function returns the\n current moving minimum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmin( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 3.0 )\n -5.0\n > m = accumulator( 5.0 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmin, incrmmax, incrmmidrange, incrmrange, incrmsummary\n","incrmminabs":"\nincrmminabs( W )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n minimum absolute value. If not provided a value, the accumulator function\n returns the current moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 2.0\n > m = accumulator( 5.0 )\n 3.0\n > m = accumulator()\n 3.0\n\n See Also\n --------\n incrminabs, incrmmaxabs, incrmmin\n","incrmminmax":"\nincrmminmax( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum and maximum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmax( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmmax, incrminmax, incrmmin, incrmrange\n","incrmminmaxabs":"\nincrmminmaxabs( [out,] W )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n\n The `W` parameter defines the number of values over which to compute moving\n minimum and maximum absolute values.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmaxabs( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 3.0, 5.0 ]\n > mm = accumulator()\n [ 3.0, 5.0 ]\n\n See Also\n --------\n incrminmaxabs, incrmmax, incrmmaxabs, incrmmin, incrmminabs, incrmminmax\n","incrmmpe":"\nincrmmpe( W )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean percentage error. If not provided input values, the accumulator\n function returns the current moving mean percentage error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmpe( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator( 3.0, 2.0 )\n ~-55.56\n > m = accumulator( 2.0, 5.0 )\n ~-46.67\n > m = accumulator()\n ~-46.67\n\n See Also\n --------\n incrmmape, incrmme, incrmpe\n","incrmmse":"\nincrmmse( W )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean squared error.\n\n If provided a value, the accumulator function returns an updated moving mean\n squared error. If not provided a value, the accumulator function returns the\n current moving mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmse( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator( 3.0, 2.0 )\n 17.0\n > m = accumulator( 5.0, -2.0 )\n 33.0\n > m = accumulator()\n 33.0\n\n See Also\n --------\n incrmrmse, incrmrss, incrmse\n","incrmpcorr":"\nincrmpcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation coefficient. If not provided values, the accumulator\n function returns the current moving sample correlation coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator( 3.0, -1.0 )\n ~-0.925\n > r = accumulator( 5.0, -9.5 )\n ~-0.863\n > r = accumulator()\n ~-0.863\n\n See Also\n --------\n incrmcovariance, incrmpcorrdist, incrpcorr\n","incrmpcorr2":"\nincrmpcorr2( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving squared sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n squared sample correlation coefficient. If not provided values, the\n accumulator function returns the current moving squared sample correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr2( 3 );\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator( 3.0, -1.0 )\n ~0.86\n > r2 = accumulator( 5.0, -9.5 )\n ~0.74\n > r2 = accumulator()\n ~0.74\n\n See Also\n --------\n incrmapcorr, incrmpcorr, incrpcorr2\n","incrmpcorrdist":"\nincrmpcorrdist( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n However, due to limitations inherent in representing numeric values using\n floating-point format (i.e., the inability to represent numeric values with\n infinite precision), the correlation distance between perfectly correlated\n random variables may *not* be `0` or `2`. In fact, the correlation distance\n is *not* guaranteed to be strictly on the interval [0,2]. Any computed\n distance should, however, be within floating-point roundoff error.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation distance.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation distance. If not provided values, the accumulator\n function returns the current moving sample correlation distance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorrdist( 3 );\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator( 3.0, -1.0 )\n ~1.925\n > d = accumulator( 5.0, -9.5 )\n ~1.863\n > d = accumulator()\n ~1.863\n\n See Also\n --------\n incrmpcorr, incrpcorrdist\n","incrmpe":"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n\n If provided input values, the accumulator function returns an updated mean\n percentage error. If not provided input values, the accumulator function\n returns the current mean percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpe();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator()\n ~-58.33\n\n See Also\n --------\n incrmape, incrme, incrmmpe\n","incrmprod":"\nincrmprod( W )\n Returns an accumulator function which incrementally computes a moving\n product.\n\n The `W` parameter defines the number of values over which to compute the\n moving product.\n\n If provided a value, the accumulator function returns an updated moving\n product. If not provided a value, the accumulator function returns the\n current moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n For accumulations over large windows or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmprod( 3 );\n > var p = accumulator()\n null\n > p = accumulator( 2.0 )\n 2.0\n > p = accumulator( -5.0 )\n -10.0\n > p = accumulator( 3.0 )\n -30.0\n > p = accumulator( 5.0 )\n -75.0\n > p = accumulator()\n -75.0\n\n See Also\n --------\n incrmsum, incrprod\n","incrmrange":"\nincrmrange( W )\n Returns an accumulator function which incrementally computes a moving range.\n\n The `W` parameter defines the number of values over which to compute the\n moving range.\n\n If provided a value, the accumulator function returns an updated moving\n range. If not provided a value, the accumulator function returns the current\n moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrange( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0 )\n 0.0\n > r = accumulator( -5.0 )\n 7.0\n > r = accumulator( 3.0 )\n 8.0\n > r = accumulator( 5.0 )\n 10.0\n > r = accumulator()\n 10.0\n\n See Also\n --------\n incrmmax, incrmmean, incrmmin, incrmsummary, incrrange\n","incrmrmse":"\nincrmrmse( W )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving root mean squared error.\n\n If provided a value, the accumulator function returns an updated moving root\n mean squared error. If not provided a value, the accumulator function\n returns the current moving root mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrmse( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator( 3.0, 2.0 )\n ~4.12\n > r = accumulator( 5.0, -2.0 )\n ~5.74\n > r = accumulator()\n ~5.74\n\n See Also\n --------\n incrmmse, incrmrss, incrrmse\n","incrmrss":"\nincrmrss( W )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n\n The `W` parameter defines the number of values over which to compute the\n moving residual sum of squares.\n\n If provided a value, the accumulator function returns an updated moving\n residual sum of squares. If not provided a value, the accumulator function\n returns the current moving residual sum of squares.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrss( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator( 3.0, 2.0 )\n 51.0\n > r = accumulator( 5.0, -2.0 )\n 99.0\n > r = accumulator()\n 99.0\n\n See Also\n --------\n incrrss, incrmmse, incrmrmse\n","incrmse":"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n\n If provided input values, the accumulator function returns an updated mean\n squared error. If not provided input values, the accumulator function\n returns the current mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmse();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator()\n 25.0\n\n See Also\n --------\n incrmmse, incrrmse, incrrss\n","incrmstdev":"\nincrmstdev( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving corrected sample standard deviation.\n\n If provided a value, the accumulator function returns an updated moving\n corrected sample standard deviation. If not provided a value, the\n accumulator function returns the current moving corrected sample standard\n deviation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmstdev( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator( 3.0 )\n ~4.36\n > s = accumulator( 5.0 )\n ~5.29\n > s = accumulator()\n ~5.29\n\n See Also\n --------\n incrmmean, incrmsummary, incrmvariance, incrstdev\n","incrmsum":"\nincrmsum( W )\n Returns an accumulator function which incrementally computes a moving sum.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsum( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator( 3.0 )\n 0.0\n > s = accumulator( 5.0 )\n 3.0\n > s = accumulator()\n 3.0\n\n See Also\n --------\n incrmmean, incrmsummary, incrsum\n","incrmsumabs":"\nincrmsumabs( W )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator( 3.0 )\n 10.0\n > s = accumulator( -5.0 )\n 13.0\n > s = accumulator()\n 13.0\n\n See Also\n --------\n incrmmeanabs, incrmsum, incrsum, incrsumabs\n","incrmsumabs2":"\nincrmsumabs2( W )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs2( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator( 3.0 )\n 38.0\n > s = accumulator( -5.0 )\n 59.0\n > s = accumulator()\n 59.0\n\n See Also\n --------\n incrmmeanabs2, incrmsumabs, incrsumabs, incrsumabs2\n","incrmsummary":"\nincrmsummary( W )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n\n The `W` parameter defines the number of values over which to compute the\n moving statistical summary.\n\n If provided a value, the accumulator function returns an updated moving\n statistical summary. If not provided a value, the accumulator function\n returns the current moving statistical summary.\n\n The returned summary is an object containing the following fields:\n\n - window: window size.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - range: range.\n - midrange: arithmetic mean of the minimum and maximum values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n summaries are calculated from smaller sample sizes. Until the window is\n full, each returned summary is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsummary( 3 );\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsum, incrmvariance, incrsummary\n","incrmsumprod":"\nincrmsumprod( W )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n\n The `W` parameter defines the number of (x,y) pairs over which to compute\n the moving sum of products.\n\n If provided input values, the accumulator function returns an updated moving\n sum. If not provided input values, the accumulator function returns the\n current moving sum.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumprod( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator( 3.0, -2.0 )\n -10.0\n > s = accumulator( 5.0, 3.0 )\n -1.0\n > s = accumulator()\n -1.0\n\n See Also\n --------\n incrmprod, incrmsum, incrsumprod\n","incrmvariance":"\nincrmvariance( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample variance.\n\n If provided a value, the accumulator function returns an updated moving\n unbiased sample variance. If not provided a value, the accumulator function\n returns the current moving unbiased sample variance.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvariance( 3 );\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator( 3.0 )\n 19.0\n > s2 = accumulator( 5.0 )\n 28.0\n > s2 = accumulator()\n 28.0\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsummary, incrvariance\n","incrmvmr":"\nincrmvmr( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n\n The `W` parameter defines the number of values over which to compute the\n moving variance-to-mean ratio.\n\n If provided a value, the accumulator function returns an updated moving\n variance-to-mean ratio. If not provided a value, the accumulator function\n returns the current moving variance-to-mean ratio.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvmr( 3 );\n > var F = accumulator()\n null\n > F = accumulator( 2.0 )\n 0.0\n > F = accumulator( 1.0 )\n ~0.33\n > F = accumulator( 3.0 )\n 0.5\n > F = accumulator( 7.0 )\n ~2.55\n > F = accumulator()\n ~2.55\n\n See Also\n --------\n incrmmean, incrmvariance, incrvmr\n","incrnancount":"\nincrnancount()\n Returns an accumulator function which incrementally updates a count,\n ignoring `NaN` values.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnancount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n See Also\n --------\n incrnansum\n","incrnansum":"\nincrnansum()\n Returns an accumulator function which incrementally computes a sum, ignoring\n `NaN` values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( NaN )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n See Also\n --------\n incrnansumabs, incrsum\n","incrnansumabs":"\nincrnansumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values, ignoring NaN values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( NaN )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n See Also\n --------\n incrnansum, incrnansumabs2, incrsumabs\n","incrnansumabs2":"\nincrnansumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values, ignoring NaN values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( NaN )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n See Also\n --------\n incrnansum, incrnansumabs, incrsumabs2\n","incrpcorr":"\nincrpcorr( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated sample\n correlation coefficient. If not provided values, the accumulator function\n returns the current sample correlation coefficient.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator()\n ~-1.0\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrsummary\n","incrpcorr2":"\nincrpcorr2( [mx, my] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr2();\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator()\n ~1.0\n\n See Also\n --------\n incrapcorr, incrmpcorr2, incrpcorr\n","incrpcorrdist":"\nincrpcorrdist( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n If provided values, the accumulator function returns an updated sample\n correlation distance. If not provided values, the accumulator function\n returns the current sample correlation distance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdist();\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator()\n ~2.0\n\n See Also\n --------\n incrcovariance, incrpcorr, incrsummary\n","incrpcorrdistmat":"\nincrpcorrdistmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation distance matrix. If not provided a data vector, the\n accumulator function returns the current sample correlation distance matrix.\n\n Due to limitations inherent in representing numeric values using floating-\n point format (i.e., the inability to represent numeric values with infinite\n precision), the correlation distance between perfectly correlated random\n variables may *not* be `0` or `2`. In fact, the correlation distance is\n *not* guaranteed to be strictly on the interval [0,2]. Any computed distance\n should, however, be within floating-point roundoff error.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation distance matrix or a square 2-dimensional\n ndarray for storing the correlation distance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdistmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrpcorrdist, incrpcorrmat\n","incrpcorrmat":"\nincrpcorrmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation matrix. If not provided a data vector, the accumulator\n function returns the current sample correlation matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation matrix or a square 2-dimensional ndarray for\n storing the correlation matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovmat, incrpcorr, incrpcorrdistmat\n","incrprod":"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n\n If provided a value, the accumulator function returns an updated product. If\n not provided a value, the accumulator function returns the current product.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrprod();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -10.0\n > v = accumulator()\n -10.0\n\n See Also\n --------\n incrmprod, incrsum, incrsummary\n","incrrange":"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n\n If provided a value, the accumulator function returns an updated range. If\n not provided a value, the accumulator function returns the current range.\n\n If provided `NaN`, the range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrange();\n > var v = accumulator()\n null\n > v = accumulator( -2.0 )\n 0.0\n > v = accumulator( 1.0 )\n 3.0\n > v = accumulator( 3.0 )\n 5.0\n > v = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmean, incrmin, incrmrange, incrsummary\n","incrrmse":"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n\n If provided input values, the accumulator function returns an updated root\n mean squared error. If not provided input values, the accumulator function\n returns the current root mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrmse();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator()\n 5.0\n\n See Also\n --------\n incrmrmse, incrmse, incrrss\n","incrrss":"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n\n If provided input values, the accumulator function returns an updated\n residual sum of squares. If not provided input values, the accumulator\n function returns the current residual sum of squares.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrss();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator()\n 50.0\n\n See Also\n --------\n incrmrss, incrmse, incrrmse\n","incrskewness":"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n\n If provided a value, the accumulator function returns an updated corrected\n sample skewness. If not provided a value, the accumulator function returns\n the current corrected sample skewness.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrskewness();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( -5.0 )\n null\n > v = accumulator( -10.0 )\n ~0.492\n > v = accumulator()\n ~0.492\n\n See Also\n --------\n incrkurtosis, incrmean, incrstdev, incrsummary, incrvariance\n","incrspace":"\nincrspace( start, stop[, increment] )\n Generates a linearly spaced numeric array using a provided increment.\n\n If an `increment` is not provided, the default `increment` is `1`.\n\n The output array is guaranteed to include the `start` value but does not\n include the `stop` value.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Array element bound.\n\n increment: number (optional)\n Increment. Default: `1`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = incrspace( 0, 11, 2 )\n [ 0, 2, 4, 6, 8, 10 ]\n\n See Also\n --------\n linspace, logspace\n","incrstdev":"\nincrstdev( [mean] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n\n If provided a value, the accumulator function returns an updated corrected\n sample standard deviation. If not provided a value, the accumulator function\n returns the current corrected sample standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrstdev();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator()\n ~4.95\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrsummary, incrvariance\n","incrsum":"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n See Also\n --------\n incrcount, incrmean, incrmsum, incrprod, incrsummary\n","incrsumabs":"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n See Also\n --------\n incrmeanabs, incrmsumabs, incrsum\n","incrsumabs2":"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n See Also\n --------\n incrmeanabs2, incrmsumabs2, incrsumabs\n","incrsummary":"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n\n If provided a value, the accumulator function returns an updated summary. If\n not provided a value, the accumulator function returns the current summary.\n\n The returned summary is an object containing the following fields:\n\n - count: count.\n - max: maximum value.\n - min: minimum value.\n - range: range.\n - midrange: mid-range.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - skewness: corrected sample skewness.\n - kurtosis: corrected sample excess kurtosis.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsummary();\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrcount, incrkurtosis, incrmax, incrmean, incrmidrange, incrmin, incrmsummary, incrrange, incrskewness, incrstdev, incrsum, incrvariance\n","incrsumprod":"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n\n If provided input values, the accumulator function returns an updated sum.\n If not provided input values, the accumulator function returns the current\n sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumprod();\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator()\n -4.0\n\n See Also\n --------\n incrmsumprod, incrprod, incrsum\n","incrvariance":"\nincrvariance( [mean] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n\n If provided a value, the accumulator function returns an updated unbiased\n sample variance. If not provided a value, the accumulator function returns\n the current unbiased sample variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvariance();\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator()\n 24.5\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrstdev, incrsummary\n","incrvmr":"\nincrvmr( [mean] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvmr();\n > var D = accumulator()\n null\n > D = accumulator( 2.0 )\n 0.0\n > D = accumulator( 1.0 )\n ~0.33\n > D = accumulator()\n ~0.33\n\n See Also\n --------\n incrmean, incrmvmr, incrvariance\n","incrwmean":"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n\n If provided arguments, the accumulator function returns an updated weighted\n mean. If not provided arguments, the accumulator function returns the\n current weighted mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n The accumulator function accepts two arguments:\n\n - x: value\n - w: weight\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrwmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0, 1.0 )\n 2.0\n > mu = accumulator( 2.0, 0.5 )\n 2.0\n > mu = accumulator( 3.0, 1.5 )\n 2.5\n > mu = accumulator()\n 2.5\n\n See Also\n --------\n increwmean, incrmean, incrmmean\n","ind2sub":"\nind2sub( shape, idx[, options] )\n Converts a linear index to an array of subscripts.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n Returns\n -------\n out: Array\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var s = ind2sub( d, 17 )\n [ 1, 2, 2 ]\n\n\nind2sub.assign( shape, idx[, options], out )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n out: Array|TypedArray|Object\n Output array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var out = [ 0, 0, 0 ];\n > var s = ind2sub.assign( d, 17, out )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n See Also\n --------\n array, ndarray, sub2ind\n","ind2sub.assign":"\nind2sub.assign( shape, idx[, options], out )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n out: Array|TypedArray|Object\n Output array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var out = [ 0, 0, 0 ];\n > var s = ind2sub.assign( d, 17, out )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n See Also\n --------\n array, ndarray, sub2ind","indexOf":"\nindexOf( arr, searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n Search is performed using *strict equality* comparison.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object.\n\n searchElement: any\n Element to find.\n\n fromIndex: integer (optional)\n Starting index (if negative, the start index is determined relative to\n last element).\n\n Returns\n -------\n out: integer\n Index or -1.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ 4, 3, 2, 1 ];\n > var idx = indexOf( arr, 3 )\n 1\n > arr = [ 4, 3, 2, 1 ];\n > idx = indexOf( arr, 5 )\n -1\n\n // Using a `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, 3 )\n 5\n\n // `fromIndex` which exceeds `array` length:\n > arr = [ 1, 2, 3, 4, 2, 5 ];\n > idx = indexOf( arr, 2, 10 )\n -1\n\n // Negative `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\n > idx = indexOf( arr, 2, -4 )\n 5\n > idx = indexOf( arr, 2, -1 )\n 7\n\n // Negative `fromIndex` exceeding input `array` length:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, -10 )\n 1\n\n // Array-like objects:\n > var str = 'bebop';\n > idx = indexOf( str, 'o' )\n 3\n\n","inherit":"\ninherit( ctor, superCtor )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n\n This function is not designed to work with ES2015/ES6 classes. For\n ES2015/ES6 classes, use `class` with `extends`.\n\n Parameters\n ----------\n ctor: Object|Function\n Constructor which will inherit.\n\n superCtor: Object|Function\n Super (parent) constructor.\n\n Returns\n -------\n out: Object|Function\n Child constructor.\n\n Examples\n --------\n // Create a parent constructor:\n > function Foo() { return this; };\n > Foo.prototype.beep = function beep() { return 'boop'; };\n\n // Create a child constructor:\n > function Bar() { Foo.call( this ); return this; };\n\n // Setup inheritance:\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var v = bar.beep()\n 'boop'\n\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value[, level] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited enumerable properties.\n\n Examples\n --------\n > var props = inheritedEnumerableProperties( {} )\n\n See Also\n --------\n enumerableProperties, enumerablePropertiesIn, inheritedEnumerablePropertySymbols, inheritedKeys, inheritedNonEnumerableProperties, inheritedProperties\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedEnumerablePropertySymbols( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbols, inheritedKeys, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedKeys":"\ninheritedKeys( value[, level] )\n Returns an array of an object's inherited enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable property names.\n\n Examples\n --------\n > var keys = inheritedKeys( {} )\n\n See Also\n --------\n objectKeys, keysIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value[, level] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited non-enumerable properties.\n\n Examples\n --------\n > var props = inheritedNonEnumerableProperties( {} )\n\n See Also\n --------\n inheritedEnumerableProperties, inheritedNonEnumerablePropertyNames, inheritedNonEnumerablePropertySymbols, inheritedKeys, nonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value[, level] )\n Returns an array of an object's inherited non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited non-enumerable property names.\n\n Examples\n --------\n > var keys = inheritedNonEnumerablePropertyNames( {} )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertySymbols, objectKeys, nonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedNonEnumerablePropertySymbols( [] )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertyNames, nonEnumerableProperties, nonEnumerablePropertyNames, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedProperties":"\ninheritedProperties( value[, level] )\n Returns an array of an object's inherited property names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited property names and symbols.\n\n Examples\n --------\n > var symbols = inheritedProperties( [] )\n\n See Also\n --------\n properties, propertiesIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value, property[, level] )\n Returns a property descriptor for an object's inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var desc = inheritedPropertyDescriptor( {}, 'toString' )\n {...}\n\n See Also\n --------\n propertyDescriptor, propertyDescriptorIn, inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value[, level] )\n Returns an object's inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object\n An object's inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = inheritedPropertyDescriptors( obj )\n { 'foo': {...}, ... }\n\n See Also\n --------\n propertyDescriptors, propertyDescriptorsIn, inheritedKeys, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyNames":"\ninheritedPropertyNames( value[, level] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable and non-enumerable property\n names.\n\n Examples\n --------\n > var keys = inheritedPropertyNames( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertySymbols, propertyNames, propertyNamesIn\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value[, level] )\n Returns an array of an object's inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited symbol properties.\n\n Examples\n --------\n > var symbols = inheritedPropertySymbols( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, propertySymbols, propertySymbolsIn\n","inheritedWritableProperties":"\ninheritedWritableProperties( value[, level] )\n Returns an array of an object's inherited writable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited writable properties.\n\n Examples\n --------\n > var props = inheritedWritableProperties( {} )\n\n See Also\n --------\n inheritedWritablePropertyNames, inheritedWritablePropertySymbols, writableProperties, writablePropertiesIn, properties\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value[, level] )\n Returns an array of an object's inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited writable property names.\n\n Examples\n --------\n > var keys = inheritedWritablePropertyNames( {} )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertyNames, writablePropertyNamesIn, properties\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value[, level] )\n Returns an array of an object's inherited writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited writable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedWritablePropertySymbols( [] )\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertySymbols, writablePropertySymbolsIn, properties\n","inmap":"\ninmap( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmap( arr, foo )\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEach, inmapRight, map\n","inmapAsync":"\ninmapAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: value used to update the collection\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 2000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 2000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n\n\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n See Also\n --------\n forEachAsync, inmapRightAsync, inmap\n","inmapAsync.factory":"\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n See Also\n --------\n forEachAsync, inmapRightAsync, inmap","inmapRight":"\ninmapRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmapRight( arr, foo )\n 2: 3.0\n 1: 2.0\n 0: 1.0\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEachRight, inmap, mapRight\n","inmapRightAsync":"\ninmapRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: value used to update the collection\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 6000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 6000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n\n\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n See Also\n --------\n forEachRightAsync, inmapAsync, inmapRight\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n See Also\n --------\n forEachRightAsync, inmapAsync, inmapRight","inspectSinkStream":"\ninspectSinkStream( [options,] clbk )\n Returns a writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream","inspectStream":"\ninspectStream( [options,] clbk )\n Returns a transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream\n","inspectStream.factory":"\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","inspectStream.objectMode":"\ninspectStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream","instanceOf":"\ninstanceOf( value, constructor )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n\n While the prototype of an `object` created using object literal notion is\n `undefined`, the function returns `true` when provided an `object` literal\n and the `Object` constructor. This maintains consistent behavior with the\n `instanceof` operator.\n\n Parameters\n ----------\n value: any\n Input value.\n\n constructor: Function\n Constructor.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an instance of a provided constructor.\n\n Examples\n --------\n > var bool = instanceOf( [], Array )\n true\n > bool = instanceOf( {}, Object )\n true\n > bool = instanceOf( null, Object )\n false\n\n See Also\n --------\n isPrototypeOf, constructorName, inherit, typeOf\n","INT8_MAX":"\nINT8_MAX\n Maximum signed 8-bit integer.\n\n The maximum signed 8-bit integer is given by `2^7 - 1`.\n\n Examples\n --------\n > INT8_MAX\n 127\n\n See Also\n --------\n INT8_MIN\n","INT8_MIN":"\nINT8_MIN\n Minimum signed 8-bit integer.\n\n The minimum signed 8-bit integer is given by `-(2^7)`.\n\n Examples\n --------\n > INT8_MIN\n -128\n\n See Also\n --------\n INT8_MAX\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n\n Examples\n --------\n > INT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT16_NUM_BYTES, INT32_NUM_BYTES, UINT8_NUM_BYTES\n","Int8Array":"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array()\n \n\n\nInt8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Int8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'\n\n\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n \n\n\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5\n\n\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5\n\n\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int8Array.from":"\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int8Array.of":"\nInt8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1","Int8Array.name":"\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n ","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Int8Array.prototype.length":"\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","INT16_MAX":"\nINT16_MAX\n Maximum signed 16-bit integer.\n\n The maximum signed 16-bit integer is given by `2^15 - 1`.\n\n Examples\n --------\n > INT16_MAX\n 32767\n\n See Also\n --------\n INT16_MIN\n","INT16_MIN":"\nINT16_MIN\n Minimum signed 16-bit integer.\n\n The minimum signed 16-bit integer is given by `-(2^15)`.\n\n Examples\n --------\n > INT16_MIN\n -32768\n\n See Also\n --------\n INT16_MAX\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n\n Examples\n --------\n > INT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT32_NUM_BYTES, INT8_NUM_BYTES, UINT16_NUM_BYTES\n","Int16Array":"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array()\n \n\n\nInt16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Int16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'\n\n\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n \n\n\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10\n\n\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5\n\n\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int16Array.from":"\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int16Array.of":"\nInt16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2","Int16Array.name":"\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n ","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2","Int16Array.prototype.length":"\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","INT32_MAX":"\nINT32_MAX\n Maximum signed 32-bit integer.\n\n The maximum signed 32-bit integer is given by `2^31 - 1`.\n\n Examples\n --------\n > INT32_MAX\n 2147483647\n\n See Also\n --------\n INT32_MIN\n","INT32_MIN":"\nINT32_MIN\n Minimum signed 32-bit integer.\n\n The minimum signed 32-bit integer is given by `-(2^31)`.\n\n Examples\n --------\n > INT32_MIN\n -2147483648\n\n See Also\n --------\n INT32_MAX\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n\n Examples\n --------\n > INT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT16_NUM_BYTES, INT8_NUM_BYTES, UINT32_NUM_BYTES\n","Int32Array":"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array()\n \n\n\nInt32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 5, 5, 5 ] );\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Int32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'\n\n\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n \n\n\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20\n\n\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5\n\n\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int32Array.from":"\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int32Array.of":"\nInt32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4","Int32Array.name":"\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n ","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Int32Array.prototype.length":"\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n\n Examples\n --------\n > IS_BIG_ENDIAN\n \n\n See Also\n --------\n IS_LITTLE_ENDIAN\n","IS_BROWSER":"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n\n Examples\n --------\n > IS_BROWSER\n \n\n","IS_DARWIN":"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n\n Examples\n --------\n > IS_DARWIN\n \n\n","IS_ELECTRON":"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n\n Examples\n --------\n > IS_ELECTRON\n \n\n See Also\n --------\n IS_ELECTRON_MAIN, IS_ELECTRON_RENDERER\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n\n Examples\n --------\n > IS_ELECTRON_MAIN\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_RENDERER\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n\n Examples\n --------\n > IS_ELECTRON_RENDERER\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_MAIN\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n\n Examples\n --------\n > IS_LITTLE_ENDIAN\n \n\n See Also\n --------\n IS_BIG_ENDIAN\n","IS_NODE":"\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n\n Examples\n --------\n > IS_NODE\n \n\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n\n Examples\n --------\n > IS_WEB_WORKER\n \n\n","IS_WINDOWS":"\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n\n Examples\n --------\n > IS_WINDOWS\n \n\n","isAbsolutePath":"\nisAbsolutePath( value )\n Tests if a value is an absolute path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an absolute path.\n\n Examples\n --------\n // Windows environment:\n > var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n\n // POSIX environment:\n > bool = isAbsolutePath( '/foo/bar/baz' )\n true\n\n\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false\n\n\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isRelativePath\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false","isAbsolutePath.win32":"\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isRelativePath","isAccessorArray":"\nisAccessorArray( value )\n Tests if a value is an array-like object supporting the accessor (get/set)\n protocol.\n\n An accessor array is defined as an array, typed array, or an array-like\n object (excluding strings and functions) having `get` and `set` methods for\n accessing array elements.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an accessor array.\n\n Examples\n --------\n > var bool = isAccessorArray( new Complex64Array( 10 ) )\n true\n > bool = isAccessorArray( [] )\n false\n > bool = isAccessorArray( { 'length': 0 } )\n false\n > bool = isAccessorArray( {} )\n false\n\n See Also\n --------\n isArrayLike, isArrayLikeObject, isCollection\n","isAccessorProperty":"\nisAccessorProperty( value, property )\n Tests if an object's own property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has an accessor\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorProperty( obj, 'boop' )\n false\n > bool = isAccessorProperty( obj, 'beep' )\n true\n\n See Also\n --------\n hasOwnProp, isAccessorPropertyIn, isDataProperty\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value, property )\n Tests if an object's own or inherited property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has an\n accessor descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorPropertyIn( obj, 'boop' )\n false\n > bool = isAccessorPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n hasProp, isAccessorProperty, isDataPropertyIn\n","isAlphagram":"\nisAlphagram( value )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n\n The function first checks that an input value is a string before validating\n that the value is an alphagram. For non-string values, the function returns\n `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an alphagram.\n\n Examples\n --------\n > var out = isAlphagram( 'beep' )\n true\n > out = isAlphagram( 'zba' )\n false\n > out = isAlphagram( '' )\n false\n\n See Also\n --------\n isAnagram\n","isAlphaNumeric":"\nisAlphaNumeric( str )\n Tests whether a string contains only alphanumeric characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only alphanumeric\n characters.\n\n Examples\n --------\n > var bool = isAlphaNumeric( 'abc0123456789' )\n true\n > bool = isAlphaNumeric( 'abcdef' )\n true\n > bool = isAlphaNumeric( '0xff' )\n true\n > bool = isAlphaNumeric( '' )\n false\n\n See Also\n --------\n isDigitString\n","isAnagram":"\nisAnagram( str, value )\n Tests if a value is an anagram.\n\n Parameters\n ----------\n str: string\n Comparison string.\n\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an anagram.\n\n Examples\n --------\n > var str1 = 'I am a weakish speller';\n > var str2 = 'William Shakespeare';\n > var bool = isAnagram( str1, str2 )\n true\n > bool = isAnagram( 'bat', 'tabba' )\n false\n\n See Also\n --------\n isAlphagram\n","isArguments":"\nisArguments( value )\n Tests if a value is an arguments object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an arguments object.\n\n Examples\n --------\n > function foo() { return arguments; };\n > var bool = isArguments( foo() )\n true\n > bool = isArguments( [] )\n false\n\n","isArray":"\nisArray( value )\n Tests if a value is an array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array.\n\n Examples\n --------\n > var bool = isArray( [] )\n true\n > bool = isArray( {} )\n false\n\n See Also\n --------\n isArrayLike\n","isArrayArray":"\nisArrayArray( value )\n Tests if a value is an array of arrays.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of arrays.\n\n Examples\n --------\n > var bool = isArrayArray( [ [], [] ] )\n true\n > bool = isArrayArray( [ {}, {} ] )\n false\n > bool = isArrayArray( [] )\n false\n\n","isArrayBuffer":"\nisArrayBuffer( value )\n Tests if a value is an ArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an ArrayBuffer.\n\n Examples\n --------\n > var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\n true\n > bool = isArrayBuffer( [] )\n false\n\n See Also\n --------\n isSharedArrayBuffer, isTypedArray\n","isArrayBufferView":"\nisArrayBufferView( value )\n Tests if a value is a `ArrayBuffer` view.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `ArrayBuffer` view.\n\n Examples\n --------\n > var bool = isArrayBufferView( new Int8Array() )\n true\n > bool = isArrayBufferView( [] )\n false\n\n See Also\n --------\n isDataView, isTypedArray\n","isArrayLength":"\nisArrayLength( value )\n Tests if a value is a valid array length.\n\n A valid length property for an Array instance is any integer value on the\n interval [0, 2^32-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a valid array length.\n\n Examples\n --------\n > var bool = isArrayLength( 5 )\n true\n > bool = isArrayLength( 2.0e200 )\n false\n > bool = isArrayLength( -3.14 )\n false\n > bool = isArrayLength( null )\n false\n\n See Also\n --------\n isArray\n","isArrayLike":"\nisArrayLike( value )\n Tests if a value is array-like.\n\n If provided a string, the function returns `true`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is array-like.\n\n Examples\n --------\n > var bool = isArrayLike( [] )\n true\n > bool = isArrayLike( { 'length': 10 } )\n true\n > bool = isArrayLike( 'beep' )\n true\n > bool = isArrayLike( null )\n false\n\n See Also\n --------\n isArray, isArrayLikeObject, isCollection\n","isArrayLikeObject":"\nisArrayLikeObject( value )\n Tests if a value is an array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object.\n\n Examples\n --------\n > var bool = isArrayLikeObject( [] )\n true\n > bool = isArrayLikeObject( { 'length': 10 } )\n true\n > bool = isArrayLikeObject( 'beep' )\n false\n\n See Also\n --------\n isArray, isArrayLike, isCollection\n","isASCII":"\nisASCII( str )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string has all ASCII characters.\n\n Examples\n --------\n > var str = 'beep boop';\n > var bool = isASCII( str )\n true\n > bool = isASCII( fromCodePoint( 130 ) )\n false\n\n See Also\n --------\n isString\n","isBetween":"\nisBetween( value, a, b[, left, right] )\n Tests if a value is between two values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is between two values.\n\n Examples\n --------\n > var bool = isBetween( 3.14, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.0, 4.0 )\n true\n > bool = isBetween( 4.0, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.14, 4.0 )\n false\n > bool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\n false\n > bool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetweenArray\n","isBetweenArray":"\nisBetweenArray( value, a, b[, left, right] )\n Tests if a value is an array-like object where every element is between two\n values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object where every\n element is between two values.\n\n Examples\n --------\n > var arr = [ 3.0, 3.14, 4.0 ];\n > var bool = isBetweenArray( arr, 3.0, 4.0 )\n true\n > bool = isBetweenArray( arr, 3.14, 4.0 )\n false\n > bool = isBetweenArray( arr, 3.0, 3.14 )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetween\n","isBigInt":"\nisBigInt( value )\n Tests if a value is a BigInt.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a BigInt.\n\n Examples\n --------\n > var bool = isBigInt( BigInt( '1' ) )\n true\n > bool = isBigInt( Object( BigInt( '1' ) ) )\n true\n > bool = isBigInt( {} )\n false\n > bool = isBigInt( null )\n false\n > bool = isBigInt( true )\n false\n\n","isBigInt64Array":"\nisBigInt64Array( value )\n Tests if a value is a BigInt64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a BigInt64Array.\n\n Examples\n --------\n > var bool = isBigInt64Array( new BigInt64Array( 10 ) )\n true\n > bool = isBigInt64Array( [] )\n false\n\n See Also\n --------\n isBigUint64Array\n","isBigUint64Array":"\nisBigUint64Array( value )\n Tests if a value is a BigUint64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a BigUint64Array.\n\n Examples\n --------\n > var bool = isBigUint64Array( new BigUint64Array( 10 ) )\n true\n > bool = isBigUint64Array( [] )\n false\n\n See Also\n --------\n isBigInt64Array\n","isBinaryString":"\nisBinaryString( value )\n Tests if a value is a binary string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a binary string.\n\n Examples\n --------\n > var bool = isBinaryString( '1000101' )\n true\n > bool = isBinaryString( 'beep' )\n false\n > bool = isBinaryString( '' )\n false\n\n See Also\n --------\n isString\n","isBlankString":"\nisBlankString( value )\n Tests if a value is a blank string (i.e., an empty string or a string\n consisting only of whitespace characters).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a blank string.\n\n Examples\n --------\n > var bool = isBlankString( ' ' )\n true\n > bool = isBlankString( 'beep' )\n false\n > bool = isBlankString( null )\n false\n\n See Also\n --------\n isString, isEmptyString\n","isBoolean":"\nisBoolean( value )\n Tests if a value is a boolean.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean.\n\n Examples\n --------\n > var bool = isBoolean( false )\n true\n > bool = isBoolean( new Boolean( false ) )\n true\n\n\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false\n\n\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true\n\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false","isBoolean.isObject":"\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true","isBooleanArray":"\nisBooleanArray( value )\n Tests if a value is an array-like object of booleans.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object of booleans.\n\n Examples\n --------\n > var bool = isBooleanArray( [ true, false, true ] )\n true\n > bool = isBooleanArray( [ true, 'abc', false ] )\n false\n\n\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false\n\n\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true\n\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false","isBooleanArray.objects":"\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true","isBoxedPrimitive":"\nisBoxedPrimitive( value )\n Tests if a value is a JavaScript boxed primitive.\n\n Boxed primitive objects can be created with one of the following:\n\n - new Boolean()\n - new Number()\n - new String()\n - Object( Symbol() ) (ES6/ES2015)\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a JavaScript boxed primitive.\n\n Examples\n --------\n > var bool = isBoxedPrimitive( new Boolean( false ) )\n true\n > bool = isBoxedPrimitive( true )\n false\n\n See Also\n --------\n isPrimitive\n","isBuffer":"\nisBuffer( value )\n Tests if a value is a Buffer instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Buffer instance.\n\n Examples\n --------\n > var bool = isBuffer( new Buffer( 'beep' ) )\n true\n > bool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\n true\n > bool = isBuffer( {} )\n false\n > bool = isBuffer( [] )\n false\n\n","isCapitalized":"\nisCapitalized( value )\n Tests if a value is a string having an uppercase first character.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string with an uppercase first\n character.\n\n Examples\n --------\n > var bool = isCapitalized( 'Hello' )\n true\n > bool = isCapitalized( 'world' )\n false\n\n See Also\n --------\n isString\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value )\n Tests if a value is a matrix which is symmetric about its center.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a centrosymmetric matrix.\n\n Examples\n --------\n > var buf = [ 2, 1, 1, 2 ];\n > var M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isCentrosymmetricMatrix( M )\n true\n > bool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isCentrosymmetricMatrix( 3.14 )\n false\n > bool = isCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isCircular":"\nisCircular( value )\n Tests if an object-like value contains a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an object-like value contains a circular\n reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircular( obj )\n true\n > bool = isCircular( {} )\n false\n > bool = isCircular( null )\n false\n\n See Also\n --------\n isCircularArray, isCircularPlainObject\n","isCircularArray":"\nisCircularArray( value )\n Tests if a value is an array containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing a\n circular reference.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > arr.push( arr );\n > var bool = isCircularArray( arr )\n true\n > bool = isCircularArray( [] )\n false\n > bool = isCircularArray( null )\n false\n\n See Also\n --------\n isCircular, isCircularPlainObject\n","isCircularPlainObject":"\nisCircularPlainObject( value )\n Tests if a value is a plain object containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object containing a\n circular reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircularPlainObject( obj )\n true\n > bool = isCircularPlainObject( {} )\n false\n > bool = isCircularPlainObject( null )\n false\n\n See Also\n --------\n isCircular, isCircularArray\n","isClass":"\nisClass( value )\n Tests if a value is a class.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a class.\n\n Examples\n --------\n > var bool = isClass( class Person {} )\n true\n > bool = isClass( function Person() {} )\n false\n > bool = isClass( {} )\n false\n > bool = isClass( null )\n false\n > bool = isClass( true )\n false\n","isCollection":"\nisCollection( value )\n Tests if a value is a collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a collection.\n\n Examples\n --------\n > var bool = isCollection( [] )\n true\n > bool = isCollection( { 'length': 0 } )\n true\n > bool = isCollection( {} )\n false\n\n See Also\n --------\n isArrayLike, isArrayLikeObject\n","isComplex":"\nisComplex( value )\n Tests if a value is a 64-bit or 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit or 128-bit complex\n number.\n\n Examples\n --------\n > var bool = isComplex( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex( 3.14 )\n false\n > bool = isComplex( {} )\n false\n\n See Also\n --------\n isComplex64, isComplex128\n","isComplex64":"\nisComplex64( value )\n Tests if a value is a 64-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit complex number.\n\n Examples\n --------\n > var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex64( new Complex128( 3.0, 1.0 ) )\n false\n > bool = isComplex64( 3.14 )\n false\n > bool = isComplex64( {} )\n false\n\n See Also\n --------\n isComplex, isComplex128\n","isComplex64Array":"\nisComplex64Array( value )\n Tests if a value is a Complex64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex64Array.\n\n Examples\n --------\n > var bool = isComplex64Array( new Complex64Array( 10 ) )\n true\n > bool = isComplex64Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128Array, isComplexTypedArray\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64MatrixLike( M )\n true\n > bool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64MatrixLike( 3.14 )\n false\n > bool = isComplex64MatrixLike( {} )\n false\n\n See Also\n --------\n isComplex128MatrixLike, isndarrayLike, isMatrixLike\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value )\n Tests if a value is an ndarray-like object containing single-precision\n complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64ndarrayLike( M )\n true\n > bool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64ndarrayLike( 3.14 )\n false\n > bool = isComplex64ndarrayLike( {} )\n false\n\n See Also\n --------\n isComplex128ndarrayLike, isndarrayLike\n","isComplex64VectorLike":"\nisComplex64VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64VectorLike( M )\n true\n > bool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64VectorLike( 3.14 )\n false\n > bool = isComplex64VectorLike( {} )\n false\n\n See Also\n --------\n isComplex128VectorLike, isndarrayLike, isVectorLike\n","isComplex128":"\nisComplex128( value )\n Tests if a value is a 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 128-bit complex number.\n\n Examples\n --------\n > var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex128( new Complex64( 2.0, 2.0 ) )\n false\n > bool = isComplex128( 3.14 )\n false\n > bool = isComplex128( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64\n","isComplex128Array":"\nisComplex128Array( value )\n Tests if a value is a Complex128Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex128Array.\n\n Examples\n --------\n > var bool = isComplex128Array( new Complex128Array( 10 ) )\n true\n > bool = isComplex128Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex128, isComplex64Array, isComplexTypedArray\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing double-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex128';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex128MatrixLike( M )\n true\n > bool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128MatrixLike( 3.14 )\n false\n > bool = isComplex128MatrixLike( {} )\n false\n\n See Also\n --------\n isComplex64MatrixLike, isndarrayLike, isMatrixLike\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value )\n Tests if a value is an ndarray-like object containing double-precision\n complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n double-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex128';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex128ndarrayLike( M )\n true\n > bool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128ndarrayLike( 3.14 )\n false\n > bool = isComplex128ndarrayLike( {} )\n false\n\n See Also\n --------\n isComplex64ndarrayLike, isndarrayLike\n","isComplex128VectorLike":"\nisComplex128VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing double-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex128';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex128VectorLike( M )\n true\n > bool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128VectorLike( 3.14 )\n false\n > bool = isComplex128VectorLike( {} )\n false\n\n See Also\n --------\n isComplex64VectorLike, isndarrayLike, isVectorLike\n","isComplexLike":"\nisComplexLike( value )\n Tests if a value is a complex number-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a complex number-like object.\n\n Examples\n --------\n > var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplexLike( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplexLike( 3.14 )\n false\n > bool = isComplexLike( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128\n","isComplexTypedArray":"\nisComplexTypedArray( value )\n Tests if a value is a complex typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a complex typed array.\n\n Examples\n --------\n > var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n true\n\n See Also\n --------\n isComplex, isComplex64Array, isComplex128Array\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value )\n Tests if a value is complex-typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is complex-typed-array-like.\n\n Examples\n --------\n > var bool = isComplexTypedArrayLike( new Complex128Array() )\n true\n > bool = isComplexTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4,\n ... 'get': function get() {},\n ... 'set': function set() {}\n ... })\n true\n\n See Also\n --------\n isComplexLike, isComplexTypedArray, isComplex64Array, isComplex128Array\n","isComposite":"\nisComposite( value )\n Tests if a value is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a composite number.\n\n Examples\n --------\n > var bool = isComposite( 4.0 )\n true\n > bool = isComposite( new Number( 4.0 ) )\n true\n > bool = isComposite( 3.14 )\n false\n > bool = isComposite( -4.0 )\n false\n > bool = isComposite( null )\n false\n\n\nisComposite.isPrimitive( value )\n Tests if a value is a number primitive which is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n composite number.\n\n Examples\n --------\n > var bool = isComposite.isPrimitive( 4.0 )\n true\n > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n false\n\n\nisComposite.isObject( value )\n Tests if a value is a number object having a value which is a composite\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a composite number.\n\n Examples\n --------\n > var bool = isComposite.isObject( 4.0 )\n false\n > bool = isComposite.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isPrime\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value )\n Tests if a value is a number primitive which is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n composite number.\n\n Examples\n --------\n > var bool = isComposite.isPrimitive( 4.0 )\n true\n > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n false","isComposite.isObject":"\nisComposite.isObject( value )\n Tests if a value is a number object having a value which is a composite\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a composite number.\n\n Examples\n --------\n > var bool = isComposite.isObject( 4.0 )\n false\n > bool = isComposite.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isPrime","isConfigurableProperty":"\nisConfigurableProperty( value, property )\n Tests if an object's own property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurableProperty( obj, 'boop' )\n true\n > bool = isConfigurableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isReadableProperty, isWritableProperty\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurablePropertyIn( obj, 'boop' )\n true\n > bool = isConfigurablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isCubeNumber":"\nisCubeNumber( value )\n Tests if a value is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber( 8.0 )\n true\n > bool = isCubeNumber( new Number( 8.0 ) )\n true\n > bool = isCubeNumber( 3.14 )\n false\n > bool = isCubeNumber( -5.0 )\n false\n > bool = isCubeNumber( null )\n false\n\n\nisCubeNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a cube\n number.\n\n Examples\n --------\n > var bool = isCubeNumber.isPrimitive( 8.0 )\n true\n > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n false\n\n\nisCubeNumber.isObject( value )\n Tests if a value is a number object having a value which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber.isObject( 8.0 )\n false\n > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a cube\n number.\n\n Examples\n --------\n > var bool = isCubeNumber.isPrimitive( 8.0 )\n true\n > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n false","isCubeNumber.isObject":"\nisCubeNumber.isObject( value )\n Tests if a value is a number object having a value which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber.isObject( 8.0 )\n false\n > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber","isDataProperty":"\nisDataProperty( value, property )\n Tests if an object's own property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has a data descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataProperty( obj, 'boop' )\n true\n > bool = isDataProperty( obj, 'beep' )\n false\n\n See Also\n --------\n hasOwnProp, isAccessorProperty, isDataPropertyIn\n","isDataPropertyIn":"\nisDataPropertyIn( value, property )\n Tests if an object's own or inherited property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has a data\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataPropertyIn( obj, 'boop' )\n true\n > bool = isDataPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n hasProp, isAccessorPropertyIn, isDataProperty\n","isDataView":"\nisDataView( value )\n Tests if a value is a DataView.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a DataView.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 10 );\n > var bool = isDataView( new DataView( buf ) )\n true\n > bool = isDataView( [] )\n false\n\n See Also\n --------\n isArrayBuffer, isTypedArray\n","isDateObject":"\nisDateObject( value )\n Tests if a value is a Date object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Date object.\n\n Examples\n --------\n > var bool = isDateObject( new Date() )\n true\n > bool = isDateObject( '2017-01-01' )\n false\n\n","isDateObjectArray":"\nisDateObjectArray( value )\n Tests if a value is an array-like object containing only Date objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if value is an array-like object containing only Date\n objects.\n\n Examples\n --------\n > var bool = isDateObjectArray( [ new Date(), new Date() ] )\n true\n > bool = isDateObjectArray( [ {}, {} ] )\n false\n > bool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\n false\n > bool = isDateObjectArray( [] )\n false\n\n See Also\n --------\n isDateObject\n","isDigitString":"\nisDigitString( str )\n Tests whether a string contains only numeric digits.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only numeric digits.\n\n Examples\n --------\n > var bool = isDigitString( '0123456789' )\n true\n > bool = isDigitString( 'abcdef' )\n false\n > bool = isDigitString( '0xff' )\n false\n > bool = isDigitString( '' )\n false\n\n See Also\n --------\n isHexString, isString\n","isEmailAddress":"\nisEmailAddress( value )\n Tests if a value is an email address.\n\n Validation is not rigorous. *9* RFCs relate to email addresses, and\n accounting for all of them is a fool's errand. The function performs the\n simplest validation; i.e., requiring at least one `@` symbol.\n\n For rigorous validation, send a confirmation email. If the email bounces,\n consider the email invalid.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an email address.\n\n Examples\n --------\n > var bool = isEmailAddress( 'beep@boop.com' )\n true\n > bool = isEmailAddress( 'beep' )\n false\n > bool = isEmailAddress( null )\n false\n\n","isEmptyArray":"\nisEmptyArray( value )\n Tests if a value is an empty array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty array.\n\n Examples\n --------\n > var bool = isEmptyArray( [] )\n true\n > bool = isEmptyArray( [ 1, 2, 3 ] )\n false\n > bool = isEmptyArray( {} )\n false\n\n See Also\n --------\n isArray, isEmptyArrayLikeObject, isEmptyCollection\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value )\n Tests if a value is an empty array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an empty array-like object.\n\n Examples\n --------\n > var bool = isEmptyArrayLikeObject( [] )\n true\n > bool = isEmptyArrayLikeObject( { 'length': 0 } )\n true\n > bool = isEmptyArrayLikeObject( '' )\n false\n\n See Also\n --------\n isArrayLikeObject, isEmptyArray, isEmptyCollection\n","isEmptyCollection":"\nisEmptyCollection( value )\n Tests if a value is an empty collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty collection.\n\n Examples\n --------\n > var bool = isEmptyCollection( [] )\n true\n > bool = isEmptyCollection( { 'length': 0 } )\n true\n > bool = isEmptyCollection( [ 1, 2, 3 ] )\n false\n > bool = isEmptyCollection( {} )\n false\n\n See Also\n --------\n isCollection, isEmptyArray, isEmptyArrayLikeObject\n","isEmptyObject":"\nisEmptyObject( value )\n Tests if a value is an empty object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty object.\n\n Examples\n --------\n > var bool = isEmptyObject( {} )\n true\n > bool = isEmptyObject( { 'beep': 'boop' } )\n false\n > bool = isEmptyObject( [] )\n false\n\n See Also\n --------\n isObject, isPlainObject\n","isEmptyString":"\nisEmptyString( value )\n Tests if a value is an empty string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty string.\n\n Examples\n --------\n > var bool = isEmptyString( '' )\n true\n > bool = isEmptyString( new String( '' ) )\n true\n > bool = isEmptyString( 'beep' )\n false\n > bool = isEmptyString( [] )\n false\n\n\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false\n\n\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n See Also\n --------\n isString\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false","isEmptyString.isObject":"\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n See Also\n --------\n isString","isEnumerableProperty":"\nisEnumerableProperty( value, property )\n Tests if an object's own property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is enumerable.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isEnumerableProperty( beep, 'boop' )\n true\n > bool = isEnumerableProperty( beep, 'hasOwnProperty' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isEnumerablePropertyIn( obj, 'boop' )\n true\n > bool = isEnumerablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isError":"\nisError( value )\n Tests if a value is an Error object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Error object.\n\n Examples\n --------\n > var bool = isError( new Error( 'beep' ) )\n true\n > bool = isError( {} )\n false\n\n","isEvalError":"\nisEvalError( value )\n Tests if a value is an EvalError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided an EvalError (or a descendant) object,\n false positives may occur due to the fact that the EvalError constructor\n inherits from Error and has no internal class of its own. Hence, EvalError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an EvalError object.\n\n Examples\n --------\n > var bool = isEvalError( new EvalError( 'beep' ) )\n true\n > bool = isEvalError( {} )\n false\n\n See Also\n --------\n isError\n","isEven":"\nisEven( value )\n Tests if a value is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether is an even number.\n\n Examples\n --------\n > var bool = isEven( 4.0 )\n true\n > bool = isEven( new Number( 4.0 ) )\n true\n > bool = isEven( 3.0 )\n false\n > bool = isEven( -3.14 )\n false\n > bool = isEven( null )\n false\n\n\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false\n\n\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n See Also\n --------\n isOdd\n","isEven.isPrimitive":"\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false","isEven.isObject":"\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n See Also\n --------\n isOdd","isFalsy":"\nisFalsy( value )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is falsy.\n\n Examples\n --------\n > var bool = isFalsy( false )\n true\n > bool = isFalsy( '' )\n true\n > bool = isFalsy( 0 )\n true\n > bool = isFalsy( null )\n true\n > bool = isFalsy( void 0 )\n true\n > bool = isFalsy( NaN )\n true\n > bool = isFalsy( {} )\n false\n > bool = isFalsy( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n","isFalsyArray":"\nisFalsyArray( value )\n Tests if a value is an array-like object containing only falsy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only falsy values.\n\n Examples\n --------\n > var bool = isFalsyArray( [ null, '' ] )\n true\n > bool = isFalsyArray( [ {}, [] ] )\n false\n > bool = isFalsyArray( [] )\n false\n\n See Also\n --------\n isFalsy, isTruthyArray\n","isFinite":"\nisFinite( value )\n Tests if a value is a finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a finite number.\n\n Examples\n --------\n > var bool = isFinite( 5.0 )\n true\n > bool = isFinite( new Number( 5.0 ) )\n true\n > bool = isFinite( 1.0/0.0 )\n false\n > bool = isFinite( null )\n false\n\n\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isFiniteArray, isInfinite\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false","isFinite.isObject":"\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isFiniteArray, isInfinite","isFiniteArray":"\nisFiniteArray( value )\n Tests if a value is an array-like object of finite numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of finite\n numbers.\n\n Examples\n --------\n > var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n false\n\n\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isFinite, isInfinite\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isFiniteArray.objects":"\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isFinite, isInfinite","isFloat32Array":"\nisFloat32Array( value )\n Tests if a value is a Float32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float32Array.\n\n Examples\n --------\n > var bool = isFloat32Array( new Float32Array( 10 ) )\n true\n > bool = isFloat32Array( [] )\n false\n\n See Also\n --------\n isFloat64Array\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32MatrixLike( M )\n true\n > bool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32MatrixLike( 3.14 )\n false\n > bool = isFloat32MatrixLike( {} )\n false\n\n See Also\n --------\n isFloat64MatrixLike, isndarrayLike, isMatrixLike\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value )\n Tests if a value is an ndarray-like object containing single-precision\n floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32ndarrayLike( M )\n true\n > bool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32ndarrayLike( 3.14 )\n false\n > bool = isFloat32ndarrayLike( {} )\n false\n\n See Also\n --------\n isFloat64ndarrayLike, isndarrayLike\n","isFloat32VectorLike":"\nisFloat32VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32VectorLike( M )\n true\n > bool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32VectorLike( 3.14 )\n false\n > bool = isFloat32VectorLike( {} )\n false\n\n See Also\n --------\n isFloat64VectorLike, isndarrayLike, isVectorLike\n","isFloat64Array":"\nisFloat64Array( value )\n Tests if a value is a Float64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float64Array.\n\n Examples\n --------\n > var bool = isFloat64Array( new Float64Array( 10 ) )\n true\n > bool = isFloat64Array( [] )\n false\n\n See Also\n --------\n isFloat32Array\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64MatrixLike( M )\n true\n > bool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64MatrixLike( 3.14 )\n false\n > bool = isFloat64MatrixLike( {} )\n false\n\n See Also\n --------\n isFloat32MatrixLike, isndarrayLike, isMatrixLike\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value )\n Tests if a value is an ndarray-like object containing double-precision\n floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64ndarrayLike( M )\n true\n > bool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64ndarrayLike( 3.14 )\n false\n > bool = isFloat64ndarrayLike( {} )\n false\n\n See Also\n --------\n isFloat32ndarrayLike, isndarrayLike\n","isFloat64VectorLike":"\nisFloat64VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64VectorLike( M )\n true\n > bool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64VectorLike( 3.14 )\n false\n > bool = isFloat64VectorLike( {} )\n false\n\n See Also\n --------\n isFloat32VectorLike, isndarrayLike, isVectorLike\n","isFunction":"\nisFunction( value )\n Tests if a value is a function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a function.\n\n Examples\n --------\n > function beep() {};\n > var bool = isFunction( beep )\n true\n > bool = isFunction( {} )\n false\n\n","isFunctionArray":"\nisFunctionArray( value )\n Tests if a value is an array-like object containing only functions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n functions.\n\n Examples\n --------\n > function beep() {};\n > function boop() {};\n > var bool = isFunctionArray( [ beep, boop ] )\n true\n > bool = isFunctionArray( [ {}, beep ] )\n false\n > bool = isFunctionArray( [] )\n false\n\n See Also\n --------\n isArray\n","isGeneratorObject":"\nisGeneratorObject( value )\n Tests if a value is a generator object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a generator object.\n\n Examples\n --------\n > function* generateID() {\n ... var idx = 0;\n ... while ( idx < idx+1 ) {\n ... yield idx;\n ... idx += 1;\n ... }\n ... };\n > var bool = isGeneratorObject( generateID() )\n true\n > bool = isGeneratorObject( generateID )\n false\n > bool = isGeneratorObject( {} )\n false\n > bool = isGeneratorObject( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObjectLike\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value )\n Tests if a value is generator object-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is generator object-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {},\n ... 'return': function noop() {},\n ... 'throw': function noop() {}\n ... };\n > var bool = isGeneratorObjectLike( obj )\n true\n > bool = isGeneratorObjectLike( {} )\n false\n > bool = isGeneratorObjectLike( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObject\n","isgzipBuffer":"\nisgzipBuffer( value )\n Tests if a value is a gzip buffer.\n\n A gzip buffer is defined as either a Node.js Buffer or Uint8Array which\n contains a 10-byte header, a body containing the compressed payload, and an\n 8-byte footer containing a CRC-32 checksum and the length of the original\n uncompressed data, modulo 2^32.\n\n This function only examines the 10-byte header to ensure the header includes\n the expected magic number and compression method. The function does not\n perform an integrity check.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a gzip buffer.\n\n Examples\n --------\n > var buf = new Uint8Array( 20 );\n > buf[ 0 ] = 31; // 0x1f => magic number\n > buf[ 1 ] = 139; // 0x8b\n > buf[ 2 ] = 8; // 0x08 => compression method\n > var bool = isgzipBuffer( buf )\n true\n > bool = isgzipBuffer( [] )\n false\n\n See Also\n --------\n isBuffer, isUint8Array\n","isHexString":"\nisHexString( str )\n Tests whether a string contains only hexadecimal digits.\n\n The function does not recognize `x` (as in the standard `0x` prefix).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only hexadecimal digits.\n\n Examples\n --------\n > var bool = isHexString( '0123456789abcdefABCDEF' )\n true\n > bool = isHexString( '0xffffff' )\n false\n > bool = isHexString( 'x' )\n false\n > bool = isHexString( '' )\n false\n\n See Also\n --------\n isString\n","isInfinite":"\nisInfinite( value )\n Tests if a value is an infinite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an infinite number.\n\n Examples\n --------\n > var bool = isInfinite( 1.0/0.0 )\n true\n > bool = isInfinite( new Number( -1.0/0.0 ) )\n true\n > bool = isInfinite( 5.0 )\n false\n > bool = isInfinite( '1.0/0.0' )\n false\n\n\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false\n\n\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n See Also\n --------\n isFinite\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false","isInfinite.isObject":"\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n See Also\n --------\n isFinite","isInheritedProperty":"\nisInheritedProperty( value, property )\n Tests if an object has an inherited property.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has an inherited property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isInheritedProperty( beep, 'boop' )\n false\n > bool = isInheritedProperty( beep, 'toString' )\n true\n > bool = isInheritedProperty( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp, hasProp\n","isInt8Array":"\nisInt8Array( value )\n Tests if a value is an Int8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int8Array.\n\n Examples\n --------\n > var bool = isInt8Array( new Int8Array( 10 ) )\n true\n > bool = isInt8Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt32Array\n","isInt16Array":"\nisInt16Array( value )\n Tests if a value is an Int16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int16Array.\n\n Examples\n --------\n > var bool = isInt16Array( new Int16Array( 10 ) )\n true\n > bool = isInt16Array( [] )\n false\n\n See Also\n --------\n isInt32Array, isInt8Array\n","isInt32Array":"\nisInt32Array( value )\n Tests if a value is an Int32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int32Array.\n\n Examples\n --------\n > var bool = isInt32Array( new Int32Array( 10 ) )\n true\n > bool = isInt32Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt8Array\n","isInteger":"\nisInteger( value )\n Tests if a value is an integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an integer.\n\n Examples\n --------\n > var bool = isInteger( 5.0 )\n true\n > bool = isInteger( new Number( 5.0 ) )\n true\n > bool = isInteger( -3.14 )\n false\n > bool = isInteger( null )\n false\n\n\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isNumber\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false","isInteger.isObject":"\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isNumber","isIntegerArray":"\nisIntegerArray( value )\n Tests if a value is an array-like object of integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of integer\n values.\n\n Examples\n --------\n > var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isIntegerArray( [ -3.0, '3.0' ] )\n false\n\n\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isIntegerArray.objects":"\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isIterableLike":"\nisIterableLike( value )\n Tests if a value is iterable-like.\n\n In order to be iterable, an object must implement the @@iterator method,\n which, when called, returns an iterator protocol-compliant object.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n In environments lacking Symbol.iterator support, this function always\n returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterable-like.\n\n Examples\n --------\n > var bool = isIterableLike( [ 1, 2, 3 ] )\n \n > bool = isIterableLike( {} )\n false\n > bool = isIterableLike( null )\n false\n\n See Also\n --------\n isIteratorLike\n","isIteratorLike":"\nisIteratorLike( value )\n Tests if a value is iterator-like.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterator-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {}\n ... };\n > var bool = isIteratorLike( obj )\n true\n > bool = isIteratorLike( {} )\n false\n > bool = isIteratorLike( null )\n false\n\n See Also\n --------\n isIterableLike\n","isJSON":"\nisJSON( value )\n Tests if a value is a parseable JSON string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a parseable JSON string.\n\n Examples\n --------\n > var bool = isJSON( '{\"a\":5}' )\n true\n > bool = isJSON( '{a\":5}' )\n false\n\n","isLeapYear":"\nisLeapYear( value )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n\n A leap year is defined as any year which is exactly divisible by 4, except\n for years which are exactly divisible by 100 and not by 400. In this\n definition, 100 corresponds to years marking a new century, and 400\n corresponds to the length of the *leap cycle*.\n\n If not provided any arguments, the function returns a boolean indicating\n if the current year (according to local time) is a leap year.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value corresponds to a leap year.\n\n Examples\n --------\n > var bool = isLeapYear( new Date() )\n \n > bool = isLeapYear( 1996 )\n true\n > bool = isLeapYear( 2001 )\n false\n\n","isLocalhost":"\nisLocalhost( value )\n Tests whether a value is a localhost hostname.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a localhost hostname.\n\n Examples\n --------\n > var bool = isLocalhost( 'localhost' )\n true\n > bool = isLocalhost( '127.0.0.1' )\n true\n > bool = isLocalhost( 'stdlib.io' )\n false\n","isLowercase":"\nisLowercase( value )\n Tests if a value is a lowercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a lowercase string.\n\n Examples\n --------\n > var bool = isLowercase( 'hello' )\n true\n > bool = isLowercase( 'World' )\n false\n\n See Also\n --------\n isString, isUppercase\n","isMatrixLike":"\nisMatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isMatrixLike( M )\n true\n > bool = isMatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isMatrixLike( 3.14 )\n false\n > bool = isMatrixLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isndarrayLike, isTypedArrayLike, isVectorLike\n","isMethod":"\nisMethod( value, property )\n Tests if an object has a specified method name.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n The function only searches own properties.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': function beep() { return 'beep'; } };\n > var bool = isMethod( beep, 'boop' )\n true\n > bool = isMethod( beep, 'toString' )\n false\n\n See Also\n --------\n hasOwnProp, isFunction, isMethodIn\n","isMethodIn":"\nisMethodIn( value, property )\n Tests if an object has a specified method name, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isMethodIn( beep, 'toString' )\n true\n > bool = isMethodIn( beep, 'boop' )\n false\n > bool = isMethodIn( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp, isFunction, isMethod\n","isMultiSlice":"\nisMultiSlice( value )\n Tests if a value is a MultiSlice object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a MultiSlice object.\n\n Examples\n --------\n > var bool = isMultiSlice( new MultiSlice() )\n true\n > bool = isMultiSlice( 3.14 )\n false\n > bool = isMultiSlice( {} )\n false\n\n See Also\n --------\n isSlice, MultiSlice\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value )\n Tests if a value is named typed tuple-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is named typed tuple-like.\n\n Examples\n --------\n > var Point = namedtypedtuple( [ 'x', 'y' ] );\n > var p = new Point();\n > var bool = isNamedTypedTupleLike( p )\n true\n > bool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isNamedTypedTupleLike( 3.14 )\n false\n > bool = isNamedTypedTupleLike( {} )\n false\n\n See Also\n --------\n namedtypedtuple\n","isnan":"\nisnan( value )\n Tests if a value is NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is NaN.\n\n Examples\n --------\n > var bool = isnan( NaN )\n true\n > bool = isnan( new Number( NaN ) )\n true\n > bool = isnan( 3.14 )\n false\n > bool = isnan( null )\n false\n\n\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false\n\n\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n See Also\n --------\n isNumber\n","isnan.isPrimitive":"\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false","isnan.isObject":"\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n See Also\n --------\n isNumber","isNaNArray":"\nisNaNArray( value )\n Tests if a value is an array-like object containing only NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n NaN values.\n\n Examples\n --------\n > var bool = isNaNArray( [ NaN, NaN, NaN ] )\n true\n > bool = isNaNArray( [ NaN, 2 ] )\n false\n\n\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true\n\n\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n See Also\n --------\n isnan\n","isNaNArray.primitives":"\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true","isNaNArray.objects":"\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n See Also\n --------\n isnan","isNativeFunction":"\nisNativeFunction( value )\n Tests if a value is a native function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a native function.\n\n Examples\n --------\n > var bool = isNativeFunction( Date )\n true\n > function beep() {};\n > bool = isNativeFunction( beep )\n false\n > bool = isNativeFunction( {} )\n false\n\n See Also\n --------\n isFunction\n","isndarrayLike":"\nisndarrayLike( value )\n Tests if a value is ndarray-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is ndarray-like.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isndarrayLike( M )\n true\n > bool = isndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isndarrayLike( 3.14 )\n false\n > bool = isndarrayLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isTypedArrayLike, isVectorLike\n","isNegativeInteger":"\nisNegativeInteger( value )\n Tests if a value is a negative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative integer.\n\n Examples\n --------\n > var bool = isNegativeInteger( -5.0 )\n true\n > bool = isNegativeInteger( new Number( -5.0 ) )\n true\n > bool = isNegativeInteger( 5.0 )\n false\n > bool = isNegativeInteger( -3.14 )\n false\n > bool = isNegativeInteger( null )\n false\n\n\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isNegativeIntegerArray":"\nisNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only negative integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative integers.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNegativeNumber":"\nisNegativeNumber( value )\n Tests if a value is a negative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative number.\n\n Examples\n --------\n > var bool = isNegativeNumber( -5.0 )\n true\n > bool = isNegativeNumber( new Number( -5.0 ) )\n true\n > bool = isNegativeNumber( -3.14 )\n true\n > bool = isNegativeNumber( 5.0 )\n false\n > bool = isNegativeNumber( null )\n false\n\n\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n See Also\n --------\n isNumber\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n See Also\n --------\n isNumber","isNegativeNumberArray":"\nisNegativeNumberArray( value )\n Tests if a value is an array-like object containing only negative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNegativeZero":"\nisNegativeZero( value )\n Tests if a value is negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero( -0.0 )\n true\n > bool = isNegativeZero( new Number( -0.0 ) )\n true\n > bool = isNegativeZero( -3.14 )\n false\n > bool = isNegativeZero( 0.0 )\n false\n > bool = isNegativeZero( null )\n false\n\n\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false\n\n\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n See Also\n --------\n isNumber, isPositiveZero\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false","isNegativeZero.isObject":"\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n See Also\n --------\n isNumber, isPositiveZero","isNodeBuiltin":"\nisNodeBuiltin( str )\n Tests whether a string matches a Node.js built-in module name.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string matches a Node.js built-in module\n name.\n\n Examples\n --------\n > var bool = isNodeBuiltin( 'cluster' )\n true\n > bool = isNodeBuiltin( 'crypto' )\n true\n > bool = isNodeBuiltin( 'fs-extra' )\n false\n > bool = isNodeBuiltin( '' )\n false\n\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value )\n Tests if a value is Node duplex stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node duplex stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Duplex;\n > s = new Stream();\n > var bool = isNodeDuplexStreamLike( s )\n true\n > bool = isNodeDuplexStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value )\n Tests if a value is Node readable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node readable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Readable;\n > s = new Stream();\n > var bool = isNodeReadableStreamLike( s )\n true\n > bool = isNodeReadableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeREPL":"\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if running in a Node.js REPL environment.\n\n Examples\n --------\n > var bool = isNodeREPL()\n \n\n","isNodeStreamLike":"\nisNodeStreamLike( value )\n Tests if a value is Node stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Stream;\n > s = new Stream();\n > var bool = isNodeStreamLike( s )\n true\n > bool = isNodeStreamLike( {} )\n false\n\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value )\n Tests if a value is Node transform stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node transform stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Transform;\n > s = new Stream();\n > var bool = isNodeTransformStreamLike( s )\n true\n > bool = isNodeTransformStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value )\n Tests if a value is Node writable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node writable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Writable;\n > s = new Stream();\n > var bool = isNodeWritableStreamLike( s )\n true\n > bool = isNodeWritableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value, property )\n Tests if an object's own property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurableProperty( obj, 'boop' )\n false\n > bool = isNonConfigurableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurablePropertyIn( obj, 'boop' )\n false\n > bool = isNonConfigurablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value, property )\n Tests if an object's own property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerableProperty( obj, 'boop' )\n false\n > bool = isNonEnumerableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadableProperty, isWritableProperty\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerablePropertyIn( obj, 'boop' )\n false\n > bool = isNonEnumerablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadablePropertyIn, isWritablePropertyIn\n","isNonNegativeFinite":"\nisNonNegativeFinite( value )\n Tests if a value is a nonnegative finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative finite number.\n\n Examples\n --------\n > var bool = isNonNegativeFinite( 5.0 )\n true\n > bool = isNonNegativeFinite( new Number( 5.0 ) )\n true\n > bool = isNonNegativeFinite( 3.14 )\n true\n > bool = isNonNegativeFinite( -5.0 )\n false\n > bool = isNonNegativeFinite( null )\n false\n > bool = isNonNegativeFinite( PINF )\n false\n\n\nisNonNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeFinite.isObject( value )\n Tests if a value is a number object having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a \n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isObject( 3.0 )\n false\n > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonNegativeNumber, isNumber\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value )\n Tests if a value is a number object having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a \n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isObject( 3.0 )\n false\n > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonNegativeNumber, isNumber","isNonNegativeInteger":"\nisNonNegativeInteger( value )\n Tests if a value is a nonnegative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative integer.\n\n Examples\n --------\n > var bool = isNonNegativeInteger( 5.0 )\n true\n > bool = isNonNegativeInteger( new Number( 5.0 ) )\n true\n > bool = isNonNegativeInteger( 3.14 )\n false\n > bool = isNonNegativeInteger( -5.0 )\n false\n > bool = isNonNegativeInteger( null )\n false\n\n\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNonNegativeNumber, isNumber\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNonNegativeNumber, isNumber","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative integers.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonNegativeNumber":"\nisNonNegativeNumber( value )\n Tests if a value is a nonnegative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative number.\n\n Examples\n --------\n > var bool = isNonNegativeNumber( 5.0 )\n true\n > bool = isNonNegativeNumber( new Number( 5.0 ) )\n true\n > bool = isNonNegativeNumber( 3.14 )\n true\n > bool = isNonNegativeNumber( -5.0 )\n false\n > bool = isNonNegativeNumber( null )\n false\n\n\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNonNegativeFinite, isNonNegativeInteger, isNumber\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNonNegativeFinite, isNonNegativeInteger, isNumber","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonPositiveInteger":"\nisNonPositiveInteger( value )\n Tests if a value is a nonpositive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive integer.\n\n Examples\n --------\n > var bool = isNonPositiveInteger( -5.0 )\n true\n > bool = isNonPositiveInteger( new Number( -5.0 ) )\n true\n > bool = isNonPositiveInteger( 5.0 )\n false\n > bool = isNonPositiveInteger( -3.14 )\n false\n > bool = isNonPositiveInteger( null )\n false\n\n\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive integers.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonPositiveNumber":"\nisNonPositiveNumber( value )\n Tests if a value is a nonpositive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive number.\n\n Examples\n --------\n > var bool = isNonPositiveNumber( -5.0 )\n true\n > bool = isNonPositiveNumber( new Number( -5.0 ) )\n true\n > bool = isNonPositiveNumber( -3.14 )\n true\n > bool = isNonPositiveNumber( 5.0 )\n false\n > bool = isNonPositiveNumber( null )\n false\n\n\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isNumber","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value )\n Tests if a value is a non-symmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a non-symmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 2, 3, 4 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isNonSymmetricMatrix( M )\n true\n > bool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isNonSymmetricMatrix( 3.14 )\n false\n > bool = isNonSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isNull":"\nisNull( value )\n Tests if a value is null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is null.\n\n Examples\n --------\n > var bool = isNull( null )\n true\n > bool = isNull( true )\n false\n\n See Also\n --------\n isUndefined, isUndefinedOrNull\n","isNullArray":"\nisNullArray( value )\n Tests if a value is an array-like object containing only null values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n null values.\n\n Examples\n --------\n > var bool = isNullArray( [ null, null, null ] )\n true\n > bool = isNullArray( [ NaN, 2, null ] )\n false\n\n See Also\n --------\n isArray, isNull\n","isNumber":"\nisNumber( value )\n Tests if a value is a number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number.\n\n Examples\n --------\n > var bool = isNumber( 3.14 )\n true\n > bool = isNumber( new Number( 3.14 ) )\n true\n > bool = isNumber( NaN )\n true\n > bool = isNumber( null )\n false\n\n\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false\n\n\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true\n\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false","isNumber.isObject":"\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true","isNumberArray":"\nisNumberArray( value )\n Tests if a value is an array-like object containing only numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n numbers.\n\n Examples\n --------\n > var bool = isNumberArray( [ 1, 2, 3 ] )\n true\n > bool = isNumberArray( [ '1', 2, 3 ] )\n false\n\n\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false\n\n\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isNumber, isNumericArray\n","isNumberArray.primitives":"\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false","isNumberArray.objects":"\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isNumber, isNumericArray","isNumericArray":"\nisNumericArray( value )\n Tests if a value is a numeric array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a numeric array.\n\n Examples\n --------\n > var bool = isNumericArray( new Int8Array( 10 ) )\n true\n > bool = isNumericArray( [ 1, 2, 3 ] )\n true\n > bool = isNumericArray( [ '1', '2', '3' ] )\n false\n\n See Also\n --------\n isArray, isNumberArray, isTypedArray\n\n","isObject":"\nisObject( value )\n Tests if a value is an object; e.g., `{}`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an object.\n\n Examples\n --------\n > var bool = isObject( {} )\n true\n > bool = isObject( true )\n false\n\n See Also\n --------\n isObjectLike, isPlainObject\n","isObjectArray":"\nisObjectArray( value )\n Tests if a value is an array-like object containing only objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n objects.\n\n Examples\n --------\n > var bool = isObjectArray( [ {}, new Number(3.0) ] )\n true\n > bool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isObject\n","isObjectLike":"\nisObjectLike( value )\n Tests if a value is object-like.\n\n Return values are the same as would be obtained using the built-in `typeof`\n operator except that `null` is not considered an object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is object-like.\n\n Examples\n --------\n > var bool = isObjectLike( {} )\n true\n > bool = isObjectLike( [] )\n true\n > bool = isObjectLike( null )\n false\n\n See Also\n --------\n isObject, isPlainObject\n","isOdd":"\nisOdd( value )\n Tests if a value is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an odd number.\n\n Examples\n --------\n > var bool = isOdd( 5.0 )\n true\n > bool = isOdd( new Number( 5.0 ) )\n true\n > bool = isOdd( 4.0 )\n false\n > bool = isOdd( new Number( 4.0 ) )\n false\n > bool = isOdd( -3.14 )\n false\n > bool = isOdd( null )\n false\n\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false\n\n\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n See Also\n --------\n isEven\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false","isOdd.isObject":"\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n See Also\n --------\n isEven","isoWeeksInYear":"\nisoWeeksInYear( [year] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n\n By default, the function returns the number of ISO weeks in the current year\n (according to local time). To determine the number of ISO weeks for a\n particular year, provide either a year or a `Date` object.\n\n Parameters\n ----------\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Number of ISO weeks in a year.\n\n Examples\n --------\n > var num = isoWeeksInYear()\n \n > num = isoWeeksInYear( 2015 )\n 53\n > num = isoWeeksInYear( 2017 )\n 52\n\n","isPersymmetricMatrix":"\nisPersymmetricMatrix( value )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a persymmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 2, 3, 1 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isPersymmetricMatrix( M )\n true\n > bool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isPersymmetricMatrix( 3.14 )\n false\n > bool = isPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isPlainObject":"\nisPlainObject( value )\n Tests if a value is a plain object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object.\n\n Examples\n --------\n > var bool = isPlainObject( {} )\n true\n > bool = isPlainObject( null )\n false\n\n See Also\n --------\n isObject\n","isPlainObjectArray":"\nisPlainObjectArray( value )\n Tests if a value is an array-like object containing only plain objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n plain objects.\n\n Examples\n --------\n > var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isPlainObjectArray( [ {}, new Number(3.0) ] )\n false\n > bool = isPlainObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPlainObject\n","isPositiveInteger":"\nisPositiveInteger( value )\n Tests if a value is a positive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive integer.\n\n Examples\n --------\n > var bool = isPositiveInteger( 5.0 )\n true\n > bool = isPositiveInteger( new Number( 5.0 ) )\n true\n > bool = isPositiveInteger( 3.14 )\n false\n > bool = isPositiveInteger( -5.0 )\n false\n > bool = isPositiveInteger( null )\n false\n\n\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isPositiveIntegerArray":"\nisPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only positive integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive integers.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isInteger, isPositiveInteger\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isInteger, isPositiveInteger","isPositiveNumber":"\nisPositiveNumber( value )\n Tests if a value is a positive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive number.\n\n Examples\n --------\n > var bool = isPositiveNumber( 5.0 )\n true\n > bool = isPositiveNumber( new Number( 5.0 ) )\n true\n > bool = isPositiveNumber( 3.14 )\n true\n > bool = isPositiveNumber( -5.0 )\n false\n > bool = isPositiveNumber( null )\n false\n\n\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber","isPositiveNumberArray":"\nisPositiveNumberArray( value )\n Tests if a value is an array-like object containing only positive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive numbers.\n\n Examples\n --------\n > var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isNumber, isPositiveNumber\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isNumber, isPositiveNumber","isPositiveZero":"\nisPositiveZero( value )\n Tests if a value is positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero( 0.0 )\n true\n > bool = isPositiveZero( new Number( 0.0 ) )\n true\n > bool = isPositiveZero( -3.14 )\n false\n > bool = isPositiveZero( -0.0 )\n false\n > bool = isPositiveZero( null )\n false\n\n\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false\n\n\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n See Also\n --------\n isNumber, isNegativeZero\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false","isPositiveZero.isObject":"\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n See Also\n --------\n isNumber, isNegativeZero","isPrime":"\nisPrime( value )\n Tests if a value is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a prime number.\n\n Examples\n --------\n > var bool = isPrime( 5.0 )\n true\n > bool = isPrime( new Number( 5.0 ) )\n true\n > bool = isPrime( 3.14 )\n false\n > bool = isPrime( -5.0 )\n false\n > bool = isPrime( null )\n false\n\n\nisPrime.isPrimitive( value )\n Tests if a value is a number primitive which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a prime\n number.\n\n Examples\n --------\n > var bool = isPrime.isPrimitive( 5.0 )\n true\n > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n false\n\n\nisPrime.isObject( value )\n Tests if a value is a number object having a value which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a prime number.\n\n Examples\n --------\n > var bool = isPrime.isObject( 5.0 )\n false\n > bool = isPrime.isObject( new Number( 5.0 ) )\n true\n\n\n See Also\n --------\n isComposite, isInteger, isNumber\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value )\n Tests if a value is a number primitive which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a prime\n number.\n\n Examples\n --------\n > var bool = isPrime.isPrimitive( 5.0 )\n true\n > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n false","isPrime.isObject":"\nisPrime.isObject( value )\n Tests if a value is a number object having a value which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a prime number.\n\n Examples\n --------\n > var bool = isPrime.isObject( 5.0 )\n false\n > bool = isPrime.isObject( new Number( 5.0 ) )\n true\n\n\n See Also\n --------\n isComposite, isInteger, isNumber","isPrimitive":"\nisPrimitive( value )\n Tests if a value is a JavaScript primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a JavaScript primitive.\n\n Examples\n --------\n > var bool = isPrimitive( true )\n true\n > bool = isPrimitive( {} )\n false\n\n See Also\n --------\n isBoxedPrimitive\n","isPrimitiveArray":"\nisPrimitiveArray( value )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n JavaScript primitives.\n\n Examples\n --------\n > var bool = isPrimitiveArray( [ '3', 2, null ] )\n true\n > bool = isPrimitiveArray( [ {}, 2, 1 ] )\n false\n > bool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPrimitive\n","isPRNGLike":"\nisPRNGLike( value )\n Tests if a value is PRNG-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is PRNG-like.\n\n Examples\n --------\n > var bool = isPRNGLike( base.random.randu )\n true\n > bool = isPRNGLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isPRNGLike( 3.14 )\n false\n > bool = isPRNGLike( {} )\n false\n\n","isProbability":"\nisProbability( value )\n Tests if a value is a probability.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a probability.\n\n Examples\n --------\n > var bool = isProbability( 0.5 )\n true\n > bool = isProbability( new Number( 0.5 ) )\n true\n > bool = isProbability( 3.14 )\n false\n > bool = isProbability( -5.0 )\n false\n > bool = isProbability( null )\n false\n\n\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false\n\n\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false","isProbability.isObject":"\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n See Also\n --------\n isNumber","isProbabilityArray":"\nisProbabilityArray( value )\n Tests if a value is an array-like object containing only probabilities.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\n true\n > bool = isProbabilityArray( [ 0.8, 1.2 ] )\n false\n > bool = isProbabilityArray( [ 0.8, '0.2' ] )\n false\n\n\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false\n\n\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n See Also\n --------\n isArray, isProbability\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false","isProbabilityArray.objects":"\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n See Also\n --------\n isArray, isProbability","isPropertyKey":"\nisPropertyKey( value )\n Tests whether a value is a property key.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether value is a property key.\n\n Examples\n --------\n > var out = isPropertyKey( 'foo' )\n true\n > out = isPropertyKey( 1 )\n true\n > out = isPropertyKey( true )\n false\n\n See Also\n --------\n isString, isSymbol, isNonNegativeInteger, hasOwnProp, hasProp","isPrototypeOf":"\nisPrototypeOf( value, proto )\n Tests if an object's prototype chain contains a provided prototype.\n\n The function returns `false` if provided a primitive value.\n\n This function is generally more robust than the `instanceof` operator (e.g.,\n where inheritance is performed without using constructors).\n\n Parameters\n ----------\n value: any\n Input value.\n\n proto: Object|Function\n Prototype.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a provided prototype exists in a prototype chain.\n\n Examples\n --------\n > function Foo() { return this; };\n > function Bar() { return this; };\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var bool = isPrototypeOf( bar, Foo.prototype )\n true\n\n See Also\n --------\n getPrototypeOf\n","isRangeError":"\nisRangeError( value )\n Tests if a value is a RangeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a RangeError (or a descendant) object,\n false positives may occur due to the fact that the RangeError constructor\n inherits from Error and has no internal class of its own. Hence, RangeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a RangeError object.\n\n Examples\n --------\n > var bool = isRangeError( new RangeError( 'beep' ) )\n true\n > bool = isRangeError( {} )\n false\n\n See Also\n --------\n isError\n","isReadableProperty":"\nisReadableProperty( value, property )\n Tests if an object's own property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadableProperty( obj, 'boop' )\n true\n > bool = isReadableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isReadablePropertyIn, isWritableProperty\n","isReadablePropertyIn":"\nisReadablePropertyIn( value, property )\n Tests if an object's own or inherited property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadablePropertyIn( obj, 'boop' )\n true\n > bool = isReadablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isReadableProperty, isWritablePropertyIn\n","isReadOnlyProperty":"\nisReadOnlyProperty( value, property )\n Tests if an object's own property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is read-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyProperty( obj, 'boop' )\n true\n > bool = isReadOnlyProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadableProperty, isWritableProperty\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is read-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyPropertyIn( obj, 'boop' )\n true\n > bool = isReadOnlyPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isReadWriteProperty":"\nisReadWriteProperty( value, property )\n Tests if an object's own property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWriteProperty( obj, 'boop' )\n true\n > bool = isReadWriteProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadableProperty, isWritableProperty\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value, property )\n Tests if an object's own or inherited property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable\n and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWritePropertyIn( obj, 'boop' )\n true\n > bool = isReadWritePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadablePropertyIn, isWritablePropertyIn\n","isReferenceError":"\nisReferenceError( value )\n Tests if a value is a ReferenceError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a ReferenceError (or a descendant)\n object, false positives may occur due to the fact that the ReferenceError\n constructor inherits from Error and has no internal class of its own.\n Hence, ReferenceError impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a ReferenceError object.\n\n Examples\n --------\n > var bool = isReferenceError( new ReferenceError( 'beep' ) )\n true\n > bool = isReferenceError( {} )\n false\n\n See Also\n --------\n isError\n","isRegExp":"\nisRegExp( value )\n Tests if a value is a regular expression.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression.\n\n Examples\n --------\n > var bool = isRegExp( /\\.+/ )\n true\n > bool = isRegExp( {} )\n false\n\n","isRegExpString":"\nisRegExpString( value )\n Tests if a value is a regular expression string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression string.\n\n Examples\n --------\n > var bool = isRegExpString( '/beep/' )\n true\n > bool = isRegExpString( 'beep' )\n false\n > bool = isRegExpString( '' )\n false\n > bool = isRegExpString( null )\n false\n\n See Also\n --------\n isRegExp\n","isRelativePath":"\nisRelativePath( value )\n Tests if a value is a relative path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a relative path.\n\n Examples\n --------\n // Windows environments:\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n\n // POSIX environments:\n > bool = isRelativePath( './foo/bar/baz' )\n true\n\n\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false\n\n\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isAbsolutePath\n","isRelativePath.posix":"\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false","isRelativePath.win32":"\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isAbsolutePath","isSafeInteger":"\nisSafeInteger( value )\n Tests if a value is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a safe integer.\n\n Examples\n --------\n > var bool = isSafeInteger( 5.0 )\n true\n > bool = isSafeInteger( new Number( 5.0 ) )\n true\n > bool = isSafeInteger( 2.0e200 )\n false\n > bool = isSafeInteger( -3.14 )\n false\n > bool = isSafeInteger( null )\n false\n\n\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isInteger, isNumber\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false","isSafeInteger.isObject":"\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isInteger, isNumber","isSafeIntegerArray":"\nisSafeIntegerArray( value )\n Tests if a value is an array-like object containing only safe integers.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing\n only safe integers.\n\n Examples\n --------\n > var arr = [ -3.0, new Number(0.0), 2.0 ];\n > var bool = isSafeIntegerArray( arr )\n true\n > arr = [ -3.0, '3.0' ];\n > bool = isSafeIntegerArray( arr )\n false\n\n\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false\n\n\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isSafeInteger\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isSafeInteger","isSameArray":"\nisSameArray( v1, v2 )\n Tests if two arguments are both generic arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0 ];\n > var y = [ 1.0, 2.0, 3.0 ];\n > var bool = isSameArray( x, y )\n true\n\n > x = [ NaN, NaN, NaN ];\n > y = [ NaN, NaN, NaN ];\n > bool = isSameArray( x, y )\n true\n\n See Also\n --------\n isArray, isSameValue\n","isSameComplex64":"\nisSameComplex64( v1, v2 )\n Tests if two arguments are both single-precision complex floating-point\n numbers and have the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex64( 1.0, 2.0 );\n > var y = new Complex64( 1.0, 2.0 );\n > var bool = isSameComplex64( x, y )\n true\n\n > x = new Complex64( NaN, NaN );\n > y = new Complex64( NaN, NaN );\n > bool = isSameComplex64( x, y )\n true\n\n See Also\n --------\n isComplex64, isSameComplex128, isSameValue\n","isSameComplex64Array":"\nisSameComplex64Array( v1, v2 )\n Tests if two arguments are both Complex64Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var bool = isSameComplex64Array( x, y )\n true\n\n > x = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n > y = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n > bool = isSameComplex64Array( x, y )\n true\n\n See Also\n --------\n isComplex64Array, isSameComplex128Array, isSameFloat32Array, isSameValue\n","isSameComplex128":"\nisSameComplex128( v1, v2 )\n Tests if two arguments are both double-precision complex floating-point\n numbers and have the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex128( 1.0, 2.0 );\n > var y = new Complex128( 1.0, 2.0 );\n > var bool = isSameComplex128( x, y )\n true\n\n > x = new Complex128( NaN, NaN );\n > y = new Complex128( NaN, NaN );\n > bool = isSameComplex128( x, y )\n true\n\n See Also\n --------\n isComplex128, isSameComplex64, isSameValue\n","isSameComplex128Array":"\nisSameComplex128Array( v1, v2 )\n Tests if two arguments are both Complex128Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var bool = isSameComplex128Array( x, y )\n true\n\n > x = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n > y = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n > bool = isSameComplex128Array( x, y )\n true\n\n See Also\n --------\n isComplex128Array, isSameComplex64Array, isSameFloat64Array, isSameValue\n","isSameFloat32Array":"\nisSameFloat32Array( v1, v2 )\n Tests if two arguments are both Float32Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > var bool = isSameFloat32Array( x, y )\n true\n\n > x = new Float32Array( [ NaN, NaN, NaN ] );\n > y = new Float32Array( [ NaN, NaN, NaN ] );\n > bool = isSameFloat32Array( x, y )\n true\n\n See Also\n --------\n isSameFloat64Array, isSameValue\n","isSameFloat64Array":"\nisSameFloat64Array( v1, v2 )\n Tests if two arguments are both Float64Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > var bool = isSameFloat64Array( x, y )\n true\n\n > x = new Float64Array( [ NaN, NaN, NaN ] );\n > y = new Float64Array( [ NaN, NaN, NaN ] );\n > bool = isSameFloat64Array( x, y )\n true\n\n See Also\n --------\n isSameFloat32Array, isSameValue\n","isSameNativeClass":"\nisSameNativeClass( a, b )\n Tests if two arguments have the same native class.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments have the same native class.\n\n Examples\n --------\n > var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\n true\n > bool = isSameNativeClass( 'beep', 'boop' )\n true\n > bool = isSameNativeClass( {}, [] )\n false\n\n See Also\n --------\n isSameType, isSameValue, isStrictEqual\n","isSameType":"\nisSameType( a, b )\n Tests if two arguments have the same type.\n\n The function uses the `typeof` operator to test for the same type.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments have the same type.\n\n Examples\n --------\n > var bool = isSameType( true, true )\n true\n > bool = isSameType( {}, [] )\n true\n > bool = isSameType( 3.12, -3.12 )\n true\n > bool = isSameType( 0.0, '0.0' )\n false\n\n See Also\n --------\n isSameNativeClass, isSameValue, isStrictEqual\n","isSameValue":"\nisSameValue( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValue( true, true )\n true\n > bool = isSameValue( {}, {} )\n false\n > bool = isSameValue( -0.0, -0.0 )\n true\n > bool = isSameValue( -0.0, 0.0 )\n false\n > bool = isSameValue( NaN, NaN )\n true\n\n See Also\n --------\n isSameValueZero, isStrictEqual\n","isSameValueZero":"\nisSameValueZero( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValueZero( true, true )\n true\n > bool = isSameValueZero( {}, {} )\n false\n > bool = isSameValueZero( -0.0, -0.0 )\n true\n > bool = isSameValueZero( -0.0, 0.0 )\n true\n > bool = isSameValueZero( NaN, NaN )\n true\n\n See Also\n --------\n isSameValue, isStrictEqual\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value )\n Tests if a value is a SharedArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SharedArrayBuffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffer...\n > var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\n true\n > bool = isSharedArrayBuffer( [] )\n false\n\n See Also\n --------\n isArrayBuffer, isTypedArray\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value )\n Tests if a value is a skew-centrosymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-centrosymmetric matrix.\n\n Examples\n --------\n > var buf = [ 2, 1, -1, -2 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewCentrosymmetricMatrix( M )\n true\n > bool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewCentrosymmetricMatrix( 3.14 )\n false\n > bool = isSkewCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isCentrosymmetricMatrix, isMatrixLike, isSkewSymmetricMatrix\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value )\n Tests if a value is a skew-persymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-persymmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 0, 0, -1 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewPersymmetricMatrix( M )\n true\n > bool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewPersymmetricMatrix( 3.14 )\n false\n > bool = isSkewPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isPersymmetricMatrix, isSkewSymmetricMatrix\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-symmetric matrix.\n\n Examples\n --------\n > var buf = [ 0, -1, 1, 0 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewSymmetricMatrix( M )\n true\n > bool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewSymmetricMatrix( 3.14 )\n false\n > bool = isSkewSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSkewSymmetricMatrix, isSquareMatrix\n","isSlice":"\nisSlice( value )\n Tests if a value is a Slice object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a Slice object.\n\n Examples\n --------\n > var bool = isSlice( new Slice( 10 ) )\n true\n > bool = isSlice( 3.14 )\n false\n > bool = isSlice( {} )\n false\n\n See Also\n --------\n isMultiSlice, Slice\n","isSquareMatrix":"\nisSquareMatrix( value )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object having equal dimensions.\n\n Examples\n --------\n > var buf = [ 0, 0, 0, 0 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSquareMatrix( M )\n true\n > bool = isSquareMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSquareMatrix( 3.14 )\n false\n > bool = isSquareMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSymmetricMatrix\n","isSquareNumber":"\nisSquareNumber( value )\n Tests if a value is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber( 4.0 )\n true\n > bool = isSquareNumber( new Number( 4.0 ) )\n true\n > bool = isSquareNumber( 3.14 )\n false\n > bool = isSquareNumber( -5.0 )\n false\n > bool = isSquareNumber( null )\n false\n\n\nisSquareNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isPrimitive( 4.0 )\n true\n > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n false\n\n\nisSquareNumber.isObject( value )\n Tests if a value is a number object having a value which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isObject( 4.0 )\n false\n > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isCubeNumber, isInteger, isNumber, isTriangularNumber\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isPrimitive( 4.0 )\n true\n > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n false","isSquareNumber.isObject":"\nisSquareNumber.isObject( value )\n Tests if a value is a number object having a value which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isObject( 4.0 )\n false\n > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isCubeNumber, isInteger, isNumber, isTriangularNumber","isSquareTriangularNumber":"\nisSquareTriangularNumber( value )\n Tests if a value is a square triangular number.\n\n Return values are not reliable for numbers greater than 1125899906842624.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber( 36.0 )\n true\n > bool = isSquareTriangularNumber( new Number( 36.0 ) )\n true\n > bool = isSquareTriangularNumber( 3.14 )\n false\n > bool = isSquareTriangularNumber( -5.0 )\n false\n > bool = isSquareTriangularNumber( null )\n false\n\n\nisSquareTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false\n\n\nisSquareTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a square\n triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isObject( 36.0 )\n false\n > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isTriangularNumber\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a square\n triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isObject( 36.0 )\n false\n > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isTriangularNumber","isStrictEqual":"\nisStrictEqual( a, b )\n Tests if two arguments are strictly equal.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are strictly equal.\n\n Examples\n --------\n > var bool = isStrictEqual( true, true )\n true\n > bool = isStrictEqual( {}, {} )\n false\n > bool = isStrictEqual( -0.0, -0.0 )\n true\n > bool = isStrictEqual( -0.0, 0.0 )\n false\n > bool = isStrictEqual( NaN, NaN )\n false\n\n See Also\n --------\n isSameValue\n","isString":"\nisString( value )\n Tests if a value is a string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string.\n\n Examples\n --------\n > var bool = isString( 'beep' )\n true\n > bool = isString( new String( 'beep' ) )\n true\n > bool = isString( 5 )\n false\n\n\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false\n\n\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false\n\n","isString.isPrimitive":"\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false","isString.isObject":"\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false","isStringArray":"\nisStringArray( value )\n Tests if a value is an array of strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of strings.\n\n Examples\n --------\n > var bool = isStringArray( [ 'abc', 'def' ] )\n true\n > bool = isStringArray( [ 'abc', 123 ] )\n false\n\n\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false\n\n\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isString\n","isStringArray.primitives":"\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false","isStringArray.objects":"\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isString","isSymbol":"\nisSymbol( value )\n Tests if a value is a symbol.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symbol.\n\n Examples\n --------\n > var bool = isSymbol( Symbol( 'beep' ) )\n true\n > bool = isSymbol( Object( Symbol( 'beep' ) ) )\n true\n > bool = isSymbol( {} )\n false\n > bool = isSymbol( null )\n false\n > bool = isSymbol( true )\n false\n\n","isSymbolArray":"\nisSymbolArray( value )\n Tests if a value is an array-like object containing only symbols.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only symbols.\n\n Examples\n --------\n > var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\n true\n > bool = isSymbolArray( Symbol( 'beep' ) )\n false\n > bool = isSymbolArray( [] )\n false\n > bool = isSymbolArray( {} )\n false\n > bool = isSymbolArray( null )\n false\n > bool = isSymbolArray( true )\n false\n\n\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false\n\n\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n See Also\n --------\n isArray, isSymbol\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false","isSymbolArray.objects":"\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n See Also\n --------\n isArray, isSymbol","isSymmetricMatrix":"\nisSymmetricMatrix( value )\n Tests if a value is a square matrix which equals its transpose.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symmetric matrix.\n\n Examples\n --------\n > var buf = [ 0, 1, 1, 2 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSymmetricMatrix( M )\n true\n > bool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSymmetricMatrix( 3.14 )\n false\n > bool = isSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isNonSymmetricMatrix, isSquareMatrix\n","isSyntaxError":"\nisSyntaxError( value )\n Tests if a value is a SyntaxError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a SyntaxError (or a descendant) object,\n false positives may occur due to the fact that the SyntaxError constructor\n inherits from Error and has no internal class of its own. Hence, SyntaxError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SyntaxError object.\n\n Examples\n --------\n > var bool = isSyntaxError( new SyntaxError( 'beep' ) )\n true\n > bool = isSyntaxError( {} )\n false\n\n See Also\n --------\n isError\n","isTriangularNumber":"\nisTriangularNumber( value )\n Tests if a value is a triangular number.\n\n Return values are not reliable for numbers greater than 1125899906842624.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber( 36.0 )\n true\n > bool = isTriangularNumber( new Number( 36.0 ) )\n true\n > bool = isTriangularNumber( 3.14 )\n false\n > bool = isTriangularNumber( -5.0 )\n false\n > bool = isTriangularNumber( null )\n false\n\n\nisTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false\n\n\nisTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a triangular\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isObject( 36.0 )\n false\n > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isSquareTriangularNumber\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a triangular\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isObject( 36.0 )\n false\n > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isSquareTriangularNumber","isTruthy":"\nisTruthy( value )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is truthy.\n\n Examples\n --------\n > var bool = isTruthy( true )\n true\n > bool = isTruthy( {} )\n true\n > bool = isTruthy( [] )\n true\n > bool = isTruthy( false )\n false\n > bool = isTruthy( '' )\n false\n > bool = isTruthy( 0 )\n false\n > bool = isTruthy( null )\n false\n > bool = isTruthy( void 0 )\n false\n > bool = isTruthy( NaN )\n false\n\n See Also\n --------\n isFalsy\n","isTruthyArray":"\nisTruthyArray( value )\n Tests if a value is an array-like object containing only truthy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only truthy values.\n\n Examples\n --------\n > var bool = isTruthyArray( [ {}, [] ] )\n true\n > bool = isTruthyArray( [ null, '' ] )\n false\n > bool = isTruthyArray( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n","isTypedArray":"\nisTypedArray( value )\n Tests if a value is a typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a typed array.\n\n Examples\n --------\n > var bool = isTypedArray( new Int8Array( 10 ) )\n true\n\n See Also\n --------\n isArray, isTypedArrayLike\n","isTypedArrayLength":"\nisTypedArrayLength( value )\n Tests if a value is a valid typed array length.\n\n A valid length property for a typed array instance is any integer value on\n the interval [0, 2^53-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a valid typed array length.\n\n Examples\n --------\n > var bool = isTypedArrayLength( 5 )\n true\n > bool = isTypedArrayLength( 2.0e200 )\n false\n > bool = isTypedArrayLength( -3.14 )\n false\n > bool = isTypedArrayLength( null )\n false\n\n See Also\n --------\n isArrayLength, isTypedArray\n","isTypedArrayLike":"\nisTypedArrayLike( value )\n Tests if a value is typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is typed-array-like.\n\n Examples\n --------\n > var bool = isTypedArrayLike( new Int16Array() )\n true\n > bool = isTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4\n ... })\n true\n\n See Also\n --------\n isTypedArray\n","isTypeError":"\nisTypeError( value )\n Tests if a value is a TypeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a TypeError (or a descendant) object,\n false positives may occur due to the fact that the TypeError constructor\n inherits from Error and has no internal class of its own. Hence, TypeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a TypeError object.\n\n Examples\n --------\n > var bool = isTypeError( new TypeError( 'beep' ) )\n true\n > bool = isTypeError( {} )\n false\n\n See Also\n --------\n isError\n","isUint8Array":"\nisUint8Array( value )\n Tests if a value is a Uint8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8Array.\n\n Examples\n --------\n > var bool = isUint8Array( new Uint8Array( 10 ) )\n true\n > bool = isUint8Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint32Array\n","isUint8ClampedArray":"\nisUint8ClampedArray( value )\n Tests if a value is a Uint8ClampedArray.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8ClampedArray.\n\n Examples\n --------\n > var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\n true\n > bool = isUint8ClampedArray( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint8Array\n","isUint16Array":"\nisUint16Array( value )\n Tests if a value is a Uint16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint16Array.\n\n Examples\n --------\n > var bool = isUint16Array( new Uint16Array( 10 ) )\n true\n > bool = isUint16Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint32Array, isUint8Array\n","isUint32Array":"\nisUint32Array( value )\n Tests if a value is a Uint32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint32Array.\n\n Examples\n --------\n > var bool = isUint32Array( new Uint32Array( 10 ) )\n true\n > bool = isUint32Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint8Array\n","isUNCPath":"\nisUNCPath( value )\n Tests if a value is a UNC path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a UNC path.\n\n Examples\n --------\n > var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isUNCPath( '/foo/bar/baz' )\n false\n\n","isUndefined":"\nisUndefined( value )\n Tests if a value is undefined.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined.\n\n Examples\n --------\n > var bool = isUndefined( void 0 )\n true\n > bool = isUndefined( null )\n false\n\n See Also\n --------\n isNull, isUndefinedOrNull\n","isUndefinedOrNull":"\nisUndefinedOrNull( value )\n Tests if a value is undefined or null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined or null.\n\n Examples\n --------\n > var bool = isUndefinedOrNull( void 0 )\n true\n > bool = isUndefinedOrNull( null )\n true\n > bool = isUndefinedOrNull( false )\n false\n\n See Also\n --------\n isNull, isUndefined\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value )\n Tests if a value is an array of probabilities that sum to one.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of probabilities that sum\n to one.\n\n Examples\n --------\n > var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\n true\n > bool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\n true\n > bool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\n false\n > bool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n false\n\n See Also\n --------\n isProbability, isProbabilityArray\n","isUppercase":"\nisUppercase( value )\n Tests if a value is an uppercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an uppercase string.\n\n Examples\n --------\n > var bool = isUppercase( 'HELLO' )\n true\n > bool = isUppercase( 'World' )\n false\n\n See Also\n --------\n isLowercase, isString\n","isURI":"\nisURI( value )\n Tests if a value is a URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URI.\n\n Examples\n --------\n > var bool = isURI( 'http://google.com' )\n true\n > bool = isURI( 'http://localhost/' )\n true\n > bool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\n true\n > bool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\n true\n\n // No scheme:\n > bool = isURI( '' )\n false\n > bool = isURI( 'foo@bar' )\n false\n > bool = isURI( '://foo/' )\n false\n\n // Illegal characters:\n > bool = isURI( 'http://' )\n false\n\n // Invalid path:\n > bool = isURI( 'http:////foo.html' )\n false\n\n // Incomplete hex escapes:\n > bool = isURI( 'http://example.w3.org/%a' )\n false\n\n","isURIError":"\nisURIError( value )\n Tests if a value is a URIError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a URIError (or a descendant) object,\n false positives may occur due to the fact that the URIError constructor\n inherits from Error and has no internal class of its own. Hence, URIError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URIError object.\n\n Examples\n --------\n > var bool = isURIError( new URIError( 'beep' ) )\n true\n > bool = isURIError( {} )\n false\n\n See Also\n --------\n isError\n","isVectorLike":"\nisVectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isVectorLike( M )\n true\n > bool = isVectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isVectorLike( 3.14 )\n false\n > bool = isVectorLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isndarrayLike, isTypedArrayLike\n","isWhitespace":"\nisWhitespace( str )\n Tests whether a string contains only white space characters.\n\n A white space character is defined as one of the 25 characters defined as a\n white space (\"WSpace=Y\",\"WS\") character in the Unicode 9.0 character\n database, as well as one related white space character without the Unicode\n character property \"WSpace=Y\" (zero width non-breaking space which was\n deprecated as of Unicode 3.2).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only white space\n characters.\n\n Examples\n --------\n > var bool = isWhitespace( ' ' )\n true\n > bool = isWhitespace( 'abcdef' )\n false\n > bool = isWhitespace( '' )\n false\n\n See Also\n --------\n reWhitespace\n","isWritableProperty":"\nisWritableProperty( value, property )\n Tests if an object's own property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritableProperty( obj, 'boop' )\n true\n > bool = isWritableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadableProperty, isReadWriteProperty, isWritablePropertyIn, isWriteOnlyProperty\n","isWritablePropertyIn":"\nisWritablePropertyIn( value, property )\n Tests if an object's own or inherited property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritablePropertyIn( obj, 'boop' )\n true\n > bool = isWritablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadablePropertyIn, isReadWritePropertyIn, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value, property )\n Tests if an object's own property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is write-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyProperty( obj, 'boop' )\n false\n > bool = isWriteOnlyProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is write-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyPropertyIn( obj, 'boop' )\n false\n > bool = isWriteOnlyPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isWritablePropertyIn, isWriteOnlyProperty\n","iterAbs":"\niterAbs( iterator )\n Returns an iterator which iteratively computes the absolute value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAbs( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.abs, iterAbs2\n","iterAbs2":"\niterAbs2( iterator )\n Returns an iterator which iteratively computes the squared absolute value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAbs2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.abs2, iterAbs\n","iterAcos":"\niterAcos( iterator )\n Returns an iterator which iteratively computes the arccosine.\n\n The domain of arccosine is restricted to [-1,1]. If an iterated value is\n outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acos, iterAcosh, iterAsin, iterAtan\n","iterAcosh":"\niterAcosh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arccosine.\n\n The domain of the hyperbolic arccosine is restricted to [1,+infinity). If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acosh, iterAcos, iterAsinh, iterAtanh\n","iterAcot":"\niterAcot( iterator )\n Returns an iterator which iteratively computes the inverse cotangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acot, iterAcos, iterAcoth, iterAsin, iterAtan\n","iterAcoth":"\niterAcoth( iterator )\n Returns an iterator which iteratively computes the inverse hyperbolic\n cotangent.\n\n The domain of the inverse hyperbolic cotangent is restricted to (-inf,-1]\n and [1,inf). If an iterated value is outside of the domain, the returned\n iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acoth, iterAcosh, iterAcot, iterAsinh, iterAtanh\n","iterAcovercos":"\niterAcovercos( iterator )\n Returns an iterator which iteratively computes the inverse coversed cosine.\n\n The domain of inverse coversed cosine is restricted to [-2,0]. If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcovercos( random.iterators.uniform( -2.0, 0.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acovercos, iterAcoversin, iterAvercos, iterCovercos, iterVercos\n","iterAcoversin":"\niterAcoversin( iterator )\n Returns an iterator which iteratively computes the inverse coversed sine.\n\n The domain of inverse coversed sine is restricted to [0,2]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acoversin, iterAcovercos, iterAversin, iterCoversin, iterVersin\n","iterAdd":"\niterAdd( iter0, ...iterator )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to add.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterAdd( it1, it2 );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide, iterMultiply, iterSubtract\n","iterAdvance":"\niterAdvance( iterator[, n] )\n Advances an entire iterator.\n\n The function *eagerly* advances an input iterator `n` iterations or until\n the input iterator finishes, whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Input iterator to advance.\n\n n: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Input iterator.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var it = iterAdvance( arr, 4 );\n > var v = it.next().value\n 1\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterHead, iterSlice\n","iterAhavercos":"\niterAhavercos( iterator )\n Returns an iterator which iteratively computes the inverse half-value versed\n cosine.\n\n The domain of inverse half-value versed cosine is restricted to [0,1]. If\n an iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ahavercos, iterAhaversin, iterHavercos, iterVercos\n","iterAhaversin":"\niterAhaversin( iterator )\n Returns an iterator which iteratively computes the inverse half-value versed\n sine.\n\n The domain of inverse half-value versed sine is restricted to [-2,0]. If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ahaversin, iterAhavercos, iterHaversin, iterVersin\n","iterAny":"\niterAny( iterator )\n Tests whether at least one iterated value is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a value is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterAny( arr )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNone, iterSome\n","iterAnyBy":"\niterAnyBy( iterator, predicate[, thisArg ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for any iterated value. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > function fcn( v ) { return ( v === 1 ); };\n > var bool = iterAnyBy( arr, fcn )\n true\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNoneBy, iterSomeBy\n","iterAsin":"\niterAsin( iterator )\n Returns an iterator which iteratively computes the arcsine.\n\n The domain of arcsine is restricted to [-1,1]. If an iterated value is\n outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.asin, iterAcos, iterAsinh, iterAtan\n","iterAsinh":"\niterAsinh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arcsine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.asinh, iterAcosh, iterAsin, iterAtanh\n","iterAtan":"\niterAtan( iterator )\n Returns an iterator which iteratively computes the arctangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atan, iterAcos, iterAsin, iterAtanh\n","iterAtan2":"\niterAtan2( y, x )\n Returns an iterator which iteratively computes the angle in the plane (in\n radians) between the positive x-axis and the ray from (0,0) to the point\n (x,y).\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n y: Object|number\n Input iterator.\n\n x: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( -2.0, 2.0 );\n > var y = random.iterators.uniform( -2.0, 2.0 );\n > var it = iterAtan2( y, x );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atan2, iterAtan\n","iterAtanh":"\niterAtanh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arctangent.\n\n The domain of hyperbolic arctangent is restricted to [-1,1]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atanh, iterAcosh, iterAsinh, iterAtan\n","iterator2array":"\niterator2array( iterator[, out][, mapFcn[, thisArg]] )\n Creates (or fills) an array from an iterator.\n\n When invoked, an input function is provided two arguments:\n\n - value: iterated value\n - index: iterated value index (zero-based)\n\n If provided an output array, the function fills the output array with\n iterated values.\n\n Iteration stops when an output array is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n out: ArrayLikeObject (optional)\n Output array-like object.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var opts = { 'iter': 10 };\n > var arr = iterator2array( random.iterators.randu( opts ) )\n\n See Also\n --------\n array2iterator, iterator2arrayview\n","iterator2arrayview":"\niterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view with values returned from an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: destination index (zero-based)\n - n: iteration index (zero-based)\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayview( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iterator, iterator2arrayviewRight\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: destination index (zero-based)\n - n: iteration index (zero-based)\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayviewRight( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iteratorRight, iterator2arrayview\n","iteratorStream":"\niteratorStream( iterator[, options] )\n Creates a readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n In binary mode, if an iterator generates `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n explicitly map `undefined` values to a different value by wrapping the\n provided iterator with another iterator.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream( it );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );\n\n\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n","iteratorStream.factory":"\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream","IteratorSymbol":"\nIteratorSymbol\n Iterator symbol.\n\n This symbol specifies the default iterator for an object.\n\n The symbol is only supported in ES6/ES2015+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = IteratorSymbol\n\n See Also\n --------\n Symbol\n","iterAvercos":"\niterAvercos( iterator )\n Returns an iterator which iteratively computes the inverse versed cosine.\n\n The domain of inverse versed cosine is restricted to [-2,0]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.avercos, iterAversin, iterVersin\n","iterAversin":"\niterAversin( iterator )\n Returns an iterator which iteratively computes the inverse versed sine.\n\n The domain of inverse versed sine is restricted to [0,2]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.aversin, iterAvercos, iterVercos\n","iterawgn":"\niterawgn( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating pseudorandom numbers\n drawn from a standard normal distribution. If provided, the `state` and\n `seed` options are ignored. In order to seed the returned iterator, one\n must seed the provided `prng` (assuming the provided `prng` is\n seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function|null\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawgn( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawln, iterawun\n","iterawln":"\niterawln( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawln( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawun\n","iterawun":"\niterawun( iterator, sigma[, options] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawun( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawln\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettPulse, iterHannPulse, iterPulse, iterTriangleWave\n","iterBartlettPulse":"\niterBartlettPulse( [options] )\n Returns an iterator which generates a Bartlett pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterTriangleWave\n","iterBesselj0":"\niterBesselj0( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBesselj0( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.besselj0, iterBesselj1, iterBessely0, iterBessely1\n","iterBesselj1":"\niterBesselj1( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order one.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBesselj1( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.besselj1, iterBesselj0, iterBessely0, iterBessely1\n","iterBessely0":"\niterBessely0( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBessely0( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.bessely0, iterBesselj0, iterBesselj1, iterBessely1\n","iterBessely1":"\niterBessely1( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order one.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBessely1( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.bessely1, iterBesselj0, iterBesselj1, iterBessely0\n","iterBeta":"\niterBeta( x, y )\n Returns an iterator which iteratively evaluates the beta function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n y: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( 0.0, 2.0 );\n > var it = iterBeta( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.beta, iterBetaln\n","iterBetaln":"\niterBetaln( x, y )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n beta function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n y: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( 0.0, 2.0 );\n > var it = iterBetaln( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.betaln, iterBeta\n","iterBinet":"\niterBinet( iterator )\n Returns an iterator which iteratively evaluates Binet's formula extended to\n real numbers.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBinet( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.binet\n","iterCbrt":"\niterCbrt( iterator )\n Returns an iterator which iteratively computes the cube root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCbrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cbrt, iterPow, iterSqrt\n","iterCeil":"\niterCeil( iterator )\n Returns an iterator which rounds each iterated value toward positive\n infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil, iterFloor, iterRound\n","iterCeil2":"\niterCeil2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward positive infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil2, iterCeil, iterCeil10, iterFloor2, iterRound2\n","iterCeil10":"\niterCeil10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward positive infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil10, iterCeil, iterCeil2, iterFloor10, iterRound10\n","iterCompositesSeq":"\niterCompositesSeq( [options] )\n Returns an iterator which generates a sequence of composite numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCompositesSeq();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n > v = it.next().value\n 8\n\n See Also\n --------\n iterIntegersSeq, iterPositiveIntegersSeq, iterPrimesSeq\n","iterConcat":"\niterConcat( iter0, ...iterator )\n Returns an iterator which iterates over the values of two or more iterators.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to concatenate.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = array2iterator( [ 3, 4 ] );\n > var it = iterConcat( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n","iterConstant":"\niterConstant( value[, options] )\n Returns an iterator which always returns the same value.\n\n When provided an object reference, the returned iterator always returns the\n same reference.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n value: any\n Value to return.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterConstant( 3.14 );\n > var v = it.next().value\n 3.14\n > v = it.next().value\n 3.14\n\n See Also\n --------\n constantFunction\n","iterContinuedFraction":"\niterContinuedFraction( iterator[, options] )\n Evaluates the terms of a continued fraction.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Maximum number of iterations. Default: 1e308.\n\n options.tol: number (optional)\n Tolerance at which to terminate further evaluation of the continued\n fraction. Default: floating-point epsilon.\n\n Returns\n -------\n out: number|null\n Result.\n\n Examples\n --------\n > var terms = array2iterator( [ 3, 4, 12, 4 ] );\n > var v = iterContinuedFraction( terms )\n ~3.245\n\n See Also\n --------\n iterContinuedFractionSeq\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x[, options] )\n Returns an iterator which generates a list of all continued fraction terms\n which can be obtained given the precision of `x`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x: number\n Input value.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Maximum number of iterations. Default: 1e308.\n\n options.tol: number (optional)\n Tolerance at which to terminate further evaluation of the continued\n fraction. Default: floating-point epsilon.\n\n options.returns: string (optional)\n Specifies the type of result to return. Must be one of\n\n - terms: return continued fraction terms\n - convergents: return continued fraction convergents\n - *: return both continued fraction terms and their associated\n convergents as a two-element array.\n\n Default: 'terms'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n // Return continued fraction terms...\n > var it = iterContinuedFractionSeq( 3.245 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 4\n > v = it.next().value\n 12\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n // Return continued fraction convergents...\n > it = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\n > v = it.next().value\n 3.0\n > v = it.next().value\n 3.25\n > v = it.next().value\n ~3.2449\n > v = it.next().value\n 3.245\n > bool = it.next().done\n true\n\n See Also\n --------\n iterContinuedFraction\n","iterCos":"\niterCos( iterator )\n Returns an iterator which iteratively computes the cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCos( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cos, iterCospi, iterSin, iterTan\n","iterCosh":"\niterCosh( iterator )\n Returns an iterator which iteratively computes the hyperbolic cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterCosh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.cosh, iterCos, iterSinh, iterTanh\n","iterCosineWave":"\niterCosineWave( [options] )\n Returns an iterator which generates a cosine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a cosine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCosineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterCosm1":"\niterCosm1( iterator )\n Returns an iterator which iteratively computes `cos(x) - 1`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCosm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.cosm1, iterCos\n","iterCospi":"\niterCospi( iterator )\n Returns an iterator which computes the cosine of each iterated value times\n π.\n\n Computes cos(πx) more accurately than cos(pi*x), especially for large x.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCospi( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cospi, iterCos\n","iterCounter":"\niterCounter( iterator )\n Returns an iterator which iteratively computes the number of iterated\n values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCounter( random.iterators.randu() );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterLength\n","iterCovercos":"\niterCovercos( iterator )\n Returns an iterator which iteratively computes the coversed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCovercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.covercos, iterCoversin, iterVercos\n","iterCoversin":"\niterCoversin( iterator )\n Returns an iterator which iteratively computes the coversed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCoversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.coversin, iterCovercos, iterVersin\n","iterCubesSeq":"\niterCubesSeq( [options] )\n Returns an iterator which generates a sequence of cubes.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 208063.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCubesSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 8\n\n See Also\n --------\n iterFourthPowersSeq, iterSquaresSeq\n","itercugmean":"\nitercugmean( iterator )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n\n If provided a negative value, the iterated value is `NaN` for all future\n invocations.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercugmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~3.16\n > v = it.next().value\n ~3.11\n > v = it.next().value\n ~3.50\n\n See Also\n --------\n itercuhmean, itercumean\n","itercuhmean":"\nitercuhmean( iterator )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercuhmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~2.86\n > v = it.next().value\n ~2.90\n > v = it.next().value\n ~3.24\n\n See Also\n --------\n itercugmean, itercumean\n","itercumax":"\nitercumax( iterator )\n Returns an iterator which iteratively computes a cumulative maximum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumax( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumidrange, itercumin, itercurange, itermax\n","itercumaxabs":"\nitercumaxabs( iterator )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumaxabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumax, itercuminabs, itermaxabs\n","itercumean":"\nitercumean( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumean( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.25\n\n See Also\n --------\n itercumidrange, itercusum, itermean\n","itercumeanabs":"\nitercumeanabs( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n 3.75\n\n See Also\n --------\n itercumean, itercumeanabs2, itercusumabs, itermeanabs\n","itercumeanabs2":"\nitercumeanabs2( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs2( arr );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n 15.75\n\n See Also\n --------\n itercumean, itercumeanabs, itercusumabs2, itermeanabs2\n","itercumidrange":"\nitercumidrange( iterator )\n Returns an iterator which iteratively computes a cumulative mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumidrange( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itercumean, itercumax, itercumin, itercurange, itermidrange\n","itercumin":"\nitercumin( iterator )\n Returns an iterator which iteratively computes a cumulative minimum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumin( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itercumax, itercumidrange, itercurange, itermin\n","itercuminabs":"\nitercuminabs( iterator )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuminabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n\n See Also\n --------\n itercumaxabs, itercumin, iterminabs\n","itercuprod":"\nitercuprod( iterator )\n Returns an iterator which iteratively computes a cumulative product.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuprod( arr );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -150.0\n\n See Also\n --------\n itercusum, iterprod\n","itercurange":"\nitercurange( iterator )\n Returns an iterator which iteratively computes a cumulative range.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercurange( arr );\n > var r = it.next().value\n 0.0\n > r = it.next().value\n 7.0\n > r = it.next().value\n 8.0\n > r = it.next().value\n 10.0\n\n See Also\n --------\n itercumax, itercumean, itercumin, iterrange\n","itercusum":"\nitercusum( iterator )\n Returns an iterator which iteratively computes a cumulative sum.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusum( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 5.0\n\n See Also\n --------\n itercumean, itersum, itercuprod\n","itercusumabs":"\nitercusumabs( iterator )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 15.0\n\n See Also\n --------\n itercumeanabs, itercusum, itersumabs\n","itercusumabs2":"\nitercusumabs2( iterator )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs2( arr );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 63.0\n\n See Also\n --------\n itercumeanabs2, itercusumabs, itersumabs2\n","iterDatespace":"\niterDatespace( start, stop[, N][, options] )\n Returns an iterator which returns evenly spaced dates over a specified\n interval.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: integer|string|Date\n Starting date either as a `Date` object, JavaScript timestamp, or a date\n string (inclusive).\n\n stop: integer|string|Date\n Stopping value either as a `Date` object, JavaScript timestamp, or a\n date string (inclusive).\n\n N: integer (optional)\n Number of values. Default: 100.\n\n options: Object (optional)\n Function options.\n\n options.round: string (optional)\n Specifies how sub-millisecond times should be rounded. Must be one of\n the following: 'floor', 'ceil', or 'round'. Default: 'floor'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var t1 = new Date();\n > var it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterator2array, iterIncrspace, iterLinspace, iterLogspace, iterStep\n","iterDedupe":"\niterDedupe( iterator[, limit] )\n Returns an iterator which removes consecutive duplicated values.\n\n `NaN` values are considered distinct.\n\n Uniqueness is determined according to strict equality. Accordingly, objects\n are *not* checked for deep equality.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > var it = iterDedupe( arr );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupeBy, iterUnique\n","iterDedupeBy":"\niterDedupeBy( iterator, [limit,] fcn )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n\n The provided function is provided five arguments:\n\n - curr: current source iterated value\n - sprev: previous source iterated value\n - dprev: previous downstream iterated value\n - index: source iteration index (zero-based)\n - acc: previous resolved value\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n fcn: Function\n Function indicating whether an iterated value is a \"duplicate\".\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > function fcn( v ) { return v; };\n > var it = iterDedupeBy( arr, fcn );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupe, iterUnique\n","iterDeg2rad":"\niterDeg2rad( iterator )\n Returns an iterator which iteratively converts an angle from degrees to\n radians.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -360.0, 360.0 );\n > var it = iterDeg2rad( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.deg2rad, iterRad2deg\n","iterDigamma":"\niterDigamma( iterator )\n Returns an iterator which iteratively evaluates the digamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.01, 5.0 );\n > var it = iterDigamma( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.digamma, iterGamma, iterTrigamma\n","iterDiracComb":"\niterDiracComb( [options] )\n Returns an iterator which generates a Dirac comb.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracComb();\n > var v = it.next().value\n Infinity\n > v = it.next().value\n 0.0\n\n See Also\n --------\n iterPulse\n","iterDiracDelta":"\niterDiracDelta( iterator )\n Returns an iterator which iteratively evaluates the Dirac delta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracDelta( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.diracDelta\n","iterDivide":"\niterDivide( iter0, ...iterator )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterDivide( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 0.5\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterMultiply\n","iterEllipe":"\niterEllipe( iterator )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the second kind.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.0, 1.0 );\n > var it = iterEllipe( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.ellipe, iterEllipk\n","iterEllipk":"\niterEllipk( iterator )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the first kind.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.0, 1.0 );\n > var it = iterEllipk( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.ellipk, iterEllipe\n","iterEmpty":"\niterEmpty()\n Returns an empty iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEmpty();\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterConstant\n","iterErf":"\niterErf( iterator )\n Returns an iterator which iteratively evaluates the error function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErf( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erf, iterErfc, iterErfinv, iterErfcinv\n","iterErfc":"\niterErfc( iterator )\n Returns an iterator which iteratively evaluates the complementary error\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfc( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfc, iterErf, iterErfinv, iterErfcinv\n","iterErfcinv":"\niterErfcinv( iterator )\n Returns an iterator which iteratively evaluates the inverse complementary\n error function.\n\n The domain of inverse complementary error function is restricted to [0,2].\n If an iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfcinv, iterErf, iterErfc, iterErfinv\n","iterErfinv":"\niterErfinv( iterator )\n Returns an iterator which iteratively evaluates the inverse error function.\n\n The domain of inverse error function is restricted to [-1,1]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfinv, iterErf, iterErfc, iterErfcinv\n","iterEta":"\niterEta( iterator )\n Returns an iterator which iteratively evaluates the Dirichlet eta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEta( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.eta\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options] )\n Returns an iterator which generates an interleaved sequence of even\n integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n > v = it.next().value\n -2\n\n See Also\n --------\n iterIntegersSeq, iterOddIntegersSeq\n","iterEvery":"\niterEvery( iterator )\n Tests whether all iterated values are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is falsy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\n > var bool = iterEvery( arr )\n false\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNone, iterSome\n","iterEveryBy":"\niterEveryBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a falsy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterEveryBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNoneBy, iterSomeBy\n","iterExp":"\niterExp( iterator )\n Returns an iterator which iteratively evaluates the natural exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterExp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.exp, iterExp10, iterExp2, iterExpm1, iterLn\n","iterExp2":"\niterExp2( iterator )\n Returns an iterator which iteratively evaluates the base `2` exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExp2( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.exp2, iterExp, iterExp10, iterLog2\n","iterExp10":"\niterExp10( iterator )\n Returns an iterator which iteratively evaluates the base `10` exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExp10( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.exp10, iterExp, iterExp2, iterLog10\n","iterExpit":"\niterExpit( iterator )\n Returns an iterator which iteratively evaluates the standard logistic\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 1.0 );\n > var it = iterExpit( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expit, iterExp, iterLogit\n","iterExpm1":"\niterExpm1( iterator )\n Returns an iterator which iteratively computes `exp(x) - 1`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterExpm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expm1, iterExp, iterExpm1rel\n","iterExpm1rel":"\niterExpm1rel( iterator )\n Returns an iterator which iteratively evaluates the relative error\n exponential.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExpm1rel( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expm1rel, iterExp, iterExpm1\n","iterFactorial":"\niterFactorial( iterator )\n Returns an iterator which iteratively evaluates the factorial function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorial( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.factorial, iterFactorialln\n","iterFactorialln":"\niterFactorialln( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n factorial function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorialln( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.factorialln, iterFactorial\n","iterFactorialsSeq":"\niterFactorialsSeq( [options] )\n Returns an iterator which generates a sequence of factorials.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorialsSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterFactorial\n","iterFibonacciSeq":"\niterFibonacciSeq( [options] )\n Returns an iterator which generates a Fibonacci sequence.\n\n The returned iterator can only generate the first 79 Fibonacci numbers, as\n larger Fibonacci numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFibonacciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n base.fibonacci, iterLucasSeq, iterNegaFibonacciSeq, iterNonFibonacciSeq\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options] )\n Returns an iterator which generates a sequence of fifth powers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9741.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFifthPowersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 32\n\n See Also\n --------\n iterCubesSeq, iterFourthPowersSeq, iterSquaresSeq\n","iterFill":"\niterFill( iterator, value[, begin[, end]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n replaces the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n value: any\n Static value.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\n > var r = it.next().value\n 3.14\n > r = it.next().value\n 3.14\n > r = it.next().value\n \n\n","iterFilter":"\niterFilter( iterator, predicate[, thisArg] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilter( it1, f );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterFilterMap, iterMap, iterReject\n","iterFilterMap":"\niterFilterMap( iterator, fcn[, thisArg] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n\n When invoked, the callback function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If the callback returns `undefined`, the iterator invokes the function for\n the next value of the provided iterator; otherwise, the iterator returns\n the callback's return value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Callback function which both filters and maps.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v > 2 ) { return v * 10 }; };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilterMap( it1, f );\n > var v = it2.next().value\n 30\n > v = it2.next().value\n 40\n\n See Also\n --------\n iterFilter, iterMap\n","iterFirst":"\niterFirst( iterator )\n Returns the first iterated value.\n\n The function does *not* consume an entire iterator before returning.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The first iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\n > var v = iterFirst( arr )\n 1\n\n See Also\n --------\n iterHead, iterLast, iterNth\n","iterFlatTopPulse":"\niterFlatTopPulse( [options] )\n Returns an iterator which generates a flat top pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFlatTopPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse\n","iterFloor":"\niterFloor( iterator )\n Returns an iterator which rounds each iterated value toward negative\n infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor, iterCeil, iterRound\n","iterFloor2":"\niterFloor2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward negative infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor2, iterCeil2, iterFloor, iterFloor10, iterRound2\n","iterFloor10":"\niterFloor10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward negative infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor10, iterCeil10, iterFloor, iterFloor2, iterRound10\n","iterFlow":"\niterFlow( methods )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n\n The methods argument should be an object which maps constructor method names\n to iterator functions.\n\n Each iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n When a fluent interface iterator method is invoked, the method invokes the\n corresponding iterator function with an iterator and provided method\n arguments.\n\n If an iterator function returns an iterator, the corresponding fluent\n interface method returns a new fluent interface instance; otherwise, the\n corresponding fluent interface method returns the iterator function result.\n\n The iterator function evaluation context is always `null`.\n\n Iterator functions which return iterators are expected to return iterator\n protocol-compliant objects (i.e., an object having a `next` method which\n returns the next iterated value (if one exists) assigned to a `value`\n property and a `done` property having a boolean value indicating whether the\n iterator is finished).\n\n If an environment supports `Symbol.iterator`, the returned constructor\n returns iterators which are iterable.\n\n Parameters\n ----------\n methods: Object\n An object mapping method names to iterator functions.\n\n Returns\n -------\n FluentIterator: Function\n Fluent interface iterator constructor.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o )\n\n\nFluentIterator( iterator )\n Returns a new fluent interface iterator from a source iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n Returns\n -------\n iterator: Object\n Fluent interface iterator.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var bool = it.head( 3 ).some( 2 )\n false\n\n\nFluentIterator.prototype.next()\n Returns the next iterated value.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > v = it2.next().value\n 0\n > v = it2.next().value\n 1\n\n\nFluentIterator.prototype.return( [value] )\n Finishes an iterator and returns a provided value.\n\n Parameters\n ----------\n value: any (optional)\n Value to return.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > var bool = it2.return().done\n true\n > v = it2.next().value\n undefined\n\n See Also\n --------\n iterPipeline\n","iterForEach":"\niterForEach( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterForEach( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterMap\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options] )\n Returns an iterator which generates a sequence of fourth powers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9741.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFourthPowersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 16\n\n See Also\n --------\n iterCubesSeq, iterFifthPowersSeq, iterSquaresSeq\n","iterFresnelc":"\niterFresnelc( iterator )\n Returns an iterator which iteratively computes the Fresnel integral C(x).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterFresnelc( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.fresnelc, iterFresnels\n","iterFresnels":"\niterFresnels( iterator )\n Returns an iterator which iteratively computes the Fresnel integral S(x).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterFresnels( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.fresnels, iterFresnelc\n","iterGamma":"\niterGamma( iterator )\n Returns an iterator which iteratively evaluates the gamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterGamma( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.gamma, iterGamma1pm1, iterGammaln\n","iterGamma1pm1":"\niterGamma1pm1( iterator )\n Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n cancellation errors for small `x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterGamma1pm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.gamma1pm1, iterGamma\n","iterGammaln":"\niterGammaln( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n gamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterGammaln( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.gammaln, iterGamma\n","iterHacovercos":"\niterHacovercos( iterator )\n Returns an iterator which iteratively computes the half-value coversed\n cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHacovercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.hacovercos, iterCovercos, iterHacoversin\n","iterHacoversin":"\niterHacoversin( iterator )\n Returns an iterator which iteratively computes the half-value coversed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHacoversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.hacoversin, iterCoversin, iterHacovercos\n","iterHannPulse":"\niterHannPulse( [options] )\n Returns an iterator which generates a Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterSineWave\n","iterHavercos":"\niterHavercos( iterator )\n Returns an iterator which iteratively computes the half-value versed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHavercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.havercos, iterHaversin, iterVercos\n","iterHaversin":"\niterHaversin( iterator )\n Returns an iterator which iteratively computes the half-value versed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHaversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.haversin, iterHavercos, iterVersin\n","iterHead":"\niterHead( iterator, n )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n\n If a provided iterator only generates `m` values and `m` is less than `n`,\n the returned iterator only returns `m` values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of values.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHead( random.iterators.randu(), 5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterSlice\n","iterIncrspace":"\niterIncrspace( start, stop[, increment] )\n Returns an iterator which returns evenly spaced numbers according to a\n specified increment.\n\n Beware that values which follow the starting value are subject to floating-\n point rounding errors.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number\n Stopping value (exclusive).\n\n increment: number (optional)\n Increment. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterIncrspace( 0, 101, 2 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, iterDatespace, iterLinspace, iterLogspace, iterStep, iterUnitspace\n","iterIntegersSeq":"\niterIntegersSeq( [options] )\n Returns an iterator which generates an interleaved integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 18014398509481984.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n -1\n\n See Also\n --------\n iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterIntersection":"\niterIntersection( iter0, ...iterator )\n Returns an iterator which returns the intersection of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterIntersection( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersectionByHash, iterUnion, iterUnique\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n A returned iterator internally buffers unique hashes, along with the *first*\n iterated value resolving to a hash, and, thus, has O(N) memory requirements,\n where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > function f( v ) { return v.toString(); };\n > var it = iterIntersectionByHash( it1, it2, f );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUniqueByHash\n","iterInv":"\niterInv( iterator )\n Returns an iterator which iteratively computes the multiplicative inverse.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterInv( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.inv, iterPow\n","iterLanczosPulse":"\niterLanczosPulse( [options] )\n Returns an iterator which generates a Lanczos pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLanczosPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterPeriodicSinc\n","iterLast":"\niterLast( iterator )\n Consumes an entire iterator and returns the last iterated value.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The last iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var v = iterLast( arr )\n 1\n\n See Also\n --------\n iterFirst, iterNth\n","iterLength":"\niterLength( iterator )\n Consumes an entire iterator and returns the number of iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n len: integer\n Iterator length.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var len = iterLength( arr )\n 5\n\n See Also\n --------\n iterCounter\n","iterLinspace":"\niterLinspace( start, stop[, N] )\n Returns an iterator which returns evenly spaced numbers over a specified\n interval.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number\n Stopping value (inclusive).\n\n N: integer (optional)\n Number of values. Default: 100.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLinspace( 0, 99, 100 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLogspace, iterStep, iterUnitspace\n","iterLn":"\niterLn( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLn( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ln, iterExp, iterLog10, iterLog1p, iterLog2\n","iterLog":"\niterLog( x, b )\n Returns an iterator which iteratively computes the base `b` logarithm.\n\n For negative `b` or `x` iterated values, the returned iterator returns\n `NaN`.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n b: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 100.0 );\n > var y = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterLog( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log, iterLog10, iterLog1p, iterLog2, iterPow\n","iterLog1mexp":"\niterLog1mexp( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1-exp(-|x|)`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1mexp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1mexp, iterLog, iterLog1p, iterLog1pexp, iterPow\n","iterLog1p":"\niterLog1p( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1p( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1p, iterLog, iterLog10, iterLog2, iterPow\n","iterLog1pexp":"\niterLog1pexp( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+exp(x)`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1pexp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1pexp, iterLog, iterLog1p, iterLog1mexp, iterPow\n","iterLog2":"\niterLog2( iterator )\n Returns an iterator which iteratively evaluates the binary logarithm.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log2, iterLog, iterLog10, iterLog1p, iterPow\n","iterLog10":"\niterLog10( iterator )\n Returns an iterator which iteratively evaluates the common logarithm\n (logarithm with base 10).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog10( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log10, iterLog, iterLog1p, iterLog2, iterPow\n","iterLogit":"\niterLogit( iterator )\n Returns an iterator which iteratively evaluates the logit function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 1.0 );\n > var it = iterLogit( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.logit\n","iterLogspace":"\niterLogspace( start, stop[, N][, options] )\n Returns an iterator which returns evenly spaced numbers on a log scale.\n\n In linear space, the sequence starts at `base` raised to the power of\n `start` and ends with `base` raised to the power of `stop`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Exponent of starting value.\n\n stop: number\n Exponent of stopping value.\n\n N: integer (optional)\n Number of values. Default: 100.\n\n options: Object (optional)\n Function options.\n\n options.base: number (optional)\n Base of log space. Default: 10.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLogspace( 0, 3, 4 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 10\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterStep\n","iterLucasSeq":"\niterLucasSeq( [options] )\n Returns an iterator which generates a Lucas sequence.\n\n The returned iterator can only generate the first 77 Lucas numbers, as\n larger Lucas numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 77.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLucasSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 1\n\n See Also\n --------\n base.lucas, iterFibonacciSeq, iterNegaLucasSeq\n","iterMap":"\niterMap( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return v * 10.0; };\n > var it = iterMap( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFilter, iterFilterMap, iterForEach, iterReject\n","iterMapN":"\niterMapN( iter0, ...iterator, fcn[, thisArg] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n\n When invoked, the callback function is provided `N+1` arguments, where `N`\n is the number of provided iterators and the last argument is the iteration\n index:\n\n - ...value: iterated values\n - index: iteration index (zero-based)\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators.\n\n fcn: Function\n Function to invoke with iterated values.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > function fcn( x, y ) { return x + y; };\n > var it = iterMapN( it1, it2, fcn );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterMap\n","itermax":"\nitermax( iterator )\n Computes the maximum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermax( arr )\n 3.0\n\n See Also\n --------\n itermidrange, itermin, itermmax, iterrange\n","itermaxabs":"\nitermaxabs( iterator )\n Computes the maximum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermaxabs( arr )\n 4.0\n\n See Also\n --------\n itermax, iterminabs, itermmaxabs\n","itermean":"\nitermean( iterator )\n Computes an arithmetic mean over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = itermean( arr )\n 2.5\n\n See Also\n --------\n itermidrange, itermmean, iterstdev, itersum, itervariance\n","itermeanabs":"\nitermeanabs( iterator )\n Computes an arithmetic mean of absolute values for all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs( arr )\n 2.5\n\n See Also\n --------\n itermean, itermmeanabs, itersumabs\n","itermeanabs2":"\nitermeanabs2( iterator )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs2( arr )\n 7.5\n\n See Also\n --------\n itermean, itermeanabs, itermmeanabs2, itersumabs2\n","itermidrange":"\nitermidrange( iterator )\n Computes the mid-range of all iterated values.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Mid-range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = itermidrange( arr )\n -0.5\n\n See Also\n --------\n itermean, itermax, itermin, iterrange\n","itermin":"\nitermin( iterator )\n Computes the minimum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermin( arr )\n -3.0\n\n See Also\n --------\n itermax, itermidrange, itermmin, iterrange\n","iterminabs":"\niterminabs( iterator )\n Computes the minimum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = iterminabs( arr )\n 1.0\n\n See Also\n --------\n itermaxabs, itermin, itermminabs\n","itermmax":"\nitermmax( iterator, W )\n Returns an iterator which iteratively computes a moving maximum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmax( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermax, itermmidrange, itermmin, itermrange\n","itermmaxabs":"\nitermmaxabs( iterator, W )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmaxabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermaxabs, itermmax, itermminabs\n","itermmean":"\nitermmean( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmean( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.0\n\n See Also\n --------\n itermean, itermsum\n","itermmeanabs":"\nitermmeanabs( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n ~4.33\n\n See Also\n --------\n itermeanabs, itermmean, itermsumabs\n","itermmeanabs2":"\nitermmeanabs2( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of squared absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs2( arr, 3 );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n ~19.67\n\n See Also\n --------\n itermeanabs2, itermmeanabs, itermsumabs2\n","itermmidrange":"\nitermmidrange( iterator, W )\n Returns an iterator which iteratively computes a moving mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmidrange( arr, 3 );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itermidrange, itermmean, itermmax, itermmin, itermrange\n","itermmin":"\nitermmin( iterator, W )\n Returns an iterator which iteratively computes a moving minimum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmin( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itermin, itermmax, itermmidrange, itermrange\n","itermminabs":"\nitermminabs( iterator, W )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermminabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n\n See Also\n --------\n iterminabs, itermmaxabs, itermmin\n","iterMod":"\niterMod( iter0, ...iterator )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterMod( it1, it2 );\n > var v = it.next().value\n 0.0\n > v = it.next().value\n 2.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide\n","itermprod":"\nitermprod( iterator, W )\n Returns an iterator which iteratively computes a moving product.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermprod( arr, 3 );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -75.0\n\n See Also\n --------\n itermsum, iterprod\n","itermrange":"\nitermrange( iterator, W )\n Returns an iterator which iteratively computes a moving range.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermrange( arr, 3 );\n > var m = it.next().value\n 0.0\n > m = it.next().value\n 7.0\n > m = it.next().value\n 8.0\n > m = it.next().value\n 10.0\n\n See Also\n --------\n itermmax, itermmean, itermmin, iterrange\n","itermsum":"\nitermsum( iterator, W )\n Returns an iterator which iteratively computes a moving sum.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsum( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 3.0\n\n See Also\n --------\n itermmean, itersum\n","itermsumabs":"\nitermsumabs( iterator, W )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 13.0\n\n See Also\n --------\n itermmeanabs, itermsum, itersum, itersumabs\n","itermsumabs2":"\nitermsumabs2( iterator, W )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs2( arr, 3 );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 59.0\n\n See Also\n --------\n itermmeanabs2, itermsumabs, itersumabs, itersumabs2\n","iterMultiply":"\niterMultiply( iter0, ...iterator )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to multiply.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterMultiply( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 8.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterSubtract\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options] )\n Returns an iterator which generates a negaFibonacci sequence.\n\n The returned iterator can only generate the first 79 negaFibonacci numbers,\n as larger negaFibonacci numbers cannot be safely represented in double-\n precision floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegaFibonacciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n base.negafibonacci, iterFibonacciSeq, iterNonFibonacciSeq\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options] )\n Returns an iterator which generates a negaLucas sequence.\n\n The returned iterator can only generate the first 77 negaLucas numbers, as\n larger negaLucas numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 77.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegaLucasSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n -1\n\n See Also\n --------\n base.negalucas, iterLucasSeq, iterNegaFibonacciSeq\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of negative even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeEvenIntegersSeq();\n > var v = it.next().value\n -2\n > v = it.next().value\n -4\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterNonPositiveEvenIntegersSeq\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options] )\n Returns an iterator which generates a negative integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740991.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeIntegersSeq();\n > var v = it.next().value\n -1\n > v = it.next().value\n -2\n\n See Also\n --------\n iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options] )\n Returns an iterator which generates a sequence of negative odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeOddIntegersSeq();\n > var v = it.next().value\n -1\n > v = it.next().value\n -3\n\n See Also\n --------\n iterOddIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeEvenIntegersSeq, iterPositiveOddIntegersSeq\n","iterNone":"\niterNone( iterator )\n Tests whether all iterated values are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is truthy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterNone( arr )\n false\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNoneBy, iterSome\n","iterNoneBy":"\niterNoneBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a falsy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v <= 0 ); };\n > var bool = iterNoneBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNone, iterSomeBy\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonFibonacciSeq();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n\n See Also\n --------\n base.nonfibonacci, iterFibonacciSeq\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of nonnegative even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370497.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonNegativeEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveEvenIntegersSeq, iterPositiveEvenIntegersSeq\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options] )\n Returns an iterator which generates a nonnegative integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonNegativeIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterIntegersSeq, iterNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of nonpositive even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370497.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonPositiveEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n -2\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeEvenIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeEvenIntegersSeq\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options] )\n Returns an iterator which generates a nonpositive integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonPositiveIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n -1\n\n See Also\n --------\n iterIntegersSeq, iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterPositiveIntegersSeq\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options] )\n Returns an iterator which generates a sequence of nonsquares.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199349647256.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonSquaresSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 5\n\n See Also\n --------\n iterCubesSeq, iterSquaresSeq\n","iterNth":"\niterNth( iterator, n )\n Returns the nth iterated value.\n\n If `n` exceeds the total number of iterations, the function returns\n `undefined`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Iteration number.\n\n Returns\n -------\n v: any\n The nth iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\n > var v = iterNth( arr, 3 )\n 1\n\n See Also\n --------\n iterFirst, iterLast\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options] )\n Returns an iterator which generates an interleaved sequence of odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterOddIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n -1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq\n","iterPeriodicSinc":"\niterPeriodicSinc( n[, options] )\n Returns an iterator which generates a periodic sinc waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Order.\n\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 100.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPeriodicSinc( 7 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterSineWave\n","iterPipeline":"\niterPipeline( iterFcn[, ...iterFcn] )\n Returns an iterator pipeline.\n\n Parameters\n ----------\n iterFcn: Function|Array\n Iterator function or an array of iterator functions.\n\n iterFcn: ...Function (optional)\n Iterator functions.\n\n Returns\n -------\n fcn( src ): Function\n Iterator pipeline which accepts a single argument, a source iterator.\n\n Examples\n --------\n > var it1 = iterThunk( iterHead, 100 );\n > function f( r ) { return ( r > 0.95 ); };\n > var it2 = iterThunk( iterSomeBy, 5, f );\n > var p = iterPipeline( it1, it2 );\n > var bool = p( random.iterators.randu() )\n \n\n See Also\n --------\n iterFlow, iterThunk\n","iterPop":"\niterPop( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the last value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPop( it1 );\n > var v = it2.next().value\n 1\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPush, iterShift, iterSlice\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of positive even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveEvenIntegersSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 4\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNegativeEvenIntegersSeq, iterNonNegativeEvenIntegersSeq, iterPositiveIntegersSeq, iterPositiveOddIntegersSeq\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options] )\n Returns an iterator which generates a positive integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740991.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeIntegersSeq\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options] )\n Returns an iterator which generates a sequence of positive odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveOddIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterOddIntegersSeq, iterIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterPositiveIntegersSeq\n","iterPow":"\niterPow( base, exponent )\n Returns an iterator which iteratively evaluates the exponential function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n base: Object|number\n Input iterator.\n\n exponent: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( -2.0, 2.0 );\n > var it = iterPow( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.pow, iterExp, iterLog\n","iterPrimesSeq":"\niterPrimesSeq( [options] )\n Returns an iterator which generates a sequence of prime numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 245181918813464.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPrimesSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 5\n\n See Also\n --------\n iterCompositesSeq, iterIntegersSeq, iterPositiveIntegersSeq\n","iterprod":"\niterprod( iterator )\n Computes the product of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Product.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = iterprod( arr )\n 24.0\n\n See Also\n --------\n itermprod, itersum\n","iterPulse":"\niterPulse( [options] )\n Returns an iterator which generates a pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 10.\n\n options.duration: integer (optional)\n Pulse duration (i.e., the number of consecutive iterations of maximum\n amplitude during one period). Default: floor(options.period/2).\n\n options.min: number (optional)\n Minimum amplitude. Default: 0.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPulse();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterPush":"\niterPush( iterator, ...items )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to append.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPush( it1, 3, 4 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterUnshift\n","iterRad2deg":"\niterRad2deg( iterator )\n Returns an iterator which iteratively converts an angle from radians to\n degrees.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterRad2deg( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.rad2deg, iterDeg2rad\n","iterRamp":"\niterRamp( iterator )\n Returns an iterator which iteratively evaluates the ramp function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRamp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ramp\n","iterrange":"\niterrange( iterator )\n Computes the range of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = iterrange( arr )\n 7.0\n\n See Also\n --------\n itermax, itermean, itermin, itermrange\n","iterReject":"\niterReject( iterator, predicate[, thisArg] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterReject( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterFilter, iterMap\n","iterReplicate":"\niterReplicate( iterator, n )\n Returns an iterator which replicates each iterated value `n` times.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of times each iterated value is replicated.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > var it2 = iterReplicate( it1, 2 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterReplicateBy\n","iterReplicateBy":"\niterReplicateBy( iterator, fcn[, thisArg] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n\n The callback function is provided three arguments:\n\n - value: iterated value\n - index: source iteration index (zero-based)\n - n: iteration index (zero-based)\n\n The callback function is invoked *once* per iterated value of the provided\n iterator.\n\n The callback function *must* return an integer value. If the return value is\n less than or equal to zero, the returned iterator skips an iterated value\n and invokes the callback for the next iterated value of the provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function which returns the number of times an iterated value should be\n replicated.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > function f( v, i ) { return i + 1; };\n > var it2 = iterReplicateBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterReplicate\n","iterRound":"\niterRound( iterator )\n Returns an iterator which rounds each iterated value to the nearest integer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round, iterCeil, iterFloor, iterTrunc\n","iterRound2":"\niterRound2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two on a linear scale.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round2, iterCeil2, iterFloor2, iterRound, iterRound10, iterTrunc2\n","iterRound10":"\niterRound10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 on a linear scale.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round10, iterCeil10, iterFloor10, iterRound, iterRound2, iterTrunc10\n","iterRsqrt":"\niterRsqrt( iterator )\n Returns an iterator which iteratively computes the reciprocal (inverse)\n square root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRsqrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.rsqrt, iterSqrt\n","iterSawtoothWave":"\niterSawtoothWave( [options] )\n Returns an iterator which generates a sawtooth wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSawtoothWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSineWave, iterSquareWave, iterTriangleWave\n","iterShift":"\niterShift( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the first value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterShift( it1 );\n > var v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPop, iterSlice, iterUnshift\n","iterSignum":"\niterSignum( iterator )\n Returns an iterator which iteratively evaluates the signum function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSignum( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.signum\n","iterSin":"\niterSin( iterator )\n Returns an iterator which iteratively computes the sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSin( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sin, iterCos, iterSinpi, iterTan\n","iterSinc":"\niterSinc( iterator )\n Returns an iterator which iteratively computes the normalized cardinal sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterSinc( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sinc, iterSin\n","iterSineWave":"\niterSineWave( [options] )\n Returns an iterator which generates a sine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a sine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterCosineWave, iterPulse, iterSawtoothWave, iterSquareWave, iterTriangleWave\n","iterSinh":"\niterSinh( iterator )\n Returns an iterator which iteratively evaluates the hyperbolic sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterSinh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sinh, iterCosh, iterTanh\n","iterSinpi":"\niterSinpi( iterator )\n Returns an iterator which computes the sine of each iterated value times π.\n\n Computes sin(πx) more accurately than sin(pi*x), especially for large x.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSinpi( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sinpi, iterSin\n","iterSlice":"\niterSlice( iterator[, begin[, end]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n returns the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSlice( random.iterators.randu(), 5, 10 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterHead\n","iterSome":"\niterSome( iterator, n )\n Tests whether at least `n` iterated values are truthy.\n\n The function immediately returns upon finding `n` truthy values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an iterator returns at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = iterSome( arr, 3 )\n true\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNone, iterSomeBy\n","iterSomeBy":"\niterSomeBy( iterator, n, predicate[, thisArg ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering `n` truthy return values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Minimum number of successful values.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for at least `n` iterated values. Otherwise, the function returns\n `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterSomeBy( arr, 3, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNoneBy, iterSome\n","iterSpence":"\niterSpence( iterator )\n Returns an iterator which iteratively evaluates Spence's function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 100.0 );\n > var it = iterSpence( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.spence\n","iterSqrt":"\niterSqrt( iterator )\n Returns an iterator which iteratively computes the principal square root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSqrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sqrt, iterCbrt, iterRsqrt\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator )\n Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n accurately for small `x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 100.0 );\n > var it = iterSqrt1pm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sqrt1pm1, iterSqrt\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options] )\n Returns an iterator which generates a sequence of squared triangular\n numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 11585.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquaredTriangularSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 9\n\n See Also\n --------\n iterTriangularSeq\n","iterSquaresSeq":"\niterSquaresSeq( [options] )\n Returns an iterator which generates a sequence of squares.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 94906265.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquaresSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 4\n\n See Also\n --------\n iterCubesSeq, iterNonSquaresSeq\n","iterSquareWave":"\niterSquareWave( [options] )\n Returns an iterator which generates a square wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a square wave repeats).\n This must be an even integer in order to ensure a 50% duty cycle.\n Default: 10.\n\n options.min: number (optional)\n Minimum amplitude. Default: -1.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquareWave();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterTriangleWave\n","iterstdev":"\niterstdev( iterator[, mean] )\n Computes a correct sample standard deviation over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Corrected sample standard deviation.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var m = iterstdev( arr )\n ~4.95\n\n See Also\n --------\n itermean, itervariance\n","iterStep":"\niterStep( start, increment[, N] )\n Returns an iterator which returns a sequence of numbers according to a\n specified increment.\n\n Beware that values which follow the starting value are subject to floating-\n point rounding errors.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n increment: number\n Increment.\n\n N: number (optional)\n Number of values. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterStep( 0, 2, 10 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterLogspace, iterUnitspace\n","iterStrided":"\niterStrided( iterator, stride[, offset[, eager]] )\n Returns an iterator which steps by a specified amount.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n stride: integer\n Stride (i.e., step amount).\n\n offset: integer (optional)\n Index of the first iterated value. Default: 0.\n\n eager: boolean (optional)\n Boolean indicating whether to eagerly advance the input iterator when\n provided a non-zero offset. Default: false.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n > var it = iterStrided( arr, 2, 1 );\n > var r = it.next().value\n 1\n > r = it.next().value\n 3\n\n See Also\n --------\n iterAdvance, iterNth, iterStridedBy\n","iterStridedBy":"\niterStridedBy( iterator, fcn[, offset[, eager]][, thisArg] )\n Returns an iterator which steps according to a provided callback function.\n\n When invoked, the input function is provided four arguments:\n\n - value: iterated value\n - i: input iteration index (zero-based)\n - n: output (strided) iteration index (zero-based)\n - curr: current stride\n\n The return value of the input function specifies the next stride.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Stride function (i.e., a function which returns the step amount).\n\n offset: integer (optional)\n Index of the first iterated value. Default: 0.\n\n eager: boolean (optional)\n Boolean indicating whether to eagerly advance the input iterator when\n provided a non-zero offset. Default: false.\n\n thisArg: any (optional)\n Stride function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n > function stride( v, i ) { return (i % 10)+1; };\n > var it = iterStridedBy( arr, stride );\n > var r = it.next().value\n 0\n > r = it.next().value\n 1\n > r = it.next().value\n 3\n\n See Also\n --------\n iterAdvance, iterNth, iterStrided\n","iterSubtract":"\niterSubtract( iter0, ...iterator )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to subtract.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 5.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterSubtract( it1, it2 );\n > var v = it.next().value\n -2.0\n > v = it.next().value\n 1.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterMultiply\n","itersum":"\nitersum( iterator )\n Computes the sum of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = itersum( arr )\n 10.0\n\n See Also\n --------\n itermean, itermsum, iterprod\n","itersumabs":"\nitersumabs( iterator )\n Computes the sum of absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs( arr )\n 10.0\n\n See Also\n --------\n itermeanabs, itermsumabs, itersum\n","itersumabs2":"\nitersumabs2( iterator )\n Computes the sum of squared absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs2( arr )\n 30.0\n\n See Also\n --------\n itermeanabs2, itermsumabs2, itersumabs\n","iterTan":"\niterTan( iterator )\n Returns an iterator which iteratively evaluates the tangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.57, 1.57 );\n > var it = iterTan( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.tan, iterCos, iterSin\n","iterTanh":"\niterTanh( iterator )\n Returns an iterator which iteratively evaluates the hyperbolic tangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -4.0, 4.0 );\n > var it = iterTanh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.tanh, iterCosh, iterSinh, iterTan\n","iterThunk":"\niterThunk( iterFcn[, ...args] )\n Returns an iterator \"thunk\".\n\n A provided iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n The returned function expects a single argument, an iterator.\n\n This function is useful within the context of iterator pipelines as a means\n to defer execution until a pipeline is ready for data flow.\n\n Parameters\n ----------\n iterFcn: Function\n Iterator function.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n fcn( iter ): Function\n Function which accepts a single argument, an iterator, and invokes a\n previously provided iterator function with the provided iterator and any\n previously provided arguments.\n\n Examples\n --------\n > var fcn = iterThunk( iterSome, 3 );\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = fcn( arr )\n true\n\n See Also\n --------\n iterPipeline\n","iterTriangleWave":"\niterTriangleWave( [options] )\n Returns an iterator which generates a triangle wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangleWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave\n","iterTriangularSeq":"\niterTriangularSeq( [options] )\n Returns an iterator which generates a sequence of triangular numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 134217727.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangularSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterSquaredTriangularSeq\n","iterTrigamma":"\niterTrigamma( iterator )\n Returns an iterator which iteratively evaluates the trigamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.01, 50.0 );\n > var it = iterTrigamma( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.trigamma, iterDigamma, iterGamma\n","iterTrunc":"\niterTrunc( iterator )\n Returns an iterator which rounds each iterated value toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc, iterCeil, iterFloor, iterRound\n","iterTrunc2":"\niterTrunc2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc2, iterCeil2, iterFloor2, iterRound2, iterTrunc\n","iterTrunc10":"\niterTrunc10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc10, iterCeil10, iterFloor10, iterRound10, iterTrunc\n","iterUnion":"\niterUnion( iter0, ...iterator )\n Returns an iterator which returns the union of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the total number of source iterator\n values.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterUnion( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 4\n > v = it.next().value\n 5\n > v = it.next().value\n 3\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUnique\n","iterUnique":"\niterUnique( iterator )\n Returns an iterator which returns unique values.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = iterUnique( it1 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUniqueBy, iterUniqueByHash\n","iterUniqueBy":"\niterUniqueBy( iterator, predicate[, thisArg] )\n Returns an iterator which returns unique values according to a predicate\n function.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n A predicate function is invoked for each iterated value against each value\n in an internal buffer consisting of previously identified unique values.\n Thus, as the number of unique values grows, so, too, does the number of\n predicate function invocations per iterated value.\n\n An iterated value is considered \"unique\" if the predicate function returns\n truthy values for all comparisons of the iterated value with each value in\n the internal buffer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n A binary function with parameters `a` and `b` corresponding to iterated\n values. If the values are the same, the function should return `false`\n (i.e., non-unique); otherwise, if the values are distinct, the function\n should return `true` (i.e., unique).\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( a, b ) { return ( a !== b ); };\n > var it2 = iterUniqueBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueByHash\n","iterUniqueByHash":"\niterUniqueByHash( iterator, hashFcn[, thisArg] )\n Returns an iterator which returns unique values according to a hash\n function.\n\n A returned iterator internally buffers unique hashes and, thus, has O(N)\n memory requirements.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( v ) { return v.toString(); };\n > var it2 = iterUniqueByHash( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueBy\n","iterUnitspace":"\niterUnitspace( start[, stop] )\n Returns an iterator which returns numbers incremented by one.\n\n The iterator stops once the `stop` value is exceeded.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number (optional)\n Stopping value. Default: +infinity.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterUnitspace( 0, 99 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterator2array, iterIncrspace, iterLinspace, iterStep\n","iterUnshift":"\niterUnshift( iterator, ...items )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to prepend.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterUnshift( it1, 3, 4 );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterPush, iterShift\n","itervariance":"\nitervariance( iterator[, mean] )\n Computes an unbiased sample variance over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Unbiased sample variance.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var s2 = itervariance( arr )\n 24.5\n\n See Also\n --------\n itermean, iterstdev\n","iterVercos":"\niterVercos( iterator )\n Returns an iterator which iteratively computes the versed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterVercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.vercos, iterCos, iterSin, iterVersin\n","iterVersin":"\niterVersin( iterator )\n Returns an iterator which iteratively computes the versed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterVersin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.versin, iterCos, iterSin, iterVercos\n","iterZeta":"\niterZeta( iterator )\n Returns an iterator which iteratively evaluates the Riemann zeta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 1.1, 50.0 );\n > var it = iterZeta( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.zeta\n","joinStream":"\njoinStream( [options] )\n Returns a transform stream which joins streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = joinStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n splitStream\n","joinStream.factory":"\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","joinStream.objectMode":"\njoinStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n splitStream","kde2d":"\nkde2d( x, y[, options] )\n Two-dimensional kernel density estimation.\n\n Parameters\n ----------\n x: Array\n Array of x values.\n\n y: Array\n Array of y values.\n\n options: Object (optional)\n Function options.\n\n options.h: number (optional)\n Array of length two containing the bandwidth values for x and y.\n\n options.n: number (optional)\n Number of partitions on the x- and y-axes. Default: `25`.\n\n options.xMin: number (optional)\n Lower limit of x.\n\n options.xMax: number (optional)\n Upper limit of x.\n\n options.yMin: number (optional)\n Lower limit of y.\n\n options.yMax: number (optional)\n Upper limit of y.\n\n options.kernel: string|Function\n A string or function to specifying the used kernel function. Default:\n `'gaussian'`.\n\n Returns\n -------\n out: Object\n Object containing the density estimates (`z`) along grid points (`x` and\n `y` values).\n\n Examples\n --------\n > var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\n > var y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\n > var out = kde2d( x, y )\n { 'x': [1, ... ], 'y': [0.05, ...], 'z': ndarray{Float64Array[0.031, ...] }\n\n","kebabcase":"\nkebabcase( str )\n Converts a string to kebab case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Kebab-cased string.\n\n Examples\n --------\n > var out = kebabcase( 'Hello World!' )\n 'hello-world'\n > out = kebabcase( 'I am a tiny little teapot' )\n 'i-am-a-tiny-little-teapot'\n\n See Also\n --------\n camelcase, constantcase, pascalcase, snakecase","keyBy":"\nkeyBy( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n\n When invoked, the input function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyBy( arr, toKey )\n { '1': { 'a': 1 }, '2': { 'a': 2 } }\n\n See Also\n --------\n forEach\n","keyByRight":"\nkeyByRight( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n\n When invoked, the input function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyByRight( arr, toKey )\n { '2': { 'a': 2 }, '1': { 'a': 1 } }\n\n See Also\n --------\n forEachRight, keyBy\n","keysIn":"\nkeysIn( obj )\n Returns an array of an object's own and inherited enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = keysIn( obj )\n e.g., [ 'beep', 'foo' ]\n\n See Also\n --------\n objectEntriesIn, objectKeys, objectValuesIn\n","kruskalTest":"\nkruskalTest( ...x[, options] )\n Computes the Kruskal-Wallis test for equal medians.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = kruskalTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = kruskalTest( arr, { 'groups': groups } )\n\n","kstest":"\nkstest( x, y[, ...params][, options] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n\n For a numeric array or typed array `x`, a Kolmogorov-Smirnov goodness-of-fit\n is computed for the null hypothesis that the values of `x` come from the\n distribution specified by `y`. `y` can be either a string with the name of\n the distribution to test against, or a function.\n\n In the latter case, `y` is expected to be the cumulative distribution\n function (CDF) of the distribution to test against, with its first parameter\n being the value at which to evaluate the CDF and the remaining parameters\n constituting the parameters of the distribution. The parameters of the\n distribution are passed as additional arguments after `y` from `kstest` to\n the chosen CDF. The function returns an object holding the calculated test\n statistic `statistic` and the `pValue` of the test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the hypothesis test results.\n\n Parameters\n ----------\n x: Array\n Input array holding numeric values.\n\n y: Function|string\n Either a CDF function or a string denoting the name of a distribution.\n\n params: ...number (optional)\n Distribution parameters passed to reference CDF.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array is already in sorted order.\n Default: `false`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that the true distribution of `x` is not equal\n to the reference distribution specified by `y` (`two-sided`), whether it\n is `less` than the reference distribution or `greater` than the\n reference distribution. Default: `'two-sided'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.alternative: string\n Used test alternative. Either `two-sided`, `less` or `greater`.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Verify that data is drawn from a normal distribution:\n > var rnorm = base.random.normal.factory({ 'seed': 4839 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n // Test against N(0,1)\n > var out = kstest( x, 'normal', 0.0, 1.0 )\n { pValue: 0.0, statistic: 0.847, ... }\n\n // Test against N(3,1)\n > out = kstest( x, 'normal', 3.0, 1.0 )\n { pValue: 0.6282, statistic: 0.0733, ... }\n\n // Verify that data is drawn from a uniform distribution:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0 )\n { pValue: ~0.703, statistic: ~0.069, ... }\n\n // Print output:\n > out.print()\n Kolmogorov-Smirnov goodness-of-fit test.\n\n Null hypothesis: the CDF of `x` is equal equal to the reference CDF.\n\n pValue: 0.7039\n statistic: 0.0689\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Set custom significance level:\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\n { pValue: ~0.7039, statistic: ~0.069, ... }\n\n // Carry out one-sided hypothesis tests:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\n { pValue: ~0.358, statistic: ~0.07, ... }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\n { pValue: ~0.907, statistic: ~0.02, ... }\n\n // Set `sorted` option to true when data is in increasing order:\n > x = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n { pValue: ~1, statistic: 0.1, ... }\n\n","leveneTest":"\nleveneTest( x[, ...y[, options]] )\n Computes Levene's test for equal variances.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n y: ...Array (optional)\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Array\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = leveneTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = leveneTest( arr, { 'groups': groups } )\n\n See Also\n --------\n vartest, bartlettTest\n","LinkedList":"\nLinkedList()\n Linked list constructor.\n\n Returns\n -------\n list: Object\n Linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the last node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = LinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n DoublyLinkedList, Stack\n","linspace":"\nlinspace( start, stop, length[, options] )\n Generates a linearly spaced array over a specified interval.\n\n If the specified length is zero, the function returns an empty array.\n\n If the specified length is one, the function returns an array containing\n `stop`, but not `start`, when `endpoint` is true; otherwise, the function\n returns an array containing `start`, but not `stop`.\n\n For real-valued `start` and `stop`, if `start` is less than `stop`, the\n output array will contain ascending values, and, if `start` is greater than\n `stop`, the output array will contain descending values.\n\n When the output array length is greater than one and `endpoint` is true, the\n output array is guaranteed to include the `start` and `stop` values. Beware,\n however, that values between `start` and `stop` are subject to floating-\n point rounding errors.\n\n If both `start` and `stop` are real-valued, the output array data type may\n be any floating-point data type or 'generic'. However, if either `start` or\n `stop` are complex numbers, the output array type must be a complex\n floating-point data type or 'generic'.\n\n When writing to a complex floating-point output array, real-valued `start`\n and `stop` values are treated as complex numbers having a real component\n equaling the provided value and having an imaginary component equaling zero.\n\n When generating linearly spaced complex floating-point numbers, the real and\n imaginary components are generated separately.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n length: integer\n Length of output array.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Must be a floating-point data type or 'generic'.\n If both `start` and `stop` are the same type (either 'float64',\n 'complex64', or 'complex128'), the default output array data type is\n the same type as the input values (either 'float64', 'complex64', or\n 'complex128', respectively). Otherwise, the default output array data\n type is 'complex128'.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `length + 1` linearly spaced\n values over the interval `[start, stop]` and only writes `length` values\n to the output array, thus excluding `stop` from the output array.\n Accordingly, for a fixed `length`, the spacing between adjacent values\n in the output array changes depending on the value of `endpoint`.\n Default: true.\n\n Returns\n -------\n arr: Array\n Linearly spaced array.\n\n Examples\n --------\n > var arr = linspace( 0.0, 100.0, 6 )\n [ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n > arr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\n [ 0.0, 20.0, 40.0, 60.0, 80.0 ]\n > arr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n [ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n\n\nlinspace.assign( start, stop, out[, options] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n\n If the provided output array is empty, the function returns the provided\n output array unchanged.\n\n If the provided output array contains a single element, the function writes\n the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n function writes the `start` value, but not `stop`.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n out: ArrayLikeObject\n Output array.\n\n options: Object (optional)\n Options.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `N+1` linearly spaced values\n (where `N` is the length of the provided output array) over the interval\n `[start, stop]` and only writes `N` values to the output array, thus\n excluding `stop` from the output array. Accordingly, for a fixed `N`,\n the spacing between adjacent values in the output array changes\n depending on the value of `endpoint`. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0, 0 ];\n > var out = linspace.assign( 0, 100, arr )\n [ 0, 20, 40, 60, 80, 100 ]\n > var bool = ( arr === out )\n true\n > arr = [ 0, 0, 0, 0, 0 ];\n > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n [ 0, 20, 40, 60, 80 ]\n\n See Also\n --------\n incrspace, logspace\n","linspace.assign":"\nlinspace.assign( start, stop, out[, options] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n\n If the provided output array is empty, the function returns the provided\n output array unchanged.\n\n If the provided output array contains a single element, the function writes\n the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n function writes the `start` value, but not `stop`.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n out: ArrayLikeObject\n Output array.\n\n options: Object (optional)\n Options.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `N+1` linearly spaced values\n (where `N` is the length of the provided output array) over the interval\n `[start, stop]` and only writes `N` values to the output array, thus\n excluding `stop` from the output array. Accordingly, for a fixed `N`,\n the spacing between adjacent values in the output array changes\n depending on the value of `endpoint`. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0, 0 ];\n > var out = linspace.assign( 0, 100, arr )\n [ 0, 20, 40, 60, 80, 100 ]\n > var bool = ( arr === out )\n true\n > arr = [ 0, 0, 0, 0, 0 ];\n > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n [ 0, 20, 40, 60, 80 ]\n\n See Also\n --------\n incrspace, logspace","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of negative opinion words.\n\n Examples\n --------\n > var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n [ '2-faced', '2-faces', 'abnormal', 'abolish', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. \"Mining and Summarizing Customer\n Reviews.\" In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. \"Opinion Observer:\n Analyzing and Comparing Opinions on the Web.\" In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_POSITIVE_OPINION_WORDS_EN\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of positive opinion words.\n\n Examples\n --------\n > var list = LIU_POSITIVE_OPINION_WORDS_EN()\n [ 'a+', 'abound', 'abounds', 'abundance', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. 'Mining and Summarizing Customer\n Reviews.' In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. 'Opinion Observer:\n Analyzing and Comparing Opinions on the Web.' In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_NEGATIVE_OPINION_WORDS_EN\n","LN_HALF":"\nLN_HALF\n Natural logarithm of `1/2`.\n\n Examples\n --------\n > LN_HALF\n -0.6931471805599453\n\n","LN_PI":"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n\n Examples\n --------\n > LN_PI\n 1.1447298858494002\n\n See Also\n --------\n PI\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n\n Examples\n --------\n > LN_SQRT_TWO_PI\n 0.9189385332046728\n\n See Also\n --------\n PI\n","LN_TWO_PI":"\nLN_TWO_PI\n Natural logarithm of `2π`.\n\n Examples\n --------\n > LN_TWO_PI\n 1.8378770664093456\n\n See Also\n --------\n TWO_PI\n","LN2":"\nLN2\n Natural logarithm of `2`.\n\n Examples\n --------\n > LN2\n 0.6931471805599453\n\n See Also\n --------\n LN10\n","LN10":"\nLN10\n Natural logarithm of `10`.\n\n Examples\n --------\n > LN10\n 2.302585092994046\n\n See Also\n --------\n LN2\n","LOG2E":"\nLOG2E\n Base 2 logarithm of Euler's number.\n\n Examples\n --------\n > LOG2E\n 1.4426950408889634\n\n See Also\n --------\n E, LOG10E\n","LOG10E":"\nLOG10E\n Base 10 logarithm of Euler's number.\n\n Examples\n --------\n > LOG10E\n 0.4342944819032518\n\n See Also\n --------\n E, LOG2E\n","logspace":"\nlogspace( a, b[, length] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n\n If a `length` is not provided, the default output array length is `10`.\n\n The output array includes the values `10^a` and `10^b`.\n\n Parameters\n ----------\n a: number\n Exponent of start value.\n\n b: number\n Exponent of end value.\n\n length: integer (optional)\n Length of output array. Default: `10`.\n\n Returns\n -------\n arr: Array\n Logarithmically spaced numeric array.\n\n Examples\n --------\n > var arr = logspace( 0, 2, 6 )\n [ 1, ~2.5, ~6.31, ~15.85, ~39.81, 100 ]\n\n See Also\n --------\n incrspace, linspace\n","lowercase":"\nlowercase( str )\n Converts a string to lowercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Lowercase string.\n\n Examples\n --------\n > var out = lowercase( 'bEEp' )\n 'beep'\n\n See Also\n --------\n uncapitalize, uppercase\n","lowercaseKeys":"\nlowercaseKeys( obj )\n Converts each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'A': 1, 'B': 2 };\n > var out = lowercaseKeys( obj )\n { 'a': 1, 'b': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n","lowess":"\nlowess( x, y[, options] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n\n Parameters\n ----------\n x: Array\n x-axis values (abscissa values).\n\n y: Array\n Corresponding y-axis values (ordinate values).\n\n options: Object (optional)\n Function options.\n\n options.f: number (optional)\n Positive number specifying the smoothing span, i.e., the proportion of\n points which influence smoothing at each value. Larger values\n correspond to more smoothing. Default: `2/3`.\n\n options.nsteps: number (optional)\n Number of iterations in the robust fit (fewer iterations translates to\n faster function execution). If set to zero, the nonrobust fit is\n returned. Default: `3`.\n\n options.delta: number (optional)\n Nonnegative number which may be used to reduce the number of\n computations. Default: 1/100th of the range of `x`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array `x` is sorted. Default: `false`.\n\n Returns\n -------\n out: Object\n Object with ordered x-values and fitted values.\n\n Examples\n --------\n > var x = new Float64Array( 100 );\n > var y = new Float64Array( x.length );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = i;\n ... y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n ... }\n > var out = lowess( x, y );\n > var yhat = out.y;\n\n > var h = Plot( [ x, x ], [ y, yhat ] );\n > h.lineStyle = [ 'none', '-' ];\n > h.symbols = [ 'closed-circle', 'none' ];\n\n > h.view( 'window' );\n\n","lpad":"\nlpad( str, len[, pad] )\n Left pads a string such that the padded string has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = lpad( 'a', 5 )\n ' a'\n > out = lpad( 'beep', 10, 'b' )\n 'bbbbbbbeep'\n > out = lpad( 'boop', 12, 'beep' )\n 'beepbeepboop'\n\n See Also\n --------\n pad, rpad\n","ltrim":"\nltrim( str )\n Trims whitespace from the beginning of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n 'Beep \\t\\t\\n '\n\n See Also\n --------\n trim, rtrim\n","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common male first names.\n\n Examples\n --------\n > var list = MALE_FIRST_NAMES_EN()\n [ 'Aaron', 'Ab', 'Abba', 'Abbe', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. 'Moby Word II.' .\n\n See Also\n --------\n FEMALE_FIRST_NAMES_EN\n","map":"\nmap( arr, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = map( arr, f )\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = map( arr, f );\n > var v = out.get( 1, 1 )\n 5\n\n\nmap.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n mapRight, reduce\n","map.assign":"\nmap.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n mapRight, reduce","map2":"\nmap2( x, y, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to a new array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Input arrays must be either both array-like objects or both ndarray-like\n objects.\n\n If input arrays are array-like objects, the arrays must have the same number\n of elements.\n\n If input arrays are ndarray-like objects, the arrays must be broadcast\n compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = map2( x, y, f )\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > x = array( x, { 'shape': [ 2, 3 ] } );\n > y = array( y, { 'shape': [ 2, 3 ] } );\n > out = map2( x, y, f );\n > var v = out.get( 1, 1 )\n 6\n\n\nmap2.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n map\n","map2.assign":"\nmap2.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n map","map2d":"\nmap2d( arr, fcn[, thisArg] )\n Applies a function to each nested element in an array of arrays and assigns\n the result to a nested element in a new array of arrays.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array of arrays.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\n > var out = map2d( arr, f );\n > out[ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map3d, map4d, map5d, reduce2d\n","map2Right":"\nmap2Right( x, y, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to a new array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Input arrays must be either both array-like objects or both ndarray-like\n objects.\n\n If input arrays are array-like objects, the arrays must have the same number\n of elements.\n\n If input arrays are ndarray-like objects, the arrays must be broadcast\n compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = map2Right( x, y, f )\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > x = array( x, { 'shape': [ 2, 3 ] } );\n > y = array( y, { 'shape': [ 2, 3 ] } );\n > out = map2Right( x, y, f );\n > var v = out.get( 1, 1 )\n 6\n\n\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2Right.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2Right.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n mapRight, map2\n","map2Right.assign":"\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2Right.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2Right.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n mapRight, map2","map3d":"\nmap3d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a three-dimensional nested\n array and assigns the result to a nested element in a new three-dimensional\n nested array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject>\n Input three-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>\n Three-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\n > var out = map3d( arr, f );\n > out[ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map4d, map5d\n","map4d":"\nmap4d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a four-dimensional nested array\n and assigns the result to a nested element in a new four-dimensional nested\n array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input four-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>>\n Four-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\n > var out = map4d( arr, f );\n > out[ 0 ][ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map3d, map5d\n","map5d":"\nmap5d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a five-dimensional nested array\n and assigns the result to a nested element in a new five-dimensional nested\n array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input five-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>>>\n Five-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\n > var out = map5d( arr, f );\n > out[ 0 ][ 0 ][ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ][ 0 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map3d, map4d\n","mapArguments":"\nmapArguments( fcn, clbk[, thisArg] )\n Returns a function that applies arguments to a provided function after\n transforming arguments according to a callback function.\n\n The callback function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > function clbk( v ) { return v * 2; };\n > var bar = mapArguments( foo, clbk );\n > var out = bar( 1, 2, 3 )\n [ 2, 4, 6 ]\n\n See Also\n --------\n filterArguments\n","mapFun":"\nmapFun( fcn, n[, thisArg] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n The invoked function is provided a single argument: the invocation index\n (zero-based).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n thisArg: any (optional)\n Function execution context.\n\n Returns\n -------\n out: Array\n Array of accumulated function return values.\n\n Examples\n --------\n > function fcn( i ) { return i; };\n > var arr = mapFun( fcn, 5 )\n [ 0, 1, 2, 3, 4 ]\n\n See Also\n --------\n mapFunAsync\n","mapFunAsync":"\nmapFunAsync( fcn, n, [options,] done )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n For each iteration, the provided function is invoked with two arguments:\n\n - `index`: invocation index (starting from zero)\n - `next`: callback to be invoked upon function completion\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n done: Function\n A callback invoked upon executing a provided function `n` times or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > mapFunAsync( fcn, 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Limit number of concurrent invocations:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'limit': 2 };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Sequential invocation:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'series': true };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n See Also\n --------\n mapFun\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n See Also\n --------\n mapFun","mapKeys":"\nmapKeys( obj, transform )\n Maps keys from one object to a new object having the same values.\n\n The transform function is provided three arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n\n The value returned by a transform function should be a value which can be\n serialized as an object key.\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values specify the keys of the output object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapKeys( obj, transform )\n { 'a1': 1, 'b2': 2 }\n\n See Also\n --------\n mapValues\n","mapKeysAsync":"\nmapKeysAsync( obj, [options,] transform, done )\n Maps keys from one object to a new object having the same values.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n - `next`: a callback to be invoked after processing an object `key`\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - `key`\n - `next`\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - `key`\n - `value`\n - `next`\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `key`: transformed key\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The key returned by a transform function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapKeysAsync( obj, transform, done )\n { 'a:1': 1, 'b:2': 2 }\n\n // Limit number of concurrent invocations:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n // Process sequentially:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n See Also\n --------\n mapKeys, mapValuesAsync\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n See Also\n --------\n mapKeys, mapValuesAsync","mapReduce":"\nmapReduce( arr, initial, mapper, reducer[, thisArg] )\n Performs a map-reduce operation for each element in an array and returns the\n accumulated result.\n\n When invoked, the mapping function is provided three arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n When invoked, the reducing function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: result after applying the mapping function to the current array\n element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a single-pass map-reduce\n operation over the entire input ndarray (i.e., higher-order ndarray\n dimensions are flattened to a single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n mapper: Function\n Mapping function.\n\n reducer: Function\n Reducing function.\n\n thisArg: any (optional)\n Execution context for the reducing function.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f1 = naryFunction( base.abs, 1 );\n > var f2 = naryFunction( base.add, 2 );\n > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n > var out = mapReduce( arr, 0.0, f1, f2 )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapReduce( arr, 0.0, f1, f2 )\n 21.0\n\n See Also\n --------\n map, mapReduceRight, reduce\n","mapReduceRight":"\nmapReduceRight( arr, initial, mapper, reducer[, thisArg] )\n Performs a map-reduce operation for each element in an array while iterating\n from right to left and returns the accumulated result.\n\n When invoked, the mapping function is provided three arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n When invoked, the reducing function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: result after applying the mapping function to the current array\n element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a single-pass map-reduce\n operation over the entire input ndarray (i.e., higher-order ndarray\n dimensions are flattened to a single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n mapper: Function\n Mapping function.\n\n reducer: Function\n Reducing function.\n\n thisArg: any (optional)\n Execution context for the reducing function.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f1 = naryFunction( base.abs, 1 );\n > var f2 = naryFunction( base.add, 2 );\n > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n > var out = mapReduceRight( arr, 0.0, f1, f2 )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapReduceRight( arr, 0.0, f1, f2 )\n 21.0\n\n See Also\n --------\n mapRight, mapReduce, reduceRight\n","mapRight":"\nmapRight( arr, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = mapRight( arr, f )\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapRight( arr, f );\n > var v = out.get( 1, 1 )\n 5\n\n\nmapRight.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > mapRight.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > mapRight.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n map, reduce\n","mapRight.assign":"\nmapRight.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > mapRight.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > mapRight.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n map, reduce","mapValues":"\nmapValues( obj, transform )\n Maps values from one object to a new object having the same keys.\n\n The transform function is provided three arguments:\n\n - `value`: object value corresponding to `key`\n - `key`: object key\n - `obj`: the input object\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( value, key ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapValues( obj, transform )\n { 'a': 'a1', 'b': 'b2' }\n\n See Also\n --------\n mapKeys, omitBy, pickBy\n","mapValuesAsync":"\nmapValuesAsync( obj, [options,] transform, done )\n Maps values from one object to a new object having the same keys.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - `value`: object value corresponding to `key`\n - `key`: object key\n - `obj`: the input object\n - `next`: a callback to be invoked after processing an object `value`\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - `value`\n - `next`\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - `value`\n - `key`\n - `next`\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `value`: transformed value\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapValuesAsync( obj, transform, done )\n { 'a': 'a:1', 'b': 'b:2' }\n\n // Limit number of concurrent invocations:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n // Process sequentially:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n See Also\n --------\n mapKeysAsync, mapValues\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n See Also\n --------\n mapKeysAsync, mapValues","maskArguments":"\nmaskArguments( fcn, mask[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a specified mask.\n\n Only those arguments having a truthy mask value are applied to a provided\n function.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n mask: ArrayLikeObject\n Mask array.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > var bar = maskArguments( foo, [ 1, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n filterArguments, rejectArguments, reorderArguments, reverseArguments\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n\n Examples\n --------\n > MAX_ARRAY_LENGTH\n 4294967295\n\n See Also\n --------\n MAX_TYPED_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n\n Examples\n --------\n > MAX_TYPED_ARRAY_LENGTH\n 9007199254740991\n\n See Also\n --------\n MAX_ARRAY_LENGTH\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x, shape )\n Broadcasts an ndarray to a specified shape if and only if the specified\n shape differs from the provided ndarray's shape.\n\n If a provided ndarray has the same shape as the specified shape, the\n function returns the provided ndarray.\n\n If a provided ndarray has a different (broadcast compatible) shape than the\n specified shape, the function returns a new *read-only* ndarray view of the\n provided ndarray's data. The view is typically *not* contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to the input ndarray may affect multiple elements. If you need to\n write to the input ndarray, copy the input ndarray before broadcasting.\n\n The function throws an error if a provided ndarray is incompatible with a\n provided shape.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n shape: ArrayLikeObject\n Desired shape.\n\n Returns\n -------\n out: ndarray\n Broadcasted array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\n \n > sh = y.shape\n [ 3, 2, 2 ]\n > var v = y.get( 0, 0, 0 )\n 1\n > v = y.get( 0, 0, 1 )\n 2\n > v = y.get( 0, 1, 0 )\n 3\n > v = y.get( 0, 1, 1 )\n 4\n > v = y.get( 1, 0, 0 )\n 1\n > v = y.get( 1, 1, 0 )\n 3\n > v = y.get( 2, 0, 0 )\n 1\n > v = y.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, ndarray, broadcastArray, maybeBroadcastArrays\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays )\n Broadcasts ndarrays to a common shape.\n\n The function supports two (mutually exclusive) means of providing ndarray\n arguments:\n\n 1. Providing a single array containing ndarray arguments.\n 2. Providing ndarray arguments as separate arguments.\n\n If a provided ndarray has a shape matching the common shape, the function\n returns the provided ndarray.\n\n If a provided ndarray has a different (broadcast compatible) shape than the\n common shape, the function returns a new *read-only* ndarray view of the\n provided ndarray's data. The view is typically *not* contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to a view may affect multiple elements. If you need to write to an\n input ndarray, copy the input ndarray before broadcasting.\n\n The function throws an error if a provided broadcast-incompatible ndarrays.\n\n Parameters\n ----------\n arrays: ...ndarray|ArrayLikeObject\n Array arguments.\n\n Returns\n -------\n out: Array\n Broadcasted arrays.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = ndzeros( [ 3, 2, 2 ] )\n \n > var out = maybeBroadcastArrays( [ x, y ] )\n [ , ]\n\n // Retrieve the broadcasted \"x\" array:\n > var bx = out[ 0 ]\n \n > sh = bx.shape\n [ 3, 2, 2 ]\n\n // Retrieve broadcasted elements...\n > var v = bx.get( 0, 0, 0 )\n 1\n > v = bx.get( 0, 0, 1 )\n 2\n > v = bx.get( 0, 1, 0 )\n 3\n > v = bx.get( 0, 1, 1 )\n 4\n > v = bx.get( 1, 0, 0 )\n 1\n > v = bx.get( 1, 1, 0 )\n 3\n > v = bx.get( 2, 0, 0 )\n 1\n > v = bx.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, ndarray, broadcastArrays, maybeBroadcastArray\n","memoize":"\nmemoize( fcn[, hashFunction] )\n Returns a memoized function.\n\n The function does not set the `length` property of the returned function.\n Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n The function serializes provided arguments as a string and stores results\n using the string as an identifier. To use a custom hash function, provide a\n hash function argument.\n\n Parameters\n ----------\n fcn: Function\n Function to memoize.\n\n hashFunction: Function (optional)\n Function to map a set of arguments to a single value identifying that\n set.\n\n Returns\n -------\n out: Function\n Memoized function.\n\n Examples\n --------\n > function factorial( n ) {\n ... var prod;\n ... var i;\n ... prod = 1;\n ... for ( i = n; i > 1; i-- ) {\n ... prod *= i;\n ... }\n ... return prod;\n ... };\n > var memoized = memoize( factorial );\n > var v = memoized( 5 )\n 120\n > v = memoized( 5 )\n 120\n\n","merge":"\nmerge( target, ...source )\n Merges objects into a target object.\n\n The target object is mutated.\n\n Only plain objects are merged and extended. Other values/types are either\n deep copied or assigned.\n\n Support for deep merging class instances is inherently fragile.\n\n `Number`, `String`, and `Boolean` objects are merged as primitives.\n\n Functions are not deep copied.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n source: ...Object\n Source objects (i.e., objects to be merged into the target object).\n\n Returns\n -------\n out: Object\n Merged (target) object.\n\n Examples\n --------\n > var target = { 'a': 'beep' };\n > var source = { 'a': 'boop', 'b': 'bap' };\n > var out = merge( target, source )\n { 'a': 'boop', 'b': 'bap' }\n > var bool = ( out === target )\n true\n\n\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n See Also\n --------\n copy\n","merge.factory":"\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n See Also\n --------\n copy","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var ms = days * MILLISECONDS_IN_DAY\n 271296000\n\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var ms = hrs * MILLISECONDS_IN_HOUR\n 11304000\n\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var ms = mins * MILLISECONDS_IN_MINUTE\n 188400\n\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n Number of milliseconds in a second.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var secs = 3.14;\n > var ms = secs * MILLISECONDS_IN_SECOND\n 3140\n\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n Number of milliseconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var weeks = 3.14;\n > var ms = weeks * MILLISECONDS_IN_WEEK\n 1899072000\n\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options] )\n Returns data for Charles Joseph Minard's cartographic depiction of\n Napoleon's Russian campaign of 1812.\n\n Data includes the following:\n\n - army: army size\n - cities: cities\n - labels: map labels\n - temperature: temperature during the army's return from Russia\n - rivers: river data\n\n Temperatures are on the Réaumur scale. Multiply each temperature by `1.25`\n to convert to Celsius.\n\n River data is formatted as GeoJSON.\n\n River data is incomplete, with portions of rivers missing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n Minard's data.\n\n Examples\n --------\n > var data = MINARD_NAPOLEONS_MARCH();\n > var army = data.army\n [...]\n > var cities = data.cities\n [...]\n > var labels = data.labels\n [...]\n > var river = data.river\n {...}\n > var t = data.temperature\n [...]\n\n References\n ----------\n - Minard, Charles Joseph. 1869. *Tableaux graphiques et cartes figuratives*.\n Ecole nationale des ponts et chaussées.\n - Wilkinson, Leland. 2005. *The Grammar of Graphics*. Springer-Verlag New\n York. doi:10.1007/0-387-28695-0.\n\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n Number of minutes in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var mins = days * MINUTES_IN_DAY\n 4521.6\n\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var mins = hrs * MINUTES_IN_HOUR\n 188.4\n\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n Number of minutes in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var mins = wks * MINUTES_IN_WEEK\n 31651.2\n\n","minutesInMonth":"\nminutesInMonth( [month[, year]] )\n Returns the number of minutes in a month.\n\n By default, the function returns the number of minutes in the current month\n of the current year (according to local time). To determine the number of\n minutes for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Minutes in a month.\n\n Examples\n --------\n > var num = minutesInMonth()\n \n > num = minutesInMonth( 2 )\n \n > num = minutesInMonth( 2, 2016 )\n 41760\n > num = minutesInMonth( 2, 2017 )\n 40320\n\n // Other ways to supply month:\n > num = minutesInMonth( 'feb', 2016 )\n 41760\n > num = minutesInMonth( 'february', 2016 )\n 41760\n\n See Also\n --------\n minutesInYear\n","minutesInYear":"\nminutesInYear( [value] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n\n By default, the function returns the number of minutes in the current year\n (according to local time). To determine the number of minutes for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of minutes in a year.\n\n Examples\n --------\n > var num = minutesInYear()\n \n > num = minutesInYear( 2016 )\n 527040\n > num = minutesInYear( 2017 )\n 525600\n\n See Also\n --------\n minutesInMonth\n","MOBY_DICK":"\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n\n Each array element has the following fields:\n\n - chapter: book chapter (number or identifier)\n - title: chapter title (if available; otherwise, empty)\n - text: chapter text\n\n Returns\n -------\n out: Array\n Book text.\n\n Examples\n --------\n > var data = MOBY_DICK()\n [ {...}, {...}, ... ]\n\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n\n Returns\n -------\n out: Array\n List of month names.\n\n Examples\n --------\n > var list = MONTH_NAMES_EN()\n [ 'January', 'February', 'March', 'April', ... ]\n\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n Number of months in a year.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var yrs = 3.14;\n > var mons = yrs * MONTHS_IN_YEAR\n 37.68\n\n","moveProperty":"\nmoveProperty( source, prop, target )\n Moves a property from one object to another object.\n\n The property is deleted from the source object and the property's descriptor\n is preserved during transfer.\n\n If a source property is not configurable, the function throws an error, as\n the property cannot be deleted from the source object.\n\n Parameters\n ----------\n source: Object\n Source object.\n\n prop: string\n Property to move.\n\n target: Object\n Target object.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether operation was successful.\n\n Examples\n --------\n > var obj1 = { 'a': 'b' };\n > var obj2 = {};\n > var bool = moveProperty( obj1, 'a', obj2 )\n true\n > bool = moveProperty( obj1, 'c', obj2 )\n false\n\n","MultiSlice":"\nMultiSlice( ...slice )\n Returns a multi-slice.\n\n Parameters\n ----------\n ...slice: Slice|integer|null|undefined\n Slice arguments.\n\n Returns\n -------\n s: MultiSlice\n MultiSlice instance.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n\n\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n\n Returns\n -------\n ndims: integer\n Number of slice dimensions.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.ndims\n 3\n\n\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n\n Returns\n -------\n data: Array\n Slice data.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.data\n [ 2, , 1 ]\n\n\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n\n Returns\n -------\n str: string\n Serialized multi-slice string.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.toString()\n 'MultiSlice(2,Slice(2,10,null),1)'\n\n\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 2, 10, 1 );\n > var ms = new MultiSlice( 2, s );\n > ms.toJSON()\n {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n See Also\n --------\n ndarray, Slice\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n\n Returns\n -------\n ndims: integer\n Number of slice dimensions.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.ndims\n 3","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n\n Returns\n -------\n data: Array\n Slice data.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.data\n [ 2, , 1 ]","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n\n Returns\n -------\n str: string\n Serialized multi-slice string.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.toString()\n 'MultiSlice(2,Slice(2,10,null),1)'","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 2, 10, 1 );\n > var ms = new MultiSlice( 2, s );\n > ms.toJSON()\n {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n See Also\n --------\n ndarray, Slice","namedtypedtuple":"\nnamedtypedtuple( fields[, options] )\n Returns a named typed tuple factory.\n\n Named tuples assign a property name, and thus a meaning, to each position in\n a tuple and allow for more readable, self-documenting code.\n\n Named typed tuples can be used wherever typed arrays are used, with the\n added benefit that they allow accessing fields by both field name and\n position index.\n\n Named typed tuples may be one the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n fields: Array\n Field (property) names.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Default tuple data type. If a data type is not provided to a named typed\n tuple factory, this option specifies the underlying tuple data type.\n Default: 'float64'.\n\n options.name: string (optional)\n Tuple name. Default: 'tuple'.\n\n Returns\n -------\n factory: Function\n Named typed tuple factory.\n\n Examples\n --------\n > var opts = {};\n > opts.name = 'Point';\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var tuple = factory();\n\n\nfactory()\n Returns a named typed tuple of the default data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory();\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory( dtype )\n Returns a named typed tuple of the specified data type.\n\n Parameters\n ----------\n dtype: string\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( 'int32' );\n > p.x\n 0\n > p.y\n 0\n > p[ 0 ]\n 0\n > p[ 1 ]\n 0\n\n\nfactory( typedarray[, dtype] )\n Creates a named typed tuple from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a named typed tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( Float64Array[ 1.0, -1.0 ] );\n > p.x\n 1.0\n > p.y\n -1.0\n > p[ 0 ]\n 1.0\n > p[ 1 ]\n -1.0\n\n\nfactory( obj[, dtype] )\n Creates a named typed tuple from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a named typed\n tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( [ 1, -1 ], 'int32' );\n > p.x\n 1\n > p.y\n -1\n > p[ 0 ]\n 1\n > p[ 1 ]\n -1\n\n\nfactory( buffer[, byteOffset][, dtype] )\n Returns a named typed tuple view of an ArrayBuffer.\n\n The view length equals the number of tuple fields.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first tuple element.\n Default: 0.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var buf = new ArrayBuffer( 16 );\n > var p = factory( buf, 4, 'float32' );\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory.from( src[, map[, thisArg]] )\n Creates a new named typed tuple from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n - field: tuple field.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of tuple elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > function mapFcn( v ) { return v * 2.0; };\n > var p = factory.from( [ 1.0, -1.0 ], mapFcn );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.fromObject( obj[, map[, thisArg]] )\n Creates a new named typed tuple from an object containing tuple fields.\n\n A callback is provided the following arguments:\n\n - value: source object tuple field value.\n - field: source object tuple field name.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n map: Function (optional)\n Callback to invoke for each source object tuple field.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.fromObject( { 'x': 2.0, 'y': -2.0 } );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.of( element0[, element1[, ...elementN]] )\n Creates a new named typed tuple from a variable number of arguments.\n\n The number of arguments *must* equal the number of tuple fields.\n\n Parameters\n ----------\n element0: number\n Tuple element.\n\n element1: number (optional)\n Tuple element.\n\n elementN: number (optional)\n Tuple elements.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.of( 2.0, -2.0 );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\ntuple.BYTES_PER_ELEMENT\n Size (in bytes) of each tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.BYTES_PER_ELEMENT\n 8\n\n\ntuple.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.buffer\n \n\n\ntuple.byteLength\n Length (in bytes) of the tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteLength\n 16\n\n\ntuple.byteOffset\n Offset (in bytes) of a tuple from the start of its underlying ArrayBuffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteOffset\n 0\n\n\ntuple.length\n Tuple length (i.e., number of elements).\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.length\n 2\n\n\ntuple.name\n Tuple name.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.name\n 'Point'\n\n\ntuple.fields\n Returns the list of tuple fields.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fields\n [ 'x', 'y' ]\n\n\ntuple.orderedFields\n Returns the list of tuple fields in index order.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.sort();\n > p[ 0 ]\n -1.0\n > p.fields\n [ 'x', 'y' ]\n > p.orderedFields\n [ 'y', 'x' ]\n\n\ntuple.copyWithin( target, start[, end] )\n Copies a sequence of elements within the tuple starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > p.copyWithin( 3, 0, 2 );\n > p.w\n 2.0\n > p.v\n -2.0\n\n\ntuple.entries()\n Returns an iterator for iterating over tuple key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple key-value pairs.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.entries();\n > it.next().value\n [ 0, 'x', 1.0 ]\n > it.next().value\n [ 1, 'y', -1.0 ]\n > it.next().done\n true\n\n\ntuple.every( predicate[, thisArg] )\n Tests whether all tuple elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all tuple elements pass.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > p.every( predicate )\n false\n\n\ntuple.fieldOf( searchElement[, fromIndex] )\n Returns the field of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var f = p.fieldOf( 2.0 )\n undefined\n > f = p.fieldOf( -1.0 )\n 'z'\n\n\ntuple.fill( value[, start[, end]] )\n Fills a tuple from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last tuple element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fill( 2.0 );\n > p.x\n 2.0\n > p.y\n 2.0\n\n\ntuple.filter( predicate[, thisArg] )\n Creates a new tuple which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n If a predicate function does not return a truthy value for any tuple\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters tuple elements. If a predicate function\n returns a truthy value, a tuple element is included in the output tuple;\n otherwise, a tuple element is not included in the output tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var p2 = p1.filter( predicate );\n > p2.fields\n [ 'x', 'y' ]\n\n\ntuple.find( predicate[, thisArg] )\n Returns the first tuple element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = p.find( predicate )\n -1.0\n\n\ntuple.findField( predicate[, thisArg] )\n Returns the field of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var f = p.findField( predicate )\n 'z'\n\n\ntuple.findIndex( predicate[, thisArg] )\n Returns the index of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = p.findIndex( predicate )\n 2\n\n\ntuple.forEach( fcn[, thisArg] )\n Invokes a callback for each tuple element.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each tuple element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > var str = ' ';\n > function fcn( v, i, f ) { str += f + '=' + v + ' '; };\n > p.forEach( fcn );\n > str\n ' x=1 y=0 z=-1 '\n\n\ntuple.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether a tuple includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a tuple includes a search element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var bool = p.includes( 2.0 )\n false\n > bool = p.includes( -1.0 )\n true\n\n\ntuple.indexOf( searchElement[, fromIndex] )\n Returns the index of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var idx = p.indexOf( 2.0 )\n -1\n > idx = p.indexOf( -1.0 )\n 2\n\n\ntuple.ind2key( ind )\n Converts a tuple index to a field name.\n\n If provided an out-of-bounds index, the method returns `undefined`.\n\n Parameters\n ----------\n ind: integer\n Tuple index. If less than zero, the method resolves the index relative\n to the last tuple element.\n\n Returns\n -------\n field: string|undefined\n Field name.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.ind2key( 1 )\n 'y'\n > p.ind2key( 100 )\n undefined\n\n\ntuple.join( [separator] )\n Serializes a tuple by joining all tuple elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating tuple elements. Default: ','.\n\n Returns\n -------\n str: string\n Tuple serialized as a string.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > p.join( '|' )\n '1|0|-1'\n\n\ntuple.keys()\n Returns an iterator for iterating over tuple keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple keys.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.keys();\n > it.next().value\n [ 0, 'x' ]\n > it.next().value\n [ 1, 'y' ]\n > it.next().done\n true\n\n\ntuple.key2ind( field )\n Converts a field name to a tuple index.\n\n If provided an unknown field name, the method returns `-1`.\n\n Parameters\n ----------\n field: string\n Tuple field name.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.key2ind( 'y' )\n 1\n\n\ntuple.lastFieldOf( searchElement[, fromIndex] )\n Returns the field of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var f = p.lastFieldOf( 2.0 )\n undefined\n > f = p.lastFieldOf( 0.0 )\n 'w'\n\n\ntuple.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = p.lastIndexOf( 2.0 )\n -1\n > idx = p.lastIndexOf( 0.0 )\n 3\n\n\ntuple.map( fcn[, thisArg] )\n Maps each tuple element to an element in a new tuple.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n Parameters\n ----------\n fcn: Function\n Function which maps tuple elements to elements in the new tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var p2 = p1.map( fcn );\n > p2.x\n 2.0\n > p2.y\n 0.0\n > p2.z\n -2.0\n\n\ntuple.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first tuple element as the first argument and the second tuple\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduce( fcn, 0.0 )\n 2.0\n\n\ntuple.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last tuple element as the first argument and the second-to-last\n tuple element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduceRight( fcn, 0.0 )\n 2.0\n\n\ntuple.reverse()\n Reverses a tuple *in-place*.\n\n This method mutates the tuple on which the method is invoked.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.x\n 1.0\n > p.reverse();\n > p[ 0 ]\n -1.0\n > p.x\n 1.0\n\n\ntuple.set( arr[, offset] )\n Sets tuple elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing tuple values to set.\n\n offset: integer (optional)\n Tuple index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 1 ]\n 0.0\n > p.y\n 0.0\n > p.set( [ -2.0, 2.0 ], 1 );\n > p[ 1 ]\n -2.0\n > p.y\n -2.0\n > p[ 2 ]\n 2.0\n > p.z\n 2.0\n\n\ntuple.slice( [begin[, end]] )\n Copies tuple elements to a new tuple with the same underlying data type as\n the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > p1.fields\n [ 'x', 'y', 'z' ]\n > var p2 = p1.slice( 1 );\n > p2.fields\n [ 'y', 'z' ]\n > p2.y\n 0.0\n > p2.z\n -1.0\n\n\ntuple.some( predicate[, thisArg] )\n Tests whether at least one tuple element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one tuple element passes.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > p.some( predicate )\n true\n\n\ntuple.sort( [compareFunction] )\n Sorts a tuple *in-place*.\n\n Sorting a tuple does *not* affect field assignments. Accessing a tuple field\n before and after sorting will always return the same tuple element. However,\n this behavior is generally not true when accessing tuple elements according\n to tuple index. In summary, sorting affects index order but not field\n assignments.\n\n The comparison function is provided two tuple elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the tuple on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > p.sort();\n > p.orderedFields\n [ 'v', 'y', 'z', 'x', 'w' ]\n > p[ 0 ]\n -2.0\n > p.x\n 1.0\n > p[ 1 ]\n -1.0\n > p.y\n -1.0\n > p.key2ind( 'x' )\n 3\n\n\ntuple.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n arr: TypedArray\n A new typed array view.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr = p.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n > arr.length\n 3\n\n\ntuple.subtuple( [begin[, end]] )\n Creates a new named typed tuple over the same underlying ArrayBuffer and\n with the same underlying data type as the host tuple.\n\n If the function is unable to resolve indices to a non-empty tuple\n subsequence, the function returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray|null\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p1 = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var p2 = p1.subtuple( 2 );\n > p2.fields\n [ 'z', 'w', 'v' ]\n > p2[ 0 ]\n 0.0\n > p2.z\n 0.0\n > p2[ 1 ]\n 2.0\n > p2.w\n 2.0\n > p2[ 2 ]\n -2.0\n > p2.v\n -2.0\n > p2.length\n 3\n\n\ntuple.toJSON()\n Serializes a tuple as JSON.\n\n Returns\n -------\n obj: Object\n A tuple JSON representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toJSON()\n { 'x': 1.0, 'y': -1.0, 'z': 0.0 }\n\n\ntuple.toLocaleString( [locales[, options]] )\n Serializes a tuple as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ], 'int32' );\n > p.toLocaleString()\n '1,-1,0'\n\n\ntuple.toString()\n Serializes a tuple as a string.\n\n Returns\n -------\n str: string\n A tuple string representation.\n\n Examples\n --------\n > opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toString()\n 'Point(x=1, y=-1, z=0)'\n\n\ntuple.values()\n Returns an iterator for iterating over tuple elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple elements.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n See Also\n --------\n typedarray\n","NAN":"\nNAN\n Double-precision floating-point NaN.\n\n Examples\n --------\n > NAN\n NaN\n\n See Also\n --------\n FLOAT32_NAN\n","naryFunction":"\nnaryFunction( fcn, arity[, thisArg] )\n Returns a function that applies a specified number of arguments to a\n provided function.\n\n The returned function *always* invokes the wrapped function with a specified\n number of arguments, even when the returned function is provided fewer\n arguments.\n\n The value for the missing arguments is equal to `undefined`.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n arity: integer\n Number of arguments.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = naryFunction( foo, 2 );\n > var out = bar( 1, 2, 3 )\n [ 1, 2, undefined ]\n\n See Also\n --------\n maskArguments, pickArguments\n","nativeClass":"\nnativeClass( value )\n Returns a string value indicating a specification defined classification of\n an object.\n\n The function is *not* robust for ES2015+ environments. In ES2015+,\n `Symbol.toStringTag` allows overriding the default description of an object.\n While measures are taken to uncover the default description, such measures\n can be thwarted. While this function remains useful for type-checking, be\n aware that value impersonation is possible. Where possible, prefer functions\n tailored to checking for particular value types, as specialized functions\n are better equipped to address `Symbol.toStringTag`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n String value indicating a specification defined classification of the\n input value.\n\n Examples\n --------\n > var str = nativeClass( 'a' )\n '[object String]'\n > str = nativeClass( 5 )\n '[object Number]'\n > function Beep(){};\n > str = nativeClass( new Beep() )\n '[object Object]'\n\n See Also\n --------\n constructorName, typeOf\n","ndarray":"\nndarray( dtype, buffer, shape, strides, offset, order[, options] )\n Returns an ndarray.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n ndarray: ndarray\n ndarray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nndarray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, FancyArray\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","ndarray.prototype.data":"\nndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","ndarray.prototype.flags":"\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","ndarray.prototype.length":"\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","ndarray.prototype.offset":"\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","ndarray.prototype.order":"\nndarray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","ndarray.prototype.shape":"\nndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","ndarray.prototype.strides":"\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","ndarray.prototype.get":"\nndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","ndarray.prototype.iget":"\nndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","ndarray.prototype.set":"\nndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","ndarray.prototype.iset":"\nndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","ndarray.prototype.toString":"\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, FancyArray","ndarray2array":"\nndarray2array( x )\n Converts an ndarray to a generic array.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n Returns\n -------\n out: Array|Array\n Generic array (which may include nested arrays).\n\n Examples\n --------\n > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var out = ndarray2array( arr )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n array, ndarray\n","ndarrayCastingModes":"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n\n The output array contains the following modes:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow \"safe\" casts.\n - 'mostly-safe': allow \"safe\" casts and, for floating-point data types,\n downcasts.\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers and\n floats).\n\n Returns\n -------\n out: Array\n List of ndarray casting modes.\n\n Examples\n --------\n > var out = ndarrayCastingModes()\n [ 'none', 'equiv', 'safe', 'mostly-safe', 'same-kind', 'unsafe' ]\n\n See Also\n --------\n array, ndarray\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x )\n Returns the underlying data buffer of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: ArrayLikeObject\n Underlying data buffer.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n \n\n See Also\n --------\n array, ndarray, ndarrayDataType\n","ndarrayDataType":"\nndarrayDataType( x )\n Returns the data type of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n dt: string\n Data type.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n 'float64'\n\n See Also\n --------\n array, ndarray, ndarrayDataTypes\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind] )\n Returns a list of ndarray data types.\n\n The function supports the following data type \"kinds\":\n\n - floating_point: floating-point data types.\n - real_floating_point: real-valued floating-point data types.\n - complex_floating_point: complex-valued floating-point data types.\n - integer: integer data types.\n - signed_integer: signed integer data types.\n - unsigned_integer: unsigned integer data types.\n - real: real-valued data types.\n - numeric: numeric data types.\n - typed: typed data types.\n - all: all data types.\n\n Parameters\n ----------\n kind: string (optional)\n Data type kind.\n\n Returns\n -------\n out: Array\n List of ndarray data types.\n\n Examples\n --------\n > var out = ndarrayDataTypes()\n \n > out = ndarrayDataTypes( 'floating_point' )\n \n\n See Also\n --------\n arrayDataTypes, array, ndarray, typedarrayDataTypes\n","ndarrayDispatch":"\nndarrayDispatch( fcns, types, data, nargs, nin, nout )\n Returns an ndarray function interface which performs multiple dispatch.\n\n An ndarray function interface has the following signature:\n\n f( x, y, ... )\n\n where\n\n - x: ndarray.\n - y: ndarray.\n - ...: additional ndarrays.\n\n The number of parameters is derived from `nargs`, the number of input\n ndarrays is derived from `nin`, and the number of output ndarrays is derived\n from `nout`.\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of ndarray functions. An ndarray function should have the following\n signature:\n\n f( arrays, data )\n\n where\n\n - arrays: array containing input and output ndarrays.\n - data: ndarray function data (e.g., a callback).\n\n For convenience, a single ndarray function may be provided which will be\n invoked whenever the ndarray argument data types match a sequence of\n types in `types`. Providing a single ndarray function is particularly\n convenient for the case where, regardless of array data types,\n traversing arrays remains the same, but the ndarray function `data`\n differs (e.g., callbacks which differ based on the array data types).\n\n types: ArrayLikeObject\n One-dimensional list of ndarray argument data types.\n\n data: ArrayLikeObject|null\n ndarray function data (e.g., callbacks). If `null`, a returned ndarray\n function interface does **not** provide a `data` argument to an invoked\n ndarray function.\n\n nargs: integer\n Total number of ndarray function interface arguments.\n\n nin: integer\n Number of input ndarrays.\n\n nout: integer\n Number of output ndarrays.\n\n Returns\n -------\n fcn: Function\n ndarray function interface.\n\n Examples\n --------\n // Define ndarray argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of ndarray function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create an ndarray function interface for applying unary callbacks:\n > var f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\n\n // Create an input ndarray:\n > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n // Create an output ndarray:\n > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n // Compute the element-wise absolute value:\n > f( x, y );\n > ybuf\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n array, ndarray\n","ndarrayFlag":"\nndarrayFlag( x, name )\n Returns a specified flag for a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n name: string|symbol\n Flag name.\n\n Returns\n -------\n out: any\n Flag value.\n\n Examples\n --------\n > var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n \n\n See Also\n --------\n array, ndarray, ndarrayFlags\n","ndarrayFlags":"\nndarrayFlags( x )\n Returns the flags of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Object\n Flags.\n\n Examples\n --------\n > var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n {...}\n\n See Also\n --------\n array, ndarray, ndarrayFlag\n","ndarrayIndexModes":"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n\n The output array contains the following modes:\n\n - throw: specifies that a function should throw an error when an index is\n outside a restricted interval.\n - normalize: specifies that a function should normalize negative indices and\n throw an error when an index is outside a restricted interval.\n - wrap: specifies that a function should wrap around an index using modulo\n arithmetic.\n - clamp: specifies that a function should set an index less than zero to\n zero (minimum index) and set an index greater than a maximum index value to\n the maximum possible index.\n\n Returns\n -------\n out: Array\n List of ndarray index modes.\n\n Examples\n --------\n > var out = ndarrayIndexModes()\n [ 'throw', 'normalize', 'clamp', 'wrap' ]\n\n See Also\n --------\n array, ndarray\n","ndarrayMinDataType":"\nndarrayMinDataType( value )\n Returns the minimum ndarray data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n real numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n ndarray data type.\n\n Examples\n --------\n > var dt = ndarrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = ndarrayMinDataType( 3 )\n 'uint8'\n > dt = ndarrayMinDataType( -3 )\n 'int8'\n > dt = ndarrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast and, for floating-point data types, can be downcast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be cast.\n\n Examples\n --------\n > var out = ndarrayMostlySafeCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts, ndarraySameKindCasts\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype] )\n Returns the next larger ndarray data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = ndarrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayOffset":"\nndarrayOffset( x )\n Returns the index offset specifying the underlying buffer index of the first\n iterated ndarray element.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Index offset.\n\n Examples\n --------\n > var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n 0\n\n See Also\n --------\n array, ndarray, ndarrayShape, ndarrayStrides\n","ndarrayOrder":"\nndarrayOrder( x )\n Returns the layout order of a provided ndarray.\n\n If unable to resolve a layout order, the function returns `null`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: string|null\n Layout order.\n\n Examples\n --------\n > var opts = { 'order': 'row-major' };\n > var dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n 'row-major'\n\n See Also\n --------\n array, ndarray, ndarrayOrders, ndarrayShape, ndarrayStrides\n","ndarrayOrders":"\nndarrayOrders()\n Returns a list of ndarray orders.\n\n The output array contains the following orders:\n\n - row-major: row-major (C-style) order.\n - column-major: column-major (Fortran-style) order.\n\n Returns\n -------\n out: Array\n List of ndarray orders.\n\n Examples\n --------\n > var out = ndarrayOrders()\n [ 'row-major', 'column-major' ]\n\n See Also\n --------\n array, ndarray\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1, dtype2] )\n Returns the ndarray data type with the smallest size and closest \"kind\" to\n which ndarray data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: any (optional)\n ndarray data type value.\n\n dtype2: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = ndarrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = ndarraySafeCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySameKindCasts\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same \"kind\".\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast or cast\n within the same \"kind\".\n\n Examples\n --------\n > var out = ndarraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarrayShape":"\nndarrayShape( x )\n Returns the shape of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Array\n Shape.\n\n Examples\n --------\n > var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n [ 3, 3, 3 ]\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayStrides\n","ndarrayStride":"\nndarrayStride( x, dim )\n Returns the stride along a specified dimension for a provided ndarray.\n\n A \"stride\" is the linear distance (i.e., number of elements) between\n adjacent elements along a specified dimension.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n Returns\n -------\n out: integer\n Stride.\n\n Examples\n --------\n > var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n 9\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape, ndarrayStrides\n","ndarrayStrides":"\nndarrayStrides( x )\n Returns the strides of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Array\n Strides.\n\n Examples\n --------\n > var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n [ 9, 3, 1 ]\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape\n","ndat":"\nndat( x[, ...indices] )\n Returns an ndarray element.\n\n Negative indices are resolved relative to the last element along the\n respective dimension, with the last element corresponding to `-1`.\n\n If provided out-of-bounds indices, the function always returns `undefined`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n indices: ...integer (optional)\n Index arguments. The number of index arguments must equal the number of\n dimensions.\n\n Returns\n -------\n out: any\n Element value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > ndat( x, 0, 1 )\n 2\n > ndat( x, 1, 0 )\n 3\n\n See Also\n --------\n array, ndslice\n","ndempty":"\nndempty( shape[, options] )\n Returns an uninitialized ndarray having a specified shape and data type.\n\n In browser environments, the function always returns zero-filled ndarrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n For returned ndarrays whose underlying memory is *not* initialized, memory\n contents are unknown and may contain *sensitive* data.\n\n Parameters\n ----------\n shape: ArrayLikeObject|integer\n Array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Underlying data type. Default: 'float64'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = ndempty( [ 2, 2 ] )\n \n > var sh = arr.shape\n [ 2, 2 ]\n > var dt = arr.dtype\n 'float64'\n\n See Also\n --------\n ndemptyLike, ndzeros\n","ndemptyLike":"\nndemptyLike( x[, options] )\n Returns an uninitialized ndarray having the same shape and data type as a\n provided input ndarray.\n\n The function infers the following attributes from the input array:\n\n - shape: array shape.\n - dtype: underlying array data type.\n - order: whether the array order is row-major (C-style) or column-major\n (Fortran-style).\n\n In browser environments, the function always returns zero-filled ndarrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n For returned ndarrays whose underlying memory is *not* initialized, memory\n contents are unknown and may contain *sensitive* data.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.shape: ArrayLikeObject|integer (optional)\n Array shape. Overrides the input array's inferred shape.\n\n options.dtype: string (optional)\n Array data type. Overrides the input array's inferred data type.\n\n options.order: string (optional)\n Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n style)). Overrides the input array's inferred order.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var dt = x.dtype\n 'float64'\n > var y = ndemptyLike( x )\n \n > sh = y.shape\n [ 2, 2 ]\n > dt = y.dtype\n 'float64'\n\n See Also\n --------\n ndempty, ndzerosLike\n","ndims":"\nndims( x )\n Returns the number of ndarray dimensions.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Number of dimensions.\n\n Examples\n --------\n > var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n 3\n\n See Also\n --------\n array, ndarray, numel, ndarrayShape\n","nditerColumnEntries":"\nnditerColumnEntries( x[, options] )\n Returns an iterator which returns [index, column] pairs for each column in a\n matrix (or stack of matrices).\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerColumnEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ null, 0 ]\n > ndarray2array( v[ 1 ] )\n [ 1, 3 ]\n > v = it.next().value;\n > v[ 0 ]\n [ null, 1 ]\n > ndarray2array( v[ 1 ] )\n [ 2, 4 ]\n\n See Also\n --------\n nditerColumns, nditerEntries, nditerRowEntries, ndslice\n","nditerColumns":"\nnditerColumns( x[, options] )\n Returns an iterator which iterates over each column in a matrix (or stack of\n matrices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerColumns( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ 1, 3 ]\n > v = it.next().value;\n > ndarray2array( v )\n [ 2, 4 ]\n\n See Also\n --------\n nditerColumnEntries, nditerRows, ndslice\n","nditerEntries":"\nnditerEntries( x[, options] )\n Returns an iterator which returns [index, value] pairs for each element in a\n provided ndarray.\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator returns values\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manor, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerEntries( x );\n > var v = it.next().value\n [ [ 0, 0 ], 1 ]\n > v = it.next().value\n [ [ 0, 1 ], 2 ]\n\n See Also\n --------\n ndarray, nditerIndices, nditerValues\n","nditerIndices":"\nnditerIndices( shape[, options] )\n Returns an iterator which returns indices for use indexing into an ndarray\n having a specified shape.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n shape: Array\n Input shape.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator iterates over\n the last dimensions first, thus corresponding to iteration over\n contiguous data stored in row-major order. Must be either 'row-major'\n or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerIndices( x.shape );\n > var v = it.next().value\n [ 0, 0 ]\n > v = it.next().value\n [ 0, 1 ]\n\n See Also\n --------\n ndarray, nditerEntries, nditerValues\n","nditerMatrices":"\nnditerMatrices( x[, options] )\n Returns an iterator which iterates over each matrix in a stack of matrices.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerMatrices( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrixEntries, nditerRows, ndslice\n","nditerMatrixEntries":"\nnditerMatrixEntries( x[, options] )\n Returns an iterator which returns [index, matrix] pairs for each matrix in a\n stack of matrices.\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerMatrixEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ 0, null, null ]\n > ndarray2array( v[ 1 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumnEntries, nditerEntries, nditerMatrices, nditerRowEntries, ndslice\n","nditerRowEntries":"\nnditerRowEntries( x[, options] )\n Returns an iterator which returns [index, row] pairs for each row in a\n matrix (or stack of matrices).\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerRowEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ 0, null ]\n > ndarray2array( v[ 1 ] )\n [ 1, 2 ]\n > v = it.next().value;\n > v[ 0 ]\n [ 1, null ]\n > ndarray2array( v[ 1 ] )\n [ 3, 4 ]\n\n See Also\n --------\n nditerColumnEntries, nditerEntries, nditerRows, ndslice\n","nditerRows":"\nnditerRows( x[, options] )\n Returns an iterator which iterates over each row in a matrix (or stack of\n matrices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerRows( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ 1, 2 ]\n > v = it.next().value;\n > ndarray2array( v )\n [ 3, 4 ]\n\n See Also\n --------\n nditerColumns, nditerRowEntries, ndslice\n","nditerValues":"\nnditerValues( x[, options] )\n Returns an iterator which returns individual elements from a provided\n ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator returns values\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manor, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerValues( x );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n ndarray, nditerEntries, nditerIndices\n","ndslice":"\nndslice( x, ...s[, options] )\n Returns a read-only view of an input ndarray.\n\n The function supports three (mutually exclusive) means of providing slice\n arguments:\n\n 1. Providing a single MultiSlice object.\n 2. Providing a single array containing slice arguments.\n 3. Providing slice arguments as separate arguments.\n\n An individual slice argument must be either a Slice, an integer, null, or\n undefined.\n\n In all cases, the number of slice dimensions must match the number of array\n dimensions.\n\n If providing a MultiSlice object or an array of slice arguments, no other\n slice arguments should be provided.\n\n Mixing function invocation styles (e.g., providing multiple MultiSlice\n objects or providing an array of slice arguments followed by additional\n slice arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n Slice arguments.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var s = new MultiSlice( null, 1 )\n \n > var y = ndslice( x, s )\n \n > y.shape\n [ 2 ]\n > ndarray2array( y )\n [ 2, 4 ]\n\n See Also\n --------\n array, ndat, ndarray, ndsliceAssign, ndsliceDimension\n","ndsliceAssign":"\nndsliceAssign( x, y, ...s[, options] )\n Assigns element values from a broadcasted input ndarray to corresponding\n elements in an output ndarray view.\n\n The function supports three (mutually exclusive) means of providing slice\n arguments:\n\n 1. Providing a single MultiSlice object.\n 2. Providing a single array containing slice arguments.\n 3. Providing slice arguments as separate arguments.\n\n An individual slice argument must be either a Slice, an integer, null, or\n undefined.\n\n In all cases, the number of slice dimensions must match the number of output\n array dimensions.\n\n If providing a MultiSlice object or an array of slice arguments, no other\n slice arguments should be provided.\n\n Mixing function invocation styles (e.g., providing multiple MultiSlice\n objects or providing an array of slice arguments followed by additional\n slice arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array. The input array must be broadcast compatible with the\n output array view and must have a data type which can be safely cast to\n the output array data type. Floating-point data types (both real and\n complex) are allowed to downcast to a lower precision data type of the\n same kind (e.g., element values from a 'float64' input array can be\n assigned to corresponding elements in a 'float32' output array).\n\n y: ndarray\n Output array. The output array must be writable.\n\n s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n Slice arguments.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var y = ndzeros( [ 2, 2 ] )\n \n > var x = scalar2ndarray( 3.0 )\n \n > var s = new MultiSlice( null, 1 )\n \n > var out = ndsliceAssign( x, y, s )\n \n > var bool = ( out === y )\n true\n > ndarray2array( y )\n [ [ 0.0, 3.0 ], [ 0.0, 3.0 ] ]\n\n See Also\n --------\n array, ndarray, ndslice\n","ndsliceDimension":"\nndsliceDimension( x, dim, slice[, options] )\n Returns a read-only view of an input ndarray when sliced along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n slice: Slice|integer|null|undefined\n Slice object or an integer. If provided `null` or `undefined`, the\n returned view includes all elements along a specified dimension. If\n provided an integer less than zero, the corresponding element along the\n specified dimension is resolved relative to the last element along that\n dimension. For negative integers, the last element corresponds to the\n value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimension( x, 1, 1 )\n \n > y.shape\n [ 2 ]\n > ndarray2array( y )\n [ 2, 4 ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceDimensionTo\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x, dim, start[, options] )\n Returns a read-only shifted view of an input ndarray along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n start: integer\n Starting index (inclusive). If less than zero, the corresponding element\n along the specified dimension is resolved relative to the last element\n along that dimension. For negative integers, the last element\n corresponds to the value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimensionFrom( x, 1, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 2 ], [ 4 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionTo, ndsliceFrom\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x, dim, stop[, options] )\n Returns a read-only truncated view of an input ndarray along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n stop: integer\n Ending index (exclusive). If less than zero, the corresponding element\n along the specified dimension is resolved relative to the last element\n along that dimension. For negative integers, the last element\n corresponds to the value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimensionTo( x, 1, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 1 ], [ 3 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionFrom, ndsliceTo\n","ndsliceFrom":"\nndsliceFrom( x, ...start[, options] )\n Returns a read-only shifted view of an input ndarray.\n\n The function supports two (mutually exclusive) means of providing starting\n indices:\n\n 1. Providing a single array containing start arguments.\n 2. Providing start arguments as separate arguments.\n\n An individual start argument must be either an integer, null, or undefined.\n\n In all cases, the number of start indices must match the number of array\n dimensions.\n\n If providing an array of start arguments, no other start arguments should be\n provided.\n\n Mixing function invocation styles (e.g., providing an array of start\n arguments followed by additional start arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n start: ...null|void|integer\n Starting indices (inclusive). If an element is either `null` or\n `undefined`, the function returns a view containing all elements along\n that dimension. A negative integer indicates to resolve a starting index\n relative to the last element along a corresponding dimension, with the\n last element having index `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceFrom( x, 0, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 2 ], [ 4 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceTo\n","ndsliceTo":"\nndsliceTo( x, ...stop[, options] )\n Returns a read-only truncated view of an input ndarray.\n\n The function supports two (mutually exclusive) means of providing ending\n indices:\n\n 1. Providing a single array containing stop arguments.\n 2. Providing stop arguments as separate arguments.\n\n An individual stop argument must be either an integer, null, or undefined.\n\n In all cases, the number of stop indices must match the number of array\n dimensions.\n\n If providing an array of stop arguments, no other stop arguments should be\n provided.\n\n Mixing function invocation styles (e.g., providing an array of stop\n arguments followed by additional stop arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n stop: ...null|void|integer\n Ending indices (exclusive). If an ending index is either `null` or\n `undefined`, the function returns a view containing all elements along\n that dimension. A negative integer indicates to resolve an ending index\n relative to the last element along a corresponding dimension, with the\n last element having index `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceTo( x, 1, 1 )\n \n > y.shape\n [ 1, 1 ]\n > ndarray2array( y )\n [ [ 1 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionTo, ndsliceFrom\n","ndzeros":"\nndzeros( shape[, options] )\n Returns a zero-filled ndarray having a specified shape and data type.\n\n Parameters\n ----------\n shape: ArrayLikeObject|integer\n Array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Underlying data type. Default: 'float64'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = ndzeros( [ 2, 2 ] )\n \n > var sh = arr.shape\n [ 2, 2 ]\n > var dt = arr.dtype\n 'float64'\n\n See Also\n --------\n ndempty, ndzerosLike\n","ndzerosLike":"\nndzerosLike( x[, options] )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n\n The function infers the following attributes from the input array:\n\n - shape: array shape.\n - dtype: underlying array data type.\n - order: whether the array order is row-major (C-style) or column-major\n (Fortran-style).\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.shape: ArrayLikeObject|integer (optional)\n Array shape. Overrides the input array's inferred shape.\n\n options.dtype: string (optional)\n Array data type. Overrides the input array's inferred data type.\n\n options.order: string (optional)\n Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n style)). Overrides the input array's inferred order.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var dt = x.dtype\n 'float64'\n > var y = ndzerosLike( x )\n \n > sh = y.shape\n [ 2, 2 ]\n > dt = y.dtype\n 'float64'\n\n See Also\n --------\n ndemptyLike, ndzeros\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str[, fromIndex] )\n Returns the next extended grapheme cluster break in a string after a\n specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n fromIndex: integer (optional)\n Position. Default: 0.\n\n Returns\n -------\n out: integer\n Next extended grapheme cluster break position.\n\n Examples\n --------\n > var out = nextGraphemeClusterBreak( 'last man standing', 4 )\n 5\n > out = nextGraphemeClusterBreak( 'presidential election', 8 )\n 9\n > out = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\n 3\n > out = nextGraphemeClusterBreak( '🌷' )\n -1\n\n See Also\n --------\n numGraphemeClusters, prevGraphemeClusterBreak","nextTick":"\nnextTick( clbk[, ...args] )\n Adds a callback to the \"next tick queue\".\n\n The queue is fully drained after the current operation on the JavaScript\n stack runs to completion and before the event loop is allowed to continue.\n\n Parameters\n ----------\n clbk: Function\n Callback to invoke.\n\n ...args: any (optional)\n Arguments to provide to the callback upon invocation.\n\n Examples\n --------\n > function f() { console.log( 'beep' ); };\n > nextTick( f )\n\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n\n Returns\n -------\n out: Array\n Nightingale's data.\n\n Examples\n --------\n > var data = NIGHTINGALES_ROSE()\n [{...}, {...}, ...]\n\n References\n ----------\n - Nightingale, Florence. 1859. *A contribution to the sanitary history of\n the British army during the late war with Russia*. London, United Kingdom:\n John W. Parker and Son..\n\n","NINF":"\nNINF\n Double-precision floating-point negative infinity.\n\n Examples\n --------\n > NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_NINF, PINF\n","NODE_VERSION":"\nNODE_VERSION\n Node version.\n\n Examples\n --------\n > NODE_VERSION\n \n\n","none":"\nnone( collection )\n Tests whether all elements in a collection are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are falsy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0 ];\n > var bool = none( arr )\n true\n\n See Also\n --------\n any, every, forEach, noneBy, some\n","noneBy":"\nnoneBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = noneBy( arr, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, none, noneByRight, someBy\n","noneByAsync":"\nnoneByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync\n","noneByAsync.factory":"\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync","noneByRight":"\nnoneByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ -1, -2, -3, -4 ];\n > var bool = noneByRight( arr, positive )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, none, noneBy, someByRight\n","noneByRightAsync":"\nnoneByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync","nonEnumerableProperties":"\nnonEnumerableProperties( value )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own non-enumerable properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var props = nonEnumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerableProperties, inheritedNonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited non-enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = nonEnumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerablePropertiesIn, inheritedNonEnumerableProperties, nonEnumerableProperties, propertiesIn\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value )\n Returns an array of an object's own non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNames( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n objectKeys, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNamesIn( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n keysIn, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNames, propertyNamesIn\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value )\n Returns an array of an object's own non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNames, nonEnumerablePropertySymbolsIn, propertySymbols\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertySymbolsIn\n","nonIndexKeys":"\nnonIndexKeys( obj )\n Returns an array of an object's own enumerable property names which are not\n integer indices.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; this[0] = 3.14; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = nonIndexKeys( obj )\n e.g., [ 'beep' ]\n\n See Also\n --------\n objectEntries, objectKeys, objectValues\n","noop":"\nnoop()\n A function which does nothing.\n\n Examples\n --------\n > noop();\n\n","now":"\nnow()\n Returns the time in seconds since the epoch.\n\n The Unix epoch is 00:00:00 UTC on 1 January 1970.\n\n Returns\n -------\n out: integer\n Time in seconds since the epoch.\n\n Examples\n --------\n > var ts = now()\n \n\n","NUM_CPUS":"\nNUM_CPUS\n Number of CPUs.\n\n In browser environments, the number of CPUs is determined by querying the\n hardware concurrency API.\n\n In Node.js environments, the number of CPUs is determined via the `os`\n module.\n\n Examples\n --------\n > NUM_CPUS\n \n\n","num2words":"\nnum2words( value[, options] )\n Converts a number to a word representation.\n\n Parameters\n ----------\n value: integer\n Input value.\n\n options: Object (optional)\n Options.\n\n options.lang: string (optional)\n Language code. Supported languages:\n\n - en: English.\n - de: German.\n\n Default: `'en'`.\n\n Returns\n -------\n out: string\n Word representation of number.\n\n Examples\n --------\n > var out = num2words( 123 )\n 'one hundred twenty-three'\n\n > out = num2words( 16.31 )\n 'sixteen point three one'\n\n > out = num2words( 123, { 'lang': 'de' } )\n 'einhundertdreiundzwanzig'\n\n","Number":"\nNumber( value )\n Returns a Number object.\n\n This constructor should be used sparingly. Always prefer number primitives.\n\n Parameters\n ----------\n value: number\n Value to wrap in a Number object.\n\n Returns\n -------\n out: Number\n Number object.\n\n Examples\n --------\n > var v = new Number( 5 )\n \n\n","numel":"\nnumel( x )\n Returns the number of elements in an ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Number of elements.\n\n Examples\n --------\n > var n = numel( ndzeros( [ 3, 3, 3 ] ) )\n 27\n\n See Also\n --------\n array, ndarray, numelDimension\n","numelDimension":"\nnumelDimension( x, dim )\n Returns the size (i.e., number of elements) of a specified dimension for a\n provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n Returns\n -------\n out: integer\n Dimension size.\n\n Examples\n --------\n > var out = numelDimension( ndzeros( [ 4, 2, 3 ] ), 0 )\n 4\n\n See Also\n --------\n array, ndarray, numel\n","numGraphemeClusters":"\nnumGraphemeClusters( str )\n Returns the number of grapheme clusters in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Number of grapheme clusters.\n\n Examples\n --------\n > var out = numGraphemeClusters( 'beep' )\n 4\n > out = numGraphemeClusters( '🌷' )\n 1\n\n See Also\n --------\n nextGraphemeClusterBreak\n","Object":"\nObject( value )\n Returns an object.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n If provided an existing object, the function returns the input value\n unchanged.\n\n Otherwise, if provided any other value (e.g., a number, string, etc), the\n function will return an object of the corresponding type.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > var o = new Object( null )\n {}\n > o = new Object( 5.0 )\n \n > o = new Object( 'beep' )\n \n\nObject.assign( target, ...sources )\n Assigns enumerable and own properties from source objects to a target\n object.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n sources: ...Object\n Source objects.\n\n Returns\n -------\n out: Object\n Target object.\n\n Examples\n --------\n > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n { 'a': 1, 'b': 2 }\n\nObject.create( prototype, properties )\n Creates a new object with a specified prototype object and properties.\n\n Parameters\n ----------\n prototype: Object\n Prototype object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }\n\nObject.defineProperties( obj, properties )\n Defines properties for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }\n\nObject.defineProperty( obj, key, descriptor )\n Defines a property for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n descriptor: Object\n Property descriptor.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperty( {}, 'a', {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': false\n })\n { 'a': 1 }\n\nObject.entries( obj )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of [key, value] pairs.\n\n Examples\n --------\n > var o = Object.entries( { 'a': 1, 'b': 2 } )\n [ [ 'a', 1 ], [ 'b', 2 ] ]\n\nObject.freeze( obj )\n Freezes an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.freeze( { 'a': 1 } )\n { 'a': 1 }\n\nObject.getOwnPropertyDescriptor( obj, key )\n Returns an object's own property descriptor.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n Returns\n -------\n out: Object\n Property descriptor.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }\n\nObject.getOwnPropertyDescriptors( obj )\n Returns an object's own property descriptors.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Property descriptors.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n {\n 'a': {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n },\n 'b': {\n 'value': 2,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n }\n }\n\nObject.getOwnPropertyNames( obj )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]\n\nObject.getOwnPropertySymbols( obj )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of symbol property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n []\n\nObject.getPrototypeOf( obj )\n Returns an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Prototype.\n\n Examples\n --------\n > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n \n\nObject.hasOwn( obj, p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n true\n\nObject.is( value1, value2 )\n Returns a boolean indicating whether two values are the same value.\n\n Parameters\n ----------\n value1: any\n First value.\n\n value2: any\n Second value.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether two values are the same value.\n\n Examples\n --------\n > var o = Object.is( 1, 1 )\n true\n > var o = Object.is( 1, '1' )\n false\n\nObject.isExtensible( obj )\n Returns a boolean indicating whether an object is extensible.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is extensible.\n\n Examples\n --------\n > var o = Object.isExtensible( { 'a': 1 } )\n true\n\nObject.isFrozen( obj )\n Returns a boolean indicating whether an object is frozen.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is frozen.\n\n Examples\n --------\n > var o = Object.isFrozen( { 'a': 1 } )\n false\n > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n true\n\nObject.isSealed( obj )\n Returns a boolean indicating whether an object is sealed.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is sealed.\n\n Examples\n --------\n > var o = Object.isSealed( { 'a': 1 } )\n false\n > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n true\n\nObject.keys( obj )\n Returns an array of an object's own enumerable string-keyed property\n names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.keys( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]\n\nObject.preventExtensions( obj )\n Prevents the addition of new properties to an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.preventExtensions( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n\nObject.seal( obj )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.seal( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n > delete o.a;\n > o\n { 'a': 1 }\n\nObject.setPrototypeOf( obj, proto )\n Sets an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n proto: Object\n Prototype.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n { 'a': 1 }\n > o.b\n 2\n\nObject.values( obj )\n Returns an array of an object's own enumerable property values.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property values.\n\n Examples\n --------\n > var o = Object.values( { 'a': 1, 'b': 2 } )\n [ 1, 2 ]\n\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n \n\nObject.prototype.toString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n \n\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n\n Returns\n -------\n out: any\n Primitive value of the object.\n\n Examples\n --------\n > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n {}\n\nObject.prototype.hasOwnProperty( p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n true\n\nObject.prototype.isPrototypeOf( obj )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object exists in another object's\n prototype chain.\n\n Examples\n --------\n > var p = { 'a': 1 };\n > var o = { '__proto__': p };\n > var b = o.isPrototypeOf( p );\n true\n\nObject.prototype.propertyIsEnumerable( p )\n Returns a boolean indicating whether an object's property is enumerable.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object's property is enumerable.\n\n Examples\n --------\n > var o = { 'a': 1, 'b': 2 };\n > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n true\n\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n\n Examples\n --------\n > var o = new Object( null );\n > var ctr = o.constructor;\n \n\n","Object.assign":"\nObject.assign( target, ...sources )\n Assigns enumerable and own properties from source objects to a target\n object.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n sources: ...Object\n Source objects.\n\n Returns\n -------\n out: Object\n Target object.\n\n Examples\n --------\n > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n { 'a': 1, 'b': 2 }","Object.create":"\nObject.create( prototype, properties )\n Creates a new object with a specified prototype object and properties.\n\n Parameters\n ----------\n prototype: Object\n Prototype object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }","Object.defineProperties":"\nObject.defineProperties( obj, properties )\n Defines properties for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }","Object.defineProperty":"\nObject.defineProperty( obj, key, descriptor )\n Defines a property for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n descriptor: Object\n Property descriptor.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperty( {}, 'a', {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': false\n })\n { 'a': 1 }","Object.entries":"\nObject.entries( obj )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of [key, value] pairs.\n\n Examples\n --------\n > var o = Object.entries( { 'a': 1, 'b': 2 } )\n [ [ 'a', 1 ], [ 'b', 2 ] ]","Object.freeze":"\nObject.freeze( obj )\n Freezes an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.freeze( { 'a': 1 } )\n { 'a': 1 }","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj, key )\n Returns an object's own property descriptor.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n Returns\n -------\n out: Object\n Property descriptor.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj )\n Returns an object's own property descriptors.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Property descriptors.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n {\n 'a': {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n },\n 'b': {\n 'value': 2,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n }\n }","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of symbol property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n []","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj )\n Returns an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Prototype.\n\n Examples\n --------\n > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n ","Object.hasOwn":"\nObject.hasOwn( obj, p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n true","Object.is":"\nObject.is( value1, value2 )\n Returns a boolean indicating whether two values are the same value.\n\n Parameters\n ----------\n value1: any\n First value.\n\n value2: any\n Second value.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether two values are the same value.\n\n Examples\n --------\n > var o = Object.is( 1, 1 )\n true\n > var o = Object.is( 1, '1' )\n false","Object.isExtensible":"\nObject.isExtensible( obj )\n Returns a boolean indicating whether an object is extensible.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is extensible.\n\n Examples\n --------\n > var o = Object.isExtensible( { 'a': 1 } )\n true","Object.isFrozen":"\nObject.isFrozen( obj )\n Returns a boolean indicating whether an object is frozen.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is frozen.\n\n Examples\n --------\n > var o = Object.isFrozen( { 'a': 1 } )\n false\n > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n true","Object.isSealed":"\nObject.isSealed( obj )\n Returns a boolean indicating whether an object is sealed.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is sealed.\n\n Examples\n --------\n > var o = Object.isSealed( { 'a': 1 } )\n false\n > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n true","Object.keys":"\nObject.keys( obj )\n Returns an array of an object's own enumerable string-keyed property\n names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.keys( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]","Object.preventExtensions":"\nObject.preventExtensions( obj )\n Prevents the addition of new properties to an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.preventExtensions( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }","Object.seal":"\nObject.seal( obj )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.seal( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n > delete o.a;\n > o\n { 'a': 1 }","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj, proto )\n Sets an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n proto: Object\n Prototype.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n { 'a': 1 }\n > o.b\n 2","Object.values":"\nObject.values( obj )\n Returns an array of an object's own enumerable property values.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property values.\n\n Examples\n --------\n > var o = Object.values( { 'a': 1, 'b': 2 } )\n [ 1, 2 ]","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n ","Object.prototype.toString":"\nObject.prototype.toString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n ","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n\n Returns\n -------\n out: any\n Primitive value of the object.\n\n Examples\n --------\n > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n {}","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n true","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object exists in another object's\n prototype chain.\n\n Examples\n --------\n > var p = { 'a': 1 };\n > var o = { '__proto__': p };\n > var b = o.isPrototypeOf( p );\n true","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p )\n Returns a boolean indicating whether an object's property is enumerable.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object's property is enumerable.\n\n Examples\n --------\n > var o = { 'a': 1, 'b': 2 };\n > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n true","Object.prototype.constructor":"\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n\n Examples\n --------\n > var o = new Object( null );\n > var ctr = o.constructor;\n ","objectEntries":"\nobjectEntries( obj )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var entries = objectEntries( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntriesIn, objectFromEntries, objectKeys, objectValues\n","objectEntriesIn":"\nobjectEntriesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var entries = objectEntriesIn( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntries, objectFromEntries, keysIn, objectValuesIn\n","objectFromEntries":"\nobjectFromEntries( entries )\n Creates an object from an array of key-value pairs.\n\n Parameters\n ----------\n entries: Array\n Input object.\n\n Returns\n -------\n out: Object\n Object created from `[key, value]` pairs.\n\n Examples\n --------\n > var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\n > var obj = objectFromEntries( entries )\n { 'beep': 'boop', 'foo': 'bar' }\n\n See Also\n --------\n objectEntries\n","objectInverse":"\nobjectInverse( obj[, options] )\n Inverts an object, such that keys become values and values become keys.\n\n Beware when providing objects having values which are themselves objects.\n The function relies on native object serialization (`#toString`) when\n converting values to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverse( obj )\n { 'beep': 'a', 'boop': 'b' }\n\n // Duplicate values:\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverse( obj )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverse( obj, { 'duplicates': false } )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverseBy\n","objectInverseBy":"\nobjectInverseBy( obj, [options,] transform )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n\n The transform function is provided three arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n\n The value returned by a transform function should be a value which can be\n serialized as an object key. Hence, beware when providing objects having\n values which are themselves objects. The function relies on native object\n serialization (`#toString`) when converting transform function return values\n to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n transform: Function\n Transform function.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverseBy( obj, transform )\n { 'abeep': 'a', 'bboop': 'b' }\n\n // Duplicate values:\n > function transform( key, value ) { return value; };\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverseBy( obj, transform )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverseBy( obj, { 'duplicates': false }, transform )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverse\n","objectKeys":"\nobjectKeys( value )\n Returns an array of an object's own enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = objectKeys( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectEntries, keysIn, nonIndexKeys, objectValues\n","objectValues":"\nobjectValues( obj )\n Returns an array of an object's own enumerable property values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var vals = objectValues( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntries, objectKeys\n","objectValuesIn":"\nobjectValuesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var values = objectValuesIn( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntriesIn, keysIn, objectValues\n","omit":"\nomit( obj, keys )\n Returns a partial object copy excluding specified keys.\n\n The function returns a shallow copy.\n\n The function ignores non-existent keys.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to exclude.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omit( obj1, 'b' )\n { 'a': 1 }\n\n See Also\n --------\n omitBy\n","omitBy":"\nomitBy( obj, predicate )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n\n The function returns a shallow copy.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) { return ( value > 1 ); };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omitBy( obj1, predicate )\n { 'a': 1 }\n\n See Also\n --------\n omit\n","open":"\nopen( path[, flags[, mode]], clbk )\n Asynchronously opens a file.\n\n Some characters, such as <>:\"/\\|?*, are reserved under Windows.\n Under NTFS, if the path contains a colon, Node.js will open a file system\n stream.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon opening a file.\n\n Examples\n --------\n > function onOpen( error, fd ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... close.sync( fd );\n ... }\n ... };\n > open( './beep/boop.txt', onOpen );\n\n\nopen.sync( path[, flags[, mode]] )\n Synchronously opens a file.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n Returns\n -------\n fd: Error|integer\n File descriptor.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.txt' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n close, exists, readFile\n","open.sync":"\nopen.sync( path[, flags[, mode]] )\n Synchronously opens a file.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n Returns\n -------\n fd: Error|integer\n File descriptor.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.txt' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n close, exists, readFile","openURL":"\nopenURL( url )\n Opens a URL in a user's default browser.\n\n In a non-browser environment, the function returns an unreferenced child\n process. In a browser environment, the function returns a reference to a\n `window` object.\n\n Parameters\n ----------\n url: string\n URL to open.\n\n Returns\n -------\n out: process|Window\n Child process or `window` object.\n\n Examples\n --------\n > var out = openURL( 'https://google.com' );\n\n","ordinalize":"\nordinalize( value[, options] )\n Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n\n Parameters\n ----------\n value: string|integer\n Input value.\n\n options: Object (optional)\n Options.\n\n options.lang: string (optional)\n Language code. Supported languages:\n\n - en: English.\n - es: Spanish.\n - fin: Finnish.\n - fr: French.\n - de: Dutch.\n - it: Italian.\n - pt: Portuguese.\n - swe: Swedish.\n\n Default: `'en'`.\n\n options.suffixOnly: boolean (optional)\n Boolean indicating whether to return only the suffix. Default: `false`.\n\n options.gender: string (optional)\n Grammatical gender (used if applicable); must be either 'masculine' or\n 'feminine'. Default: `'masculine'`.\n\n Returns\n -------\n out: string\n Ordinal string or suffix.\n\n Examples\n --------\n > var out = ordinalize( '1' )\n '1st'\n > out = ordinalize( 2, { 'suffixOnly': true } )\n 'nd'\n > out = ordinalize( '3', { 'lang': 'es' } )\n '3º'\n\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 21 attributes:\n\n - obs: observation number\n - town: town name\n - town_id: town identifier\n - tract: tract identifier\n - lon: longitude\n - lat: latitude\n - medv: median value of owner-occupied homes in $1000's\n - cmedv: corrected median value of owner-occupied homes in $1000's\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n The dataset augments the original dataset from Harrison and Rubinfeld (1978)\n by including geo-referencing and spatial estimation for each observation.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = PACE_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n - Pace, R. Kelley, and Otis W. Gilley. 1997. \"Using the Spatial\n Configuration of the Data to Improve Estimation.\" _The Journal of Real\n Estate Finance and Economics_ 14 (3): 333–40. doi:10.1023/A:1007762613901.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, HARRISON_BOSTON_HOUSE_PRICES_CORRECTED\n","pad":"\npad( str, len[, options] )\n Pads a `string` such that the padded `string` has length `len`.\n\n Any padding which does not evenly divide available space is trimmed such\n that the returned string length is always `len`.\n\n If `len < str.length`, the input string is trimmed.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n options: Object (optional)\n Options.\n\n options.lpad: string (optional)\n String used to left pad.\n\n options.rpad: string (optional)\n String used to right pad.\n\n options.centerRight: boolean (optional)\n Boolean indicating whether to center right in the event of a tie.\n Default: `false` (i.e., center left).\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n // Standard usage:\n > var out = pad( 'a', 5 )\n 'a '\n\n // Left pad:\n > out = pad( 'a', 10, { 'lpad': 'b' } )\n 'bbbbbbbbba'\n\n // Right pad:\n > out = pad( 'a', 12, { 'rpad': 'b' } )\n 'abbbbbbbbbbb'\n\n // Center an input string:\n > var opts = { 'lpad': 'a', 'rpad': 'c' };\n > out = pad( 'b', 11, opts )\n 'aaaaabccccc'\n\n // Left center:\n > opts.centerRight = false;\n > out = pad( 'b', 10, opts )\n 'aaaabccccc'\n\n // Right center:\n > opts.centerRight = true;\n > out = pad( 'b', 10, opts )\n 'aaaaabcccc'\n\n // Output string always length `len`:\n > opts = { 'lpad': 'boop', 'rpad': 'woot' };\n > out = pad( 'beep', 10, opts )\n 'boobeepwoo'\n\n // Pad right, trim right:\n > out = pad( 'beep', 2 )\n 'be'\n\n // Pad left, trim left:\n > opts = { 'lpad': 'b' };\n > out = pad( 'beep', 2, opts )\n 'ep'\n\n // Pad both, trim both:\n > opts = { 'lpad': '@', 'rpad': '!' };\n > out = pad( 'beep', 2, opts )\n 'ee'\n\n // Pad both, trim both starting from left:\n > out = pad( 'abcdef', 3, opts )\n 'cde'\n\n // Pad both, trim both starting from right:\n > opts.centerRight = true;\n > out = pad( 'abcdef', 3, opts )\n 'bcd'\n\n See Also\n --------\n lpad, rpad\n","padjust":"\npadjust( pvals, method[, comparisons] )\n Adjusts supplied p-values for multiple comparisons via a specified method.\n\n The `method` parameter can be one of the following values:\n\n - **bh**: Benjamini-Hochberg procedure controlling the False Discovery\n Rate (FDR).\n - **bonferroni**: Bonferroni correction fixing the family-wise error rate\n by multiplying the p-values with the number of comparisons. The Bonferroni\n correction is usually a too conservative adjustment compared to the others.\n - **by**: Procedure by Benjamini & Yekutieli for controlling the False\n Discovery Rate (FDR) under dependence.\n - **holm**: Hommel's method controlling family-wise error rate. It is\n uniformly more powerful than the Bonferroni correction.\n - **hommel**: Hommel's method, which is valid when hypothesis tests are\n independent. It is more expensive to compute than the other methods.\n\n By default, the number of comparisons for which the p-values should be\n corrected is equal to the number of provided p-values. Alternatively, it is\n possible to set `comparisons` to a number greater than the length of\n `pvals`. In that case, the methods assume `comparisons - pvals.length`\n unobserved p-values that are greater than all observed p-values (for Holm's\n method and the Bonferroni correction) or equal to `1` for the remaining\n methods.\n\n Parameters\n ----------\n pvals: Array\n P-values to be adjusted.\n\n method: string\n Correction method.\n\n comparisons: integer (optional)\n Number of comparisons. Default value: `pvals.length`.\n\n Returns\n -------\n out: Array\n Array containing the corrected p-values.\n\n Examples\n --------\n > var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\n > var out = padjust( pvalues, 'bh' )\n [ 0.04, 0.075, ~0.205, 0.6, 0.25 ]\n\n > out = padjust( pvalues, 'bonferroni' )\n [ 0.04, 0.15, 0.615, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'by' )\n [ ~0.457, ~0.856, 1.0, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'holm' )\n [ 0.2, 0.6, 1.0, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'hommel' )\n [ 0.16, 0.6, 1.0, 1.0, 1.0 ]\n\n","papply":"\npapply( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var add2 = papply( add, 2 );\n > var sum = add2( 3 )\n 5\n\n See Also\n --------\n papplyRight\n","papplyRight":"\npapplyRight( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function say( text, name ) { return text + ', ' + name + '.'; };\n > var toGrace = papplyRight( say, 'Grace Hopper' );\n > var str = toGrace( 'Hello' )\n 'Hello, Grace Hopper.'\n > str = toGrace( 'Thank you' )\n 'Thank you, Grace Hopper.'\n\n See Also\n --------\n papply\n","parallel":"\nparallel( files, [options,] clbk )\n Executes scripts in parallel.\n\n Relative file paths are resolved relative to the current working directory.\n\n Ordered script output does not imply that scripts are executed in order. To\n preserve script order, execute the scripts sequentially via some other\n means.\n\n Parameters\n ----------\n files: Array\n Script file paths.\n\n options: Object (optional)\n Options.\n\n options.cmd: string (optional)\n Executable file/command. Default: `'node'`.\n\n options.concurrency: integer (optional)\n Number of scripts to execute concurrently. Script concurrency cannot\n exceed the number of scripts. By specifying a concurrency greater than\n the number of workers, a worker may be executing more than `1` script at\n any one time. While not likely to be advantageous for synchronous\n scripts, setting a higher concurrency may be advantageous for scripts\n performing asynchronous tasks. If the script concurrency is less than\n the number of workers, the number of workers is reduced to match the\n specified concurrency. Default: `options.workers`.\n\n options.workers: integer (optional)\n Number of workers. Default: number of CPUs minus `1`.\n\n options.ordered: boolean (optional)\n Boolean indicating whether to preserve the order of script output. By\n default, the `stdio` output for each script is interleaved; i.e., the\n `stdio` output from one script may be interleaved with the `stdio`\n output from one or more other scripts. To preserve the `stdio` output\n order for each script, set the `ordered` option to `true`. Default:\n `false`.\n\n options.uid: integer (optional)\n Process user identity.\n\n options.gid: integer (optional)\n Process group identity.\n\n options.maxBuffer: integer (optional)\n Max child process `stdio` buffer size. This option is only applied when\n `options.ordered = true`. Default: `200*1024*1024`.\n\n clbk: Function\n Callback to invoke after executing all scripts.\n\n Examples\n --------\n > function done( error ) { if ( error ) { throw error; } };\n > var files = [ './a.js', './b.js' ];\n > parallel( files, done );\n\n // Specify the number of workers:\n > var opts = { 'workers': 8 };\n > parallel( files, opts, done );\n\n","parseJSON":"\nparseJSON( str[, reviver] )\n Attempts to parse a string as JSON.\n\n Function behavior differs from `JSON.parse()` as follows:\n\n - throws a `TypeError` if provided any value which is not a string.\n - throws a `TypeError` if provided a `reviver` argument which is not a\n function.\n - returns, rather than throws, a `SyntaxError` if unable to parse a string\n as JSON.\n\n Parameters\n ----------\n str: string\n String to parse.\n\n reviver: Function (optional)\n Transformation function.\n\n Returns\n -------\n out: any|Error\n Parsed value or an error.\n\n Examples\n --------\n > var obj = parseJSON( '{\"beep\":\"boop\"}' )\n { 'beep': 'boop' }\n\n // Provide a reviver:\n > function reviver( key, value ) {\n ... if ( key === '' ) { return value; }\n ... if ( key === 'beep' ) { return value; }\n ... };\n > var str = '{\"beep\":\"boop\",\"a\":\"b\"}';\n > var out = parseJSON( str, reviver )\n { 'beep': 'boop' }\n\n","pascalcase":"\npascalcase( str )\n Converts a string to Pascal case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Pascal-cased string.\n\n Examples\n --------\n > var out = pascalcase( 'Hello World!' )\n 'HelloWorld'\n > out = pascalcase( 'beep boop' )\n 'BeepBoop'\n\n See Also\n --------\n camelcase, constantcase, kebabcase, snakecase","PATH_DELIMITER":"\nPATH_DELIMITER\n Platform-specific path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER\n \n\n // POSIX environment:\n > var path = '/usr/bin:/bin:/usr/sbin';\n > var parts = path.split( PATH_DELIMITER )\n [ '/usr/bin', '/bin', '/usr/sbin' ]\n\n // Windows environment:\n > path = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\n > parts = path.split( PATH_DELIMITER )\n [ 'C:\\\\Windows\\system32', 'C:\\\\Windows' ]\n\n See Also\n --------\n PATH_DELIMITER_POSIX, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_POSIX\n ':'\n > var PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\n > var paths = PATH.split( PATH_DELIMITER_POSIX )\n [ '/usr/bin', '/bin', '/usr/sbin', '/sbin', '/usr/local/bin' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_WIN32\n ';'\n > var PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\n > var paths = PATH.split( PATH_DELIMITER_WIN32 )\n [ 'C:\\\\Windows\\\\system32', 'C:\\\\Windows', 'C:\\\\Program Files\\\\node\\\\' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_POSIX\n","PATH_SEP":"\nPATH_SEP\n Platform-specific path segment separator.\n\n Examples\n --------\n > PATH_SEP\n \n\n // Windows environment:\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n // POSIX environment:\n > parts = 'foo/bar/baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP_POSIX, PATH_SEP_WIN32\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n POSIX path segment separator.\n\n Examples\n --------\n > PATH_SEP_POSIX\n '/'\n > var parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_WIN32\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n Windows path segment separator.\n\n Examples\n --------\n > PATH_SEP_WIN32\n '\\\\'\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_POSIX\n","pcorrtest":"\npcorrtest( x, y[, options] )\n Computes a Pearson product-moment correlation test between paired samples.\n\n By default, the function performs a t-test for the null hypothesis that the\n data in arrays or typed arrays `x` and `y` is not correlated. A test against\n a different population correlation can be carried out by supplying the `rho`\n option. In this case, a test using the Fisher's z transform is conducted.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Nnumber in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.rho: number (optional)\n Number denoting the correlation under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the Pearson product-moment correlation\n coefficient. The confidence interval is calculated using Fisher's\n z-transform.\n\n out.nullValue: number\n Assumed correlation under H0 (equal to the supplied `rho` option).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var rho = 0.5;\n > var x = new Array( 300 );\n > var y = new Array( 300 );\n > for ( var i = 0; i < 300; i++ ) {\n ... x[ i ] = base.random.normal( 0.0, 1.0 );\n ... y[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\n ... base.sqrt( 1.0 - (rho*rho) ) );\n ... }\n > var out = pcorrtest( x, y )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 10.115805615994121,\n ci: [ 0.4161679018930295, 0.5853122968949995 ],\n alternative: 'two-sided',\n method: 't-test for Pearson correlation coefficient',\n nullValue: 0,\n pcorr: 0.505582072355616,\n }\n\n // Print output:\n > var table = out.print()\n t-test for Pearson correlation coefficient\n\n Alternative hypothesis: True correlation coefficient is not equal to 0\n\n pValue: 0\n statistic: 9.2106\n 95% confidence interval: [0.3776,0.5544]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n","percentEncode":"\npercentEncode( str )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: string\n Percent-encoded string.\n\n Examples\n --------\n > var out = percentEncode( '☃' )\n '%E2%98%83'\n\n","PHI":"\nPHI\n Golden ratio.\n\n Examples\n --------\n > PHI\n 1.618033988749895\n\n","PI":"\nPI\n The mathematical constant `π`.\n\n Examples\n --------\n > PI\n 3.141592653589793\n\n See Also\n --------\n TWO_PI\n","PI_SQUARED":"\nPI_SQUARED\n Square of the mathematical constant `π`.\n\n Examples\n --------\n > PI_SQUARED\n 9.869604401089358\n\n See Also\n --------\n PI\n","pick":"\npick( obj, keys )\n Returns a partial object copy containing only specified keys.\n\n If a key does not exist as an own property in a source object, the key is\n ignored.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to copy.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pick( obj1, 'b' )\n { 'b': 2 }\n\n See Also\n --------\n pickBy\n","pickArguments":"\npickArguments( fcn, indices[, thisArg] )\n Returns a function that applies specified arguments to a provided function.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > var bar = pickArguments( foo, [ 0, 2 ] );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n reorderArguments, reverseArguments\n","pickBy":"\npickBy( obj, predicate )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) {\n ... return ( value > 1 );\n ... };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pickBy( obj1, predicate )\n { 'b': 2 }\n\n See Also\n --------\n pick\n","PINF":"\nPINF\n Double-precision floating-point positive infinity.\n\n Examples\n --------\n > PINF\n Infinity\n\n See Also\n --------\n NINF\n","pkg2alias":"\npkg2alias( pkg )\n Returns the alias associated with a specified package name.\n\n The function supports both internal and standalone package names.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Alias.\n\n Examples\n --------\n > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n \n > v = pkg2alias( '@stdlib/math-base-special-sin' )\n \n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n","pkg2related":"\npkg2related( pkg )\n Returns package names related to a specified package name.\n\n The function supports both internal and standalone package names.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: Array|null\n Related package names.\n\n Examples\n --------\n > var v = pkg2related( '@stdlib/math/base/special/sin' )\n [...]\n > v = pkg2related( '@stdlib/math-base-special-sin' )\n [...]\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n","pkg2standalone":"\npkg2standalone( pkg )\n Returns the standalone package name associated with a provided internal\n package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Standalone package name.\n\n Examples\n --------\n > var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n '@stdlib/math-base-special-sin'\n\n See Also\n --------\n alias2pkg, alias2standalone, aliases, pkg2alias, pkg2related\n","PLATFORM":"\nPLATFORM\n Platform on which the current process is running.\n\n Possible values:\n\n - win32\n - darwin\n - linux\n - freebsd\n - sunos\n\n Examples\n --------\n > PLATFORM\n \n\n See Also\n --------\n ARCH\n","plot":"\nplot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = plot( x, y )\n \n\n See Also\n --------\n Plot\n","Plot":"\nPlot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = Plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = Plot( x, y )\n \n\n See Also\n --------\n plot\n","pluck":"\npluck( arr, prop[, options] )\n Extracts a property value from each element of an object array.\n\n The function skips `null` and `undefined` array elements.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n prop: string\n Property to access.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. To mutate the\n input data structure (e.g., when input values can be discarded or when\n optimizing memory usage), set the `copy` option to `false`. Default:\n true.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > var out = pluck( arr, 'a' )\n [ 1, 0.5 ]\n\n > arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > out = pluck( arr, 'a', { 'copy': false } )\n [ 1, 0.5 ]\n > var bool = ( arr[ 0 ] === out[ 0 ] )\n true\n\n See Also\n --------\n deepPluck, pick\n","pop":"\npop( collection )\n Removes and returns the last element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = pop( arr )\n [ [ 1.0, 2.0, 3.0, 4.0 ], 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = pop( arr )\n [ [ 1.0 ], 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = pop( arr )\n [ { 'length': 1, '0': 1.0 }, 2.0 ]\n\n See Also\n --------\n push, shift, unshift\n","porterStemmer":"\nporterStemmer( word )\n Extracts the stem of a given word.\n\n Parameters\n ----------\n word: string\n Input word.\n\n Returns\n -------\n out: string\n Word stem.\n\n Examples\n --------\n > var out = porterStemmer( 'walking' )\n 'walk'\n > out = porterStemmer( 'walked' )\n 'walk'\n > out = porterStemmer( 'walks' )\n 'walk'\n > out = porterStemmer( '' )\n ''\n\n","prepend":"\nprepend( collection1, collection2 )\n Adds the elements of one collection to the beginning of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = prepend( arr, [ 6.0, 7.0 ] )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = prepend( arr, [ 3.0, 4.0 ] )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = prepend( arr, [ 2.0, 3.0 ] )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n append, unshift\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str[, fromIndex] )\n Returns the previous extended grapheme cluster break in a string before a\n specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n fromIndex: integer (optional)\n Position. Default: str.length-1.\n\n Returns\n -------\n out: integer\n Previous extended grapheme cluster break position.\n\n Examples\n --------\n > var out = prevGraphemeClusterBreak( 'last man standing', 4 )\n 3\n > out = prevGraphemeClusterBreak( 'presidential election', 8 )\n 7\n > out = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\n 0\n > out = prevGraphemeClusterBreak( '🌷', 1 )\n -1\n\n See Also\n --------\n numGraphemeClusters, nextGraphemeClusterBreak","PRIMES_100K":"\nPRIMES_100K()\n Returns an array containing the first 100,000 prime numbers.\n\n Returns\n -------\n out: Array\n List of primes.\n\n Examples\n --------\n > var list = PRIMES_100K()\n [ 2, 3, 5, ... ]\n\n See Also\n --------\n iterPrimesSeq\n","properties":"\nproperties( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable and non-enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = properties( obj )\n [ 'beep' ]\n\n See Also\n --------\n defineProperties, inheritedProperties, propertiesIn, propertyNames, propertySymbols\n","propertiesIn":"\npropertiesIn( value )\n Returns an array of an object's own and inherited property names and\n symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited property names and symbols.\n\n Examples\n --------\n > var props = propertiesIn( [] )\n\n See Also\n --------\n defineProperties, inheritedProperties, properties, propertyNamesIn, propertySymbolsIn\n","propertyDescriptor":"\npropertyDescriptor( value, property )\n Returns a property descriptor for an object's own property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptor( obj, 'a' )\n {...}\n\n See Also\n --------\n hasOwnProp, defineProperty, propertyDescriptorIn, propertyDescriptors\n","propertyDescriptorIn":"\npropertyDescriptorIn( value, property )\n Returns a property descriptor for an object's own or inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptorIn( obj, 'a' )\n {...}\n\n See Also\n --------\n hasProp, defineProperty, propertyDescriptor, propertyDescriptorsIn\n","propertyDescriptors":"\npropertyDescriptors( value )\n Returns an object's own property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n Property descriptors.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptors( obj )\n { 'a': {...} }\n\n See Also\n --------\n defineProperty, defineProperties, propertyDescriptor, propertyDescriptorsIn, propertyNames, propertySymbols\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value )\n Returns an object's own and inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n An object's own and inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = propertyDescriptorsIn( obj )\n { 'beep': {...}, 'foo': {...}, ... }\n\n See Also\n --------\n defineProperties, propertyDescriptorIn, propertyDescriptors, propertyNamesIn, propertySymbolsIn\n","propertyNames":"\npropertyNames( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable and non-enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNames( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNames, propertyNamesIn, propertySymbols\n","propertyNamesIn":"\npropertyNamesIn( value )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable and non-enumerable\n property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNamesIn( obj )\n e.g., [ 'beep', 'foo', ... ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNamesIn, propertyNames, propertySymbolsIn\n","propertySymbols":"\npropertySymbols( value )\n Returns an array of an object's own symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own symbol properties.\n\n Examples\n --------\n > var s = propertySymbols( {} )\n\n See Also\n --------\n propertyNames, propertySymbolsIn\n","propertySymbolsIn":"\npropertySymbolsIn( value )\n Returns an array of an object's own and inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited symbol properties.\n\n Examples\n --------\n > var s = propertySymbolsIn( [] )\n\n See Also\n --------\n propertyNamesIn, propertySymbols\n","Proxy":"\nProxy( target, handlers )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n\n The following \"traps\" are supported:\n\n - getPrototypeOf( target )\n Trap for `Object.getPrototypeOf()`. Can be used to intercept the\n `instanceof` operator. The method must return an object or `null`.\n\n - setPrototypeOf( target, prototype )\n Trap for `Object.setPrototypeOf()`. The method must return a boolean\n indicating if prototype successfully set.\n\n - isExtensible( target )\n Trap for `Object.isExtensible()`. The method must return a boolean.\n\n - preventExtensions( target )\n Trap for `Object.preventExtensions()`. The method must return a boolean.\n\n - getOwnPropertyDescriptor( target, property )\n Trap for `Object.getOwnPropertyDescriptor()`. The method must return an\n object or `undefined`.\n\n - defineProperty( target, property, descriptor )\n Trap for `Object.defineProperty()`. The method must return a boolean\n indicating whether the operation succeeded.\n\n - has( target, property )\n Trap for the `in` operator. The method must return a boolean.\n\n - get( target, property, receiver )\n Trap for retrieving property values. The method can return any value.\n\n - set( target, property, value, receiver )\n Trap for setting property values. The method should return a boolean\n indicating whether assignment succeeded.\n\n - deleteProperty( target, property )\n Trap for the `delete` operator. The method must return a boolean\n indicating whether operation succeeded.\n\n - ownKeys( target )\n Trap for `Object.keys`, `Object.getOwnPropertyNames()`, and\n `Object.getOwnPropertySymbols()`. The method must return an enumerable\n object.\n\n - apply( target, thisArg, argumentsList )\n Trap for a function call. The method can return any value.\n\n - construct( target, argumentsList, newTarget )\n Trap for the `new` operator. The method must return an object.\n\n All traps are optional. If a trap is not defined, the default behavior is to\n forward the operation to the target.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Proxy object.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = new Proxy( {}, h );\n > p.a = 3.14;\n > p.a\n 6.28\n\n\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();\n\n","Proxy.revocable":"\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();","push":"\npush( collection, ...items )\n Adds one or more elements to the end of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = push( arr, 6.0, 7.0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = push( arr, 3.0, 4.0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = push( arr, 1.0, 2.0 )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n pop, shift, unshift\n","quarterOfYear":"\nquarterOfYear( [month] )\n Returns the quarter of the year.\n\n By default, the function returns the quarter of the year for the current\n month in the current year (according to local time). To determine the\n quarter for a particular month, provide either a month or a `Date`\n object.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n Parameters\n ----------\n month: integer|string|Date (optional)\n Month (or `Date`).\n\n Returns\n -------\n out: integer\n Quarter of the year.\n\n Examples\n --------\n > var q = quarterOfYear( new Date() )\n \n > q = quarterOfYear( 4 )\n 2\n > q = quarterOfYear( 'June' )\n 2\n\n // Other ways to supply month:\n > q = quarterOfYear( 'April' )\n 2\n > q = quarterOfYear( 'apr' )\n 2\n\n See Also\n --------\n dayOfYear\n","random.array.arcsine":"\nrandom.array.arcsine( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from an arcsine\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.arcsine.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.arcsine.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.arcsine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.arcsine.PRNG;\n\n\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.arcsine.seed;\n\n\nrandom.array.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.arcsine.seedLength;\n\n\nrandom.array.arcsine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.arcsine.state\n \n\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.arcsine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.arcsine.stateLength;\n\n\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.arcsine.byteLength;\n\n See Also\n --------\n base.random.arcsine, random.strided.arcsine\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.arcsine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.arcsine.PRNG;","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.arcsine.seed;","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.arcsine.seedLength;","random.array.arcsine.state":"\nrandom.array.arcsine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.arcsine.state\n \n\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.arcsine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n ","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.arcsine.stateLength;","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.arcsine.byteLength;\n\n See Also\n --------\n base.random.arcsine, random.strided.arcsine","random.array.bernoulli":"\nrandom.array.bernoulli( len, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n\nrandom.array.bernoulli.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.bernoulli.assign( 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.bernoulli.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.bernoulli.factory();\n > var out = fcn( 3, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.bernoulli.factory( 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.bernoulli.PRNG;\n\n\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.bernoulli.seed;\n\n\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.bernoulli.seedLength;\n\n\nrandom.array.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.bernoulli.state\n \n\n > out = random.array.bernoulli( 3, 0.5 )\n \n > out = random.array.bernoulli( 3, 0.5 )\n \n\n // Set the state:\n > random.array.bernoulli.state = state;\n\n // Regenerate a previous array:\n > out = random.array.bernoulli( 3, 0.5 )\n \n\n\nrandom.array.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.bernoulli.stateLength;\n\n\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.strided.bernoulli\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.bernoulli.assign( 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.bernoulli.factory();\n > var out = fcn( 3, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.bernoulli.factory( 0.5 );\n > out = fcn( 3 )\n ","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.bernoulli.PRNG;","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.bernoulli.seed;","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.bernoulli.seedLength;","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.bernoulli.state\n \n\n > out = random.array.bernoulli( 3, 0.5 )\n \n > out = random.array.bernoulli( 3, 0.5 )\n \n\n // Set the state:\n > random.array.bernoulli.state = state;\n\n // Regenerate a previous array:\n > out = random.array.bernoulli( 3, 0.5 )\n ","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.bernoulli.stateLength;","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.strided.bernoulli","random.array.beta":"\nrandom.array.beta( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a beta\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n\nrandom.array.beta.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.beta.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.beta.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.beta.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.beta.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.beta.PRNG;\n\n\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.beta.seed;\n\n\nrandom.array.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.beta.seedLength;\n\n\nrandom.array.beta.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.beta.state\n \n\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.beta.state = state;\n\n // Regenerate a previous array:\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n\nrandom.array.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.beta.stateLength;\n\n\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.beta.byteLength;\n\n See Also\n --------\n base.random.beta, random.strided.beta\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.beta.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.beta.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.beta.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.beta.PRNG;","random.array.beta.seed":"\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.beta.seed;","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.beta.seedLength;","random.array.beta.state":"\nrandom.array.beta.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.beta.state\n \n\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.beta.state = state;\n\n // Regenerate a previous array:\n > out = random.array.beta( 3, 2.0, 5.0 )\n ","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.beta.stateLength;","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.beta.byteLength;\n\n See Also\n --------\n base.random.beta, random.strided.beta","random.array.betaprime":"\nrandom.array.betaprime( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n\nrandom.array.betaprime.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.betaprime.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.betaprime.PRNG;\n\n\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.betaprime.seed;\n\n\nrandom.array.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.betaprime.seedLength;\n\n\nrandom.array.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.betaprime.state\n \n\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n\nrandom.array.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.betaprime.stateLength;\n\n\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.betaprime.byteLength;\n\n See Also\n --------\n base.random.betaprime, random.strided.betaprime\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.betaprime.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.betaprime.PRNG;","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.betaprime.seed;","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.betaprime.seedLength;","random.array.betaprime.state":"\nrandom.array.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.betaprime.state\n \n\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n ","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.betaprime.stateLength;","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.betaprime.byteLength;\n\n See Also\n --------\n base.random.betaprime, random.strided.betaprime","random.array.binomial":"\nrandom.array.binomial( len, n, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a binomial\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n\nrandom.array.binomial.assign( n, p, out )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n Parameters\n ----------\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.binomial.assign( 17, 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.binomial.factory( [n, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n n: number (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.binomial.factory();\n > var out = fcn( 3, 17, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.binomial.factory( 17, 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.binomial.PRNG;\n\n\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.binomial.seed;\n\n\nrandom.array.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.binomial.seedLength;\n\n\nrandom.array.binomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.binomial.state\n \n\n > out = random.array.binomial( 3, 17, 0.5 )\n \n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Set the state:\n > random.array.binomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n\nrandom.array.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.binomial.stateLength;\n\n\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.binomial.byteLength;\n\n See Also\n --------\n random.array.negativeBinomial, base.random.binomial\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n, p, out )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n Parameters\n ----------\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.binomial.assign( 17, 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n n: number (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.binomial.factory();\n > var out = fcn( 3, 17, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.binomial.factory( 17, 0.5 );\n > out = fcn( 3 )\n ","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.binomial.PRNG;","random.array.binomial.seed":"\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.binomial.seed;","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.binomial.seedLength;","random.array.binomial.state":"\nrandom.array.binomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.binomial.state\n \n\n > out = random.array.binomial( 3, 17, 0.5 )\n \n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Set the state:\n > random.array.binomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.binomial( 3, 17, 0.5 )\n ","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.binomial.stateLength;","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.binomial.byteLength;\n\n See Also\n --------\n random.array.negativeBinomial, base.random.binomial","random.array.cauchy":"\nrandom.array.cauchy( len, x0, gamma[, options] )\n Returns an array containing pseudorandom numbers drawn from a Cauchy\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cauchy.assign( x0, gamma, out )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n gamma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cauchy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cauchy.PRNG;\n\n\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cauchy.seed;\n\n\nrandom.array.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cauchy.seedLength;\n\n\nrandom.array.cauchy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cauchy.state\n \n\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cauchy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cauchy.stateLength;\n\n\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cauchy.byteLength;\n\n See Also\n --------\n base.random.cauchy\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0, gamma, out )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n gamma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cauchy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cauchy.PRNG;","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cauchy.seed;","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cauchy.seedLength;","random.array.cauchy.state":"\nrandom.array.cauchy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cauchy.state\n \n\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cauchy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n ","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cauchy.stateLength;","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cauchy.byteLength;\n\n See Also\n --------\n base.random.cauchy","random.array.chi":"\nrandom.array.chi( len, k[, options] )\n Returns an array containing pseudorandom numbers drawn from a chi\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n\nrandom.array.chi.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chi.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.chi.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chi.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chi.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chi.PRNG;\n\n\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chi.seed;\n\n\nrandom.array.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chi.seedLength;\n\n\nrandom.array.chi.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chi.state\n \n\n > out = random.array.chi( 3, 2.0 )\n \n > out = random.array.chi( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chi.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chi( 3, 2.0 )\n \n\n\nrandom.array.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chi.stateLength;\n\n\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.strided.chi\n","random.array.chi.assign":"\nrandom.array.chi.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chi.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.chi.factory":"\nrandom.array.chi.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chi.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chi.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chi.PRNG;","random.array.chi.seed":"\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chi.seed;","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chi.seedLength;","random.array.chi.state":"\nrandom.array.chi.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chi.state\n \n\n > out = random.array.chi( 3, 2.0 )\n \n > out = random.array.chi( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chi.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chi( 3, 2.0 )\n ","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chi.stateLength;","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.strided.chi","random.array.chisquare":"\nrandom.array.chisquare( len, k[, options] )\n Returns an array containing pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n\nrandom.array.chisquare.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chisquare.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.chisquare.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chisquare.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chisquare.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chisquare.PRNG;\n\n\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chisquare.seed;\n\n\nrandom.array.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chisquare.seedLength;\n\n\nrandom.array.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chisquare.state\n \n\n > out = random.array.chisquare( 3, 2.0 )\n \n > out = random.array.chisquare( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chisquare.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chisquare( 3, 2.0 )\n \n\n\nrandom.array.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chisquare.stateLength;\n\n\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.strided.chisquare\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chisquare.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chisquare.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chisquare.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chisquare.PRNG;","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chisquare.seed;","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chisquare.seedLength;","random.array.chisquare.state":"\nrandom.array.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chisquare.state\n \n\n > out = random.array.chisquare( 3, 2.0 )\n \n > out = random.array.chisquare( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chisquare.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chisquare( 3, 2.0 )\n ","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chisquare.stateLength;","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.strided.chisquare","random.array.cosine":"\nrandom.array.cosine( len, mu, s[, options] )\n Returns an array containing pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cosine.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cosine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.cosine.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cosine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cosine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cosine.PRNG;\n\n\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cosine.seed;\n\n\nrandom.array.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cosine.seedLength;\n\n\nrandom.array.cosine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cosine.state\n \n\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cosine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cosine.stateLength;\n\n\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cosine.byteLength;\n\n See Also\n --------\n base.random.cosine, random.strided.cosine\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cosine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cosine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cosine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cosine.PRNG;","random.array.cosine.seed":"\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cosine.seed;","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cosine.seedLength;","random.array.cosine.state":"\nrandom.array.cosine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cosine.state\n \n\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cosine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cosine( 3, 2.0, 5.0 )\n ","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cosine.stateLength;","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cosine.byteLength;\n\n See Also\n --------\n base.random.cosine, random.strided.cosine","random.array.discreteUniform":"\nrandom.array.discreteUniform( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n\nrandom.array.discreteUniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.discreteUniform.assign( -10, 10, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.discreteUniform.factory();\n > var out = fcn( 3, -10, 10 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.discreteUniform.factory( -10, 10 );\n > out = fcn( 3 )\n \n\n\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.discreteUniform.PRNG;\n\n\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.discreteUniform.seed;\n\n\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.discreteUniform.seedLength;\n\n\nrandom.array.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Get a copy of the current state:\n > var state = random.array.discreteUniform.state\n \n\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Set the state:\n > random.array.discreteUniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.discreteUniform.stateLength;\n\n\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.discreteUniform.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.discreteUniform, random.strided.discreteUniform\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.discreteUniform.assign( -10, 10, x )\n \n > var bool = ( out === x )\n true","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.discreteUniform.factory();\n > var out = fcn( 3, -10, 10 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.discreteUniform.factory( -10, 10 );\n > out = fcn( 3 )\n ","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.discreteUniform.PRNG;","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.discreteUniform.seed;","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.discreteUniform.seedLength;","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Get a copy of the current state:\n > var state = random.array.discreteUniform.state\n \n\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Set the state:\n > random.array.discreteUniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.discreteUniform( 3, -10, 10 )\n ","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.discreteUniform.stateLength;","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.discreteUniform.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.discreteUniform, random.strided.discreteUniform","random.array.erlang":"\nrandom.array.erlang( len, k, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from an Erlang\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n\nrandom.array.erlang.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.erlang.assign( 2, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.erlang.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.erlang.factory();\n > var out = fcn( 3, 2, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.erlang.factory( 2, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.erlang.PRNG;\n\n\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.erlang.seed;\n\n\nrandom.array.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.erlang.seedLength;\n\n\nrandom.array.erlang.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.erlang.state\n \n\n > out = random.array.erlang( 3, 2, 5.0 )\n \n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Set the state:\n > random.array.erlang.state = state;\n\n // Regenerate a previous array:\n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n\nrandom.array.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.erlang.stateLength;\n\n\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.erlang.byteLength;\n\n See Also\n --------\n base.random.erlang\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.erlang.assign( 2, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.erlang.factory();\n > var out = fcn( 3, 2, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.erlang.factory( 2, 5.0 );\n > out = fcn( 3 )\n ","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.erlang.PRNG;","random.array.erlang.seed":"\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.erlang.seed;","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.erlang.seedLength;","random.array.erlang.state":"\nrandom.array.erlang.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.erlang.state\n \n\n > out = random.array.erlang( 3, 2, 5.0 )\n \n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Set the state:\n > random.array.erlang.state = state;\n\n // Regenerate a previous array:\n > out = random.array.erlang( 3, 2, 5.0 )\n ","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.erlang.stateLength;","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.erlang.byteLength;\n\n See Also\n --------\n base.random.erlang","random.array.exponential":"\nrandom.array.exponential( len, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n lambda: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n\nrandom.array.exponential.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.exponential.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.exponential.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.exponential.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.exponential.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.exponential.PRNG;\n\n\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.exponential.seed;\n\n\nrandom.array.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.exponential.seedLength;\n\n\nrandom.array.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.exponential.state\n \n\n > out = random.array.exponential( 3, 2.0 )\n \n > out = random.array.exponential( 3, 2.0 )\n \n\n // Set the state:\n > random.array.exponential.state = state;\n\n // Regenerate a previous array:\n > out = random.array.exponential( 3, 2.0 )\n \n\n\nrandom.array.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.exponential.stateLength;\n\n\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.strided.exponential\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.exponential.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.exponential.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.exponential.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.exponential.PRNG;","random.array.exponential.seed":"\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.exponential.seed;","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.exponential.seedLength;","random.array.exponential.state":"\nrandom.array.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.exponential.state\n \n\n > out = random.array.exponential( 3, 2.0 )\n \n > out = random.array.exponential( 3, 2.0 )\n \n\n // Set the state:\n > random.array.exponential.state = state;\n\n // Regenerate a previous array:\n > out = random.array.exponential( 3, 2.0 )\n ","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.exponential.stateLength;","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.strided.exponential","random.array.f":"\nrandom.array.f( len, d1, d2[, options] )\n Returns an array containing pseudorandom numbers drawn from an F\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n\nrandom.array.f.assign( d1, d2, out )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.f.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.f.factory( [d1, d2, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.f.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.f.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.f.PRNG;\n\n\nrandom.array.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.f.seed;\n\n\nrandom.array.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.f.seedLength;\n\n\nrandom.array.f.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.f.state\n \n\n > out = random.array.f( 3, 2.0, 5.0 )\n \n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.f.state = state;\n\n // Regenerate a previous array:\n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n\nrandom.array.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.f.stateLength;\n\n\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.f.byteLength;\n\n See Also\n --------\n base.random.f\n","random.array.f.assign":"\nrandom.array.f.assign( d1, d2, out )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.f.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.f.factory":"\nrandom.array.f.factory( [d1, d2, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.f.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.f.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.f.PRNG":"\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.f.PRNG;","random.array.f.seed":"\nrandom.array.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.f.seed;","random.array.f.seedLength":"\nrandom.array.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.f.seedLength;","random.array.f.state":"\nrandom.array.f.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.f.state\n \n\n > out = random.array.f( 3, 2.0, 5.0 )\n \n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.f.state = state;\n\n // Regenerate a previous array:\n > out = random.array.f( 3, 2.0, 5.0 )\n ","random.array.f.stateLength":"\nrandom.array.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.f.stateLength;","random.array.f.byteLength":"\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.f.byteLength;\n\n See Also\n --------\n base.random.f","random.array.frechet":"\nrandom.array.frechet( len, alpha, s, m[, options] )\n Returns an array containing pseudorandom numbers drawn from a Fréchet\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.frechet.assign( alpha, s, m, out )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.frechet.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.frechet.PRNG;\n\n\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.frechet.seed;\n\n\nrandom.array.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.frechet.seedLength;\n\n\nrandom.array.frechet.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.frechet.state\n \n\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.frechet.state = state;\n\n // Regenerate a previous array:\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.frechet.stateLength;\n\n\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.frechet.byteLength;\n\n See Also\n --------\n base.random.frechet\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha, s, m, out )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.frechet.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n ","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.frechet.PRNG;","random.array.frechet.seed":"\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.frechet.seed;","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.frechet.seedLength;","random.array.frechet.state":"\nrandom.array.frechet.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.frechet.state\n \n\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.frechet.state = state;\n\n // Regenerate a previous array:\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n ","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.frechet.stateLength;","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.frechet.byteLength;\n\n See Also\n --------\n base.random.frechet","random.array.gamma":"\nrandom.array.gamma( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a gamma\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gamma.PRNG;\n\n\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gamma.seed;\n\n\nrandom.array.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gamma.seedLength;\n\n\nrandom.array.gamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gamma.state\n \n\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gamma.stateLength;\n\n\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gamma.byteLength;\n\n See Also\n --------\n base.random.gamma, random.strided.gamma\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gamma.PRNG;","random.array.gamma.seed":"\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gamma.seed;","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gamma.seedLength;","random.array.gamma.state":"\nrandom.array.gamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gamma.state\n \n\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gamma( 3, 2.0, 5.0 )\n ","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gamma.stateLength;","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gamma.byteLength;\n\n See Also\n --------\n base.random.gamma, random.strided.gamma","random.array.geometric":"\nrandom.array.geometric( len, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n\nrandom.array.geometric.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.geometric.assign( 0.01, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.geometric.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.geometric.factory();\n > var out = fcn( 3, 0.01 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.geometric.factory( 0.01 );\n > out = fcn( 3 )\n \n\n\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.geometric.PRNG;\n\n\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.geometric.seed;\n\n\nrandom.array.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.geometric.seedLength;\n\n\nrandom.array.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n // Get a copy of the current state:\n > var state = random.array.geometric.state\n \n\n > out = random.array.geometric( 3, 0.01 )\n \n > out = random.array.geometric( 3, 0.01 )\n \n\n // Set the state:\n > random.array.geometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.geometric( 3, 0.01 )\n \n\n\nrandom.array.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.geometric.stateLength;\n\n\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.strided.geometric\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.geometric.assign( 0.01, x )\n \n > var bool = ( out === x )\n true","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.geometric.factory();\n > var out = fcn( 3, 0.01 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.geometric.factory( 0.01 );\n > out = fcn( 3 )\n ","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.geometric.PRNG;","random.array.geometric.seed":"\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.geometric.seed;","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.geometric.seedLength;","random.array.geometric.state":"\nrandom.array.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n // Get a copy of the current state:\n > var state = random.array.geometric.state\n \n\n > out = random.array.geometric( 3, 0.01 )\n \n > out = random.array.geometric( 3, 0.01 )\n \n\n // Set the state:\n > random.array.geometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.geometric( 3, 0.01 )\n ","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.geometric.stateLength;","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.strided.geometric","random.array.gumbel":"\nrandom.array.gumbel( len, mu, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a Gumbel\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gumbel.assign( mu, beta, out )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gumbel.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gumbel.PRNG;\n\n\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gumbel.seed;\n\n\nrandom.array.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gumbel.seedLength;\n\n\nrandom.array.gumbel.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gumbel.state\n \n\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gumbel.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gumbel.stateLength;\n\n\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gumbel.byteLength;\n\n See Also\n --------\n base.random.gumbel\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu, beta, out )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gumbel.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gumbel.PRNG;","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gumbel.seed;","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gumbel.seedLength;","random.array.gumbel.state":"\nrandom.array.gumbel.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gumbel.state\n \n\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gumbel.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n ","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gumbel.stateLength;","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gumbel.byteLength;\n\n See Also\n --------\n base.random.gumbel","random.array.hypergeometric":"\nrandom.array.hypergeometric( len, N, K, n[, options] )\n Returns an array containing pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n\nrandom.array.hypergeometric.assign( N, K, n, out )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n N: number (optional)\n Population size.\n\n K: number (optional)\n Subpopulation size.\n\n n: number (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.hypergeometric.factory();\n > var out = fcn( 3, 20, 10, 7 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n > out = fcn( 3 )\n \n\n\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.hypergeometric.PRNG;\n\n\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.hypergeometric.seed;\n\n\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.hypergeometric.seedLength;\n\n\nrandom.array.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Get a copy of the current state:\n > var state = random.array.hypergeometric.state\n \n\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Set the state:\n > random.array.hypergeometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.hypergeometric.stateLength;\n\n\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.hypergeometric.byteLength;\n\n See Also\n --------\n base.random.hypergeometric\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N, K, n, out )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n \n > var bool = ( out === x )\n true","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n N: number (optional)\n Population size.\n\n K: number (optional)\n Subpopulation size.\n\n n: number (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.hypergeometric.factory();\n > var out = fcn( 3, 20, 10, 7 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n > out = fcn( 3 )\n ","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.hypergeometric.PRNG;","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.hypergeometric.seed;","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.hypergeometric.seedLength;","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Get a copy of the current state:\n > var state = random.array.hypergeometric.state\n \n\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Set the state:\n > random.array.hypergeometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n ","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.hypergeometric.stateLength;","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.hypergeometric.byteLength;\n\n See Also\n --------\n base.random.hypergeometric","random.array.invgamma":"\nrandom.array.invgamma( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.invgamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.invgamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.invgamma.PRNG;\n\n\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.invgamma.seed;\n\n\nrandom.array.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.invgamma.seedLength;\n\n\nrandom.array.invgamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.invgamma.state\n \n\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.invgamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.invgamma.stateLength;\n\n\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.invgamma.byteLength;\n\n See Also\n --------\n base.random.invgamma, random.strided.invgamma\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.invgamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.invgamma.PRNG;","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.invgamma.seed;","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.invgamma.seedLength;","random.array.invgamma.state":"\nrandom.array.invgamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.invgamma.state\n \n\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.invgamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n ","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.invgamma.stateLength;","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.invgamma.byteLength;\n\n See Also\n --------\n base.random.invgamma, random.strided.invgamma","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n double bounded distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.kumaraswamy.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.kumaraswamy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.kumaraswamy.PRNG;\n\n\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.kumaraswamy.seed;\n\n\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.seedLength;\n\n\nrandom.array.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.kumaraswamy.state\n \n\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.kumaraswamy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.stateLength;\n\n\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.kumaraswamy.byteLength;\n\n See Also\n --------\n base.random.kumaraswamy\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.kumaraswamy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.kumaraswamy.PRNG;","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.kumaraswamy.seed;","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.seedLength;","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.kumaraswamy.state\n \n\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.kumaraswamy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n ","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.stateLength;","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.kumaraswamy.byteLength;\n\n See Also\n --------\n base.random.kumaraswamy","random.array.laplace":"\nrandom.array.laplace( len, mu, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n\nrandom.array.laplace.assign( mu, b, out )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.laplace.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.laplace.factory( [mu, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.laplace.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.laplace.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.laplace.PRNG;\n\n\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.laplace.seed;\n\n\nrandom.array.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.laplace.seedLength;\n\n\nrandom.array.laplace.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.laplace.state\n \n\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.laplace.state = state;\n\n // Regenerate a previous array:\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n\nrandom.array.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.laplace.stateLength;\n\n\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.laplace.byteLength;\n\n See Also\n --------\n base.random.laplace\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu, b, out )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.laplace.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.laplace.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.laplace.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.laplace.PRNG;","random.array.laplace.seed":"\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.laplace.seed;","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.laplace.seedLength;","random.array.laplace.state":"\nrandom.array.laplace.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.laplace.state\n \n\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.laplace.state = state;\n\n // Regenerate a previous array:\n > out = random.array.laplace( 3, 2.0, 5.0 )\n ","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.laplace.stateLength;","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.laplace.byteLength;\n\n See Also\n --------\n base.random.laplace","random.array.levy":"\nrandom.array.levy( len, mu, c[, options] )\n Returns an array containing pseudorandom numbers drawn from a Lévy\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.levy.assign( mu, c, out )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.levy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.levy.factory( [mu, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.levy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.levy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.levy.PRNG;\n\n\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.levy.seed;\n\n\nrandom.array.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.levy.seedLength;\n\n\nrandom.array.levy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.levy.state\n \n\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.levy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.levy.stateLength;\n\n\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.levy.byteLength;\n\n See Also\n --------\n base.random.levy\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu, c, out )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.levy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.levy.factory":"\nrandom.array.levy.factory( [mu, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.levy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.levy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.levy.PRNG;","random.array.levy.seed":"\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.levy.seed;","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.levy.seedLength;","random.array.levy.state":"\nrandom.array.levy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.levy.state\n \n\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.levy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.levy( 3, 2.0, 5.0 )\n ","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.levy.stateLength;","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.levy.byteLength;\n\n See Also\n --------\n base.random.levy","random.array.logistic":"\nrandom.array.logistic( len, mu, s[, options] )\n Returns an array containing pseudorandom numbers drawn from a logistic\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n\nrandom.array.logistic.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n Parameters\n ----------\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.logistic.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.logistic.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.logistic.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.logistic.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.logistic.PRNG;\n\n\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.logistic.seed;\n\n\nrandom.array.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.logistic.seedLength;\n\n\nrandom.array.logistic.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.logistic.state\n \n\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.logistic.state = state;\n\n // Regenerate a previous array:\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n\nrandom.array.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.logistic.stateLength;\n\n\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.logistic.byteLength;\n\n See Also\n --------\n base.random.logistic\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n Parameters\n ----------\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.logistic.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.logistic.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.logistic.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.logistic.PRNG;","random.array.logistic.seed":"\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.logistic.seed;","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.logistic.seedLength;","random.array.logistic.state":"\nrandom.array.logistic.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.logistic.state\n \n\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.logistic.state = state;\n\n // Regenerate a previous array:\n > out = random.array.logistic( 3, 2.0, 5.0 )\n ","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.logistic.stateLength;","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.logistic.byteLength;\n\n See Also\n --------\n base.random.logistic","random.array.lognormal":"\nrandom.array.lognormal( len, mu, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.lognormal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.lognormal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.lognormal.PRNG;\n\n\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.lognormal.seed;\n\n\nrandom.array.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.lognormal.seedLength;\n\n\nrandom.array.lognormal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.lognormal.state\n \n\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.lognormal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.lognormal.stateLength;\n\n\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.lognormal.byteLength;\n\n See Also\n --------\n base.random.lognormal, random.strided.lognormal\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.lognormal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.lognormal.PRNG;","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.lognormal.seed;","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.lognormal.seedLength;","random.array.lognormal.state":"\nrandom.array.lognormal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.lognormal.state\n \n\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.lognormal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n ","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.lognormal.stateLength;","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.lognormal.byteLength;\n\n See Also\n --------\n base.random.lognormal, random.strided.lognormal","random.array.minstd":"\nrandom.array.minstd( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n\nrandom.array.minstd.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd.normalized( 3 )\n \n\n\nrandom.array.minstd.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstd.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstd.PRNG;\n\n\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstd.seed;\n\n\nrandom.array.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstd.seedLength;\n\n\nrandom.array.minstd.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstd.state;\n\n > out = random.array.minstd( 3 )\n \n > out = random.array.minstd( 3 )\n \n\n // Set the state:\n > random.array.minstd.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstd( 3 )\n \n\n\nrandom.array.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstd.stateLength;\n\n\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstd.byteLength;\n\n See Also\n --------\n random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd.normalized( 3 )\n ","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstd.factory();\n > var out = fcn( 3 )\n ","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstd.PRNG;","random.array.minstd.seed":"\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstd.seed;","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstd.seedLength;","random.array.minstd.state":"\nrandom.array.minstd.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstd.state;\n\n > out = random.array.minstd( 3 )\n \n > out = random.array.minstd( 3 )\n \n\n // Set the state:\n > random.array.minstd.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstd( 3 )\n ","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstd.stateLength;","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstd.byteLength;\n\n See Also\n --------\n random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n\nrandom.array.minstdShuffle.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle.normalized( 3 )\n \n\n\nrandom.array.minstdShuffle.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstdShuffle.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstdShuffle.PRNG;\n\n\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstdShuffle.seed;\n\n\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.seedLength;\n\n\nrandom.array.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstdShuffle.state;\n\n > out = random.array.minstdShuffle( 3 )\n \n > out = random.array.minstdShuffle( 3 )\n \n\n // Set the state:\n > random.array.minstdShuffle.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstdShuffle( 3 )\n \n\n\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.stateLength;\n\n\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstdShuffle.byteLength;\n\n See Also\n --------\n random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle.normalized( 3 )\n ","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstdShuffle.factory();\n > var out = fcn( 3 )\n ","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstdShuffle.PRNG;","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstdShuffle.seed;","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.seedLength;","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstdShuffle.state;\n\n > out = random.array.minstdShuffle( 3 )\n \n > out = random.array.minstdShuffle( 3 )\n \n\n // Set the state:\n > random.array.minstdShuffle.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstdShuffle( 3 )\n ","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.stateLength;","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstdShuffle.byteLength;\n\n See Also\n --------\n random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle","random.array.mt19937":"\nrandom.array.mt19937( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[0, 4294967295]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n\nrandom.array.mt19937.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937.normalized( 3 )\n \n\n\nrandom.array.mt19937.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.mt19937.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.mt19937.PRNG;\n\n\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.mt19937.seed;\n\n\nrandom.array.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.mt19937.seedLength;\n\n\nrandom.array.mt19937.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.mt19937.state;\n\n > out = random.array.mt19937( 3 )\n \n > out = random.array.mt19937( 3 )\n \n\n // Set the state:\n > random.array.mt19937.state = state;\n\n // Regenerate a previous array:\n > out = random.array.mt19937( 3 )\n \n\n\nrandom.array.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.mt19937.stateLength;\n\n\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.mt19937.byteLength;\n\n See Also\n --------\n random.array.randu, base.random.mt19937, random.strided.mt19937\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937.normalized( 3 )\n ","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.mt19937.factory();\n > var out = fcn( 3 )\n ","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.mt19937.PRNG;","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.mt19937.seed;","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.mt19937.seedLength;","random.array.mt19937.state":"\nrandom.array.mt19937.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.mt19937.state;\n\n > out = random.array.mt19937( 3 )\n \n > out = random.array.mt19937( 3 )\n \n\n // Set the state:\n > random.array.mt19937.state = state;\n\n // Regenerate a previous array:\n > out = random.array.mt19937( 3 )\n ","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.mt19937.stateLength;","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.mt19937.byteLength;\n\n See Also\n --------\n random.array.randu, base.random.mt19937, random.strided.mt19937","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len, r, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a negative\n binomial distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n\nrandom.array.negativeBinomial.assign( r, p, out )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.negativeBinomial.factory();\n > var out = fcn( 3, 10, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.negativeBinomial.PRNG;\n\n\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.negativeBinomial.seed;\n\n\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.seedLength;\n\n\nrandom.array.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.negativeBinomial.state\n \n\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Set the state:\n > random.array.negativeBinomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.stateLength;\n\n\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.negativeBinomial.byteLength;\n\n See Also\n --------\n random.array.binomial, base.random.negativeBinomial\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r, p, out )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.negativeBinomial.factory();\n > var out = fcn( 3, 10, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n > out = fcn( 3 )\n ","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.negativeBinomial.PRNG;","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.negativeBinomial.seed;","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.seedLength;","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.negativeBinomial.state\n \n\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Set the state:\n > random.array.negativeBinomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n ","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.stateLength;","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.negativeBinomial.byteLength;\n\n See Also\n --------\n random.array.binomial, base.random.negativeBinomial","random.array.normal":"\nrandom.array.normal( len, mu, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a normal\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.normal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.normal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.normal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n sigma: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.normal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.normal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.normal.PRNG;\n\n\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.normal.seed;\n\n\nrandom.array.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.normal.seedLength;\n\n\nrandom.array.normal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.normal.state\n \n\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.normal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.normal.stateLength;\n\n\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.normal.byteLength;\n\n See Also\n --------\n base.random.normal, random.strided.normal\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.normal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.normal.factory":"\nrandom.array.normal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n sigma: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.normal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.normal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.normal.PRNG;","random.array.normal.seed":"\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.normal.seed;","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.normal.seedLength;","random.array.normal.state":"\nrandom.array.normal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.normal.state\n \n\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.normal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.normal( 3, 2.0, 5.0 )\n ","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.normal.stateLength;","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.normal.byteLength;\n\n See Also\n --------\n base.random.normal, random.strided.normal","random.array.pareto1":"\nrandom.array.pareto1( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n I) distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n\nrandom.array.pareto1.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.pareto1.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.pareto1.PRNG;\n\n\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.pareto1.seed;\n\n\nrandom.array.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.pareto1.seedLength;\n\n\nrandom.array.pareto1.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.pareto1.state\n \n\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.pareto1.state = state;\n\n // Regenerate a previous array:\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n\nrandom.array.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.pareto1.stateLength;\n\n\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.pareto1.byteLength;\n\n See Also\n --------\n base.random.pareto1\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.pareto1.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.pareto1.PRNG;","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.pareto1.seed;","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.pareto1.seedLength;","random.array.pareto1.state":"\nrandom.array.pareto1.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.pareto1.state\n \n\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.pareto1.state = state;\n\n // Regenerate a previous array:\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n ","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.pareto1.stateLength;","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.pareto1.byteLength;\n\n See Also\n --------\n base.random.pareto1","random.array.poisson":"\nrandom.array.poisson( len, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from a Poisson\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n lambda: number\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n\nrandom.array.poisson.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n Parameters\n ----------\n lambda: number\n Mean parameter.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.poisson.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.poisson.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.poisson.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.poisson.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.poisson.PRNG;\n\n\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.poisson.seed;\n\n\nrandom.array.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.poisson.seedLength;\n\n\nrandom.array.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.poisson.state\n \n\n > out = random.array.poisson( 3, 2.0 )\n \n > out = random.array.poisson( 3, 2.0 )\n \n\n // Set the state:\n > random.array.poisson.state = state;\n\n // Regenerate a previous array:\n > out = random.array.poisson( 3, 2.0 )\n \n\n\nrandom.array.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.poisson.stateLength;\n\n\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.strided.poisson\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n Parameters\n ----------\n lambda: number\n Mean parameter.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.poisson.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.poisson.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.poisson.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.poisson.PRNG;","random.array.poisson.seed":"\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.poisson.seed;","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.poisson.seedLength;","random.array.poisson.state":"\nrandom.array.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.poisson.state\n \n\n > out = random.array.poisson( 3, 2.0 )\n \n > out = random.array.poisson( 3, 2.0 )\n \n\n // Set the state:\n > random.array.poisson.state = state;\n\n // Regenerate a previous array:\n > out = random.array.poisson( 3, 2.0 )\n ","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.poisson.stateLength;","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.strided.poisson","random.array.randu":"\nrandom.array.randu( len[, options] )\n Returns an array containing uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n\nrandom.array.randu.factory( [options] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.randu.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.randu.PRNG;\n\n\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.randu.seed;\n\n\nrandom.array.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.randu.seedLength;\n\n\nrandom.array.randu.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.randu.state;\n\n > out = random.array.randu( 3 )\n \n > out = random.array.randu( 3 )\n \n\n // Set the state:\n > random.array.randu.state = state;\n\n // Regenerate a previous array:\n > out = random.array.randu( 3 )\n \n\n\nrandom.array.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.randu.stateLength;\n\n\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.randu.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.randu, random.strided.randu\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.randu.factory();\n > var out = fcn( 3 )\n ","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.randu.PRNG;","random.array.randu.seed":"\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.randu.seed;","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.randu.seedLength;","random.array.randu.state":"\nrandom.array.randu.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.randu.state;\n\n > out = random.array.randu( 3 )\n \n > out = random.array.randu( 3 )\n \n\n // Set the state:\n > random.array.randu.state = state;\n\n // Regenerate a previous array:\n > out = random.array.randu( 3 )\n ","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.randu.stateLength;","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.randu.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.randu, random.strided.randu","random.array.rayleigh":"\nrandom.array.rayleigh( len, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n sigma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n\nrandom.array.rayleigh.assign( sigma, out )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.rayleigh.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.rayleigh.factory( [sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.rayleigh.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.rayleigh.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.rayleigh.PRNG;\n\n\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.rayleigh.seed;\n\n\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.rayleigh.seedLength;\n\n\nrandom.array.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.rayleigh.state\n \n\n > out = random.array.rayleigh( 3, 2.0 )\n \n > out = random.array.rayleigh( 3, 2.0 )\n \n\n // Set the state:\n > random.array.rayleigh.state = state;\n\n // Regenerate a previous array:\n > out = random.array.rayleigh( 3, 2.0 )\n \n\n\nrandom.array.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.rayleigh.stateLength;\n\n\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.strided.rayleigh\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma, out )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.rayleigh.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.rayleigh.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.rayleigh.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.rayleigh.PRNG;","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.rayleigh.seed;","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.rayleigh.seedLength;","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.rayleigh.state\n \n\n > out = random.array.rayleigh( 3, 2.0 )\n \n > out = random.array.rayleigh( 3, 2.0 )\n \n\n // Set the state:\n > random.array.rayleigh.state = state;\n\n // Regenerate a previous array:\n > out = random.array.rayleigh( 3, 2.0 )\n ","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.rayleigh.stateLength;","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.strided.rayleigh","random.array.t":"\nrandom.array.t( len, v[, options] )\n Returns an array containing pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n\nrandom.array.t.assign( v, out )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.t.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.t.factory( [v, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.t.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.t.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.t.PRNG;\n\n\nrandom.array.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.t.seed;\n\n\nrandom.array.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.t.seedLength;\n\n\nrandom.array.t.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.t.state\n \n\n > out = random.array.t( 3, 2.0 )\n \n > out = random.array.t( 3, 2.0 )\n \n\n // Set the state:\n > random.array.t.state = state;\n\n // Regenerate a previous array:\n > out = random.array.t( 3, 2.0 )\n \n\n\nrandom.array.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.t.stateLength;\n\n\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.t.byteLength;\n\n See Also\n --------\n base.random.t, random.strided.t\n","random.array.t.assign":"\nrandom.array.t.assign( v, out )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.t.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.t.factory":"\nrandom.array.t.factory( [v, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.t.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.t.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.t.PRNG":"\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.t.PRNG;","random.array.t.seed":"\nrandom.array.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.t.seed;","random.array.t.seedLength":"\nrandom.array.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.t.seedLength;","random.array.t.state":"\nrandom.array.t.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.t.state\n \n\n > out = random.array.t( 3, 2.0 )\n \n > out = random.array.t( 3, 2.0 )\n \n\n // Set the state:\n > random.array.t.state = state;\n\n // Regenerate a previous array:\n > out = random.array.t( 3, 2.0 )\n ","random.array.t.stateLength":"\nrandom.array.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.t.stateLength;","random.array.t.byteLength":"\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.t.byteLength;\n\n See Also\n --------\n base.random.t, random.strided.t","random.array.triangular":"\nrandom.array.triangular( len, a, b, c[, options] )\n Returns an array containing pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.triangular.assign( a, b, c, out )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.triangular.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.triangular.PRNG;\n\n\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.triangular.seed;\n\n\nrandom.array.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.triangular.seedLength;\n\n\nrandom.array.triangular.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.triangular.state\n \n\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.triangular.state = state;\n\n // Regenerate a previous array:\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.triangular.stateLength;\n\n\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.triangular.byteLength;\n\n See Also\n --------\n base.random.triangular\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a, b, c, out )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.triangular.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n ","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.triangular.PRNG;","random.array.triangular.seed":"\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.triangular.seed;","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.triangular.seedLength;","random.array.triangular.state":"\nrandom.array.triangular.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.triangular.state\n \n\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.triangular.state = state;\n\n // Regenerate a previous array:\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n ","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.triangular.stateLength;","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.triangular.byteLength;\n\n See Also\n --------\n base.random.triangular","random.array.uniform":"\nrandom.array.uniform( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a continuous\n uniform distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n\nrandom.array.uniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.uniform.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.uniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.uniform.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.uniform.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.uniform.PRNG;\n\n\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.uniform.seed;\n\n\nrandom.array.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.uniform.seedLength;\n\n\nrandom.array.uniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.uniform.state\n \n\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.uniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n\nrandom.array.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.uniform.stateLength;\n\n\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.uniform.byteLength;\n\n See Also\n --------\n random.array.discreteUniform, base.random.uniform, random.strided.uniform\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.uniform.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.uniform.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.uniform.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.uniform.PRNG;","random.array.uniform.seed":"\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.uniform.seed;","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.uniform.seedLength;","random.array.uniform.state":"\nrandom.array.uniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.uniform.state\n \n\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.uniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.uniform( 3, 2.0, 5.0 )\n ","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.uniform.stateLength;","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.uniform.byteLength;\n\n See Also\n --------\n random.array.discreteUniform, base.random.uniform, random.strided.uniform","random.array.weibull":"\nrandom.array.weibull( len, k, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from a Weibull\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n\nrandom.array.weibull.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.weibull.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.weibull.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n lambda: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.weibull.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.weibull.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.weibull.PRNG;\n\n\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.weibull.seed;\n\n\nrandom.array.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.weibull.seedLength;\n\n\nrandom.array.weibull.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.weibull.state\n \n\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.weibull.state = state;\n\n // Regenerate a previous array:\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n\nrandom.array.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.weibull.stateLength;\n\n\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.weibull.byteLength;\n\n See Also\n --------\n base.random.weibull\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.weibull.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n lambda: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.weibull.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.weibull.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.weibull.PRNG;","random.array.weibull.seed":"\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.weibull.seed;","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.weibull.seedLength;","random.array.weibull.state":"\nrandom.array.weibull.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.weibull.state\n \n\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.weibull.state = state;\n\n // Regenerate a previous array:\n > out = random.array.weibull( 3, 2.0, 5.0 )\n ","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.weibull.stateLength;","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.weibull.byteLength;\n\n See Also\n --------\n base.random.weibull","random.iterators.arcsine":"\nrandom.iterators.arcsine( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.arcsine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.arcsine\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.bernoulli( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.bernoulli\n","random.iterators.beta":"\nrandom.iterators.beta( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.beta( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.beta\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.betaprime( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.betaprime\n","random.iterators.binomial":"\nrandom.iterators.binomial( n, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.binomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.binomial\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.boxMuller();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.boxMuller\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0, Ɣ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cauchy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cauchy\n","random.iterators.chi":"\nrandom.iterators.chi( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chi( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chi\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chisquare( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chisquare\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cosine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cosine\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned iterator, one must\n seed the provided `prng` (assuming the provided `prng` is seedable). The\n provided PRNG must have `MIN` and `MAX` properties specifying the\n minimum and maximum possible pseudorandom integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.discreteUniform( 0, 3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.discreteUniform\n","random.iterators.erlang":"\nrandom.iterators.erlang( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If `k` is not a positive integer or `λ <= 0`, the function throws an error.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.erlang( 1, 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.erlang\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.exponential( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.exponential\n","random.iterators.f":"\nrandom.iterators.f( d1, d2[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `d1 <= 0` or `d2 <= 0`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.f( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.f\n","random.iterators.frechet":"\nrandom.iterators.frechet( α, s, m[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `s <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.frechet\n","random.iterators.gamma":"\nrandom.iterators.gamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gamma\n","random.iterators.geometric":"\nrandom.iterators.geometric( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.geometric( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.geometric\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gumbel( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gumbel\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N, K, n[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n throws an error.\n\n If `n > N` or `K > N`, the function throws an error.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.hypergeometric( 20, 10, 7 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.hypergeometric\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.improvedZiggurat();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.improvedZiggurat\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.invgamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.invgamma\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `a <= 0` or `b <= 0`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.kumaraswamy( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.kumaraswamy\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.laplace( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.laplace\n","random.iterators.levy":"\nrandom.iterators.levy( μ, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.levy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.levy\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.logistic( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.logistic\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.lognormal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.lognormal\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstd();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstd, random.iterators.minstdShuffle, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstdShuffle();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstd, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Uint32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Uint32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.mt19937();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.mt19937, random.iterators.minstd, random.iterators.minstdShuffle, random.iterators.randi, random.iterators.randu\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.negativeBinomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.negativeBinomial\n","random.iterators.normal":"\nrandom.iterators.normal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.normal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.normal\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.pareto1( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.pareto1\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.poisson( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.poisson\n","random.iterators.randi":"\nrandom.iterators.randi( [options] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randi();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randi, random.iterators.randu\n","random.iterators.randn":"\nrandom.iterators.randn( [options] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: `'improved-ziggurat'`.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randn();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randn\n","random.iterators.randu":"\nrandom.iterators.randu( [options] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randu();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randu, random.iterators.randi\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.rayleigh( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.rayleigh\n","random.iterators.t":"\nrandom.iterators.t( v[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.t( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.t\n","random.iterators.triangular":"\nrandom.iterators.triangular( a, b, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.triangular\n","random.iterators.uniform":"\nrandom.iterators.uniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.uniform( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.uniform\n","random.iterators.weibull":"\nrandom.iterators.weibull( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `k <= 0` or `λ <= 0`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.weibull( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.weibull\n","random.streams.arcsine":"\nrandom.streams.arcsine( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );\n\n\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.arcsine, random.iterators.arcsine\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.arcsine, random.iterators.arcsine","random.streams.bernoulli":"\nrandom.streams.bernoulli( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );\n\n\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.bernoulli, random.iterators.bernoulli\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.bernoulli, random.iterators.bernoulli","random.streams.beta":"\nrandom.streams.beta( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );\n\n\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.beta, random.iterators.beta\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.beta, random.iterators.beta","random.streams.betaprime":"\nrandom.streams.betaprime( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );\n\n\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.betaprime, random.iterators.betaprime\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.betaprime, random.iterators.betaprime","random.streams.binomial":"\nrandom.streams.binomial( n, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial( 20, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );\n\n\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.binomial, random.iterators.binomial\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.binomial, random.iterators.binomial","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );\n\n\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn","random.streams.cauchy":"\nrandom.streams.cauchy( x0, γ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );\n\n\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cauchy, random.iterators.cauchy\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cauchy, random.iterators.cauchy","random.streams.chi":"\nrandom.streams.chi( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );\n\n\nrandom.streams.chi.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chi, random.iterators.chi\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chi, random.iterators.chi","random.streams.chisquare":"\nrandom.streams.chisquare( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );\n\n\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chisquare, random.iterators.chisquare\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chisquare, random.iterators.chisquare","random.streams.cosine":"\nrandom.streams.cosine( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );\n\n\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cosine, random.iterators.cosine\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cosine, random.iterators.cosine","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform( 2, 5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );\n\n\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.discreteUniform, random.iterators.discreteUniform\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.discreteUniform, random.iterators.discreteUniform","random.streams.erlang":"\nrandom.streams.erlang( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang( 2, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );\n\n\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.erlang, random.iterators.erlang\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.erlang, random.iterators.erlang","random.streams.exponential":"\nrandom.streams.exponential( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );\n\n\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.exponential, random.iterators.exponential\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.exponential, random.iterators.exponential","random.streams.f":"\nrandom.streams.f( d1, d2[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );\n\n\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.f, random.iterators.f\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.f, random.iterators.f","random.streams.frechet":"\nrandom.streams.frechet( α, s, m[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Fréchet distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.frechet.factory( [α, s, m,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.frechet.factory( opts );\n\n\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.frechet, random.iterators.frechet\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α, s, m,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.frechet.factory( opts );","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.frechet, random.iterators.frechet","random.streams.gamma":"\nrandom.streams.gamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );\n\n\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gamma, random.iterators.gamma\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gamma, random.iterators.gamma","random.streams.geometric":"\nrandom.streams.geometric( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );\n\n\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.geometric, random.iterators.geometric\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.geometric, random.iterators.geometric","random.streams.gumbel":"\nrandom.streams.gumbel( μ, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );\n\n\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gumbel, random.iterators.gumbel\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gumbel, random.iterators.gumbel","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N, K, n[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric( 5, 3, 2, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.hypergeometric.factory( opts );\n\n\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.hypergeometric, random.iterators.hypergeometric\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.hypergeometric.factory( opts );","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.hypergeometric, random.iterators.hypergeometric","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );\n\n\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn","random.streams.invgamma":"\nrandom.streams.invgamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );\n\n\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.invgamma, random.iterators.invgamma\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.invgamma, random.iterators.invgamma","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );\n\n\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.kumaraswamy, random.iterators.kumaraswamy\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.kumaraswamy, random.iterators.kumaraswamy","random.streams.laplace":"\nrandom.streams.laplace( μ, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );\n\n\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.laplace, random.iterators.laplace\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.laplace, random.iterators.laplace","random.streams.levy":"\nrandom.streams.levy( μ, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );\n\n\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.levy, random.iterators.levy\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.levy, random.iterators.levy","random.streams.logistic":"\nrandom.streams.logistic( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );\n\n\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.logistic, random.iterators.logistic\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.logistic, random.iterators.logistic","random.streams.lognormal":"\nrandom.streams.lognormal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );\n\n\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.lognormal, random.iterators.lognormal\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.lognormal, random.iterators.lognormal","random.streams.minstd":"\nrandom.streams.minstd( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );\n\n\nrandom.streams.minstd.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );\n\n\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.mt19937":"\nrandom.streams.mt19937( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a 32-bit Mersenne\n Twister pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );\n\n\nrandom.streams.mt19937.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial( 20.0, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );\n\n\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.negativeBinomial, random.iterators.negativeBinomial\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.negativeBinomial, random.iterators.negativeBinomial","random.streams.normal":"\nrandom.streams.normal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );\n\n\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.normal, random.iterators.normal\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.normal, random.iterators.normal","random.streams.pareto1":"\nrandom.streams.pareto1( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );\n\n\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.pareto1, random.iterators.pareto1\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.pareto1, random.iterators.pareto1","random.streams.poisson":"\nrandom.streams.poisson( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );\n\n\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.poisson, random.iterators.poisson\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.poisson, random.iterators.poisson","random.streams.randi":"\nrandom.streams.randi( [options] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );\n\n\nrandom.streams.randi.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randi, random.iterators.randi, random.streams.randu\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randi, random.iterators.randi, random.streams.randu","random.streams.randn":"\nrandom.streams.randn( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );\n\n\nrandom.streams.randn.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat","random.streams.randu":"\nrandom.streams.randu( [options] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );\n\n\nrandom.streams.randu.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randu, random.iterators.randu, random.streams.randi\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randu, random.iterators.randu, random.streams.randi","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );\n\n\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.rayleigh, random.iterators.rayleigh\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.rayleigh, random.iterators.rayleigh","random.streams.t":"\nrandom.streams.t( v[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );\n\n\nrandom.streams.t.objectMode( v[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.t, random.iterators.t\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.t, random.iterators.t","random.streams.triangular":"\nrandom.streams.triangular( a, b, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.triangular.factory( opts );\n\n\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.triangular, random.iterators.triangular\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.triangular.factory( opts );","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.triangular, random.iterators.triangular","random.streams.uniform":"\nrandom.streams.uniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );\n\n\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.uniform, random.iterators.uniform\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.uniform, random.iterators.uniform","random.streams.weibull":"\nrandom.streams.weibull( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );\n\n\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.weibull, random.iterators.weibull\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.weibull, random.iterators.weibull","random.strided.arcsine":"\nrandom.strided.arcsine( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.arcsine, random.array.arcsine\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.arcsine, random.array.arcsine","random.strided.bernoulli":"\nrandom.strided.bernoulli( N, p, sp, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.bernoulli.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.bernoulli.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.bernoulli.PRNG;\n\n\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.bernoulli.seed;\n\n\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.bernoulli.seedLength;\n\n\nrandom.strided.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.bernoulli.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.bernoulli.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.bernoulli.stateLength;\n\n\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.array.bernoulli\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n [...]","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.bernoulli.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.5 ], 0, out, 1 )\n [...]","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.bernoulli.PRNG;","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.bernoulli.seed;","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.bernoulli.seedLength;","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.bernoulli.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.bernoulli.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.bernoulli.stateLength;","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.array.bernoulli","random.strided.beta":"\nrandom.strided.beta( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.beta, random.array.beta\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.beta, random.array.beta","random.strided.betaprime":"\nrandom.strided.betaprime( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.betaprime, random.array.betaprime\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.betaprime, random.array.betaprime","random.strided.chi":"\nrandom.strided.chi( N, k, sk, out, so )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.chi.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chi.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chi.PRNG;\n\n\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chi.seed;\n\n\nrandom.strided.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chi.seedLength;\n\n\nrandom.strided.chi.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chi.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chi.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chi.stateLength;\n\n\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.array.chi\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chi.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chi.PRNG;","random.strided.chi.seed":"\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chi.seed;","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chi.seedLength;","random.strided.chi.state":"\nrandom.strided.chi.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chi.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chi.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chi.stateLength;","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.array.chi","random.strided.chisquare":"\nrandom.strided.chisquare( N, k, sk, out, so )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.chisquare.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chisquare.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chisquare.PRNG;\n\n\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chisquare.seed;\n\n\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chisquare.seedLength;\n\n\nrandom.strided.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chisquare.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chisquare.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chisquare.stateLength;\n\n\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.array.chisquare\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chisquare.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chisquare.PRNG;","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chisquare.seed;","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chisquare.seedLength;","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chisquare.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chisquare.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chisquare.stateLength;","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.array.chisquare","random.strided.cosine":"\nrandom.strided.cosine( N, mu, sm, s, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n [...]\n\n\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n os: integer\n Starting index for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.cosine, random.array.cosine\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n os: integer\n Starting index for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.cosine, random.array.cosine","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform","random.strided.exponential":"\nrandom.strided.exponential( N, lambda, sl, out, so )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.exponential.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.exponential.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.exponential.PRNG;\n\n\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.exponential.seed;\n\n\nrandom.strided.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.exponential.seedLength;\n\n\nrandom.strided.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.exponential.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.exponential.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.exponential.stateLength;\n\n\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.array.exponential\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.exponential.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.exponential.PRNG;","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.exponential.seed;","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.exponential.seedLength;","random.strided.exponential.state":"\nrandom.strided.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.exponential.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.exponential.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.exponential.stateLength;","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.array.exponential","random.strided.gamma":"\nrandom.strided.gamma( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.gamma, random.array.gamma\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.gamma, random.array.gamma","random.strided.geometric":"\nrandom.strided.geometric( N, p, sp, out, so )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.geometric.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.geometric.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.geometric.PRNG;\n\n\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.geometric.seed;\n\n\nrandom.strided.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.geometric.seedLength;\n\n\nrandom.strided.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.geometric.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.geometric.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.geometric.stateLength;\n\n\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.array.geometric\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n [...]","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.geometric.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.01 ], 0, out, 1 )\n [...]","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.geometric.PRNG;","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.geometric.seed;","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.geometric.seedLength;","random.strided.geometric.state":"\nrandom.strided.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.geometric.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.geometric.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.geometric.stateLength;","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.array.geometric","random.strided.invgamma":"\nrandom.strided.invgamma( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.invgamma, random.array.invgamma\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.invgamma, random.array.invgamma","random.strided.lognormal":"\nrandom.strided.lognormal( N, mu, sm, sigma, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n [...]\n\n\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.lognormal, random.array.lognormal\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.lognormal, random.array.lognormal","random.strided.minstd":"\nrandom.strided.minstd( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.minstd.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized( out.length, out, 1 )\n [...]","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n [...]","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu","random.strided.mt19937":"\nrandom.strided.mt19937( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937( out.length, out, 1 )\n [...]\n\n\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.mt19937, random.array.mt19937, random.strided.randu\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized( out.length, out, 1 )\n [...]","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.mt19937, random.array.mt19937, random.strided.randu","random.strided.normal":"\nrandom.strided.normal( N, mu, sm, sigma, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n [...]\n\n\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.normal, random.array.normal\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.normal, random.array.normal","random.strided.poisson":"\nrandom.strided.poisson( N, lambda, sl, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.poisson.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.poisson.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.poisson.PRNG;\n\n\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.poisson.seed;\n\n\nrandom.strided.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.poisson.seedLength;\n\n\nrandom.strided.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.poisson.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.poisson.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.poisson.stateLength;\n\n\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.array.poisson\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.poisson.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.poisson.PRNG;","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.poisson.seed;","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.poisson.seedLength;","random.strided.poisson.state":"\nrandom.strided.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.poisson.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.poisson.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.poisson.stateLength;","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.array.poisson","random.strided.randu":"\nrandom.strided.randu( N, out, so[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu( out.length, out, 1 )\n [...]\n\n\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.randu, random.array.randu, random.strided.uniform\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.randu, random.array.randu, random.strided.uniform","random.strided.rayleigh":"\nrandom.strided.rayleigh( N, sigma, ss, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.rayleigh.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.rayleigh.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.rayleigh.PRNG;\n\n\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.rayleigh.seed;\n\n\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.rayleigh.seedLength;\n\n\nrandom.strided.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.rayleigh.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.rayleigh.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.rayleigh.stateLength;\n\n\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.array.rayleigh\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.rayleigh.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.rayleigh.PRNG;","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.rayleigh.seed;","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.rayleigh.seedLength;","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.rayleigh.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.rayleigh.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.rayleigh.stateLength;","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.array.rayleigh","random.strided.t":"\nrandom.strided.t( N, v, sv, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n ov: integer\n Starting index for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.t.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.t.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.t.PRNG;\n\n\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.t.seed;\n\n\nrandom.strided.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.t.seedLength;\n\n\nrandom.strided.t.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.t.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.t.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.t.stateLength;\n\n\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.t.byteLength;\n\n See Also\n --------\n base.random.t, random.array.t\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n ov: integer\n Starting index for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.t.factory":"\nrandom.strided.t.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.t.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.t.PRNG;","random.strided.t.seed":"\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.t.seed;","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.t.seedLength;","random.strided.t.state":"\nrandom.strided.t.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.t.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.t.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.t.stateLength;","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.t.byteLength;\n\n See Also\n --------\n base.random.t, random.array.t","random.strided.uniform":"\nrandom.strided.uniform( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.uniform, random.array.uniform, random.strided.discreteUniform\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.uniform, random.array.uniform, random.strided.discreteUniform","ranks":"\nranks( arr[, options] )\n Computes the sample ranks for the values of an array-like object.\n\n When all elements of the `array` are different, the ranks are uniquely\n determined. When there are equal elements (called *ties*), the `method`\n option determines how they are handled. The default, `'average'`, replaces\n the ranks of the ties by their mean. Other possible options are `'min'` and\n `'max'`, which replace the ranks of the ties by their minimum and maximum,\n respectively. `'dense'` works like `'min'`, with the difference that the\n next highest element after a tie is assigned the next smallest integer.\n Finally, `ordinal` gives each element in `arr` a distinct rank, according to\n the position they appear in.\n\n The `missing` option is used to specify how to handle missing data.\n By default, `NaN` or `null` are treated as missing values. `'last'`specifies\n that missing values are placed last, `'first'` that the are assigned the\n lowest ranks and `'remove'` means that they are removed from the array\n before the ranks are calculated.\n\n Parameters\n ----------\n arr: Array\n Input values.\n\n options: Object (optional)\n Function options.\n\n options.method (optional)\n Method name determining how ties are treated (`average`, `min`, `max`,\n `dense`, or `ordinal`). Default: `'average'`.\n\n options.missing (optional)\n Determines where missing values go (`first`, `last`, or `remove`).\n Default: `'last'`.\n\n options.encoding (optional)\n Array of values encoding missing values. Default: `[ null, NaN ]`.\n\n Returns\n -------\n out: Array\n Array containing the computed ranks for the elements of the input array.\n\n Examples\n --------\n > var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\n > var out = ranks( arr )\n [ 2, 3, 5, 1, 4 ]\n\n // Ties are averaged:\n > arr = [ 2, 2, 1, 4, 3 ];\n > out = ranks( arr )\n [ 2.5, 2.5, 1, 5, 4 ]\n\n // Missing values are placed last:\n > arr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\n > out = ranks( arr )\n [ 6, 2.5, 2.5, 1, 5, 4, 7 ,8 ]\n\n","readDir":"\nreadDir( path, clbk )\n Asynchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n clbk: Function\n Callback to invoke after reading directory contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readDir( './beep/boop', onRead );\n\n\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n See Also\n --------\n exists, readFile\n","readDir.sync":"\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n See Also\n --------\n exists, readFile","readFile":"\nreadFile( file[, options], clbk )\n Asynchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readFile( './beep/boop.js', onRead );\n\n\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n See Also\n --------\n exists, open, readDir, readJSON, writeFile\n","readFile.sync":"\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n See Also\n --------\n exists, open, readDir, readJSON, writeFile","readFileList":"\nreadFileList( filepaths[, options], clbk )\n Asynchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Each file is represented by an object with the following fields:\n\n - file: file path\n - data: file contents as either a Buffer or string\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > readFileList( filepaths, onRead );\n\n\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );\n\n","readFileList.sync":"\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );","readJSON":"\nreadJSON( file[, options], clbk )\n Asynchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readJSON( './beep/boop.json', onRead );\n\n\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n See Also\n --------\n readFile\n","readJSON.sync":"\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n See Also\n --------\n readFile","readWASM":"\nreadWASM( file[, options], clbk )\n Asynchronously reads a file as WebAssembly.\n\n The function returns file contents as a Uint8Array.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readWASM( './beep/boop.wasm', onRead );\n\n\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n See Also\n --------\n readFile\n","readWASM.sync":"\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n See Also\n --------\n readFile","real":"\nreal( z )\n Returns the real component of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var re = real( z )\n 5.0\n\n See Also\n --------\n imag, reim\n","realarray":"\nrealarray( [dtype] )\n Creates a typed array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = realarray()\n \n > arr = realarray( 'float32' )\n \n\n\nrealarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = realarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = realarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\nrealarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = realarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\nrealarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = realarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\nrealarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = realarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","realarrayCtors":"\nrealarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = realarrayCtors( 'float64' )\n \n > ctor = realarrayCtors( 'float' )\n null\n\n See Also\n --------\n arrayCtors, complexarrayCtors\n","realarrayDataTypes":"\nrealarrayDataTypes()\n Returns a list of typed array real-valued data types.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = realarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, complexarrayDataTypes\n","realf":"\nrealf( z )\n Returns the real component of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var re = realf( z )\n 5.0\n\n See Also\n --------\n imagf, real, reimf\n","realmax":"\nrealmax( dtype )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum finite value.\n\n Examples\n --------\n > var m = realmax( 'float16' )\n 65504.0\n > m = realmax( 'float32' )\n 3.4028234663852886e+38\n\n See Also\n --------\n realmin, typemax\n","realmin":"\nrealmin( dtype )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Smallest finite normal value.\n\n Examples\n --------\n > var m = realmin( 'float16' )\n 0.00006103515625\n > m = realmin( 'float32' )\n 1.1754943508222875e-38\n\n See Also\n --------\n realmax, typemin\n","reBasename":"\nreBasename( [platform] )\n Returns a regular expression to capture the last part of a path.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reBasename()\n \n > var RE_POSIX = reBasename( 'posix' );\n > var RE_WIN32 = reBasename( 'win32' );\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var RE = reBasename.REGEXP\n \n\n\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasenamePosix, reBasenameWindows\n","reBasename.REGEXP":"\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var RE = reBasename.REGEXP\n ","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasenamePosix, reBasenameWindows","reBasenamePosix":"\nreBasenamePosix()\n Returns a regular expression to capture the last part of a POSIX path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_BASENAME_POSIX = reBasenamePosix();\n > var base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( './' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n ''\n\n\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasename, reBasenameWindows\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasename, reBasenameWindows","reBasenameWindows":"\nreBasenameWindows()\n Returns a regular expression to capture the last part of a Windows path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_BASENAME_WINDOWS = reBasenameWindows();\n > var base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n\n See Also\n --------\n reBasename, reBasenamePosix\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n\n See Also\n --------\n reBasename, reBasenamePosix","reColorHexadecimal":"\nreColorHexadecimal( [mode] )\n Returns a regular expression to match a hexadecimal color.\n\n Parameters\n ----------\n mode: string (optional)\n Color format (`full`, `shorthand`, or `either`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reColorHexadecimal();\n > var bool = RE.test( 'ffffff' )\n true\n > bool = RE.test( '000' )\n false\n > bool = RE.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP.test( '000' )\n false\n > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n false\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n false\n\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP.test( '000' )\n false\n > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n false","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n false\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n false","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n false","reDecimalNumber":"\nreDecimalNumber( [options] )\n Returns a regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to create a capture group for the match.\n Default: false.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDecimalNumber();\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true\n > bool = RE.test( '0.0' )\n true\n > bool = RE.test( '.0' )\n true\n > bool = RE.test( '0' )\n false\n > bool = RE.test( 'beep' )\n false\n\n // Create a RegExp to capture all decimal numbers:\n > var re = reDecimalNumber({ 'flags': 'g' });\n > var str = '1.234 5.6, 7.8';\n > var out = str.match( re )\n [ '1.234', '5.6', '7.8' ]\n\n\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP;\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true\n\n\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP_CAPTURE;\n > var str = '1.02';\n > var out = replace( str, RE, '$1 x $1' )\n '1.02 x 1.02'\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP;\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP_CAPTURE;\n > var str = '1.02';\n > var out = replace( str, RE, '$1 x $1' )\n '1.02 x 1.02'","reDirname":"\nreDirname( [platform] )\n Returns a regular expression to capture a path dirname.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirname()\n \n > var RE_POSIX = reDirname( 'posix' );\n > var dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > var RE_WIN32 = reDirname( 'win32' );\n > dir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n\n Examples\n --------\n > var RE = reDirname.REGEXP\n \n\n\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n\n See Also\n --------\n reDirnamePosix, reDirnameWindows, dirname\n","reDirname.REGEXP":"\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n\n Examples\n --------\n > var RE = reDirname.REGEXP\n ","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n\n See Also\n --------\n reDirnamePosix, reDirnameWindows, dirname","reDirnamePosix":"\nreDirnamePosix()\n Returns a regular expression to capture a POSIX path dirname.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirnamePosix();\n > var dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > dir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n './foo/bar'\n > dir = RE.exec( 'foo/file.pdf' )[ 1 ]\n 'foo'\n > dir = RE.exec( '/foo/bar/file' )[ 1 ]\n '/foo/bar'\n > dir = RE.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE.exec( '.' )[ 1 ]\n '.'\n > dir = RE.exec( './' )[ 1 ]\n '.'\n > dir = RE.exec( '' )[ 1 ]\n ''\n\n\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n See Also\n --------\n reDirname, reDirnameWindows, dirname\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n See Also\n --------\n reDirname, reDirnameWindows, dirname","reDirnameWindows":"\nreDirnameWindows()\n Returns a regular expression to capture a Windows path dirname.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirnameWindows();\n > var dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n > dir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n 'C:\\foo\\bar'\n > dir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'foo'\n > dir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n '\\foo\\bar'\n > dir = RE.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE.exec( '' )[ 1 ]\n ''\n\n\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n\n See Also\n --------\n reDirname, reDirnamePosix, dirname\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n\n See Also\n --------\n reDirname, reDirnamePosix, dirname","reduce":"\nreduce( arr, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a reduction over the entire\n input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input array.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > var out = reduce( arr, 0.0, f )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = reduce( arr, 0.0, f )\n 21.0\n\n See Also\n --------\n forEach, map, reduceAsync, reduceRight\n","reduce2d":"\nreduce2d( arr, initial, reducer[, thisArg] )\n Reduces the number of dimensions by one of a two-dimensional nested array by\n applying a function against an accumulator and each element along the\n innermost dimension and returning the accumulation results as a one-\n dimensional array.\n\n The applied function is provided the following arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array of arrays.\n\n initial: ArrayLikeObject\n Initial values. Must have a length equal to the size of the outermost\n input array dimension.\n\n reducer: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array\n Accumulation results.\n\n Examples\n --------\n > var f = naryFunction( base.add, 2 );\n > var arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\n > var out = reduce2d( arr, [ 0, 0 ], f )\n [ 6, 15 ]\n\n See Also\n --------\n map2d, reduce\n","reduceAsync":"\nreduceAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `next`\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `index`\n - `next`\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `accumulator`: accumulated value\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachAsync, reduce, reduceRightAsync\n","reduceAsync.factory":"\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachAsync, reduce, reduceRightAsync","reduceRight":"\nreduceRight( arr, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in an array while\n iterating from right to left and returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a reduction over the entire\n input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input array.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > var out = reduceRight( arr, 0.0, f )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = reduceRight( arr, 0.0, f )\n 21.0\n\n See Also\n --------\n forEachRight, mapRight, reduce, reduceRightAsync\n","reduceRightAsync":"\nreduceRightAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `next`\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `index`\n - `next`\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `accumulator`: accumulated value\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachRightAsync, reduceAsync, reduceRight\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachRightAsync, reduceAsync, reduceRight","reEOL":"\nreEOL( [options] )\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to create a capture group for the match.\n Default: false.\n\n Returns\n -------\n regexp: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_EOL = reEOL();\n > var bool = RE_EOL.test( '\\n' )\n true\n > bool = RE_EOL.test( '\\r\\n' )\n true\n > bool = RE_EOL.test( '\\\\r\\\\n' )\n false\n\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var bool = reEOL.REGEXP.test( 'abc' )\n false\n\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n [ '\\n', '\\n' ]\n\n","reEOL.REGEXP":"\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var bool = reEOL.REGEXP.test( 'abc' )\n false","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n [ '\\n', '\\n' ]","reExtendedLengthPath":"\nreExtendedLengthPath()\n Returns a regular expression to test if a string is an extended-length path.\n\n Extended-length paths are Windows paths which begin with `\\\\?\\`.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtendedLengthPath();\n > var path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\n > var bool = RE.test( path )\n true\n > path = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\n > bool = RE.test( path )\n true\n > path = 'C:\\\\foo\\\\bar';\n > bool = RE.test( path )\n false\n > path = '/c/foo/bar';\n > bool = RE.test( path )\n false\n > path = '/foo/bar';\n > bool = RE.test( path )\n false\n\n\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n\n Examples\n --------\n > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n false\n\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n\n Examples\n --------\n > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n false","reExtname":"\nreExtname( [platform] )\n Returns a regular expression to capture a filename extension.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtname()\n \n > var RE_POSIX = reExtname( 'posix' );\n > var ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > var RE_WIN32 = reExtname( 'win32' );\n > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n\n Examples\n --------\n > var RE = reExtname.REGEXP\n \n\n\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtnamePosix, reExtnameWindows, extname\n","reExtname.REGEXP":"\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n\n Examples\n --------\n > var RE = reExtname.REGEXP\n ","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtnamePosix, reExtnameWindows, extname","reExtnamePosix":"\nreExtnamePosix\n Returns a regular expression to capture a POSIX filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtnamePosix();\n > var ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n ''\n > ext = RE.exec( 'foo/file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE.exec( '/foo/bar/file' )[ 1 ]\n ''\n > ext = RE.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( '.' )[ 1 ]\n ''\n > ext = RE.exec( './' )[ 1 ]\n ''\n > ext = RE.exec( '' )[ 1 ]\n ''\n\n\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnameWindows, extname\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnameWindows, extname","reExtnameWindows":"\nreExtnameWindows\n Returns a regular expression to capture a Windows filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtnameWindows();\n > var ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n ''\n > ext = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n ''\n > ext = RE.exec( 'beep\\\\boop.' )[ 1 ]\n '.'\n > ext = RE.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( '' )[ 1 ]\n ''\n\n\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnamePosix, extname\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnamePosix, extname","reFilename":"\nreFilename( [platform] )\n Regular expression to split a filename.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilename()\n \n > var RE_POSIX = reFilename( 'posix' );\n > var parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\n \n > var RE_WIN32 = reFilename( 'win32' );\n > parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n \n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreFilename.REGEXP\n Regular expression to split a filename.\n\n Examples\n --------\n > var RE = reFilename.REGEXP\n \n\n\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilenamePosix, reFilenameWindows\n","reFilename.REGEXP":"\nreFilename.REGEXP\n Regular expression to split a filename.\n\n Examples\n --------\n > var RE = reFilename.REGEXP\n ","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilenamePosix, reFilenameWindows","reFilenamePosix":"\nreFilenamePosix()\n Returns a regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilenamePosix();\n > var parts = RE.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n > parts = RE.exec( './foo/bar/.gitignore' ).slice()\n [ './foo/bar/.gitignore', '', './foo/bar/', '.gitignore', '' ]\n > parts = RE.exec( 'foo/file.pdf' ).slice()\n [ 'foo/file.pdf', '', 'foo/', 'file.pdf', '.pdf' ]\n > parts = RE.exec( '/foo/bar/file' ).slice()\n [ '/foo/bar/file', '/', 'foo/bar/', 'file', '' ]\n > parts = RE.exec( 'index.js' ).slice()\n [ 'index.js', '', '', 'index.js', '.js' ]\n > parts = RE.exec( '.' ).slice()\n [ '.', '', '', '.', '' ]\n > parts = RE.exec( './' ).slice()\n [ './', '', ..., '.', '' ]\n > parts = RE.exec( '' ).slice()\n [ '', '', '', '', '' ]\n\n\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n\n Examples\n --------\n > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenameWindows\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n\n Examples\n --------\n > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenameWindows","reFilenameWindows":"\nreFilenameWindows()\n Returns a regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilenameWindows();\n > var parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n > parts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\n [ '\\\\foo\\\\bar\\\\.gitignore', '', '\\\\', 'foo\\\\bar\\\\', '.gitignore', '' ]\n > parts = RE.exec( 'foo\\\\file.pdf' ).slice()\n [ 'foo\\\\file.pdf', '', '', 'foo\\\\', 'file.pdf', '.pdf' ]\n > parts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\n [ '\\\\foo\\\\bar\\\\file', '', '\\\\', 'foo\\\\bar\\\\', 'file', '' ]\n > parts = RE.exec( 'index.js' ).slice()\n [ 'index.js', '', '', '', 'index.js', '.js' ]\n > parts = RE.exec( '.' ).slice()\n [ '.', '', '', '', '.', '' ]\n > parts = RE.exec( './' ).slice()\n [ './', '', ..., '.', '' ]\n > parts = RE.exec( '' ).slice()\n [ '', '', '', '', '', '' ]\n\n\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n\n Examples\n --------\n > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenamePosix","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n\n Examples\n --------\n > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenamePosix","reFromString":"\nreFromString( str )\n Parses a regular expression string and returns a new regular expression.\n\n Provided strings should be properly escaped.\n\n If unable to parse a string as a regular expression, the function returns\n `null`.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: RegExp|null\n Regular expression or null.\n\n Examples\n --------\n > var re = reFromString( '/beep/' )\n /beep/\n > re = reFromString( '/beep' )\n null\n\n","reFunctionName":"\nreFunctionName()\n Return a regular expression to capture a function name.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_FUNCTION_NAME = reFunctionName();\n > function beep() { return 'boop'; };\n > var name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\n 'beep'\n > name = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n ''\n\n\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n\n Examples\n --------\n > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n 'sqrt'\n\n See Also\n --------\n functionName\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n\n Examples\n --------\n > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n 'sqrt'\n\n See Also\n --------\n functionName","regexp2json":"\nregexp2json( re )\n Returns a JSON representation of a regular expression.\n\n Parameters\n ----------\n re: RegExp\n Regular expression to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n \n out.type: string\n Value type. The assigned value is always 'RegExp'.\n \n out.pattern: string\n Regular expression pattern.\n \n out.flags: string\n Regular expression flags.\n\n Examples\n --------\n > var json = regexp2json( /ab+c/ )\n {...}\n\n See Also\n --------\n reviveRegExp \n","reim":"\nreim( z )\n Returns the real and imaginary components of a double-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Float64Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var out = reim( z )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n imag, real\n","reimf":"\nreimf( z )\n Returns the real and imaginary components of a single-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Float32Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var out = reimf( z )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n imagf, realf, reim\n","rejectArguments":"\nrejectArguments( fcn, predicate[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n\n Only those arguments in which the predicate function returns a falsy value\n are applied to a provided function.\n\n The predicate function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > function predicate( v ) { return ( v === 2 ); };\n > var bar = rejectArguments( foo, predicate );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n filterArguments, maskArguments\n","removeFirst":"\nremoveFirst( str[, n][, options] )\n Removes the first character(s) of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to remove. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeFirst( 'beep' )\n 'eep'\n > out = removeFirst( 'Boop' )\n 'oop'\n > out = removeFirst( 'foo bar', 4 )\n 'bar'\n\n See Also\n --------\n removeLast\n","removeLast":"\nremoveLast( str[, n][, options] )\n Removes the last character(s) of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to remove. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to remove. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeLast( 'beep' )\n 'bee'\n > out = removeLast( 'Boop' )\n 'Boo'\n > out = removeLast( 'foo bar', 4 )\n 'foo'\n\n See Also\n --------\n removeFirst\n","removePunctuation":"\nremovePunctuation( str )\n Removes punctuation characters from a `string`.\n\n The function removes the following characters:\n\n - Apostrophe: `\n - Braces : { }\n - Brackets: [ ]\n - Colon: :\n - Comma: ,\n - Exclamation Mark: !\n - Fraction Slash: /\n - Guillemets: < >\n - Parentheses: ( )\n - Period: .\n - Semicolon: ;\n - Tilde: ~\n - Vertical Bar: |\n - Question Mark: ?\n - Quotation Marks: ' \"\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with punctuation characters removed.\n\n Examples\n --------\n > var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\n > var out = removePunctuation( str )\n 'Sun Tzu said A leader leads by example not by force'\n\n > str = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\n > out = removePunctuation( str )\n 'This function removes these characters '\n\n","removeUTF8BOM":"\nremoveUTF8BOM( str )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with BOM removed.\n\n Examples\n --------\n > var out = removeUTF8BOM( '\\ufeffbeep' )\n 'beep'\n\n","removeWords":"\nremoveWords( str, words[, ignoreCase] )\n Removes all occurrences of the given words from a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n words: Array\n Array of words to be removed.\n\n ignoreCase: boolean (optional)\n Boolean indicating whether to perform a case-insensitive operation.\n Default: `false`.\n\n Returns\n -------\n out: string\n String with words removed.\n\n Examples\n --------\n > var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\n 'beep Foo bar'\n\n // Case-insensitive:\n > out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n 'beep bar'\n\n","rename":"\nrename( oldPath, newPath, clbk )\n Asynchronously renames a file.\n\n The old path can specify a directory. In this case, the new path must either\n not exist, or it must specify an empty directory.\n\n The old pathname should not name an ancestor directory of the new pathname.\n\n If the old path points to the pathname of a file that is not a directory,\n the new path should not point to the pathname of a directory.\n\n Write access permission is required for both the directory containing the\n old path and the directory containing the new path.\n\n If the link named by the new path exists, the new path is removed and the\n old path is renamed to the new path. The link named by the new path will\n remain visible to other threads throughout the renaming operation and refer\n to either the file referred to by the new path or to the file referred to by\n the old path before the operation began.\n\n If the old path and the new path resolve to either the same existing\n directory entry or to different directory entries for the same existing\n file, no action is taken, and no error is returned.\n\n If the old path points to a pathname of a symbolic link, the symbolic link\n is renamed. If the new path points to a pathname of a symbolic link, the\n symbolic link is removed.\n\n If a link named by the new path exists and the file's link count becomes 0\n when it is removed and no process has the file open, the space occupied by\n the file is freed and the file is no longer accessible. If one or more\n processes have the file open when the last link is removed, the link is\n removed before the function returns, but the removal of file contents is\n postponed until all references to the file are closed.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n clbk: Function\n Callback to invoke upon renaming a file.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > rename( './beep/boop.txt', './beep/foo.txt', done );\n\n\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n See Also\n --------\n exists, readFile, writeFile, unlink\n","rename.sync":"\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n See Also\n --------\n exists, readFile, writeFile, unlink","reNativeFunction":"\nreNativeFunction()\n Returns a regular expression to match a native function.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reNativeFunction();\n > var bool = RE.test( Date.toString() )\n true\n > bool = RE.test( (function noop() {}).toString() )\n false\n\n\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n true\n > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n false\n\n See Also\n --------\n reFunctionName, functionName\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n true\n > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n false\n\n See Also\n --------\n reFunctionName, functionName","reorderArguments":"\nreorderArguments( fcn, indices[, thisArg] )\n Returns a function that invokes a provided function with reordered\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reordered arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reorderArguments( foo, [ 2, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 3, 1, 2 ]\n\n See Also\n --------\n maskArguments, reverseArguments\n","repeat":"\nrepeat( str, n )\n Repeats a string `n` times and returns the concatenated result.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of repetitions.\n\n Returns\n -------\n out: string\n Repeated string.\n\n Examples\n --------\n > var out = repeat( 'a', 5 )\n 'aaaaa'\n > out = repeat( '', 100 )\n ''\n > out = repeat( 'beep', 0 )\n ''\n\n See Also\n --------\n pad\n","replace":"\nreplace( str, search, newval )\n Replaces search occurrences with a replacement string.\n\n When provided a string as the search value, the function replaces *all*\n occurrences. To remove only the first match, use a regular expression.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string|RegExp\n Search expression.\n\n newval: string|Function\n Replacement value or function.\n\n Returns\n -------\n out: string\n String containing replacement(s).\n\n Examples\n --------\n // Standard usage:\n > var out = replace( 'beep', 'e', 'o' )\n 'boop'\n\n // Replacer function:\n > function replacer( match, p1 ) { return '/'+p1+'/'; };\n > var str = 'Oranges and lemons';\n > out = replace( str, /([^\\s]+)/gi, replacer )\n '/Oranges/ /and/ /lemons/'\n\n // Replace only first match:\n > out = replace( 'beep', /e/, 'o' )\n 'boep'\n\n","reRegExp":"\nreRegExp()\n Returns a regular expression to parse a regular expression string.\n\n Regular expression strings should be escaped.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reRegExp();\n > var bool = RE.test( '/^beep$/' )\n true\n > bool = RE.test( '/boop' )\n false\n\n // Escape regular expression strings:\n > bool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\n false\n > bool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n true\n\n\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n\n Examples\n --------\n > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n true\n > bool = reRegExp.REGEXP.test( '/boop' )\n false\n\n See Also\n --------\n reFromString\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n\n Examples\n --------\n > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n true\n > bool = reRegExp.REGEXP.test( '/boop' )\n false\n\n See Also\n --------\n reFromString","rescape":"\nrescape( str )\n Escapes a regular expression string.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: string\n Escaped string.\n\n Examples\n --------\n > var str = rescape( '[A-Z]*' )\n '\\\\[A\\\\-Z\\\\]\\\\*'\n\n","reSemVer":"\nreSemVer()\n Returns a regular expression to match a semantic version string.\n\n Returns\n -------\n out: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_SEMVER = reSemVer()\n \n > var bool = RE_SEMVER.test( '1.0.0' )\n true\n > bool = RE_SEMVER.test( '1.0.0-alpha.1' )\n true\n > bool = RE_SEMVER.test( 'abc' )\n false\n > bool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n true\n\n\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n\n Examples\n --------\n > var bool = reSemVer.REGEXP.test( '1.0.0' )\n true\n > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n false\n\n","reSemVer.REGEXP":"\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n\n Examples\n --------\n > var bool = reSemVer.REGEXP.test( '1.0.0' )\n true\n > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n false","resolveParentPath":"\nresolveParentPath( path[, options], clbk )\n Asynchronously resolves a path by walking parent directories.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPath( 'package.json', onPath );\n\n\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n See Also\n --------\n resolveParentPathBy\n","resolveParentPath.sync":"\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n See Also\n --------\n resolveParentPathBy","resolveParentPathBy":"\nresolveParentPathBy( path[, options], predicate, clbk )\n Asynchronously resolves a path according to a predicate function by walking\n parent directories.\n\n When invoked, the predicate function is provided two arguments:\n\n - `path`: a resolved path\n - `next`: a callback to be invoked after processing a resolved path\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided predicate function calls the `next` callback with a truthy\n `error` argument, the function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n the resolved path as the second argument.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function predicate( path, next ) {\n ... setTimeout( onTimeout, path );\n ... function onTimeout() {\n ... console.log( path );\n ... next( null, false );\n ... }\n ... };\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPathBy( 'package.json', predicate, onPath );\n\n\nresolveParentPathBy.sync( path[, options], predicate )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n\n The predicate function is provided one argument:\n\n - `path`: a resolved path\n\n The function immediately returns upon encountering a truthy return value.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > function predicate() { return false; };\n > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n See Also\n --------\n resolveParentPath\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path[, options], predicate )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n\n The predicate function is provided one argument:\n\n - `path`: a resolved path\n\n The function immediately returns upon encountering a truthy return value.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > function predicate() { return false; };\n > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n See Also\n --------\n resolveParentPath","reUncPath":"\nreUncPath()\n Return a regular expression to parse a UNC path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUncPath();\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\\\\\share';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\\\\\\\\\server\\\\share';\n > bool = RE.test( path )\n false\n > path = 'beep boop \\\\\\\\server\\\\share';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server';\n > bool = RE.test( path )\n false\n > path = '\\\\';\n > bool = RE.test( path )\n false\n > path = '';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\n > bool = RE.test( path )\n false\n > path = '//server/share';\n > bool = RE.test( path )\n false\n > path = '/foo/bar';\n > bool = RE.test( path )\n false\n > path = 'foo/bar';\n > bool = RE.test( path )\n false\n > path = './foo/bar';\n > bool = RE.test( path )\n false\n > path = '/foo/../bar';\n > bool = RE.test( path )\n false\n\n\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = reUncPath.REGEXP.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = reUncPath.REGEXP.test( path )\n true\n\n See Also\n --------\n isUNCPath\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = reUncPath.REGEXP.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = reUncPath.REGEXP.test( path )\n true\n\n See Also\n --------\n isUNCPath","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n Returns a regular expression to match a UTF-16 surrogate pair.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair();\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair.REGEXP;\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n See Also\n --------\n reUtf16UnpairedSurrogate","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair.REGEXP;\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n See Also\n --------\n reUtf16UnpairedSurrogate","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n Returns a regular expression to match an unpaired UTF-16 surrogate.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate();\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate.REGEXP;\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n See Also\n --------\n reUtf16SurrogatePair","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate.REGEXP;\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n See Also\n --------\n reUtf16SurrogatePair","reverseArguments":"\nreverseArguments( fcn[, thisArg] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reversed arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reverseArguments( foo );\n > var out = bar( 1, 2, 3 )\n [ 3, 2, 1 ]\n\n See Also\n --------\n maskArguments, reorderArguments\n","reverseString":"\nreverseString( str[, options] )\n Reverses a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to reverse. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Reversed string.\n\n Examples\n --------\n > var out = reverseString( 'foo' )\n 'oof'\n > out = reverseString( 'abcdef' )\n 'fedcba'\n\n","reviveBasePRNG":"\nreviveBasePRNG( key, value )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or PRNG.\n\n Examples\n --------\n > var str = JSON.stringify( base.random.mt19937 );\n > var r = parseJSON( str, reviveBasePRNG )\n \n\n","reviveBuffer":"\nreviveBuffer( key, value )\n Revives a JSON-serialized Buffer.\n\n The serialization format for a Buffer is an object having the following\n fields:\n\n - type: value type (Buffer)\n - data: buffer data as an array of integers\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or Buffer.\n\n Examples\n --------\n > var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\n > var buf = parseJSON( str, reviveBuffer )\n [ 5, 3 ]\n\n See Also\n --------\n buffer2json\n","reviveComplex":"\nreviveComplex( key, value )\n Revives a JSON-serialized complex number.\n\n The serialization format for complex numbers is an object having the\n following fields:\n\n - type: complex number type (e.g., \"Complex128\", \"Complex64\")\n - re: real component (number)\n - im: imaginary component (number)\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex )\n \n\n See Also\n --------\n Complex128, Complex64, reviveComplex128, reviveComplex64\n","reviveComplex64":"\nreviveComplex64( key, value )\n Revives a JSON-serialized 64-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex64 )\n \n\n See Also\n --------\n Complex64, reviveComplex128, reviveComplex\n","reviveComplex128":"\nreviveComplex128( key, value )\n Revives a JSON-serialized 128-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex128 )\n \n\n See Also\n --------\n Complex128, reviveComplex64, reviveComplex\n","reviveError":"\nreviveError( key, value )\n Revives a JSON-serialized error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or error object.\n\n Examples\n --------\n > var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\n > var err = JSON.parse( str, reviveError )\n \n\n See Also\n --------\n error2json\n","reviveRegExp":"\nreviveRegExp( key, value )\n Revives a JSON-serialized regular expression.\n\n The serialization format for a regular expression is an object having the\n following fields:\n\n - type: value type (RegExp)\n - pattern: regular expression pattern\n - flags: regular expression flags\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or regular expression.\n\n Examples\n --------\n > var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\n > var v = parseJSON( str, reviveRegExp )\n \n\n See Also\n --------\n regexp2json","reviveTypedArray":"\nreviveTypedArray( key, value )\n Revives a JSON-serialized typed array.\n\n The serialization format for typed array is an object having the following\n fields:\n\n - type: typed array type (e.g., \"Float64Array\", \"Int8Array\")\n - data: typed array data as an array of numbers\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or typed array.\n\n Examples\n --------\n > var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\n > var arr = parseJSON( str, reviveTypedArray )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n typedarray2json\n","reWhitespace":"\nreWhitespace( [options] )\n Returns a regular expression to match a white space character.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to wrap a regular expression matching a white\n space character with a capture group. Default: false.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reWhitespace();\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false\n\n\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP;\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false\n\n\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP_CAPTURE;\n > var str = 'Duplicate capture';\n > var out = replace( str, RE, '$1$1' )\n 'Duplicate capture'\n\n See Also\n --------\n isWhitespace","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP;\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP_CAPTURE;\n > var str = 'Duplicate capture';\n > var out = replace( str, RE, '$1$1' )\n 'Duplicate capture'\n\n See Also\n --------\n isWhitespace","rpad":"\nrpad( str, len[, pad] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = rpad( 'a', 5 )\n 'a '\n > out = rpad( 'beep', 10, 'p' )\n 'beeppppppp'\n > out = rpad( 'beep', 12, 'boop' )\n 'beepboopboop'\n\n See Also\n --------\n lpad, pad\n","rtrim":"\nrtrim( str )\n Trims whitespace from the end of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n ' \\t\\t\\n Beep'\n\n See Also\n --------\n ltrim, trim\n","safeintmax":"\nsafeintmax( dtype )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: integer\n Maximum safe integer.\n\n Examples\n --------\n > var m = safeintmax( 'float16' )\n 2047\n > m = safeintmax( 'float32' )\n 16777215\n\n See Also\n --------\n safeintmin, realmax, typemax\n","safeintmin":"\nsafeintmin( dtype )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: integer\n Minimum safe integer.\n\n Examples\n --------\n > var m = safeintmin( 'float16' )\n -2047\n > m = safeintmin( 'float32' )\n -16777215\n\n See Also\n --------\n safeintmax, realmin, typemin\n","sample":"\nsample( x[, options] )\n Samples elements from an array-like object.\n\n Parameters\n ----------\n x: ArrayLike\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.size: integer (optional)\n Sample size. By default, the function returns an array having the same\n length as `x`. Specify the `size` option to generate a sample of a\n different size.\n\n options.probs: Array (optional)\n Element probabilities. By default, the probability of sampling an\n element is the same for all elements. To assign elements different\n probabilities, set the `probs` option. The `probs` option must be a\n numeric array consisting of nonnegative values which sum to one. When\n sampling without replacement, note that the `probs` option denotes the\n initial element probabilities which are then updated after each draw.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. If the `replace`\n option is set to `false`, the `size` option cannot be an integer larger\n than the number of elements in `x`. Default: `true`.\n\n Returns\n -------\n out: Array\n Sample.\n\n Examples\n --------\n > var out = sample( 'abc' )\n e.g., [ 'a', 'a', 'b' ]\n > out = sample( [ 3, 6, 9 ] )\n e.g., [ 3, 9, 6 ]\n > var bool = ( out.length === 3 )\n true\n\n > out = sample( [ 3, null, NaN, 'abc', function(){} ] )\n e.g., [ 3, 'abc', null, 3, null ]\n\n // Set sample size:\n > out = sample( [ 3, 6, 9 ], { 'size': 10 } )\n e.g., [ 6, 3, 9, 9, 9, 6, 9, 6, 9, 3 ]\n > out = sample( [ 0, 1 ], { 'size': 20 } )\n e.g., [ 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0 ]\n\n // Draw without replacement:\n > out = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\n e.g., [ 6, 1, 5 ]\n > out = sample( [ 0, 1 ], { 'replace': false } )\n e.g., [ 0, 1 ]\n\n // Assigning non-uniform element probabilities:\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\n > out = sample( x, { 'probs': probs } )\n e.g., [ 5, 6, 6, 5, 6, 4 ]\n > out = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n e.g., [ 6, 4, 1 ]\n\n\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 } );\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]\n\n","sample.factory":"\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 } );\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FIN()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FR()\n [ 'a', 'à', 'â', 'abord', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_GER()\n [ 'a', 'ab', 'aber', 'ach', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_IT()\n [ 'a', 'abbastanza', 'accidenti', 'ad', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_POR()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SP()\n [ 'a', 'acuerdo', 'adelante', 'ademas', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SWE()\n [ 'aderton', 'adertonde', 'adjö', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","scalar2array":"\nscalar2array( value[, dtype] )\n Returns a single-element array containing a provided scalar value.\n\n If `value` is a number and `dtype` is a complex number data type, the\n function returns a complex number array containing a complex number whose\n real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n dtype: string (optional)\n Data type. If not provided and `value`\n\n - is a number, the default data type is the default real-valued\n floating-point data type.\n - is a complex number object of a known complex data type, the data type\n is the same as the provided value.\n - is a complex number object of an unknown data type, the default data\n type is the default complex-valued floating-point data type.\n - is any other value type, the default data type is 'generic'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = scalar2array( 1.0 )\n [ 1.0 ]\n\n See Also\n --------\n iterator2array\n","scalar2ndarray":"\nscalar2ndarray( value[, options] )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n\n If `value` is a number and `options.dtype` is a complex number data type,\n the function returns a zero-dimensional ndarray containing a complex number\n whose real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Data type. If not provided and `value`\n\n - is a number, the default data type is the default real-valued\n floating-point data type.\n - is a complex number object of a known complex data type, the data type\n is the same as the provided value.\n - is a complex number object of an unknown data type, the default data\n type is the default complex-valued floating-point data type.\n - is any other value type, the default data type is 'generic'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = scalar2ndarray( 1.0 )\n \n > var sh = x.shape\n []\n > var dt = x.dtype\n 'float64'\n > var v = x.get()\n 1.0\n\n See Also\n --------\n array, ndarray\n","sdot":"\nsdot( x, y )\n Computes the dot product of two single-precision floating-point vectors.\n\n If provided empty vectors, the function returns `0.0`.\n\n Parameters\n ----------\n x: ndarray\n First input array whose underlying data type is 'float32'.\n\n y: ndarray\n Second input array whose underlying data type is 'float32'.\n\n Returns\n -------\n dot: number\n The dot product.\n\n Examples\n --------\n > var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > sdot( x, y )\n -5.0\n\n See Also\n --------\n base.strided.sdot, ddot, gdot\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n Number of seconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var secs = days * SECONDS_IN_DAY\n 271296\n\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var secs = hrs * SECONDS_IN_HOUR\n 11304\n\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var secs = mins * SECONDS_IN_MINUTE\n 188.4\n\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n Number of seconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var secs = wks * SECONDS_IN_WEEK\n 1899072\n\n","secondsInMonth":"\nsecondsInMonth( [month[, year]] )\n Returns the number of seconds in a month.\n\n By default, the function returns the number of seconds in the current month\n of the current year (according to local time). To determine the number of\n seconds for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Seconds in a month.\n\n Examples\n --------\n > var num = secondsInMonth()\n \n > num = secondsInMonth( 2 )\n \n > num = secondsInMonth( 2, 2016 )\n 2505600\n > num = secondsInMonth( 2, 2017 )\n 2419200\n\n // Other ways to supply month:\n > num = secondsInMonth( 'feb', 2016 )\n 2505600\n > num = secondsInMonth( 'february', 2016 )\n 2505600\n\n See Also\n --------\n secondsInYear\n","secondsInYear":"\nsecondsInYear( [value] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n\n By default, the function returns the number of seconds in the current year\n (according to local time). To determine the number of seconds for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of seconds in a year.\n\n Examples\n --------\n > var num = secondsInYear()\n \n > num = secondsInYear( 2016 )\n 31622400\n > num = secondsInYear( 2017 )\n 31536000\n\n See Also\n --------\n secondsInMonth\n","seq2slice":"\nseq2slice( str, len, strict )\n Converts a subsequence string to a Slice object.\n\n A subsequence string has the following format:\n\n ::\n\n If an increment is not specified, the default increment is one. An increment\n of zero is not allowed.\n\n The start index is inclusive.\n\n The stop index is exclusive.\n\n Both start and stop indices are optional. If not provided, the start and\n stop indices default to index extremes. Which extremes correspond to which\n index depends on whether the increment is positive or negative.\n\n Both start and stop indices can be negative; in which case, the\n corresponding index is resolved by subtracting the respective value from the\n provided length.\n\n Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n 'end-3:', etc), which supports basic subtraction and division.\n\n The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n exception is when performing a division operation when the increment is less\n than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n user expectations when 'end/d' equals a whole number and slicing from right-\n to-left. The result from a division operation is rounded down to the nearest\n integer value.\n\n In non-strict mode, the resolved slice start is clamped to the slice index\n bounds [0, len).\n\n In non-strict mode, Tte resolved slice end is upper bound clamped to the\n provided length (i.e., one greater than the last possible index).\n\n When the increment is negative, the resolved slice end value may be `null`,\n thus indicating that a non-empty slice should include the first index.\n\n The function ensures that results satisfy the convention that ':n' combined\n with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n When the provided length is zero, the function always returns a slice object\n equivalent to '0:0:'.\n\n Parameters\n ----------\n str: string\n Subsequence string.\n\n len: integer\n Maximum number of elements allowed in the slice.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new seq2slice( '1:10', 10, false );\n > s.start\n 1\n > s.stop\n 10\n > s.step\n 1\n > s = new seq2slice( '2:5:2', 10, false );\n > s.start\n 2\n > s.stop\n 5\n > s.step\n 2\n\n See Also\n --------\n Slice\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj, prop, value )\n Defines a configurable read-only property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setConfigurableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setReadOnly\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n Defines a configurable read-only accessor.\n\n Configurable read-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadWriteAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadOnlyAccessor\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj, prop, getter, setter )\n Defines a configurable property having read-write accessors.\n\n Configurable read-write accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadWriteAccessor\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n Defines a configurable write-only accessor.\n\n Configurable write-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setWriteOnlyAccessor\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj, prop, fcn )\n Defines a configurable memoized read-only object property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedConfigurableReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setMemoizedReadOnly, setReadOnly\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj, prop, fcn )\n Defines a memoized read-only object property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n See Also\n --------\n defineMemoizedProperty, setReadOnly\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj, prop, value )\n Defines a non-enumerable property.\n\n Non-enumerable properties are writable and configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableProperty( obj, 'foo', 'bar' );\n > obj.foo\n 'bar'\n > objectKeys( obj )\n []\n\n See Also\n --------\n setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj, prop, value )\n Defines a non-enumerable read-only property.\n\n Non-enumerable read-only properties are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n Defines a non-enumerable read-only accessor.\n\n Non-enumerable read-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnlyAccessor\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj, prop, getter, setter )\n Defines a non-enumerable property having read-write accessors.\n\n Non-enumerable read-write accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableWriteOnlyAccessor, setReadWriteAccessor\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj, prop, setter )\n Defines a non-enumerable write-only accessor.\n\n Non-enumerable write-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnly":"\nsetReadOnly( obj, prop, value )\n Defines a read-only property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setReadOnlyAccessor, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj, prop, getter )\n Defines a read-only accessor.\n\n Read-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj, prop, getter, setter )\n Defines a property having read-write accessors.\n\n Read-write accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setWriteOnlyAccessor\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj, prop, setter )\n Defines a write-only accessor.\n\n Write-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setReadWriteAccessor\n","SharedArrayBuffer":"\nSharedArrayBuffer( size )\n Returns a shared array buffer having a specified number of bytes.\n\n A shared array buffer behaves similarly to a non-shared array buffer, except\n that a shared array buffer allows creating views of memory shared between\n threads.\n\n Buffer contents are initialized to 0.\n\n If an environment does not support shared array buffers, the function throws\n an error.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: SharedArrayBuffer\n A shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 )\n \n\n\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1\n\n\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","shift":"\nshift( collection )\n Removes and returns the first element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = shift( arr )\n [ [ 2.0, 3.0, 4.0, 5.0 ], 1.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = shift( arr )\n [ [ 2.0 ], 1.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = shift( arr )\n [ { 'length': 1, '0': 2.0 }, 1.0 ]\n\n See Also\n --------\n pop, push, unshift\n","shuffle":"\nshuffle( arr[, options] )\n Shuffles elements of an array-like object.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object to shuffle.\n\n options: Object (optional)\n Options.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n out: ArrayLike\n Shuffled array-like object.\n\n Examples\n --------\n > var data = [ 1, 2, 3 ];\n > var out = shuffle( data )\n e.g., [ 3, 1, 2 ]\n > out = shuffle( data, { 'copy': 'none' } );\n > var bool = ( data === out )\n true\n\n\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' } );\n > bool = ( arr === out )\n false\n\n See Also\n --------\n sample\n","shuffle.factory":"\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' } );\n > bool = ( arr === out )\n false\n\n See Also\n --------\n sample","sizeOf":"\nsizeOf( dtype )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - complex128: 128-bit complex numbers\n - complex64: 64-bit complex numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Size (in bytes).\n\n Examples\n --------\n > var s = sizeOf( 'int8' )\n 1\n > s = sizeOf( 'uint32' )\n 4\n\n See Also\n --------\n realmax, typemax\n","Slice":"\nSlice( [stop] )\n Returns a Slice.\n\n Parameters\n ----------\n stop: integer|null|undefined (optional)\n Ending index (exclusive).\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new Slice();\n > s = new Slice( 10 );\n\n\nSlice( start, stop[, step] )\n Returns a Slice.\n\n Parameters\n ----------\n start: integer|null|undefined\n Starting index (inclusive).\n\n stop: integer|null|undefined\n Ending index (exclusive).\n\n step: integer|null|undefined (optional)\n Index increment. A numeric index increment argument should be a non-zero\n integer value. Default: null.\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > s = new Slice( 2, 10, 1 );\n\n\nSlice.prototype.start\n Read-only property returning the starting slice index.\n\n Returns\n -------\n start: integer|null\n Starting index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.start\n null\n > s = new Slice( 2, 10 );\n > s.start\n 2\n\n\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n\n Returns\n -------\n stop: integer|null\n Ending index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.stop\n 10\n > s = new Slice( 2, 10 );\n > s.stop\n 10\n\n\nSlice.prototype.step\n Read-only property returning the index increment.\n\n Returns\n -------\n step: integer|null\n Index increment.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.step\n null\n > s = new Slice( 2, 10 );\n > s.step\n null\n > s = new Slice( 2, 10, 1 );\n > s.step\n 1\n\n\nSlice.prototype.toString()\n Serializes a Slice as a string.\n\n Returns\n -------\n str: string\n Serialized Slice string.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toString()\n 'Slice(null,10,null)'\n > s = new Slice( 2, 10, 1 );\n > s.toString()\n 'Slice(2,10,1)'\n\n\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ null, 10, null ] }\n > s = new Slice( 2, 10, 1 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n See Also\n --------\n ndarray, MultiSlice\n","Slice.prototype.start":"\nSlice.prototype.start\n Read-only property returning the starting slice index.\n\n Returns\n -------\n start: integer|null\n Starting index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.start\n null\n > s = new Slice( 2, 10 );\n > s.start\n 2","Slice.prototype.stop":"\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n\n Returns\n -------\n stop: integer|null\n Ending index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.stop\n 10\n > s = new Slice( 2, 10 );\n > s.stop\n 10","Slice.prototype.step":"\nSlice.prototype.step\n Read-only property returning the index increment.\n\n Returns\n -------\n step: integer|null\n Index increment.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.step\n null\n > s = new Slice( 2, 10 );\n > s.step\n null\n > s = new Slice( 2, 10, 1 );\n > s.step\n 1","Slice.prototype.toString":"\nSlice.prototype.toString()\n Serializes a Slice as a string.\n\n Returns\n -------\n str: string\n Serialized Slice string.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toString()\n 'Slice(null,10,null)'\n > s = new Slice( 2, 10, 1 );\n > s.toString()\n 'Slice(2,10,1)'","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ null, 10, null ] }\n > s = new Slice( 2, 10, 1 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n See Also\n --------\n ndarray, MultiSlice","snakecase":"\nsnakecase( str )\n Converts a string to snake case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Snake-cased string.\n\n Examples\n --------\n > var out = snakecase( 'Hello World!' )\n 'hello_world'\n > out = snakecase( 'I am a tiny little teapot' )\n 'i_am_a_tiny_little_teapot'\n\n See Also\n --------\n camelcase, constantcase, kebabcase, pascalcase","some":"\nsome( collection, n )\n Tests whether at least `n` elements in a collection are truthy.\n\n The function immediately returns upon finding `n` truthy elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 1, 2, 3 ];\n > var bool = some( arr, 3 )\n true\n\n See Also\n --------\n any, every, forEach, none, someBy\n","someBy":"\nsomeBy( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, -3, 4, -1 ];\n > var bool = someBy( arr, 2, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, noneBy, someByAsync, someByRight\n","someByAsync":"\nsomeByAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync\n","someByAsync.factory":"\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync","someByRight":"\nsomeByRight( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, -2, 3, 4 ];\n > var bool = someByRight( arr, 2, negative )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, noneByRight, someBy, someByRightAsync\n","someByRightAsync":"\nsomeByRightAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight","SOTU":"\nSOTU( [options] )\n Returns State of the Union (SOTU) addresses.\n\n Each State of the Union address is represented by an object with the\n following fields:\n\n - year: speech year\n - name: President name\n - party: the President's political party\n - text: speech text\n\n The following political parties are recognized:\n\n - Democratic\n - Republican\n - Democratic-Republican\n - Federalist\n - National Union\n - Whig\n - Whig & Democratic\n - none\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.name: String|Array (optional)\n President name(s).\n\n options.party: String|Array (optional)\n Political party (or parties).\n\n options.year: integer|Array (optional)\n Year(s).\n\n options.range: Array (optional)\n Two-element array specifying a year range.\n\n Returns\n -------\n out: Array\n State of the Union addresses.\n\n Examples\n --------\n > var out = SOTU()\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more Presidents...\n > var opts = { 'name': 'Barack Obama' };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more political parties...\n > opts = { 'party': [ 'Democratic', 'Federalist' ] };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses from one or more years...\n > opts = { 'year': [ 2008, 2009, 2011 ] };\n > out = SOTU( opts )\n [ {...}, {...}, {...} ]\n\n // Retrieve addresses from a range of consecutive years...\n > opts = { 'range': [ 2008, 2016 ] }\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n\n Returns\n -------\n out: Array\n List of simple American-English words.\n\n Examples\n --------\n > var list = SPACHE_REVISED()\n [ 'a', 'able', 'about', 'above', ... ]\n\n References\n ----------\n - Spache, George. 1953. \"A New Readability Formula for Primary-Grade Reading\n Materials.\" *The Elementary School Journal* 53 (7): 410–13. doi:10.1086/\n 458513.\n - Klare, George R. 1974. \"Assessing Readability.\" *Reading Research\n Quarterly* 10 (1). Wiley, International Reading Association: 62–102.\n .\n - Stone, Clarence R. 1956. \"Measuring Difficulty of Primary Reading\n Material: A Constructive Criticism of Spache's Measure.\" *The Elementary\n School Journal* 57 (1). University of Chicago Press: 36–41.\n .\n - Perera, Katherine. 2012. \"The assessment of linguistic difficulty in\n reading material.\" In *Linguistics and the Teacher*, edited by Ronald\n Carter, 101–13. Routledge Library Editions: Education. Taylor & Francis.\n .\n\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n\n Each array element has the following fields:\n\n - id: message id (relative to message group)\n - group: message group\n - checksum: object containing checksum info\n - text: message text (including headers)\n\n The message group may be one of the following:\n\n - easy-ham-1: easier to detect non-spam e-mails (2500 messages)\n - easy-ham-2: easier to detect non-spam e-mails collected at a later date\n (1400 messages)\n - hard-ham-1: harder to detect non-spam e-mails (250 messages)\n - spam-1: spam e-mails (500 messages)\n - spam-2: spam e-mails collected at a later date (1396 messages)\n\n The checksum object contains the following fields:\n\n - type: checksum type (e.g., MD5)\n - value: checksum value\n\n Returns\n -------\n out: Array\n Corpus.\n\n Examples\n --------\n > var data = SPAM_ASSASSIN()\n [ {...}, {...}, ... ]\n\n","SparklineBase":"\nSparklineBase( [data,] [options] )\n Returns a Sparkline instance.\n\n This constructor is a base Sparkline constructor from which constructors\n tailored to generating particular types of Sparkline graphics should be\n derived.\n\n At a minimum, descendants should implement a private `_render()` method\n which will be automatically invoked by the public `render()` method.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options.description: string (optional)\n Sparkline description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n sparkline: Sparkline\n Sparkline instance.\n\n sparkline.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n sparkline.bufferSize\n Data buffer size.\n\n sparkline.description\n Sparkline description.\n\n sparkline.data\n Sparkline data.\n\n sparkline.label\n Data label.\n\n sparkline.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n sparkline.render()\n Renders a sparkline. This method calls `_render()` which must be\n implemented by instances and child classes. The default behavior is\n throw an error.\n\n Examples\n --------\n > var sparkline = new SparklineBase()\n \n\n // Provide sparkline data at instantiation:\n > var data = [ 1, 2, 3 ];\n > sparkline = new SparklineBase( data )\n \n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","sparsearray2iterator":"\nsparsearray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iterator( [ 1, , 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, sparsearray2iteratorRight\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, sparsearray2iterator\n","splitStream":"\nsplitStream( [options] )\n Returns a transform stream which splits streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream.Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = splitStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\\nb\\c' );\n > s.end();\n\n See Also\n --------\n joinStream\n","splitStream.factory":"\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();","splitStream.objectMode":"\nsplitStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\\nb\\c' );\n > s.end();\n\n See Also\n --------\n joinStream","SQRT_EPS":"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n\n Examples\n --------\n > SQRT_EPS\n 0.14901161193847656e-7\n\n See Also\n --------\n EPS\n","SQRT_HALF":"\nSQRT_HALF\n Square root of `1/2`.\n\n Examples\n --------\n > SQRT_HALF\n 0.7071067811865476\n\n See Also\n --------\n LN_HALF\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n\n Examples\n --------\n > SQRT_HALF_PI\n 1.2533141373155003\n\n See Also\n --------\n PI\n","SQRT_PHI":"\nSQRT_PHI\n Square root of the golden ratio.\n\n Examples\n --------\n > SQRT_PHI\n 1.272019649514069\n\n See Also\n --------\n PHI\n","SQRT_PI":"\nSQRT_PI\n Square root of the mathematical constant `π`.\n\n Examples\n --------\n > SQRT_PI\n 1.7724538509055160\n\n See Also\n --------\n PI\n","SQRT_THREE":"\nSQRT_THREE\n Square root of `3`.\n\n Examples\n --------\n > SQRT_THREE\n 1.7320508075688772\n\n","SQRT_TWO":"\nSQRT_TWO\n Square root of `2`.\n\n Examples\n --------\n > SQRT_TWO\n 1.4142135623730951\n\n See Also\n --------\n LN2\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n\n Examples\n --------\n > SQRT_TWO_PI\n 2.5066282746310007\n\n See Also\n --------\n TWO_PI\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n Returns US birth data from 2000 to 2014, as provided by the Social Security\n Administration.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = SSA_US_BIRTHS_2000_2014()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1969_1988, CDC_NCHS_US_BIRTHS_1994_2003\n","sswap":"\nsswap( x, y )\n Interchanges two single-precision floating-point vectors.\n\n Parameters\n ----------\n x: ndarray\n First input array whose underlying data type is 'float32'.\n\n y: ndarray\n Second input array whose underlying data type is 'float32'.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n > var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > sswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.sswap, dswap, gswap\n","Stack":"\nStack()\n Stack constructor.\n\n A stack is also referred to as a \"last-in-first-out\" queue.\n\n Returns\n -------\n stack: Object\n Stack data structure.\n\n stack.clear: Function\n Clears the stack.\n\n stack.first: Function\n Returns the \"newest\" stack value (i.e., the value which is \"first-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.iterator: Function\n Returns an iterator for iterating over a stack. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from stack mutation during\n iteration, a returned iterator **always** iterates over a stack\n \"snapshot\", which is defined as the list of stack elements at the time\n of the method's invocation.\n\n stack.last: Function\n Returns the \"oldest\" stack value (i.e., the value which is \"last-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.length: integer\n Stack length.\n\n stack.pop: Function\n Removes and returns the current \"first-out\" value from the stack. If the\n stack is empty, the returned value is `undefined`.\n\n stack.push: Function\n Adds a value to the stack.\n\n stack.toArray: Function\n Returns an array of stack values.\n\n stack.toJSON: Function\n Serializes a stack as JSON.\n\n Examples\n --------\n > var s = Stack();\n > s.push( 'foo' ).push( 'bar' );\n > s.length\n 2\n > s.pop()\n 'bar'\n > s.length\n 1\n > s.pop()\n 'foo'\n > s.length\n 0\n\n See Also\n --------\n FIFO\n","standalone2pkg":"\nstandalone2pkg( pkg )\n Returns the internal package name associated with a provided standalone\n package name.\n\n Parameters\n ----------\n pkg: string\n Standalone package name.\n\n Returns\n -------\n out: string|null\n Internal package name.\n\n Examples\n --------\n > var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n alias2standalone, pkg2alias, pkg2standalone\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n Returns a string array containing two or three letter abbreviations for each\n card in a standard 52-card deck.\n\n Abbreviation format: \n\n Cards: A, 2, 3, 4, 5, 6, 7, 8, 9, 10, J, Q, K, where\n\n - A: ace\n - J: jack\n - Q: queen\n - K: king\n\n Suit abbreviations:\n\n - C: clubs\n - D: diamonds\n - H: hearts\n - S: spades\n\n Returns\n -------\n out: Array\n List of cards.\n\n Examples\n --------\n > var list = STANDARD_CARD_DECK()\n [ 'AC', '2C', '3C', ... ]\n\n","startcase":"\nstartcase( str )\n Capitalizes the first letter of each word in an input string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String containing words where each first letter is capitalized.\n\n Examples\n --------\n > var out = startcase( 'beep boop' )\n 'Beep Boop'\n\n See Also\n --------\n lowercase, uppercase\n","startsWith":"\nstartsWith( str, search[, position] )\n Tests if a string starts with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n position: integer (optional)\n Position at which to start searching for `search`. If less than `0`, the\n start position is determined relative to the end of the input string.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string starts with the characters of\n another string.\n\n Examples\n --------\n > var bool = startsWith( 'Beep', 'Be' )\n true\n > bool = startsWith( 'Beep', 'ep' )\n false\n > bool = startsWith( 'Beep', 'ee', 1 )\n true\n > bool = startsWith( 'Beep', 'ee', -3 )\n true\n > bool = startsWith( 'Beep', '' )\n true\n\n See Also\n --------\n endsWith\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n Returns a list of English stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = STOPWORDS_EN()\n [ 'a', 'about', 'above', 'across', ... ]\n\n","strided.abs":"\nstrided.abs( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs( 2, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs","strided.abs2":"\nstrided.abs2( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 9.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs2\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs2","strided.abs2By":"\nstrided.abs2By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element\n - idx: iteration index\n - xi: strided index (offsetX + idx*sx)\n - yi: strided index (offsetY + idx*sy)\n - x: the input array\n - y: the destination array\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By( x.length, x, 1, y, 1, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By( 2, x, 2, y, -1, clbk )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs2By( 2, x1, -2, y1, 1, clbk )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = [ -1.0, -2.0, -3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.absBy, strided.abs2\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = [ -1.0, -2.0, -3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.absBy, strided.abs2","strided.absBy":"\nstrided.absBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element\n - idx: iteration index\n - xi: strided index (offsetX + idx*sx)\n - yi: strided index (offsetY + idx*sy)\n - x: the input array\n - y: the destination array\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy( x.length, x, 1, y, 1, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy( 2, x, 2, y, -1, clbk )\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.absBy( 2, x1, -2, y1, 1, clbk )\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n strided.abs, strided.abs2By\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n strided.abs, strided.abs2By","strided.add":"\nstrided.add( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ 1.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -2.0, 5.0 ]\n > z0\n [ 0.0, 0.0, -2.0, 5.0 ]\n\n\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 5.0, -2.0, 0.0 ]\n\n See Also\n --------\n strided.mul, strided.sub\n","strided.add.ndarray":"\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 5.0, -2.0, 0.0 ]\n\n See Also\n --------\n strided.mul, strided.sub","strided.cbrt":"\nstrided.cbrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.scbrt, strided.sqrt\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.scbrt, strided.sqrt","strided.ceil":"\nstrided.ceil( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil","strided.deg2rad":"\nstrided.deg2rad( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~1.571, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.sdeg2rad\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.sdeg2rad","strided.dataTypes":"\nstrided.dataTypes()\n Returns a list of strided array data types.\n\n The output array contains the following data types:\n\n - binary: binary.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of strided array data types.\n\n Examples\n --------\n > var out = strided.dataTypes()\n \n\n","strided.dispatch":"\nstrided.dispatch( fcns, types, data, nargs, nin, nout )\n Returns a strided array function interface which performs multiple dispatch.\n\n Without offsets, a strided array function interface has the following\n signature:\n\n f( N, dtypeX, x, strideX, dtypeY, y, strideY, ... )\n\n where\n\n - N: number of indexed elements.\n - dtypeX: data type for `x`.\n - x: strided array.\n - strideX: index increment for `x`.\n - dtypeY: data type for `y`.\n - y: strided array.\n - strideY: index increment for `y`.\n - ...: additional strided arrays, data types, and associated strides.\n\n The number of parameters is derived from `nargs`, the number of input\n strided arrays is derived from `nin`, and the number of output strided\n arrays is derived from `nout`.\n\n Without offsets, the number of parameters must obey the following relation:\n\n nargs = 3*(nout+nin) + 1\n\n With offsets, the number of parameters must obey the following relation:\n\n nargs = 4*(nout+nin) + 1\n\n With offsets, a strided array function interface has the following\n signature:\n\n f( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY, ... )\n\n where\n\n - N: number of indexed elements.\n - dtypeX: data type for `x`.\n - x: strided array.\n - strideX: index increment for `x`.\n - offsetX: starting index for `x`.\n - dtypeY: data type for `y`.\n - y: strided array.\n - strideY: index increment for `y`.\n - offsetY: starting index for `y`.\n - ...: additional strided arrays and associated data types, strides, and\n offsets.\n\n The choice of which strided array function interface to return depends on\n the use case. The former is suitable for typed array views; while the latter\n affords alternative indexing semantics more suitable for n-dimensional\n arrays (ndarrays).\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of strided array functions. Without offsets, a strided array\n function should have the following signature:\n\n f( arrays, shape, strides, data )\n\n where\n\n - arrays: array containing strided input and output arrays.\n - shape: array containing a single element, the number of indexed\n elements.\n - strides: array containing the stride lengths for the strided input and\n output arrays.\n - data: strided array function data (e.g., a callback).\n\n With offsets, a strided array function should have the following\n signature:\n\n f( arrays, shape, strides, offsets, data )\n\n where\n\n - offsets: array containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n For convenience, a single strided array function may be provided which\n will be invoked whenever the strided array argument data types match a\n sequence of types in `types`. Providing a single strided array function\n is particularly convenient for the case where, regardless of array data\n types, traversing arrays remains the same, but the strided array\n function `data` differs (e.g., callbacks which differ based on the array\n data types).\n\n types: ArrayLikeObject\n One-dimensional list of strided array argument data types.\n\n data: ArrayLikeObject|null\n Strided array function data (e.g., callbacks). If `null`, a returned\n strided array function interface does **not** provide a `data` argument\n to an invoked strided array function.\n\n nargs: integer\n Total number of strided array function interface arguments (including\n data types, strides, and offsets).\n\n nin: integer\n Number of input strided arrays.\n\n nout: integer\n Number of output strided arrays.\n\n Returns\n -------\n fcn: Function\n Strided array function interface.\n\n Examples\n --------\n // Define strided array argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of strided array function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create a strided array function interface for applying unary callbacks:\n > var f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\n\n // Create an input strided array:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value:\n > f( x.length, 'float64', x, 1, 'float64', y, 1 );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Create a strided array function interface supporting offsets:\n > f = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\n\n // Create an input strided array:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value starting from the third element:\n > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\n > y\n [ 0.0, 0.0, 3.0, 4.0 ]\n\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns, types, data, nargs, nin, nout )\n Returns a strided array function interface which accepts a callback function\n and performs multiple dispatch.\n\n Without offsets, a strided array function interface has the following\n signature:\n\n f( N, dx, x, sx, dy, y, sy, ..., clbk[, thisArg] )\n\n where\n\n - N: number of indexed elements.\n - dx: data type for `x`.\n - x: strided array.\n - sx: index increment for `x`.\n - dy: data type for `y`.\n - y: strided array.\n - sy: index increment for `y`.\n - ...: additional strided arrays, data types, and associated strides.\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n The number of parameters is derived from `nargs`, the number of input\n strided arrays is derived from `nin`, and the number of output strided\n arrays is derived from `nout`.\n\n Without offsets, the number of parameters must obey the following relation:\n\n nargs = 3*(nout+nin) + 2\n\n With offsets, the number of parameters must obey the following relation:\n\n nargs = 4*(nout+nin) + 2\n\n With offsets, a strided array function interface has the following\n signature:\n\n f( N, dx, x, sx, ox, dy, y, sy, oy, ..., clbk[, thisArg] )\n\n where\n\n - N: number of indexed elements.\n - dx: data type for `x`.\n - x: strided array.\n - sx: index increment for `x`.\n - ox: starting index for `x`.\n - dy: data type for `y`.\n - y: strided array.\n - sy: index increment for `y`.\n - oy: starting index for `y`.\n - ...: additional strided arrays and associated data types, strides, and\n offsets.\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n The choice of which strided array function interface to return depends on\n the use case. The former is suitable for typed array views; while the latter\n affords alternative indexing semantics more suitable for n-dimensional\n arrays (ndarrays).\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of strided array functions. Without offsets, a strided array\n function should have the following signature:\n\n f( arrays, shape, strides, data, clbk, thisArg )\n\n where\n\n - arrays: array containing strided input and output arrays.\n - shape: array containing a single element, the number of indexed\n elements.\n - strides: array containing the stride lengths for the strided input and\n output arrays.\n - data: strided array function data (e.g., a callback).\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n With offsets, a strided array function should have the following\n signature:\n\n f( arrays, shape, strides, offsets, data, clbk, thisArg )\n\n where\n\n - offsets: array containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n For convenience, a single strided array function may be provided which\n will be invoked whenever the strided array argument data types match a\n sequence of types in `types`. Providing a single strided array function\n is particularly convenient for the case where, regardless of array data\n types, traversing arrays remains the same, but the strided array\n function `data` differs (e.g., callbacks which differ based on the array\n data types).\n\n types: ArrayLikeObject\n One-dimensional list of strided array argument data types.\n\n data: ArrayLikeObject|null\n Strided array function data (e.g., callbacks). If `null`, a returned\n strided array function interface does **not** provide a `data` argument\n to an invoked strided array function.\n\n nargs: integer\n Total number of strided array function interface arguments (including\n data types, strides, offsets, and the callback function).\n\n nin: integer\n Number of input strided arrays.\n\n nout: integer\n Number of output strided arrays.\n\n Returns\n -------\n fcn: Function\n Strided array function interface.\n\n Examples\n --------\n // Define strided array argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of strided array function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create a strided array function interface for applying unary callbacks:\n > var f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\n\n // Create an input strided array:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value:\n > f( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Create a strided array function interface supporting offsets:\n > f = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\n\n // Create an input strided array:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value starting from the third element:\n > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\n > y\n [ 0.0, 0.0, 3.0, 4.0 ]\n\n See Also\n --------\n strided.dispatch\n","strided.floor":"\nstrided.floor( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -4.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor","strided.inv":"\nstrided.inv( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 0.5, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.sinv\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.sinv","strided.mul":"\nstrided.mul( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ -6.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -15.0, 4.0 ]\n > z0\n [ 0.0, 0.0, -15.0, 4.0 ]\n\n\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 4.0, -15.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.sub\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 4.0, -15.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.sub","strided.ramp":"\nstrided.ramp( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.sramp\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.sramp","strided.rsqrt":"\nstrided.rsqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ ~0.333, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.sqrt, base.strided.srsqrt\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.sqrt, base.strided.srsqrt","strided.sqrt":"\nstrided.sqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt","strided.sub":"\nstrided.sub( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ -5.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -8.0, -3.0 ]\n > z0\n [ 0.0, 0.0, -8.0, -3.0 ]\n\n\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, -3.0, -8.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.mul\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, -3.0, -8.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.mul","strided.trunc":"\nstrided.trunc( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc","stridedarray2iterator":"\nstridedarray2iterator( N, src, stride, offset[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n N: integer\n Number of values to iterate.\n\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iterator\n","stridedArrayStream":"\nstridedArrayStream( N, buffer, stride, offset[, options] )\n Creates a readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );\n\n\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream","string2buffer":"\nstring2buffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = string2buffer( 'beep boop' )\n \n > b = string2buffer( '7468697320697320612074c3a97374', 'hex' );\n > b.toString()\n 'this is a tést'\n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer\n","sub2ind":"\nsub2ind( shape, ...subscript[, options] )\n Converts subscripts to a linear index.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n subscript: ...integer\n Subscripts.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string|Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If\n equal to 'throw', the function throws an error when a subscript exceeds\n array dimensions. If equal to 'normalize', the function normalizes\n negative subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', the function wraps around subscripts\n exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', the function sets subscripts exceeding array dimensions to\n either `0` (minimum index) or the maximum index along a particular\n dimension. If provided a mode array, each array element specifies the\n mode for a corresponding array dimension. If provided fewer modes than\n dimensions, the function recycles modes using modulo arithmetic.\n Default: [ 'throw' ].\n\n Returns\n -------\n idx: integer\n Linear index.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var idx = sub2ind( d, 1, 2, 2 )\n 17\n\n See Also\n --------\n array, ndarray, ind2sub\n","substringAfter":"\nsubstringAfter( str, search[, fromIndex] )\n Returns the part of a string after a specified substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n fromIndex: integer (optional)\n Index from which to start the search. Default: `0`.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var out = substringAfter( 'Hello World!', 'World' )\n '!'\n > out = substringAfter( 'Hello World!', 'Hello ' )\n 'World!'\n > out = substringAfter( 'Hello World!', 'l', 5 )\n 'd!'\n\n See Also\n --------\n substringBefore, substringBeforeLast, substringAfterLast","substringAfterLast":"\nsubstringAfterLast( str, search[, fromIndex] )\n Returns the part of a string after the last occurrence of a specified\n substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search value.\n\n fromIndex: integer (optional)\n Index of last character to be considered beginning of a match.\n Default: `str.length`.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var out = substringAfterLast( 'beep boop beep baz', 'beep' )\n ' baz'\n > out = substringAfterLast( 'Hello World!', 'Hello ' )\n 'World!'\n > out = substringAfterLast( 'Hello World!', 'o', 5 )\n ' World!'\n\n See Also\n --------\n substringBefore, substringBeforeLast, substringAfter","substringBefore":"\nsubstringBefore( str, search )\n Returns the part of a string before a specified substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = substringBefore( str, ' ' )\n 'beep'\n > out = substringBefore( str, 'o' )\n 'beep b'\n\n See Also\n --------\n substringBeforeLast, substringAfter, substringAfterLast","substringBeforeLast":"\nsubstringBeforeLast( str, search )\n Returns the part of a string before the last occurrence of a specified\n substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search value.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var str = 'Beep Boop Beep';\n > var out = substringBeforeLast( str, 'Beep' )\n 'Beep Boop '\n > out = substringBeforeLast( str, 'Boop' )\n 'Beep '\n\n See Also\n --------\n substringBefore, substringAfter, substringAfterLast","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on July 10, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on May 9, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK\n","Symbol":"\nSymbol( [description] )\n Returns a symbol.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support symbols.\n\n Parameters\n ----------\n description: string (optional)\n Symbol description which can be used for debugging but not to access the\n symbol itself.\n\n Returns\n -------\n out: symbol\n Symbol.\n\n Examples\n --------\n > var s = ( Symbol ) ? Symbol( 'beep' ) : null\n\n","tabulate":"\ntabulate( collection )\n Generates a frequency table.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulate( collection )\n [ [ 'beep', 2, 0.5 ], [ 'boop', 1, 0.25 ], [ 'foo', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulateBy\n","tabulateBy":"\ntabulateBy( collection, [options,] indicator )\n Generates a frequency table according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > function indicator( value ) { return value[ 0 ]; };\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulateBy( collection, indicator )\n [ [ 'b', 3, 0.75 ], [ 'f', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulate\n","tabulateByAsync":"\ntabulateByAsync( collection, [options,] indicator, done )\n Generates a frequency table according to an indicator function.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, indicator, done )\n 750\n 1000\n 2500\n 3000\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n 750\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n See Also\n --------\n countByAsync, groupByAsync, tabulateBy\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n See Also\n --------\n countByAsync, groupByAsync, tabulateBy","thunk":"\nthunk( fcn[, ...args] )\n Returns a thunk.\n\n Parameters\n ----------\n fcn: Function\n Function to convert to a thunk.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n out: Function\n Thunk.\n\n Examples\n --------\n > var fcn = thunk( base.add, 2, 3 );\n > var v = fcn()\n 5\n > v = fcn()\n 5\n\n","tic":"\ntic()\n Returns a high-resolution time.\n\n The returned array has the following format: `[seconds, nanoseconds]`.\n\n Returns\n -------\n out: Array\n High resolution time.\n\n Examples\n --------\n > var t = tic()\n [ , ]\n\n See Also\n --------\n toc\n","timeit":"\ntimeit( code, [options,] clbk )\n Times a snippet.\n\n If the `asynchronous` option is set to `true`, the implementation assumes\n that `before`, `after`, and `code` snippets are all asynchronous.\n Accordingly, these snippets should invoke a `next( [error] )` callback\n once complete. The implementation wraps the snippet within a function\n accepting two arguments: `state` and `next`.\n\n The `state` parameter is simply an empty object which allows the `before`,\n `after`, and `code` snippets to share state.\n\n Notes:\n\n - Snippets always run in strict mode.\n - Always verify results. Doing so prevents the compiler from performing dead\n code elimination and other optimization techniques, which would render\n timing results meaningless.\n - Executed code is not sandboxed and has access to the global state. You are\n strongly advised against timing untrusted code. To time untrusted code,\n do so in an isolated environment (e.g., a separate process with restricted\n access to both global state and the host environment).\n - Wrapping asynchronous code does add overhead, but, in most cases, the\n overhead should be negligible compared to the execution cost of the timed\n snippet.\n - When the `asynchronous` option is `true`, ensure that the main `code`\n snippet is actually asynchronous. If a snippet releases the zalgo, an\n error complaining about exceeding the maximum call stack size is highly\n likely.\n - While many benchmark frameworks calculate various statistics over raw\n timing results (e.g., mean and standard deviation), do not do this.\n Instead, consider the fastest time an approximate lower bound for how fast\n an environment can execute a snippet. Slower times are more likely\n attributable to other processes interfering with timing accuracy rather\n than attributable to variability in JavaScript's speed. In which case, the\n minimum time is most likely the only result of interest. When considering\n all raw timing results, apply common sense rather than statistics.\n\n Parameters\n ----------\n code: string\n Snippet to time.\n\n options: Object (optional)\n Options.\n\n options.before: string (optional)\n Setup code. Default: `''`.\n\n options.after: string (optional)\n Cleanup code. Default: `''`.\n\n options.iterations: integer|null (optional)\n Number of iterations. If `null`, the number of iterations is determined\n by trying successive powers of `10` until the total time is at least\n `0.1` seconds. Default: `1e6`.\n\n options.repeats: integer (optional)\n Number of repeats. Default: `3`.\n\n options.asynchronous: boolean (optional)\n Boolean indicating whether a snippet is asynchronous. Default: `false`.\n\n clbk: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > var code = 'var x = Math.pow( Math.random(), 3 );';\n > code += 'if ( x !== x ) {';\n > code += 'throw new Error( \\'Something went wrong.\\' );';\n > code += '}';\n > function done( error, results ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.dir( results );\n ... };\n > timeit( code, done )\n e.g.,\n {\n \"iterations\": 1000000,\n \"repeats\": 3,\n \"min\": [ 0, 135734733 ], // [seconds,nanoseconds]\n \"elapsed\": 0.135734733, // seconds\n \"rate\": 7367311.062526641, // iterations/second\n \"times\": [ // raw timing results\n [ 0, 145641393 ],\n [ 0, 135734733 ],\n [ 0, 140462721 ]\n ]\n }\n\n","tmpdir":"\ntmpdir()\n Returns the directory for storing temporary files.\n\n Returns\n -------\n dir: string\n Directory for temporary files.\n\n Examples\n --------\n > var dir = tmpdir()\n e.g., '/path/to/temporary/files/directory'\n\n See Also\n --------\n configdir, homedir\n","toc":"\ntoc( time )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n\n Similar to `time`, the returned array has format `[seconds, nanoseconds]`.\n\n Parameters\n ----------\n time: Array\n High-resolution time.\n\n Returns\n -------\n out: Array\n High resolution time difference.\n\n Examples\n --------\n > var start = tic();\n > var delta = toc( start )\n [ , ]\n\n See Also\n --------\n tic\n","tokenize":"\ntokenize( str[, keepWhitespace] )\n Tokenizes a string.\n\n To include whitespace characters (spaces, tabs, line breaks) in the output\n array, set `keepWhitespace` to `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n keepWhitespace: boolean (optional)\n Boolean indicating whether whitespace characters should be returned as\n part of the token array. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of tokens.\n\n Examples\n --------\n > var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\n [ 'Hello', 'Mrs.', 'Maple', ',', 'could', 'you', 'call', 'me', 'back', '?' ]\n\n > out = tokenize( 'Hello World!', true )\n [ 'Hello', ' ', 'World', '!' ]\n\n","transformStream":"\ntransformStream( [options] )\n Returns a transform stream.\n\n If a transform function is not provided, the returned stream will be a\n simple pass through stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = transformStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n","transformStream.factory":"\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","transformStream.objectMode":"\ntransformStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();","transformStream.ctor":"\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","trim":"\ntrim( str )\n Trims whitespace from the beginning and end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n 'Beep'\n\n See Also\n --------\n ltrim, pad, rtrim\n","truncate":"\ntruncate( str, len[, ending] )\n Truncates a string to a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n ending: string (optional)\n Custom ending. Default: '...'.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = truncate( str, 5 )\n 'be...'\n\n > out = truncate( str, 5, '|' )\n 'beep|'\n\n See Also\n --------\n truncateMiddle","truncateMiddle":"\ntruncateMiddle( str, len[, seq] )\n Truncates a string in the middle to a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n seq: string (optional)\n Custom replacement sequence. Default: '...'.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = truncateMiddle( str, 5 )\n 'b...p'\n\n > out = truncateMiddle( str, 5, '|' )\n 'be|op'\n\n See Also\n --------\n truncate","trycatch":"\ntrycatch( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: any\n Value to return if a function throws an error.\n\n Returns\n -------\n z: any\n Either the return value of `x` or the provided argument `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > var z = trycatch( x, -1.0 )\n \n\n See Also\n --------\n trycatchAsync, trythen\n","trycatchAsync":"\ntrycatchAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts two arguments:\n\n - error: error object\n - result: function result\n\n The `done` callback is invoked upon function completion and is provided two\n arguments:\n\n - error: error object\n - result: either the result of `x` or the provided argument `y`\n\n If `x` invokes `clbk` with an error argument, the function invokes the\n `done` callback with both the error and the argument `y`.\n\n If `x` does not invoke `clbk` with an error argument, the function invokes\n the `done` callback with a first argument equal to `null` and the function\n `result`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: any\n Value to return if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... // process error...\n ... }\n ... console.log( result );\n ... };\n > trycatchAsync( x, 'boop', done )\n 'boop'\n\n See Also\n --------\n trycatch, trythenAsync\n","tryFunction":"\ntryFunction( fcn[, thisArg] )\n Wraps a function in a try/catch block.\n\n If provided an asynchronous function, the returned function only traps\n errors which occur during the current event loop tick.\n\n If a function throws a literal, the literal is serialized as a string and\n returned as an `Error` object.\n\n Parameters\n ----------\n fcn: Function\n Function to wrap.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Wrapped function.\n\n Examples\n --------\n > function fcn() { throw new Error( 'beep boop' ); };\n > var f = tryFunction( fcn );\n > var out = f();\n > out.message\n 'beep boop'\n\n","tryRequire":"\ntryRequire( id )\n Wraps `require` in a `try/catch` block.\n\n This function traps and returns any errors encountered when attempting to\n require a module.\n\n Use caution when attempting to resolve a relative path or a local module.\n This function attempts to resolve a module from its current path. Thus, the\n function is unable to resolve anything which is not along its search path.\n For local requires, use an absolute file path.\n\n Parameters\n ----------\n id: string\n Module id.\n\n Returns\n -------\n out: any|Error\n Resolved module or an `Error`.\n\n Examples\n --------\n > var out = tryRequire( '_unknown_module_id_' )\n \n\n","trythen":"\ntrythen( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n\n The function `y` is provided a single argument:\n\n - error: the error thrown by `x`\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: Function\n Function to invoke if an initial function throws an error.\n\n Returns\n -------\n z: any\n The return value of either `x` or `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > function y() {\n ... return -1.0;\n ... };\n > var z = trythen( x, y )\n \n\n See Also\n --------\n trycatch, trythenAsync\n","trythenAsync":"\ntrythenAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the function invokes a `done` callback with\n its first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the function invokes a function `y`. The\n number of arguments provided to `y` depends on the function's length. If `y`\n is a unary function, `y` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n Otherwise, `y` is provided two arguments:\n\n - error: the error from `x`\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument equal to `null` and all other arguments provided by `y`.\n\n If the error argument is truthy, the `done` callback is invoked with only\n the error argument provided by `y`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: Function\n Function to invoke if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > trythenAsync( x, y, done )\n 'boop'\n\n See Also\n --------\n trycatchAsync, trythen\n","ttest":"\nttest( x[, y][, options] )\n Computes a one-sample or paired Student's t test.\n\n When no `y` is supplied, the function performs a one-sample t-test for the\n null hypothesis that the data in array or typed array `x` is drawn from a\n normal distribution with mean zero and unknown variance.\n\n When array or typed array `y` is supplied, the function tests whether the\n differences `x - y` come from a normal distribution with mean zero and\n unknown variance via the paired t-test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n y: Array (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed mean under H0 (or difference in means when `y` is supplied).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.mean: number\n Sample mean of `x` or `x - y`, respectively.\n\n out.sd: number\n Standard error of the mean.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample t-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ttest( x )\n {\n rejected: false,\n pValue: ~0.722,\n statistic: ~0.357,\n ci: [~-0.333,~0.479],\n // ...\n }\n\n // Paired t-test:\n > rnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\n > x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... y[ i ] = rnorm();\n ... }\n > out = ttest( x, y )\n {\n rejected: false,\n pValue: ~0.191,\n statistic: ~1.315,\n ci: [ ~-0.196, ~0.964 ],\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.1916\n statistic: 1.3148\n df: 99\n 95% confidence interval: [-0.1955,0.9635]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose custom significance level:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ttest( arr, { 'alpha': 0.01 } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0474\n statistic: 2.8284\n df: 4\n 99% confidence interval: [-1.2556,5.2556]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'mu': 5 } )\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~3.758, ~6.242 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'alternative': 'less' } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is less than 0\n\n pValue: 0.9998\n statistic: 11.1803\n df: 4\n 95% confidence interval: [-Infinity,5.9534]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n > out = ttest( arr, { 'alternative': 'greater' } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is greater than 0\n\n pValue: 0.0002\n statistic: 11.1803\n df: 4\n 95% confidence interval: [4.0466,Infinity]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n See Also\n --------\n ttest2\n","ttest2":"\nttest2( x, y[, options] )\n Computes a two-sample Student's t test.\n\n By default, the function performs a two-sample t-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n options.variance: string (optional)\n String indicating if the test should be conducted under the assumption\n that the unknown variances of the normal distributions are `equal` or\n `unequal`. As a default choice, the function carries out the Welch test\n (using the Satterthwaite approximation for the degrees of freedom),\n which does not have the requirement that the variances of the underlying\n distributions are equal. If the equal variances assumption seems\n warranted, set the option to `equal`. Default: `unequal`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Student's sleep data:\n > var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\n > var y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\n > var out = ttest2( x, y )\n {\n rejected: false,\n pValue: ~0.079,\n statistic: ~-1.861,\n ci: [ ~-3.365, ~0.205 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 95% confidence interval: [-3.3655,0.2055]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ttest2( x, y, { 'alpha': 0.1 } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 90% confidence interval: [-3.0534,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 10% significance level\n\n // Perform one-sided tests:\n > out = ttest2( x, y, { 'alternative': 'less' } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.0397\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-Infinity,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n > out = ttest2( x, y, { 'alternative': 'greater' } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.9603\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-3.0534,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Run tests with equal variances assumption:\n > x = [ 2, 3, 1, 4 ];\n > y = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\n > out = ttest2( x, y, { 'variance': 'equal' } );\n > table = out.print()\n Two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.8848\n statistic: -0.1486\n df: 10\n 95% confidence interval: [-1.9996,1.7496]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 3.0 );\n ... }\n > y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 1.0, 3.0 );\n ... }\n > out = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n {\n rejected: false,\n pValue: ~0.642,\n statistic: ~-0.466,\n ci: [ ~-0.0455, ~1.646 ],\n // ...\n }\n\n See Also\n --------\n ttest\n","TWO_PI":"\nTWO_PI\n The mathematical constant `π` times `2`.\n\n Examples\n --------\n > TWO_PI\n 6.283185307179586\n\n See Also\n --------\n PI\n","typedarray":"\ntypedarray( [dtype] )\n Creates a typed array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray()\n \n > arr = typedarray( 'float32' )\n \n\n\ntypedarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = typedarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n Complex128Array, Complex64Array, Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","typedarray2json":"\ntypedarray2json( arr )\n Returns a JSON representation of a typed array.\n\n The following typed array types are supported:\n\n - Float64Array\n - Float32Array\n - Int32Array\n - Uint32Array\n - Int16Array\n - Uint16Array\n - Int8Array\n - Uint8Array\n - Uint8ClampedArray\n - Complex64Array\n - Complex128Array\n\n The returned JSON object has the following properties:\n\n - type: typed array type\n - data: typed array data as a generic array\n\n The implementation supports custom typed arrays and sets the `type` field to\n the closest known typed array type.\n\n Parameters\n ----------\n arr: TypedArray\n Typed array to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var arr = new Float64Array( 2 );\n > arr[ 0 ] = 5.0;\n > arr[ 1 ] = 3.0;\n > var json = typedarray2json( arr )\n { 'type': 'Float64Array', 'data': [ 5.0, 3.0 ] }\n\n See Also\n --------\n reviveTypedArray\n","typedarrayCtors":"\ntypedarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayCtors( 'float64' )\n \n > ctor = typedarrayCtors( 'float' )\n null\n\n See Also\n --------\n arrayCtors\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = typedarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, ndarrayDataTypes\n","typedarraypool":"\ntypedarraypool( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n Memory is **uninitialized**, which means that the contents of a returned\n typed array may contain sensitive contents.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool()\n []\n > arr = typedarraypool( 'float32' )\n []\n\n\ntypedarraypool( length[, dtype] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > arr = typedarraypool( 5, 'int32' )\n \n\n\ntypedarraypool( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n \n\n\ntypedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n \n\n\ntypedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []\n\n\ntypedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr )\n\n\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear()\n\n\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark\n\n\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes\n\n\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n See Also\n --------\n typedarray\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n typedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n typedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]typedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []typedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]","typedarraypool.free":"\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr )","typedarraypool.clear":"\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear()","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes","typedarraypool.factory":"\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n See Also\n --------\n typedarray","typemax":"\ntypemax( dtype )\n Returns the maximum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var m = typemax( 'int8' )\n 127\n > m = typemax( 'uint32' )\n 4294967295\n\n See Also\n --------\n realmax, typemin\n","typemin":"\ntypemin( dtype )\n Returns the minimum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var m = typemin( 'int8' )\n -128\n > m = typemin( 'uint32' )\n 0\n\n See Also\n --------\n realmin, typemax\n","typeOf":"\ntypeOf( value )\n Determines a value's type.\n\n The following values are not natively provided in older JavaScript engines:\n\n - Map\n - Set\n - WeakMap\n - WeakSet\n - Symbol\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n The value's type.\n\n Examples\n --------\n // Built-ins:\n > var t = typeOf( 'a' )\n 'string'\n > t = typeOf( 5 )\n 'number'\n > t = typeOf( NaN )\n 'number'\n > t = typeOf( true )\n 'boolean'\n > t = typeOf( false )\n 'boolean'\n > t = typeOf( null )\n 'null'\n > t = typeOf( undefined )\n 'undefined'\n > t = typeOf( [] )\n 'array'\n > t = typeOf( {} )\n 'object'\n > t = typeOf( function noop() {} )\n 'function'\n > t = typeOf( Symbol( 'beep' ) )\n 'symbol'\n > t = typeOf( /.+/ )\n 'regexp'\n > t = typeOf( new String( 'beep' ) )\n 'string'\n > t = typeOf( new Number( 5 ) )\n 'number'\n > t = typeOf( new Boolean( false ) )\n 'boolean'\n > t = typeOf( new Array() )\n 'array'\n > t = typeOf( new Object() )\n 'object'\n > t = typeOf( new Int8Array( 10 ) )\n 'int8array'\n > t = typeOf( new Uint8Array( 10 ) )\n 'uint8array'\n > t = typeOf( new Uint8ClampedArray( 10 ) )\n 'uint8clampedarray'\n > t = typeOf( new Int16Array( 10 ) )\n 'int16array'\n > t = typeOf( new Uint16Array( 10 ) )\n 'uint16array'\n > t = typeOf( new Int32Array( 10 ) )\n 'int32array'\n > t = typeOf( new Uint32Array( 10 ) )\n 'uint32array'\n > t = typeOf( new Float32Array( 10 ) )\n 'float32array'\n > t = typeOf( new Float64Array( 10 ) )\n 'float64array'\n > t = typeOf( new ArrayBuffer( 10 ) )\n 'arraybuffer'\n > t = typeOf( new Date() )\n 'date'\n > t = typeOf( new RegExp( '.+' ) )\n 'regexp'\n > t = typeOf( new Map() )\n 'map'\n > t = typeOf( new Set() )\n 'set'\n > t = typeOf( new WeakMap() )\n 'weakmap'\n > t = typeOf( new WeakSet() )\n 'weakset'\n > t = typeOf( new Error( 'beep' ) )\n 'error'\n > t = typeOf( new TypeError( 'beep' ) )\n 'typeerror'\n > t = typeOf( new SyntaxError( 'beep' ) )\n 'syntaxerror'\n > t = typeOf( new ReferenceError( 'beep' ) )\n 'referenceerror'\n > t = typeOf( new URIError( 'beep' ) )\n 'urierror'\n > t = typeOf( new RangeError( 'beep' ) )\n 'rangeerror'\n > t = typeOf( new EvalError( 'beep' ) )\n 'evalerror'\n > t = typeOf( Math )\n 'math'\n > t = typeOf( JSON )\n 'json'\n\n // Arguments object:\n > function beep() { return arguments; };\n > t = typeOf( beep() )\n 'arguments'\n\n // Node.js Buffer object:\n > t = typeOf( new Buffer( 10 ) )\n 'buffer'\n\n // Custom constructor:\n > function Person() { return this };\n > t = typeOf( new Person() )\n 'person'\n\n // Anonymous constructor:\n > var Foo = function () { return this; };\n > t = typeOf( new Foo() )\n '' || 'foo'\n\n See Also\n --------\n constructorName, nativeClass\n","UINT8_MAX":"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n\n The maximum unsigned 8-bit integer is given by `2^8 - 1`.\n\n Examples\n --------\n > UINT8_MAX\n 255\n\n See Also\n --------\n INT8_MAX\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n\n Examples\n --------\n > UINT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT8_NUM_BYTES, UINT16_NUM_BYTES, UINT32_NUM_BYTES\n","Uint8Array":"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array()\n \n\n\nUint8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'\n\n\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n \n\n\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5\n\n\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5\n\n\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray\n","Uint8Array.from":"\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint8Array.of":"\nUint8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1","Uint8Array.name":"\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n ","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray","Uint8ClampedArray":"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray()\n \n\n\nUint8ClampedArray( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8ClampedArray( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8ClampedArray( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'\n\n\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n \n\n\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5\n\n\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0\n\n\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5\n\n\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n ","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array","UINT16_MAX":"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n\n The maximum unsigned 16-bit integer is given by `2^16 - 1`.\n\n Examples\n --------\n > UINT16_MAX\n 65535\n\n See Also\n --------\n INT16_MAX\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n\n Examples\n --------\n > UINT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT16_NUM_BYTES, UINT32_NUM_BYTES, UINT8_NUM_BYTES\n","Uint16Array":"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array()\n \n\n\nUint16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Uint16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'\n\n\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n \n\n\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10\n\n\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5\n\n\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Uint16Array.from":"\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint16Array.of":"\nUint16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2","Uint16Array.name":"\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n ","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray","UINT32_MAX":"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n\n The maximum unsigned 32-bit integer is given by `2^32 - 1`.\n\n Examples\n --------\n > UINT32_MAX\n 4294967295\n\n See Also\n --------\n INT32_MAX\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n\n Examples\n --------\n > UINT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT32_NUM_BYTES, UINT16_NUM_BYTES, UINT8_NUM_BYTES\n","Uint32Array":"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array()\n \n\n\nUint32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Uint32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'\n\n\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n \n\n\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20\n\n\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5\n\n\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray\n","Uint32Array.from":"\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint32Array.of":"\nUint32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4","Uint32Array.name":"\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n ","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray","umask":"\numask( [mask,] [options] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n\n A mask is a set of bits, each of which restricts how its corresponding\n permission is set for newly created files.\n\n On POSIX platforms, each file has a set of attributes that control who can\n read, write, or execute that file. Upon creating a file, file permissions\n must be set to an initial setting. The process mask restricts those\n permission settings.\n\n If the mask contains a bit set to \"1\", the corresponding initial file\n permission is disabled. If the mask contains a bit set to \"0\", the\n corresponding permission is left to be determined by the requesting process\n and the system.\n\n The process mask is thus a filter that removes permissions as a file is\n created; i.e., each bit set to a \"1\" removes its corresponding permission.\n\n In octal representation, a mask is a four digit number, e.g., 0077,\n comprised as follows:\n\n - 0: special permissions (setuid, setgid, sticky bit)\n - 0: (u)ser/owner permissions\n - 7: (g)roup permissions\n - 7: (o)thers/non-group permissions\n\n Octal codes correspond to the following permissions:\n\n - 0: read, write, execute\n - 1: read, write\n - 2: read, execute\n - 3: read\n - 4: write, execute\n - 5: write\n - 6: execute\n - 7: no permissions\n\n If provided fewer than four digits, the mask is left-padded with zeros.\n\n Note, however, that only the last three digits (i.e., the file permissions\n digits) of the mask are actually used when the mask is applied.\n\n Permissions can be represented using the following symbolic form:\n\n u=rwx,g=rwx,o=rwx\n\n where\n\n - u: user permissions\n - g: group permissions\n - o: other/non-group permissions\n - r: read\n - w: write\n - x: execute\n\n When setting permissions using symbolic notation, the function accepts a\n mask expression of the form:\n\n []\n\n where \"classes\" may be a combination of\n\n - u: user\n - g: group\n - o: other/non-group\n - a: all\n\n \"symbols\" may be a combination of\n\n - r: read\n - w: write\n - x: execute\n - X: special execute\n - s: setuid/gid on execution\n - t: sticky\n\n and \"operator\" may be one of\n\n - `+`: enable\n - `-`: disable\n - `=`: enable specified and disable unspecified permissions\n\n For example,\n\n - `u-w`: disable user write permissions\n - `u+w`: enable user write permissions\n - `u=w`: enable user write permissions and disable user read and execute\n\n To specify multiple changes, provide a comma-separated list of mask\n expressions. For example,\n\n u+rwx,g-x,o=r\n\n would enable user read, write, and execute permissions, disable group\n execute permissions, enable other read permissions, and disable other\n write and execute permissions.\n\n The `a` class indicates \"all\", which is the same as specifying \"ugo\". This\n is the default class if a class is omitted when specifying permissions. For\n example, `+x` is equivalent to `a+x` which is equivalent to `ugo+x` which\n is equivalent to `u+x,g+x,o+x` and enables execution for all classes.\n\n Parameters\n ----------\n mask: integer|string (optional)\n Mask or mask expression. If the mask is a string, the mask is assumed to\n be in symbolic notation.\n\n options: Object (optional)\n Options.\n\n options.symbolic: boolean (optional)\n Boolean indicating whether to return the mask using symbolic notation.\n\n Returns\n -------\n mask: integer|string\n Process mask. If provided a mask, the returned value is the previous\n mask; otherwise, the returned value is the current process mask.\n\n Examples\n --------\n > var mask = umask()\n \n > mask = umask( { 'symbolic': true } )\n \n\n","uncapitalize":"\nuncapitalize( str )\n Lowercases the first character of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = uncapitalize( 'Beep' )\n 'beep'\n > out = uncapitalize( 'bOOp' )\n 'bOOp'\n\n See Also\n --------\n capitalize, lowercase\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj )\n Converts the first letter of each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'AA': 1, 'BB': 2 };\n > var out = uncapitalizeKeys( obj )\n { 'aA': 1, 'bB': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n","uncurry":"\nuncurry( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurry( addX );\n > var sum = fcn( 2, 3 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( x ) {\n ... return function add( y ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurry( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addX( x ) {\n ... this.x = x;\n ... return addY;\n ... };\n > function addY( y ) {\n ... return this.x + y;\n ... };\n > fcn = uncurry( addX, {} );\n > sum = fcn( 2, 3 )\n 5\n\n See Also\n --------\n curry, uncurryRight\n","uncurryRight":"\nuncurryRight( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Provided arguments are applied starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurryRight( addX );\n > var sum = fcn( 3, 2 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( y ) {\n ... return function add( x ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurryRight( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addY( y ) {\n ... this.y = y;\n ... return addX;\n ... };\n > function addX( x ) {\n ... return x + this.y;\n ... };\n > fcn = uncurryRight( addY, {} );\n > sum = fcn( 3, 2 )\n 5\n\n See Also\n --------\n curry, curryRight, uncurry\n","UNICODE_MAX":"\nUNICODE_MAX\n Maximum Unicode code point.\n\n Examples\n --------\n > UNICODE_MAX\n 1114111\n\n See Also\n --------\n UNICODE_MAX_BMP\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n\n Examples\n --------\n > UNICODE_MAX_BMP\n 65535\n\n See Also\n --------\n UNICODE_MAX\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data,] [options] )\n Returns a sparkline column chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeColumnChartSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data,] [options] )\n Returns a sparkline line chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: LineChart\n Line chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a line chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeLineChartSparkline( data );\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeSparkline":"\nUnicodeSparkline( [data,] [options] )\n Returns a Unicode sparkline instance.\n\n The following chart types are supported:\n\n - column: column chart (e.g., ▃▆▂▄▁▅▅).\n - line: line chart (e.g., ⡈⠑⠢⠔⠒⠒⠒).\n - tristate: tristate chart (e.g., ▄▀──▀▄▄▀).\n - up-down: up/down chart (e.g., ↓↑↑↑↑↓↓↑).\n - win-loss: win/loss chart (e.g., ┌╵└┴╵╷╷╵).\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.type: string (optional)\n Chart type. Default: 'column'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.type\n Chart type.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n > chart.type = 'line';\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data,] [options] )\n Returns a sparkline tristate chart instance.\n\n In a tristate chart, negative values are encoded as lower blocks, positive\n values are encoded as upper blocks, and values equal to zero are encoded as\n middle lines.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: TristateChart\n Tristate chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a tristate chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\n > var chart = new UnicodeTristateChartSparkline( data );\n > chart.render()\n '▄▀──▀▄▄▀'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data,] [options] )\n Returns a sparkline up/down chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ↑ |\n | -1 | ↓ |\n\n If provided any other value other than 1 or -1, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: UpDownChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1 or -1.\n\n chart.render()\n Renders an up/down chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\n > var chart = new UnicodeUpDownChartSparkline( data );\n > chart.render()\n '↓↑↑↑↑↓↓↑'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data,] [options] )\n Returns a sparkline win/loss chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ╵ |\n | -1 | ╷ |\n | 2 | └ |\n | -2 | ┌ |\n\n If a `2` or `-2` is preceded by a `2` or `-2`,\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 2 | ┴ |\n | -2 | ┬ |\n\n Based on the win/loss analogy,\n\n - 1: win away\n - 2: win at home\n - -1: loss away\n - -2: loss at home\n\n If provided any value other than 1, -1, 2, or -2, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: WinLossChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1, -1, 2, or -2.\n\n chart.render()\n Renders a win/loss chart sparkline.\n\n Examples\n --------\n > var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\n > var chart = new UnicodeWinLossChartSparkline( data );\n > chart.render()\n '┌╵└┴╵╷╷╵'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline\n","unlink":"\nunlink( path, clbk )\n Asynchronously removes a directory entry.\n\n If a provided path is a symbolic link, the function removes the symbolic\n link named by the path and does not affect any file or directory named by\n the contents of the symbolic link.\n\n Otherwise, the function removes the link named by the provided path and\n decrements the link count of the file referenced by the link.\n\n When a file's link count becomes 0 and no process has the file open, the\n space occupied by the file is freed and the file is no longer accessible.\n\n If one or more processes have the file open when the last link is removed,\n the link is removed before the function returns; however, the removal of\n file contents is postponed until all references to the file are closed.\n\n If the path refers to a socket, FIFO, or device, processes which have the\n object open may continue to use it.\n\n The path argument should *not* be a directory. To remove a directory, use\n rmdir().\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n clbk: Function\n Callback to invoke upon removing an entry.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > unlink( './beep/boop.txt', done );\n\n\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n See Also\n --------\n exists\n","unlink.sync":"\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n See Also\n --------\n exists","unshift":"\nunshift( collection, ...items )\n Adds one or more elements to the beginning of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = unshift( arr, 6.0, 7.0 )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = unshift( arr, 3.0, 4.0 )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = unshift( arr, 2.0, 3.0 )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n pop, push, shift\n","until":"\nuntil( predicate, fcn[, thisArg] )\n Invokes a function until a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > until( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, untilAsync, untilEach, whilst\n","untilAsync":"\nuntilAsync( predicate, fcn, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is falsy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > untilAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, until, whileAsync\n","untilEach":"\nuntilEach( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > untilEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEachRight, whileEach\n","untilEachRight":"\nuntilEachRight( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > untilEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n untilEach, whileEachRight\n","unzip":"\nunzip( arr[, idx] )\n Unzips a zipped array (i.e., a nested array of tuples).\n\n Parameters\n ----------\n arr: Array\n Zipped array.\n\n idx: Array (optional)\n Array of indices specifying which tuple elements to unzip.\n\n Returns\n -------\n out: Array\n Array of unzipped arrays.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > var out = unzip( arr )\n [ [ 1, 2 ], [ 'a', 'b' ], [ 3, 4 ] ]\n\n // Provide indices:\n > arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > out = unzip( arr, [ 0, 2 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n zip\n","uppercase":"\nuppercase( str )\n Converts a string to uppercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uppercase string.\n\n Examples\n --------\n > var out = uppercase( 'bEEp' )\n 'BEEP'\n\n See Also\n --------\n capitalize, lowercase\n","uppercaseKeys":"\nuppercaseKeys( obj )\n Converts each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'a': 1, 'b': 2 };\n > var out = uppercaseKeys( obj )\n { 'A': 1, 'B': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n\n Returns\n -------\n out: Array\n List of US state two-letter abbreviations.\n\n Examples\n --------\n > var list = US_STATES_ABBR()\n [ 'AL', 'AK', 'AZ', 'AR', ... ]\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n\n Returns\n -------\n out: Array\n List of US state capitals.\n\n Examples\n --------\n > var list = US_STATES_CAPITALS()\n [ 'Montgomery', 'Juneau', 'Phoenix', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS_NAMES, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n\n Returns\n -------\n out: Object\n An object mapping US state capitals to state names.\n\n Examples\n --------\n > var out = US_STATES_CAPITALS_NAMES()\n { 'Montgomery': 'Alabama', 'Juneau': 'Alaska', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n\n Returns\n -------\n out: Array\n List of US state names.\n\n Examples\n --------\n > var list = US_STATES_NAMES()\n [ 'Alabama', 'Alaska', 'Arizona', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS, US_STATES_CAPITALS_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n\n Returns\n -------\n out: Object\n An object mapping US state names to state capitals.\n\n Examples\n --------\n > var out = US_STATES_NAMES_CAPITALS()\n { 'Alabama': 'Montgomery', 'Alaska': 'Juneau', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n\n The following byte sequences are used to represent a character. The sequence\n depends on the code point:\n\n 0x00000000 - 0x0000007F:\n 0xxxxxxx\n\n 0x00000080 - 0x000007FF:\n 110xxxxx 10xxxxxx\n\n 0x00000800 - 0x0000FFFF:\n 1110xxxx 10xxxxxx 10xxxxxx\n\n 0x00010000 - 0x001FFFFF:\n 11110xxx 10xxxxxx 10xxxxxx 10xxxxxx\n\n The `x` bit positions correspond to code point bits.\n\n Only the shortest possible multi-byte sequence which can represent a code\n point is used.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: Array\n Array of integers.\n\n Examples\n --------\n > var str = '☃';\n > var out = utf16ToUTF8Array( str )\n [ 226, 152, 131 ]\n\n","vartest":"\nvartest( x, y[, options] )\n Computes a two-sample F-test for equal variances.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`.\n\n options.ratio: number (optional)\n Positive number denoting the ratio of the two population variances under\n the null hypothesis. Default: `1`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the ratio of variances.\n\n out.nullValue: number\n Assumed ratio of variances under H0.\n\n out.xvar: number\n Sample variance of `x`.\n\n out.yvar: number\n Sample variance of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.dfX: number\n Numerator degrees of freedom.\n\n out.dfY: number\n Denominator degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [ 610, 610, 550, 590, 565, 570 ];\n > var y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\n > var out = vartest( x, y )\n {\n rejected: false,\n pValue: ~0.399,\n statistic: ~1.976,\n ci: [ ~0.374, ~13.542 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n F test for comparing two variances\n\n Alternative hypothesis: True ratio in variances is not equal to 1\n\n pValue: 0.3992\n statistic: 1.976\n variance of x: 617.5 (df of x: 5)\n variance of y: 312.5 (df of y: 7)\n 95% confidence interval: [0.3739,13.5417]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n See Also\n --------\n bartlettTest\n","waterfall":"\nwaterfall( fcns, clbk[, thisArg] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n\n The last argument applied to each waterfall function is a callback. The\n callback should be invoked upon a series function completion. The first\n argument is reserved as an error argument (which can be `null`). Any results\n which should be passed to the next function in the series should be provided\n beginning with the second argument.\n\n If any function calls the provided callback with a truthy `error` argument,\n the waterfall suspends execution and immediately calls the completion\n callback for subsequent error handling.\n\n Execution is *not* guaranteed to be asynchronous. To ensure asynchrony, wrap\n the completion callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > waterfall( fcns, done );\n\n\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();\n\n","waterfall.factory":"\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();","whileAsync":"\nwhileAsync( predicate, fcn, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is truthy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > whileAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, untilAsync, whilst\n","whileEach":"\nwhileEach( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > whileEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEach, whileEachRight\n","whileEachRight":"\nwhileEachRight( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > whileEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n whileEach, untilEachRight\n","whilst":"\nwhilst( predicate, fcn[, thisArg] )\n Invokes a function while a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > whilst( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, until, whileAsync, whileEach\n","wilcoxon":"\nwilcoxon( x[, y][, options] )\n Computes a one-sample or paired Wilcoxon signed rank test.\n\n When no `y` is supplied, the function performs a one-sample Wilcoxon signed\n rank test for the null hypothesis that the data is drawn from a symmetric\n distribution around zero.\n\n When `y` is supplied, the function tests whether the\n differences `x - y` come from a symmetric distribution around zero.\n\n If `x` has less than fifty elements, an exact p-value is computed if there\n are no zero values or ties. Otherwise, a normal approximation is used.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array|TypedArray\n Data array.\n\n y: Array|TypedArray (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`), or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.correction: boolean (optional)\n Determines whether to apply continuity correction adjusting the Wilcoxon\n rank statistic by 0.5 towards the mean when using the normal\n approximation. Default: `true`.\n\n options.exact: boolean (optional)\n Determines whether to force use of the exact distribution instead of a\n normal approximation when there are more than fifty data points.\n Default: `false`.\n\n options.mu: number (optional)\n Hypothesized true location under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n options.zeroMethod: string (optional)\n Method governing how zero-differences are handled (`pratt`, `wilcox`, or\n `zsplit`). When set to `pratt`, differences of zero are used to\n calculate ranks but their ranks are then dropped. When set to `wilcox`,\n all zero-differences are discarded. When set to `zsplit`, differences of\n zero are used to rank and their ranks are then split between positive\n and negative ones. Default: `'wilcox'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.nullValue: number\n Assumed location parameter under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample test:\n > var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\n > var out = wilcoxon( x )\n {\n 'rejected': true,\n 'alpha': 0.05,\n 'pValue': 0.04125976562499978,\n 'statistic': 96\n // ...\n }\n\n // Paired test:\n > runif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\n > var x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = runif();\n ... y[ i ] = runif();\n ... }\n > out = wilcoxon( x, y )\n {\n 'rejected': false,\n 'alpha': 0.05,\n 'pValue': 0.21759090963694638,\n 'statistic': 2702.5,\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired Wilcoxon signed rank test\n\n Alternative hypothesis: Median of the difference `x - y` is not equal to 0\n\n pValue: 0.2176\n statistic: 2702.5\n\n Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n // Choose custom significance level:\n > out = wilcoxon( arr, { 'alpha': 0.01 });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is not equal to 0\n\n pValue: 0.0413\n statistic: 96\n\n Test Decision: Fail to reject null in favor of alternative at 1% significance level\n\n\n // Test for a median equal to ten:\n > out = wilcoxon( arr, { 'mu': 10 })\n {\n 'rejected': false,\n 'alpha': 0.05,\n 'pValue': 0.11169650413134602,\n 'statistic': 88.5,\n 'nullValue': 10,\n // ...\n }\n\n // Perform one-sided tests:\n > out = wilcoxon( arr, { 'alternative': 'less' });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is less than 0\n\n pValue: 0.9823\n statistic: 96\n\n Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n > out = wilcoxon( arr, { 'alternative': 'greater' });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is greater than 0\n\n pValue: 0.0206\n statistic: 96\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n See Also\n --------\n ttest, ztest\n","writableProperties":"\nwritableProperties( value )\n Returns an array of an object's own writable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own writable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = writableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n inheritedWritableProperties, writablePropertiesIn, properties\n","writablePropertiesIn":"\nwritablePropertiesIn( value )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited writable property names and\n symbols.\n\n Examples\n --------\n > var props = writablePropertiesIn( [] )\n\n See Also\n --------\n inheritedWritableProperties, writableProperties, propertiesIn\n","writablePropertyNames":"\nwritablePropertyNames( value )\n Returns an array of an object's own writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNames( obj )\n [ 'a' ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writableProperties, writablePropertyNamesIn, writablePropertySymbols, propertyNames\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value )\n Returns an array of an object's own and inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNamesIn( obj )\n e.g., [ 'a', ... ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertiesIn, writablePropertyNames, writablePropertySymbolsIn, propertyNamesIn\n","writablePropertySymbols":"\nwritablePropertySymbols( value )\n Returns an array of an object's own writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbols( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writableProperties, writablePropertyNames, writablePropertySymbolsIn, propertySymbols\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited writable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbolsIn( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertiesIn, writablePropertyNamesIn, writablePropertySymbols, propertySymbolsIn\n","writeFile":"\nwriteFile( file, data[, options], clbk )\n Asynchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon writing data to a file.\n\n Examples\n --------\n > function onWrite( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > writeFile( './beep/boop.txt', 'beep boop', onWrite );\n\n\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n See Also\n --------\n exists, readFile\n","writeFile.sync":"\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n See Also\n --------\n exists, readFile","zip":"\nzip( ...arr[, options] )\n Generates array tuples from input arrays.\n\n Parameters\n ----------\n arr: ...Array\n Input arrays to be zipped.\n\n options: Object (optional)\n Options.\n\n options.trunc: boolean (optional)\n Boolean indicating whether to truncate arrays longer than the shortest\n input array. Default: `true`.\n\n options.fill: any (optional)\n Fill value used for arrays of unequal length. Default: `null`.\n\n options.arrays: boolean (optional)\n Boolean indicating whether an input array should be interpreted as an\n array of arrays to be zipped. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n // Basic usage:\n > var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\n [ [ 1, 'a' ], [ 2, 'b' ] ]\n\n // Turn off truncation:\n > var opts = { 'trunc': false };\n > out = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n [ [ 1, 'a' ], [ 2, 'b' ], [ 3, null ] ]\n\n See Also\n --------\n unzip\n","ztest":"\nztest( x, sigma[, options] )\n Computes a one-sample z-test.\n\n The function performs a one-sample z-test for the null hypothesis that the\n data in array or typed array `x` is drawn from a normal distribution with\n mean zero and standard deviation `sigma`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n sigma: number\n Known standard deviation.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for mean.\n\n out.nullValue: number\n Assumed mean value under H0.\n\n out.sd: number\n Standard error.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test (`One-Sample z-test`).\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample z-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ztest( x, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.180,\n statistic: ~-1.34,\n ci: [ ~-0.66, ~0.124 ],\n ...\n }\n\n // Choose custom significance level and print output:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ztest( arr, 2.0, { 'alpha': 0.01 } );\n > table = out.print()\n One-sample z-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0253\n statistic: 2.2361\n 99% confidence interval: [-0.3039,4.3039]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'mu': 5 } )\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~4.123, ~5.877 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'alternative': 'less' } )\n {\n alpha: 0.05,\n rejected: false,\n pValue: 1,\n statistic: 11.180339887498949,\n ci: [ -Infinity, 5.735600904580115 ],\n // ...\n }\n > out = ztest( arr, 1.0, { 'alternative': 'greater' } )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 11.180339887498949,\n ci: [ 4.264399095419885, Infinity ],\n //...\n }\n\n See Also\n --------\n ztest2\n","ztest2":"\nztest2( x, y, sigmax, sigmay[, options] )\n Computes a two-sample z-test.\n\n By default, the function performs a two-sample z-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means and known\n standard deviations `sigmax` and `sigmay`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n sigmax: number\n Known standard deviation of first group.\n\n sigmay: number\n Known standard deviation of second group.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Drawn from Normal(0,2):\n > var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n // Drawn from Normal(1,2):\n > var y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\n > var out = ztest2( x, y, 2.0, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.398,\n statistic: ~-0.844\n ci: [ ~-2.508, ~0.988 ],\n alternative: 'two-sided',\n method: 'Two-sample z-test',\n nullValue: 0,\n xmean: ~0.573,\n ymean: ~1.328\n }\n\n // Print table output:\n > var table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 95% confidence interval: [-2.508,0.998]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 60% confidence interval: [-1.5078,-0.0022]\n\n Test Decision: Reject null in favor of alternative at 40% significance level\n\n // Perform one-sided tests:\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.1993\n statistic: -0.8441\n 95% confidence interval: [-Infinity,0.7162]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.8007\n statistic: -0.8441\n 95% confidence interval: [-2.2262,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 1.0 );\n ... }\n > y = new Array( 100 );\n ... for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 0.0, 2.0 );\n ... }\n > out = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n {\n rejected: false,\n pValue: ~0.35,\n statistic: ~-0.935\n ci: [ ~1.353, ~2.229 ],\n // ...\n }\n\n See Also\n --------\n ztest\n"} \ No newline at end of file +{"abs":"\nabs( x[, options] )\n Computes the absolute value.\n\n If provided a number, the function returns a number.\n\n If provided an ndarray or array-like object, the function performs element-\n wise computation.\n\n If provided an array-like object, the function returns an array-like object\n having the same length and data type as `x`.\n\n If provided an ndarray, the function returns an ndarray having the same\n shape and data type as `x`.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject|number\n Input value.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Output array order (either row-major (C-style) or column-major (Fortran-\n style)). Only applicable when the input array is an ndarray. By default,\n the output array order is inferred from the input array.\n\n options.dtype: string (optional)\n Output array data type. Only applicable when the input array is either\n an ndarray or array-like object. By default, the output array data type\n is inferred from the input array.\n\n Returns\n -------\n y: ndarray|ArrayLikeObject|number\n Results.\n\n Examples\n --------\n // Provide a number:\n > var y = abs( -1.0 )\n 1.0\n\n // Provide an array-like object:\n > var x = new Float64Array( [ -1.0, -2.0 ] );\n > y = abs( x )\n [ 1.0, 2.0 ]\n\n > x = [ -1.0, -2.0 ];\n > y = abs( x )\n [ 1.0, 2.0 ]\n\n // Provide an ndarray:\n > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n > y = abs( x )\n \n > y.get( 0, 1 )\n 2.0\n\n\nabs.assign( x, y )\n Computes the absolute value and assigns results to a provided output array.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n Input array.\n\n y: ndarray|ArrayLikeObject\n Output array. Must be the same data \"kind\" (i.e., ndarray or array-like\n object) as the input array.\n\n Returns\n -------\n y: ndarray|ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Provide an array-like object:\n > var x = new Float64Array( [ -1.0, -2.0 ] );\n > var y = new Float64Array( x.length );\n > var out = abs.assign( x, y )\n [ 1.0, 2.0 ]\n > var bool = ( out === y )\n true\n\n > x = [ -1.0, -2.0 ];\n > y = [ 0.0, 0.0 ];\n > out = abs.assign( x, y )\n [ 1.0, 2.0 ]\n > bool = ( out === y )\n true\n\n // Provide an ndarray:\n > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n > y = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\n > out = abs.assign( x, y )\n \n > out.get( 0, 1 )\n 2.0\n > bool = ( out === y )\n true\n\n","abs.assign":"\nabs.assign( x, y )\n Computes the absolute value and assigns results to a provided output array.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n Input array.\n\n y: ndarray|ArrayLikeObject\n Output array. Must be the same data \"kind\" (i.e., ndarray or array-like\n object) as the input array.\n\n Returns\n -------\n y: ndarray|ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Provide an array-like object:\n > var x = new Float64Array( [ -1.0, -2.0 ] );\n > var y = new Float64Array( x.length );\n > var out = abs.assign( x, y )\n [ 1.0, 2.0 ]\n > var bool = ( out === y )\n true\n\n > x = [ -1.0, -2.0 ];\n > y = [ 0.0, 0.0 ];\n > out = abs.assign( x, y )\n [ 1.0, 2.0 ]\n > bool = ( out === y )\n true\n\n // Provide an ndarray:\n > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n > y = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\n > out = abs.assign( x, y )\n \n > out.get( 0, 1 )\n 2.0\n > bool = ( out === y )\n true","acartesianPower":"\nacartesianPower( x, n )\n Returns the Cartesian power.\n\n If provided an empty array, the function returns an empty array.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n n: integer\n Power.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x = [ 1, 2 ];\n > var out = acartesianPower( x, 2 )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianProduct, acartesianSquare\n","acartesianProduct":"\nacartesianProduct( x1, x2 )\n Returns the Cartesian product.\n\n If provided one or more empty arrays, the function returns an empty array.\n\n Parameters\n ----------\n x1: ArrayLikeObject\n First input array.\n\n x2: ArrayLikeObject\n Second input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x1 = [ 1, 2 ];\n > var x2 = [ 3, 4 ];\n > var out = acartesianProduct( x1, x2 )\n [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n See Also\n --------\n acartesianPower, acartesianSquare\n","acartesianSquare":"\nacartesianSquare( x )\n Returns the Cartesian square.\n\n If provided an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var out = acartesianSquare( [ 1, 2 ] )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianPower, acartesianProduct\n","acronym":"\nacronym( str[, options] )\n Generates an acronym for a given string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n options: Object (optional)\n Options.\n\n options.stopwords: Array (optional)\n Array of custom stop words.\n\n Returns\n -------\n out: string\n Acronym for the given string.\n\n Examples\n --------\n > var out = acronym( 'the quick brown fox' )\n 'QBF'\n > out = acronym( 'Hard-boiled eggs' )\n 'HBE'\n","aempty":"\naempty( length[, dtype] )\n Creates an uninitialized array having a specified length.\n\n In browser environments, the function always returns zero-filled arrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled array.\n\n In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n is *not* initialized. Memory contents are unknown and may contain\n *sensitive* data.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aempty( 2 )\n \n > arr = aempty( 2, 'float32' )\n \n\n See Also\n --------\n aemptyLike, afull, aones, azeros, ndempty\n","aemptyLike":"\naemptyLike( x[, dtype] )\n Creates an uninitialized array having the same length and data type as a\n provided input array.\n\n In browser environments, the function always returns zero-filled arrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled array.\n\n In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n is *not* initialized. Memory contents are unknown and may contain\n *sensitive* data.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var arr = aemptyLike( x )\n \n > arr = aemptyLike( x, 'float32' )\n \n\n See Also\n --------\n aempty, afullLike, aonesLike, azerosLike, ndemptyLike\n","AFINN_96":"\nAFINN_96()\n Returns a list of English words rated for valence.\n\n The returned list contains 1468 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list is an earlier version of AFINN-111.\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_96()\n [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_111\n","AFINN_111":"\nAFINN_111()\n Returns a list of English words rated for valence.\n\n The returned list contains 2477 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Words may contain numbers; e.g., \"n00b\".\n - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain diaeresis; e.g., \"naïve\".\n - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_111()\n [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_96\n","afull":"\nafull( length, value[, dtype] )\n Returns a filled array having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n value: any\n Fill value.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = afull( 2, 1.0 )\n [ 1.0, 1.0 ]\n > arr = afull( 2, 1.0, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afullLike, aones, azeros\n","afullLike":"\nafullLike( x[, dtype] )\n Returns a filled array having the same length and data type as a provided\n input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = afullLike( x, 1.0 )\n [ 1.0, 1.0 ]\n > y = afullLike( x, 1.0, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afull, aonesLike, azerosLike\n","alias2pkg":"\nalias2pkg( alias )\n Returns the package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Package name.\n\n Examples\n --------\n > var v = alias2pkg( 'base.sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n","alias2related":"\nalias2related( alias )\n Returns aliases related to a specified alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: Array|null\n Related aliases.\n\n Examples\n --------\n > var v = alias2related( 'base.sin' )\n [...]\n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n","alias2standalone":"\nalias2standalone( alias )\n Returns the standalone package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Standalone package name.\n\n Examples\n --------\n > var v = alias2standalone( 'base.sin' )\n '@stdlib/math-base-special-sin'\n\n See Also\n --------\n alias2pkg, alias2related, aliases, pkg2alias, pkg2standalone\n","aliases":"\naliases( [namespace] )\n Returns a list of standard library aliases.\n\n Parameters\n ----------\n namespace: string (optional)\n Namespace filter.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n > o = aliases( '@stdlib/math/base/special' )\n [...]\n\n See Also\n --------\n alias2pkg, alias2related, pkg2alias\n","allocUnsafe":"\nallocUnsafe( size )\n Allocates a buffer having a specified number of bytes.\n\n The underlying memory of returned buffers is not initialized. Memory\n contents are unknown and may contain sensitive data.\n\n When the size is less than half a buffer pool size, memory is allocated from\n the buffer pool for faster allocation of Buffer instances.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = allocUnsafe( 100 )\n \n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","amskfilter":"\namskfilter( x, mask )\n Returns a new array by applying a mask to a provided input array.\n\n If a mask array element is truthy, the corresponding element in `x` is\n included in the output array; otherwise, the corresponding element in `x` is\n \"masked\" and thus excluded from the output array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n mask: Array|TypedArray|Object\n Mask array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = amskfilter( x, [ 0, 1, 0, 1 ] )\n [ 2, 4 ]\n\n See Also\n --------\n amskreject\n","amskreject":"\namskreject( x, mask )\n Returns a new array by applying a mask to a provided input array.\n\n If a mask array element is falsy, the corresponding element in `x` is\n included in the output array; otherwise, the corresponding element in `x` is\n \"masked\" and thus excluded from the output array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n mask: Array|TypedArray|Object\n Mask array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = amskreject( x, [ 0, 1, 0, 1 ] )\n [ 1, 3 ]\n\n See Also\n --------\n amskfilter\n","anans":"\nanans( length[, dtype] )\n Returns an array filled with NaNs and having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = anans( 2 )\n [ NaN, NaN ]\n > arr = anans( 2, 'float32' )\n [ NaN, NaN ]\n\n See Also\n --------\n afull, anansLike, aones, azeros\n","anansLike":"\nanansLike( x[, dtype] )\n Returns an array filled with NaNs and having the same length and data type\n as a provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - generic: generic JavaScript values\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = anansLike( x )\n [ NaN, NaN ]\n > y = anansLike( x, 'float32' )\n [ NaN, NaN ]\n\n See Also\n --------\n afullLike, anans, aonesLike, azerosLike\n","anova1":"\nanova1( x, factor[, options] )\n Performs a one-way analysis of variance.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n factor: Array\n Array of treatments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.means: Object\n Group means alongside sample sizes and standard errors.\n\n out.treatment: Object\n Treatment results.\n\n out.treatment.df: number\n Treatment degrees of freedom.\n\n out.treatment.ss: number\n Treatment sum of squares.\n\n out.treatment.ms: number\n Treatment mean sum of squares.\n\n out.error: Object\n Error results.\n\n out.error.df: number\n Error degrees of freedom.\n\n out.error.ss: number\n Error sum of squares.\n\n out.error.ms: number\n Error mean sum of squares.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n > var f = [\n ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ... ];\n > var out = anova1( x, f )\n {...}\n\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n\n Anscombe's quartet is a set of 4 datasets which all have nearly identical\n simple statistical properties but vary considerably when graphed. Anscombe\n created the datasets to demonstrate why graphical data exploration should\n precede statistical data analysis and to show the effect of outliers on\n statistical properties.\n\n Returns\n -------\n out: Array\n Anscombe's quartet.\n\n Examples\n --------\n > var d = ANSCOMBES_QUARTET()\n [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n References\n ----------\n - Anscombe, Francis J. 1973. \"Graphs in Statistical Analysis.\" *The American\n Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n Ltd.]: 17–21. .\n\n","any":"\nany( collection )\n Tests whether at least one element in a collection is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an element is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 1 ];\n > var bool = any( arr )\n true\n\n See Also\n --------\n anyBy, every, forEach, none, some\n","anyBy":"\nanyBy( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4, -1 ];\n > var bool = anyBy( arr, negative )\n true\n\n See Also\n --------\n anyByAsync, anyByRight, everyBy, forEach, noneBy, someBy\n","anyByAsync":"\nanyByAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync\n","anyByAsync.factory":"\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync","anyByRight":"\nanyByRight( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, 2, 3, 4 ];\n > var bool = anyByRight( arr, negative )\n true\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByRight, forEachRight, noneByRight, someByRight\n","anyByRightAsync":"\nanyByRightAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync","aones":"\naones( length[, dtype] )\n Returns an array filled with ones and having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aones( 2 )\n [ 1.0, 1.0 ]\n > arr = aones( 2, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afull, anans, aonesLike, azeros\n","aonesLike":"\naonesLike( x[, dtype] )\n Returns an array filled with ones and having the same length and data type\n as a provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = aonesLike( x )\n [ 1.0, 1.0 ]\n > y = aonesLike( x, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afullLike, anansLike, aones, azerosLike\n","aoneTo":"\naoneTo( n[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n If `n` is equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: integer\n Number of elements.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aoneTo( 2 )\n [ 1.0, 2.0 ]\n > arr = aoneTo( 2, 'float32' )\n [ 1.0, 2.0 ]\n\n See Also\n --------\n afull, aones, aoneToLike, azeroTo\n","aoneToLike":"\naoneToLike( x[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one and having the same length and data type as a provided\n input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aoneToLike( [ 0, 0 ] )\n [ 1, 2 ]\n > arr = aoneToLike( [ 0, 0 ], 'float32' )\n [ 1.0, 2.0 ]\n\n See Also\n --------\n afullLike, aonesLike, aoneTo, azeroToLike\n","APERY":"\nAPERY\n Apéry's constant.\n\n Examples\n --------\n > APERY\n 1.2020569031595942\n\n","append":"\nappend( collection1, collection2 )\n Adds the elements of one collection to the end of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = append( arr, [ 6.0, 7.0 ] )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = append( arr, [ 3.0, 4.0 ] )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = append( arr, [ 1.0, 2.0 ] )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n prepend, push\n","ARCH":"\nARCH\n Operating system CPU architecture for which the JavaScript runtime binary\n was compiled.\n\n Current possible values:\n\n - arm\n - arm64\n - ia32\n - mips\n - mipsel\n - ppc\n - ppc64\n - s390\n - s390x\n - x32\n - x64\n\n Examples\n --------\n > ARCH\n \n\n See Also\n --------\n PLATFORM\n","argumentFunction":"\nargumentFunction( idx )\n Returns a function which always returns a specified argument.\n\n The input argument corresponds to the zero-based index of the argument to\n return.\n\n Parameters\n ----------\n idx: integer\n Argument index to return (zero-based).\n\n Returns\n -------\n out: Function\n Argument function.\n\n Examples\n --------\n > var argn = argumentFunction( 1 );\n > var v = argn( 3.14, -3.14, 0.0 )\n -3.14\n > v = argn( -1.0, -0.0, 1.0 )\n -0.0\n > v = argn( 'beep', 'boop', 'bop' )\n 'boop'\n > v = argn( 'beep' )\n undefined\n\n See Also\n --------\n constantFunction, identity\n","ARGV":"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n\n The first element is the absolute pathname of the executable that started\n the calling process.\n\n The second element is the path of the executed file.\n\n Any additional elements are additional command-line arguments.\n\n In browser environments, the array is empty.\n\n Examples\n --------\n > var execPath = ARGV[ 0 ]\n e.g., /usr/local/bin/node\n\n See Also\n --------\n ENV\n","array":"\narray( [buffer,] [options] )\n Returns a multidimensional array.\n\n Parameters\n ----------\n buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source.\n\n options: Object (optional)\n Options.\n\n options.buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source. If provided along with a `buffer` argument, the argument\n takes precedence.\n\n options.dtype: string (optional)\n Underlying storage data type. If not specified and a data source is\n provided, the data type is inferred from the provided data source. If an\n input data source is not of the same type, this option specifies the\n data type to which to cast the input data. For non-ndarray generic array\n data sources, the function casts generic array data elements to the\n default data type. In order to prevent this cast, the `dtype` option\n must be explicitly set to `'generic'`. Any time a cast is required, the\n `copy` option is set to `true`, as memory must be copied from the data\n source to an output data buffer. Default: 'float64'.\n\n options.order: string (optional)\n Specifies the memory layout of the data source as either row-major (C-\n style) or column-major (Fortran-style). The option may be one of the\n following values:\n\n - 'row-major': the order of the returned array is row-major.\n - 'column-major': the order of the returned array is column-major.\n - 'any': if a data source is column-major and not row-major, the order\n of the returned array is column-major; otherwise, the order of the\n returned array is row-major.\n - 'same': the order of the returned array matches the order of an input\n data source.\n\n Note that specifying an order which differs from the order of a\n provided data source does *not* entail a conversion from one memory\n layout to another. In short, this option is descriptive, not\n prescriptive. Default: 'row-major'.\n\n options.shape: Array (optional)\n Array shape (dimensions). If a shape is not specified, the function\n attempts to infer a shape based on a provided data source. For example,\n if provided a nested array, the function resolves nested array\n dimensions. If provided a multidimensional array data source, the\n function uses the array's associated shape. For most use cases, such\n inference suffices. For the remaining use cases, specifying a shape is\n necessary. For example, provide a shape to create a multidimensional\n array view over a linear data buffer, ignoring any existing shape meta\n data associated with a provided data source.\n\n options.flatten: boolean (optional)\n Boolean indicating whether to automatically flatten generic array data\n sources. If an array shape is not specified, the shape is inferred from\n the dimensions of nested arrays prior to flattening. If a use case\n requires partial flattening, partially flatten prior to invoking this\n function and set the option value to `false` to prevent further\n flattening during invocation. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to (shallow) copy source data to a new data\n buffer. The function does *not* perform a deep copy. To prevent\n undesired shared changes in state for generic arrays containing objects,\n perform a deep copy prior to invoking this function. Default: false.\n\n options.ndmin: integer (optional)\n Specifies the minimum number of dimensions. If an array shape has fewer\n dimensions than required by `ndmin`, the function prepends singleton\n dimensions to the array shape in order to satisfy the dimensions\n requirement. Default: 0.\n\n options.casting: string (optional)\n Specifies the casting rule used to determine acceptable casts. The\n option may be one of the following values:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow \"safe\" casts.\n - 'mostly-safe': allow \"safe casts\" and, for floating-point data types,\n downcasts.\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers\n and floats).\n\n Default: 'safe'.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. The\n option may be one of the following values:\n\n - 'throw': an ndarray instance throws an error when an index exceeds\n array dimensions.\n - 'normalize': an ndarray instance normalizes negative indices and\n throws an error when an index exceeds array dimensions.\n - 'wrap': an ndarray instance wraps around indices exceeding array\n dimensions using modulo arithmetic.\n - 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index.\n\n Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to\n\n - 'throw': an ndarray instance throws an error when a subscript exceeds\n array dimensions.\n - 'normalize': an ndarray instance normalizes negative subscripts and\n throws an error when a subscript exceeds array dimensions.\n - 'wrap': an ndarray instance wraps around subscripts exceeding array\n dimensions using modulo arithmetic.\n - 'clamp': an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index.\n\n If the number of modes is fewer than the number of dimensions, the\n function recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Multidimensional array.\n\n Examples\n --------\n // Create a 2x2 matrix:\n > var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n See Also\n --------\n ndarray\n","array2buffer":"\narray2buffer( arr )\n Allocates a buffer using an octet array.\n\n Parameters\n ----------\n arr: Array\n Array (or array-like object) of octets from which to copy.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = array2buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n Buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","array2fancy":"\narray2fancy( x[, options] )\n Converts an array to an object supporting fancy indexing.\n\n An array supporting fancy indexing is an array which supports slicing via\n indexing expressions for both retrieval and assignment.\n\n A fancy array shares the *same* data as the provided input array. Hence, any\n mutations to the returned array will affect the underlying input array and\n vice versa.\n\n For operations returning a new array (e.g., when slicing or invoking an\n instance method), a fancy array returns a new fancy array having the same\n configuration as specified by provided options.\n\n A fancy array supports indexing using positive and negative integers (both\n numeric literals and strings), Slice instances, subsequence expressions,\n mask arrays, boolean arrays, and integer arrays.\n\n A fancy array supports all properties and methods of the input array, and,\n thus, a fancy array can be consumed by any API which supports array-like\n objects.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on array views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use (e.g., in the\n REPL) and scripting. For performance critical applications, prefer\n equivalent functional APIs supporting array-like objects.\n\n Fancy arrays support broadcasting in which assigned scalars and single-\n element arrays are repeated (without additional memory allocation) to match\n the length of a target array instance.\n\n Fancy array broadcasting follows the same rules as for ndarrays.\n\n Consequently, when assigning arrays to slices, the array on the right-hand-\n side must be broadcast-compatible with number of elements in the slice.\n\n Fancy arrays support (mostly) safe casts (i.e., any cast which can be\n performed without overflow or loss of precision, with the exception of\n floating-point arrays which are also allowed to downcast from higher\n precision to lower precision).\n\n When attempting to perform an unsafe cast, fancy arrays will raise an\n exception.\n\n When assigning a real-valued scalar to a complex number array (e.g.,\n Complex128Array or Complex64Array), a fancy array will cast the real-valued\n scalar to a complex number argument having an imaginary component equal to\n zero.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking. Default:\n false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array supporting fancy indexing.\n\n Examples\n --------\n > var y = array2fancy( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]\n\n\narray2fancy.factory( [options] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an array to an object supporting fancy indexing.\n\n Examples\n --------\n > var f = array2fancy.factory();\n > var y = f( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]\n\n\narray2fancy.idx( x[, options] )\n Wraps a provided array as an array index object.\n\n For documentation and usage, see `ArrayIndex`.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n See Also\n --------\n aslice, FancyArray\n","array2fancy.factory":"\narray2fancy.factory( [options] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an array to an object supporting fancy indexing.\n\n Examples\n --------\n > var f = array2fancy.factory();\n > var y = f( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]","array2fancy.idx":"\narray2fancy.idx( x[, options] )\n Wraps a provided array as an array index object.\n\n For documentation and usage, see `ArrayIndex`.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n See Also\n --------\n aslice, FancyArray","array2iterator":"\narray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, circarray2iterator, array2iteratorRight, stridedarray2iterator\n","array2iteratorRight":"\narray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator\n","ArrayBuffer":"\nArrayBuffer( size )\n Returns an array buffer having a specified number of bytes.\n\n Buffer contents are initialized to 0.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: ArrayBuffer\n An array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n\n\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1\n\n\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > ArrayBuffer.isView( arr )\n true\n\n\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","ArrayBuffer.length":"\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1","ArrayBuffer.isView":"\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > ArrayBuffer.isView( arr )\n true","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","arraybuffer2buffer":"\narraybuffer2buffer( buf[, byteOffset[, length]] )\n Allocates a buffer from an ArrayBuffer.\n\n The behavior of this function varies across Node.js versions due to changes\n in the underlying Node.js APIs:\n\n - <3.0.0: the function copies ArrayBuffer bytes to a new Buffer instance.\n - >=3.0.0 and <5.10.0: if provided a byte offset, the function copies\n ArrayBuffer bytes to a new Buffer instance; otherwise, the function\n returns a view of an ArrayBuffer without copying the underlying memory.\n - <6.0.0: if provided an empty ArrayBuffer, the function returns an empty\n Buffer which is not an ArrayBuffer view.\n - >=6.0.0: the function returns a view of an ArrayBuffer without copying\n the underlying memory.\n\n Parameters\n ----------\n buf: ArrayBuffer\n Input array buffer.\n\n byteOffset: integer (optional)\n Index offset specifying the location of the first byte.\n\n length: integer (optional)\n Number of bytes to expose from the underlying ArrayBuffer.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var ab = new ArrayBuffer( 10 )\n \n > var buf = arraybuffer2buffer( ab )\n \n > var len = buf.length\n 10\n > buf = arraybuffer2buffer( ab, 2, 6 )\n \n > len = buf.length\n 6\n\n See Also\n --------\n Buffer, array2buffer, copyBuffer, string2buffer\n","arrayCtors":"\narrayCtors( dtype )\n Returns an array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = arrayCtors( 'float64' )\n \n > ctor = arrayCtors( 'float' )\n null\n\n See Also\n --------\n typedarrayCtors\n","arrayDataType":"\narrayDataType( array )\n Returns the data type of an array.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n array: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > var dt = arrayDataType( arr )\n 'float64'\n > dt = arrayDataType( 'beep' )\n null\n\n See Also\n --------\n arrayDataTypes\n","arrayDataTypes":"\narrayDataTypes( [kind] )\n Returns a list of array data types.\n\n When not provided a data type \"kind\", the function returns an array\n containing the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n The function supports the following data type \"kinds\":\n\n - floating_point: floating-point data types.\n - real_floating_point: real-valued floating-point data types.\n - complex_floating_point: complex-valued floating-point data types.\n - integer: integer data types.\n - signed_integer: signed integer data types.\n - unsigned_integer: unsigned integer data types.\n - real: real-valued data types.\n - numeric: numeric data types.\n - typed: \"typed\" data types.\n - all: all data types.\n\n Additionally, the function supports extending the \"kinds\" listed above by\n appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n Parameters\n ----------\n kind: string (optional)\n Data type kind.\n\n Returns\n -------\n out: Array\n List of array data types.\n\n Examples\n --------\n > var out = arrayDataTypes()\n [...]\n > out = arrayDataTypes( 'floating_point' )\n [...]\n > out = arrayDataTypes( 'floating_point_and_generic' )\n [...]\n\n See Also\n --------\n typedarrayDataTypes, ndarrayDataTypes\n","ArrayIndex":"\nArrayIndex( x[, options] )\n Wraps a provided array as an array index object.\n\n Array index instances have no explicit functionality; however, they are used\n by \"fancy\" arrays for element retrieval and assignment.\n\n By default, an instance is invalidated and removed from an internal cache\n immediately after a consumer resolves the underlying data associated with an\n instance using the `get` static method. Immediate invalidation and cache\n removal ensures that references to the underlying array are not the source\n of memory leaks.\n\n Because instances leverage an internal cache implementing the Singleton\n pattern, one must be sure to use the same constructor as consumers. If one\n uses a different constructor, the consumer will *not* be able to resolve the\n original wrapped array, as the consumer will attempt to resolve an instance\n in the wrong internal cache.\n\n Because non-persisted instances are freed after first use, in order to avoid\n holding onto memory and to allow garbage collection, one should avoid\n scenarios in which an instance is never used.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n\n\nArrayIndex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > // ...\n > ArrayIndex.free( idx.id )\n\n\nArrayIndex.get( id )\n Returns the array associated with the instance having a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing array data.\n\n out.data: Array|TypedArray|Object\n The underlying array associated with the provided identifier.\n\n out.type: string\n The type of array index.\n\n out.dtype: string\n The data type of the underlying array.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.get( idx.id )\n {...}\n\n\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array data type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.data\n [ 1, 2, 3, 4 ]\n\n\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.dtype\n 'generic'\n\n\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.id\n \n\n\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an array index is actively cached.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.isCached\n true\n\n\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n\n Returns\n -------\n out: string\n Array index type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.type\n \n\n\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toString()\n\n\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toJSON()\n { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n See Also\n --------\n array2fancy\n","ArrayIndex.free":"\nArrayIndex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > // ...\n > ArrayIndex.free( idx.id )","ArrayIndex.get":"\nArrayIndex.get( id )\n Returns the array associated with the instance having a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing array data.\n\n out.data: Array|TypedArray|Object\n The underlying array associated with the provided identifier.\n\n out.type: string\n The type of array index.\n\n out.dtype: string\n The data type of the underlying array.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.get( idx.id )\n {...}","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array data type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.data\n [ 1, 2, 3, 4 ]","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.dtype\n 'generic'","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.id\n ","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an array index is actively cached.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.isCached\n true","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n\n Returns\n -------\n out: string\n Array index type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.type\n ","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toString()","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toJSON()\n { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n See Also\n --------\n array2fancy","arrayMinDataType":"\narrayMinDataType( value )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n real numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n Array data type.\n\n Examples\n --------\n > var dt = arrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = arrayMinDataType( 3 )\n 'uint8'\n > dt = arrayMinDataType( -3 )\n 'int8'\n > dt = arrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n arrayDataTypes, arrayPromotionRules, arraySafeCasts\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast and, for floating-point data types, can be downcast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type value.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be cast.\n\n Examples\n --------\n > var out = arrayMostlySafeCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, arraySameKindCasts, ndarrayMostlySafeCasts\n","arrayNextDataType":"\narrayNextDataType( [dtype] )\n Returns the next larger array data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = arrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n arrayDataType, arrayDataTypes\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1, dtype2] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: any (optional)\n Array data type.\n\n dtype2: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = arrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n arrayDataTypes, arraySafeCasts, ndarrayPromotionRules\n","arraySafeCasts":"\narraySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = arraySafeCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arrayMostlySafeCasts, arraySameKindCasts, ndarraySafeCasts\n","arraySameKindCasts":"\narraySameKindCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast or cast within\n the same \"kind\".\n\n Examples\n --------\n > var out = arraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, ndarraySameKindCasts\n","arrayShape":"\narrayShape( arr )\n Determines array dimensions.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Array shape.\n\n Examples\n --------\n > var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n [ 2, 3 ]\n\n See Also\n --------\n ndarray\n","arrayStream":"\narrayStream( src[, options] )\n Creates a readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = arrayStream( [ 1, 2, 3 ] );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );\n\n\narrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n circularArrayStream, iteratorStream, stridedArrayStream\n","arrayStream.factory":"\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );","arrayStream.objectMode":"\narrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n circularArrayStream, iteratorStream, stridedArrayStream","arrayview2iterator":"\narrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like object\n view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, stridedarray2iterator, arrayview2iteratorRight\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, stridedarray2iterator, arrayview2iterator\n","aslice":"\naslice( x[, start[, end]] )\n Returns a shallow copy of a portion of an array.\n\n If provided an array-like object having a `slice` method, the function\n defers execution to that method and assumes that the method has the\n following signature:\n\n x.slice( start, end )\n\n If provided an array-like object without a `slice` method, the function\n copies input array elements to a new generic array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n start: integer (optional)\n Starting index (inclusive). Default: 0.\n\n end: integer (optional)\n Ending index (exclusive). Default: x.length.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = aslice( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n > out = aslice( [ 1, 2, 3, 4 ], 1 )\n [ 2, 3, 4 ]\n > out = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n [ 2, 3 ]\n\n See Also\n --------\n atake\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n Async iterator symbol.\n\n This symbol specifies the default async iterator for an object.\n\n The symbol is only supported in ES2018+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = AsyncIteratorSymbol\n\n See Also\n --------\n Symbol, IteratorSymbol\n","atake":"\natake( x, indices[, options] )\n Takes elements from an array.\n\n If `indices` is an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n indices: ArrayLikeObject\n List of element indices.\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n Specifies how to handle an index outside the interval [0, max], where\n `max` is the maximum possible array index. If equal to 'throw', the\n function throws an error. If equal to 'normalize', the function throws\n an error if provided an out-of-bounds normalized index. If equal to\n 'wrap', the function wraps around an index using modulo arithmetic. If\n equal to 'clamp', the function sets an index to either 0 (minimum index)\n or the maximum index. Default: 'normalize'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = atake( x, [ 1, 3 ] )\n [ 2, 4 ]\n\n See Also\n --------\n aslice\n","azeros":"\nazeros( length[, dtype] )\n Returns a zero-filled array having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeros( 2 )\n [ 0.0, 0.0 ]\n > arr = azeros( 2, 'float32' )\n [ 0.0, 0.0 ]\n\n See Also\n --------\n aempty, afull, anans, aones, azerosLike, ndzeros\n","azerosLike":"\nazerosLike( x[, dtype] )\n Returns a zero-filled array having the same length and data type as a\n provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = azerosLike( x )\n [ 0.0, 0.0 ]\n > y = azerosLike( x, 'float32' )\n [ 0.0, 0.0 ]\n\n See Also\n --------\n aemptyLike, afullLike, anansLike, aonesLike, azeros, ndzerosLike\n","azeroTo":"\nazeroTo( n[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n If `n` is equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: integer\n Number of elements.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeroTo( 2 )\n [ 0.0, 1.0 ]\n > arr = azeroTo( 2, 'float32' )\n [ 0.0, 1.0 ]\n\n See Also\n --------\n aempty, afull, aoneTo, azeroToLike, azeros\n","azeroToLike":"\nazeroToLike( x[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero and having the same length and data type as a provided\n input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeroToLike( [ 0, 0 ] )\n [ 0, 1 ]\n > arr = azeroToLike( [ 0, 0 ], 'float32' )\n [ 0.0, 1.0 ]\n\n See Also\n --------\n aemptyLike, afullLike, anansLike, aoneToLike, aonesLike, azeroTo, azerosLike\n","bartlettTest":"\nbartlettTest( ...x[, options] )\n Computes Bartlett’s test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = bartlettTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = bartlettTest( arr, { 'groups': groups } )\n\n See Also\n --------\n vartest, leveneTest\n","base.abs":"\nbase.abs( x )\n Computes the absolute value of a double-precision floating-point number `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.abs( -1.0 )\n 1.0\n > y = base.abs( 2.0 )\n 2.0\n > y = base.abs( 0.0 )\n 0.0\n > y = base.abs( -0.0 )\n 0.0\n > y = base.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs2, base.absf, base.labs\n","base.abs2":"\nbase.abs2( x )\n Computes the squared absolute value of a double-precision floating-point\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2( -1.0 )\n 1.0\n > y = base.abs2( 2.0 )\n 4.0\n > y = base.abs2( 0.0 )\n 0.0\n > y = base.abs2( -0.0 )\n 0.0\n > y = base.abs2( NaN )\n NaN\n\n See Also\n --------\n base.abs, base.abs2f\n","base.abs2f":"\nbase.abs2f( x )\n Computes the squared absolute value of a single-precision floating-point\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2f( -1.0 )\n 1.0\n > y = base.abs2f( 2.0 )\n 4.0\n > y = base.abs2f( 0.0 )\n 0.0\n > y = base.abs2f( -0.0 )\n 0.0\n > y = base.abs2f( NaN )\n NaN\n\n See Also\n --------\n base.abs2, base.absf\n","base.absdiff":"\nbase.absdiff( x, y )\n Computes the absolute difference.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Absolute difference.\n\n Examples\n --------\n > var d = base.absdiff( 2.0, 5.0 )\n 3.0\n > d = base.absdiff( -1.0, 3.14 )\n ~4.14\n > d = base.absdiff( 10.1, -2.05 )\n ~12.15\n > d = base.absdiff( -0.0, 0.0 )\n +0.0\n > d = base.absdiff( NaN, 5.0 )\n NaN\n > d = base.absdiff( PINF, NINF )\n Infinity\n > d = base.absdiff( PINF, PINF )\n NaN\n\n See Also\n --------\n base.reldiff, base.epsdiff\n","base.absf":"\nbase.absf( x )\n Computes the absolute value of a single-precision floating-point number `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.absf( -1.0 )\n 1.0\n > y = base.absf( 2.0 )\n 2.0\n > y = base.absf( 0.0 )\n 0.0\n > y = base.absf( -0.0 )\n 0.0\n > y = base.absf( NaN )\n NaN\n\n See Also\n --------\n base.abs, base.abs2f, base.labs\n","base.acos":"\nbase.acos( x )\n Compute the arccosine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in radians).\n\n Examples\n --------\n > var y = base.acos( 1.0 )\n 0.0\n > y = base.acos( 0.707 )\n ~0.7855\n > y = base.acos( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asin, base.atan\n","base.acosh":"\nbase.acosh( x )\n Computes the hyperbolic arccosine of a double-precision floating-point\n number.\n\n If `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosine.\n\n Examples\n --------\n > var y = base.acosh( 1.0 )\n 0.0\n > y = base.acosh( 2.0 )\n ~1.317\n > y = base.acosh( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atanh\n","base.acot":"\nbase.acot( x )\n Computes the inverse cotangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse cotangent (in radians).\n\n Examples\n --------\n > var y = base.acot( 2.0 )\n ~0.4636\n > y = base.acot( 0.0 )\n ~1.5708\n > y = base.acot( 0.5 )\n ~1.1071\n > y = base.acot( 1.0 )\n ~0.7854\n > y = base.acot( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.atan, base.cot\n","base.acoth":"\nbase.acoth( x )\n Computes the inverse hyperbolic cotangent of a double-precision floating-\n point number.\n\n The domain of the inverse hyperbolic cotangent is the union of the intervals\n (-inf,-1] and [1,inf).\n\n If provided a value on the open interval (-1,1), the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse hyperbolic cotangent.\n\n Examples\n --------\n > var y = base.acoth( 2.0 )\n ~0.5493\n > y = base.acoth( 0.0 )\n NaN\n > y = base.acoth( 0.5 )\n NaN\n > y = base.acoth( 1.0 )\n Infinity\n > y = base.acoth( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.acot, base.asinh, base.atanh\n","base.acovercos":"\nbase.acovercos( x )\n Computes the inverse coversed cosine.\n\n The inverse coversed cosine is defined as `asin(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed cosine.\n\n Examples\n --------\n > var y = base.acovercos( -1.5 )\n ~-0.5236\n > y = base.acovercos( -0.0 )\n ~1.5708\n\n See Also\n --------\n base.acoversin, base.avercos, base.covercos, base.vercos\n","base.acoversin":"\nbase.acoversin( x )\n Computes the inverse coversed sine.\n\n The inverse coversed sine is defined as `asin(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed sine.\n\n Examples\n --------\n > var y = base.acoversin( 1.5 )\n ~-0.5236\n > y = base.acoversin( 0.0 )\n ~1.5708\n\n See Also\n --------\n base.acovercos, base.aversin, base.coversin, base.versin\n","base.acsc":"\nbase.acsc( x )\n Computes the arccosecant of a number.\n\n If `|x| < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in radians).\n\n Examples\n --------\n > var y = base.acsc( 1.0 )\n ~1.57\n > y = base.acsc( PI )\n ~0.32\n > y = base.acsc( -PI )\n ~-0.32\n > y = base.acsc( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acsch, base.asec, base.asin\n","base.acsch":"\nbase.acsch( x )\n Computes the hyperbolic arccosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosecant.\n\n Examples\n --------\n > var y = base.acsch( 0.0 )\n Infinity\n > y = base.acsch( -1.0 )\n ~-0.881\n > y = base.acsch( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.acsc, base.asech, base.asinh, base.csch\n","base.add":"\nbase.add( x, y )\n Computes the sum of two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Sum.\n\n Examples\n --------\n > var v = base.add( -1.0, 5.0 )\n 4.0\n > v = base.add( 2.0, 5.0 )\n 7.0\n > v = base.add( 0.0, 5.0 )\n 5.0\n > v = base.add( -0.0, 0.0 )\n 0.0\n > v = base.add( NaN, NaN )\n NaN\n\n See Also\n --------\n base.div, base.mul, base.sub\n","base.add3":"\nbase.add3( x, y, z )\n Computes the sum of three double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add3( -1.0, 5.0, 2.0 )\n 6.0\n > v = base.add3( 2.0, 5.0, 2.0 )\n 9.0\n > v = base.add3( 0.0, 5.0, 2.0 )\n 7.0\n > v = base.add3( -0.0, 0.0, -0.0 )\n 0.0\n > v = base.add3( NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.add4":"\nbase.add4( x, y, z, w )\n Computes the sum of four double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n w: number\n Fourth input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\n 3.0\n > v = base.add4( 2.0, 5.0, 2.0, -3.0 )\n 6.0\n > v = base.add4( 0.0, 5.0, 2.0, -3.0 )\n 4.0\n > v = base.add4( -0.0, 0.0, -0.0, -0.0 )\n 0.0\n > v = base.add4( NaN, NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.add5":"\nbase.add5( x, y, z, w, u )\n Computes the sum of five double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n w: number\n Fourth input value.\n\n u: number\n Fifth input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\n 7.0\n > v = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\n 10.0\n > v = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\n 8.0\n > v = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\n 0.0\n > v = base.add5( NaN, NaN, NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.addf":"\nbase.addf( x, y )\n Computes the sum of two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Sum.\n\n Examples\n --------\n > var v = base.addf( -1.0, 5.0 )\n 4.0\n > v = base.addf( 2.0, 5.0 )\n 7.0\n > v = base.addf( 0.0, 5.0 )\n 5.0\n > v = base.addf( -0.0, 0.0 )\n 0.0\n > v = base.addf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.divf, base.mulf, base.subf\n","base.ahavercos":"\nbase.ahavercos( x )\n Computes the inverse half-value versed cosine.\n\n The inverse half-value versed cosine is defined as `2*acos(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed cosine.\n\n Examples\n --------\n > var y = base.ahavercos( 0.5 )\n ~1.5708\n > y = base.ahavercos( 0.0 )\n ~3.1416\n\n See Also\n --------\n base.ahaversin, base.havercos, base.vercos\n","base.ahaversin":"\nbase.ahaversin( x )\n Computes the inverse half-value versed sine.\n\n The inverse half-value versed sine is defined as `2*asin(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed sine.\n\n Examples\n --------\n > var y = base.ahaversin( 0.5 )\n ~1.5708\n > y = base.ahaversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.ahavercos, base.haversin, base.versin\n","base.asec":"\nbase.asec( x )\n Computes the inverse (arc) secant of a number.\n\n If `x > -1` and `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse (arc) secant.\n\n Examples\n --------\n > var y = base.asec( 1.0 )\n 0.0\n > y = base.asec( 2.0 )\n ~1.0472\n > y = base.asec( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acsc, base.asech, base.acos\n","base.asech":"\nbase.asech( x )\n Computes the hyperbolic arcsecant of a number.\n\n If `x < 0` or `x > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsecant.\n\n Examples\n --------\n > var y = base.asech( 1.0 )\n 0.0\n > y = base.asech( 0.5 )\n ~1.317\n > y = base.asech( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asec, base.asech, base.acoth\n","base.asin":"\nbase.asin( x )\n Computes the arcsine of a double-precision floating-point number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in radians).\n\n Examples\n --------\n > var y = base.asin( 0.0 )\n 0.0\n > y = base.asin( -PI/6.0 )\n ~-0.551\n > y = base.asin( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atan\n","base.asinh":"\nbase.asinh( x )\n Computes the hyperbolic arcsine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsine.\n\n Examples\n --------\n > var y = base.asinh( 0.0 )\n 0.0\n > y = base.asinh( 2.0 )\n ~1.444\n > y = base.asinh( -2.0 )\n ~-1.444\n > y = base.asinh( NaN )\n NaN\n > y = base.asinh( NINF )\n -Infinity\n > y = base.asinh( PINF )\n Infinity\n\n See Also\n --------\n base.acosh, base.asin, base.atanh\n","base.atan":"\nbase.atan( x )\n Computes the arctangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in radians).\n\n Examples\n --------\n > var y = base.atan( 0.0 )\n ~0.0\n > y = base.atan( -PI/2.0 )\n ~-1.004\n > y = base.atan( PI/2.0 )\n ~1.004\n > y = base.atan( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asin, base.atanh\n","base.atan2":"\nbase.atan2( y, x )\n Computes the angle in the plane (in radians) between the positive x-axis and\n the ray from (0,0) to the point (x,y).\n\n Parameters\n ----------\n y: number\n Coordinate along y-axis.\n\n x: number\n Coordinate along x-axis.\n\n Returns\n -------\n out: number\n Angle (in radians).\n\n Examples\n --------\n > var v = base.atan2( 2.0, 2.0 )\n ~0.785\n > v = base.atan2( 6.0, 2.0 )\n ~1.249\n > v = base.atan2( -1.0, -1.0 )\n ~-2.356\n > v = base.atan2( 3.0, 0.0 )\n ~1.571\n > v = base.atan2( -2.0, 0.0 )\n ~-1.571\n > v = base.atan2( 0.0, 0.0 )\n 0.0\n > v = base.atan2( 3.0, NaN )\n NaN\n > v = base.atan2( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.atan\n","base.atanh":"\nbase.atanh( x )\n Computes the hyperbolic arctangent of a double-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arctangent.\n\n Examples\n --------\n > var y = base.atanh( 0.0 )\n 0.0\n > y = base.atanh( 0.9 )\n ~1.472\n > y = base.atanh( 1.0 )\n Infinity\n > y = base.atanh( -1.0 )\n -Infinity\n > y = base.atanh( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asinh, base.atan\n","base.avercos":"\nbase.avercos( x )\n Computes the inverse versed cosine.\n\n The inverse versed cosine is defined as `acos(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed cosine.\n\n Examples\n --------\n > var y = base.avercos( -1.5 )\n ~2.0944\n > y = base.avercos( -0.0 )\n 0.0\n\n See Also\n --------\n base.aversin, base.versin\n","base.aversin":"\nbase.aversin( x )\n Computes the inverse versed sine.\n\n The inverse versed sine is defined as `acos(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed sine.\n\n Examples\n --------\n > var y = base.aversin( 1.5 )\n ~2.0944\n > y = base.aversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.avercos, base.vercos\n","base.bernoulli":"\nbase.bernoulli( n )\n Computes the nth Bernoulli number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Bernoulli number.\n\n Examples\n --------\n > var y = base.bernoulli( 0 )\n 1.0\n > y = base.bernoulli( 1 )\n 0.0\n > y = base.bernoulli( 2 )\n ~0.167\n > y = base.bernoulli( 3 )\n 0.0\n > y = base.bernoulli( 4 )\n ~-0.033\n > y = base.bernoulli( 5 )\n 0.0\n > y = base.bernoulli( 20 )\n ~-529.124\n > y = base.bernoulli( 260 )\n -Infinity\n > y = base.bernoulli( 262 )\n Infinity\n > y = base.bernoulli( NaN )\n NaN\n\n","base.besselj0":"\nbase.besselj0( x )\n Computes the Bessel function of the first kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj0( 0.0 )\n 1.0\n > y = base.besselj0( 1.0 )\n ~0.765\n > y = base.besselj0( PINF )\n 0.0\n > y = base.besselj0( NINF )\n 0.0\n > y = base.besselj0( NaN )\n NaN\n\n See Also\n --------\n base.besselj1, base.bessely0, base.bessely1\n","base.besselj1":"\nbase.besselj1( x )\n Computes the Bessel function of the first kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj1( 0.0 )\n 0.0\n > y = base.besselj1( 1.0 )\n ~0.440\n > y = base.besselj1( PINF )\n 0.0\n > y = base.besselj1( NINF )\n 0.0\n > y = base.besselj1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.bessely0, base.bessely1\n","base.bessely0":"\nbase.bessely0( x )\n Computes the Bessel function of the second kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely0( 0.0 )\n -Infinity\n > y = base.bessely0( 1.0 )\n ~0.088\n > y = base.bessely0( -1.0 )\n NaN\n > y = base.bessely0( PINF )\n 0.0\n > y = base.bessely0( NINF )\n NaN\n > y = base.bessely0( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely1\n","base.bessely1":"\nbase.bessely1( x )\n Computes the Bessel function of the second kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely1( 0.0 )\n -Infinity\n > y = base.bessely1( 1.0 )\n ~-0.781\n > y = base.bessely1( -1.0 )\n NaN\n > y = base.bessely1( PINF )\n 0.0\n > y = base.bessely1( NINF )\n NaN\n > y = base.bessely1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely0\n","base.beta":"\nbase.beta( x, y )\n Evaluates the beta function.\n\n Parameters\n ----------\n x: number\n First function parameter (nonnegative).\n\n y: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Evaluated beta function.\n\n Examples\n --------\n > var v = base.beta( 0.0, 0.5 )\n Infinity\n > v = base.beta( 1.0, 1.0 )\n 1.0\n > v = base.beta( -1.0, 2.0 )\n NaN\n > v = base.beta( 5.0, 0.2 )\n ~3.382\n > v = base.beta( 4.0, 1.0 )\n 0.25\n > v = base.beta( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.betainc, base.betaincinv, base.betaln\n","base.betainc":"\nbase.betainc( x, a, b[, regularized[, upper]] )\n Computes the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `NaN`.\n\n If provided `a < 0` or `b < 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betainc( 0.5, 2.0, 2.0 )\n 0.5\n > y = base.betainc( 0.5, 2.0, 2.0, false )\n ~0.083\n > y = base.betainc( 0.2, 1.0, 2.0 )\n 0.36\n > y = base.betainc( 0.2, 1.0, 2.0, true, true )\n 0.64\n > y = base.betainc( NaN, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.8, NaN, 1.0 )\n NaN\n > y = base.betainc( 0.8, 1.0, NaN )\n NaN\n > y = base.betainc( 1.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betainc( 0.5, 2.0, -2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betaincinv, base.betaln\n","base.betaincinv":"\nbase.betaincinv( p, a, b[, upper] )\n Computes the inverse of the lower incomplete beta function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second and third arguments are `a` and `b`,\n respectively.\n\n By default, the function inverts the lower regularized incomplete beta\n function. To invert the upper function, set the `upper` argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betaincinv( 0.2, 3.0, 3.0 )\n ~0.327\n > y = base.betaincinv( 0.4, 3.0, 3.0 )\n ~0.446\n > y = base.betaincinv( 0.4, 3.0, 3.0, true )\n ~0.554\n > y = base.betaincinv( 0.4, 1.0, 6.0 )\n ~0.082\n > y = base.betaincinv( 0.8, 1.0, 6.0 )\n ~0.235\n > y = base.betaincinv( NaN, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, NaN, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, 1.0, NaN )\n NaN\n > y = base.betaincinv( 1.2, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 0.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, -2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, 0.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaln\n","base.betaln":"\nbase.betaln( a, b )\n Evaluates the natural logarithm of the beta function.\n\n Parameters\n ----------\n a: number\n First function parameter (nonnegative).\n\n b: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Natural logarithm of the beta function.\n\n Examples\n --------\n > var v = base.betaln( 0.0, 0.0 )\n Infinity\n > v = base.betaln( 1.0, 1.0 )\n 0.0\n > v = base.betaln( -1.0, 2.0 )\n NaN\n > v = base.betaln( 5.0, 0.2 )\n ~1.218\n > v = base.betaln( 4.0, 1.0 )\n ~-1.386\n > v = base.betaln( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaincinv\n","base.binet":"\nbase.binet( x )\n Evaluates Binet's formula extended to real numbers.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function result.\n\n Examples\n --------\n > var y = base.binet( 0.0 )\n 0.0\n > y = base.binet( 1.0 )\n 1.0\n > y = base.binet( 2.0 )\n 1.0\n > y = base.binet( 3.0 )\n 2.0\n > y = base.binet( 4.0 )\n 3.0\n > y = base.binet( 5.0 )\n ~5.0\n > y = base.binet( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negafibonacci\n","base.binomcoef":"\nbase.binomcoef( n, k )\n Computes the binomial coefficient of two integers.\n\n If `k < 0`, the function returns `0`.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = base.binomcoef( 8, 2 )\n 28\n > v = base.binomcoef( 0, 0 )\n 1\n > v = base.binomcoef( -4, 2 )\n 10\n > v = base.binomcoef( 5, 3 )\n 10\n > v = base.binomcoef( NaN, 3 )\n NaN\n > v = base.binomcoef( 5, NaN )\n NaN\n > v = base.binomcoef( NaN, NaN )\n NaN\n\n","base.binomcoefln":"\nbase.binomcoefln( n, k )\n Computes the natural logarithm of the binomial coefficient of two integers.\n\n If `k < 0`, the function returns negative infinity.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Natural logarithm of the binomial coefficient.\n\n Examples\n --------\n > var v = base.binomcoefln( 8, 2 )\n ~3.332\n > v = base.binomcoefln( 0, 0 )\n 0.0\n > v = base.binomcoefln( -4, 2 )\n ~2.303\n > v = base.binomcoefln( 88, 3 )\n ~11.606\n > v = base.binomcoefln( NaN, 3 )\n NaN\n > v = base.binomcoefln( 5, NaN )\n NaN\n > v = base.binomcoefln( NaN, NaN )\n NaN\n\n","base.boxcox":"\nbase.boxcox( x, lambda )\n Computes a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox( 1.0, 2.5 )\n 0.0\n > v = base.boxcox( 4.0, 2.5 )\n 12.4\n > v = base.boxcox( 10.0, 2.5 )\n ~126.0911\n > v = base.boxcox( 2.0, 0.0 )\n ~0.6931\n > v = base.boxcox( -1.0, 2.5 )\n NaN\n > v = base.boxcox( 0.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcoxinv, base.boxcox1p, base.boxcox1pinv","base.boxcox1p":"\nbase.boxcox1p( x, lambda )\n Computes a one-parameter Box-Cox transformation of 1+x.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1p( 1.0, 2.5 )\n ~1.8627\n > v = base.boxcox1p( 4.0, 2.5 )\n ~21.9607\n > v = base.boxcox1p( 10.0, 2.5 )\n ~160.1246\n > v = base.boxcox1p( 2.0, 0.0 )\n ~1.0986\n > v = base.boxcox1p( -1.0, 2.5 )\n -0.4\n > v = base.boxcox1p( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1p( -1.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcox, base.boxcox1pinv, base.boxcoxinv","base.boxcox1pinv":"\nbase.boxcox1pinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1pinv( 1.0, 2.5 )\n ~0.6505\n > v = base.boxcox1pinv( 4.0, 2.5 )\n ~1.6095\n > v = base.boxcox1pinv( 10.0, 2.5 )\n ~2.6812\n > v = base.boxcox1pinv( 2.0, 0.0 )\n ~6.3891\n > v = base.boxcox1pinv( -1.0, 2.5 )\n NaN\n > v = base.boxcox1pinv( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1pinv( 1.0, NaN )\n NaN\n > v = base.boxcox1pinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcoxinv","base.boxcoxinv":"\nbase.boxcoxinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcoxinv( 1.0, 2.5 )\n ~1.6505\n > v = base.boxcoxinv( 4.0, 2.5 )\n ~2.6095\n > v = base.boxcoxinv( 10.0, 2.5 )\n ~3.6812\n > v = base.boxcoxinv( 2.0, 0.0 )\n ~7.3891\n > v = base.boxcoxinv( -1.0, 2.5 )\n NaN\n > v = base.boxcoxinv( 0.0, -1.0 )\n 1.0\n > v = base.boxcoxinv( 1.0, NaN )\n NaN\n > v = base.boxcoxinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcox1pinv","base.cabs":"\nbase.cabs( z )\n Computes the absolute value of a double-precision complex floating-point\n number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n ~5.831\n\n See Also\n --------\n base.cabs2, base.abs\n","base.cabs2":"\nbase.cabs2( z )\n Computes the squared absolute value of a double-precision complex floating-\n point number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n 34.0\n\n See Also\n --------\n base.cabs, base.abs2\n","base.cabs2f":"\nbase.cabs2f( z )\n Computes the squared absolute value of a single-precision complex floating-\n point number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n 34.0\n\n See Also\n --------\n base.cabs2, base.cabsf, base.abs2f\n","base.cabsf":"\nbase.cabsf( z )\n Computes the absolute value of a single-precision complex floating-point\n number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n ~5.831\n\n See Also\n --------\n base.cabs, base.cabs2f, base.absf\n","base.cadd":"\nbase.cadd( z1, z2 )\n Adds two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var out = base.cadd( z, z )\n \n > var re = real( out )\n 10.0\n > var im = imag( out )\n 6.0\n\n See Also\n --------\n base.cdiv, base.cmul, base.csub\n","base.caddf":"\nbase.caddf( z1, z2 )\n Adds two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var out = base.caddf( z, z )\n \n > var re = realf( out )\n 10.0\n > var im = imagf( out )\n 6.0\n\n See Also\n --------\n base.cadd, base.cmulf, base.csubf\n","base.cbrt":"\nbase.cbrt( x )\n Computes the cube root of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrt( 64.0 )\n 4.0\n > y = base.cbrt( 27.0 )\n 3.0\n > y = base.cbrt( 0.0 )\n 0.0\n > y = base.cbrt( -0.0 )\n -0.0\n > y = base.cbrt( -9.0 )\n ~-2.08\n > y = base.cbrt( NaN )\n NaN\n\n See Also\n --------\n base.pow, base.sqrt\n","base.cbrtf":"\nbase.cbrtf( x )\n Computes the cube root of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrtf( 64.0 )\n 4.0\n > y = base.cbrtf( 27.0 )\n 3.0\n > y = base.cbrtf( 0.0 )\n 0.0\n > y = base.cbrtf( -0.0 )\n -0.0\n > y = base.cbrtf( -9.0 )\n ~-2.08\n > y = base.cbrtf( NaN )\n NaN\n\n See Also\n --------\n base.cbrt, base.sqrtf\n","base.cceil":"\nbase.cceil( z )\n Rounds a double-precision complex floating-point number toward positive\n infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cceil( new Complex128( -1.5, 2.5 ) )\n \n > var re = real( v )\n -1.0\n > var im = imag( v )\n 3.0\n\n See Also\n --------\n base.cceiln, base.cfloor, base.cround\n","base.cceilf":"\nbase.cceilf( z )\n Rounds a single-precision complex floating-point number toward positive\n infinity.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\n \n > var re = real( v )\n -1.0\n > var im = imag( v )\n 3.0\n\n See Also\n --------\n base.cceil\n","base.cceiln":"\nbase.cceiln( z, n )\n Rounds each component of a double-precision complex number to the nearest\n multiple of `10^n` toward positive infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Complex128\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\n \n > var re = real( out )\n 5.56\n > var im = imag( out )\n -3.33\n\n See Also\n --------\n base.cceil, base.cfloorn, base.croundn\n","base.ccis":"\nbase.ccis( z )\n Evaluates the cis function for a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex number.\n\n Examples\n --------\n > var y = base.ccis( new Complex128( 0.0, 0.0 ) )\n \n > var re = real( y )\n 1.0\n > var im = imag( y )\n 0.0\n > y = base.ccis( new Complex128( 1.0, 0.0 ) )\n \n > re = real( y )\n ~0.540\n > im = imag( y )\n ~0.841\n\n","base.cdiv":"\nbase.cdiv( z1, z2 )\n Divides two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( -13.0, -1.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var y = base.cdiv( z1, z2 )\n \n > var re = real( y )\n 5.0\n > var im = imag( y )\n 3.0\n\n See Also\n --------\n base.cadd, base.cmul, base.csub\n","base.ceil":"\nbase.ceil( x )\n Rounds a double-precision floating-point number toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil( 3.14 )\n 4.0\n > y = base.ceil( -4.2 )\n -4.0\n > y = base.ceil( -4.6 )\n -4.0\n > y = base.ceil( 9.5 )\n 10.0\n > y = base.ceil( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceiln, base.floor, base.round\n","base.ceil2":"\nbase.ceil2( x )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil2( 3.14 )\n 4.0\n > y = base.ceil2( -4.2 )\n -4.0\n > y = base.ceil2( -4.6 )\n -4.0\n > y = base.ceil2( 9.5 )\n 16.0\n > y = base.ceil2( 13.0 )\n 16.0\n > y = base.ceil2( -13.0 )\n -8.0\n > y = base.ceil2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil10, base.floor2, base.round2\n","base.ceil10":"\nbase.ceil10( x )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil10( 3.14 )\n 10.0\n > y = base.ceil10( -4.2 )\n -1.0\n > y = base.ceil10( -4.6 )\n -1.0\n > y = base.ceil10( 9.5 )\n 10.0\n > y = base.ceil10( 13.0 )\n 100.0\n > y = base.ceil10( -13.0 )\n -10.0\n > y = base.ceil10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil2, base.floor10, base.round10\n","base.ceilb":"\nbase.ceilb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.ceilb( 3.14159, -4, 10 )\n 3.1416\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.ceilb( 3.14159, 0, 2 )\n 4.0\n\n // Round to nearest multiple of two toward positive infinity:\n > y = base.ceilb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceil, base.ceiln, base.floorb, base.roundb\n","base.ceilf":"\nbase.ceilf( x )\n Rounds a single-precision floating-point number toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilf( 3.14 )\n 4.0\n > y = base.ceilf( -4.2 )\n -4.0\n > y = base.ceilf( -4.6 )\n -4.0\n > y = base.ceilf( 9.5 )\n 10.0\n > y = base.ceilf( -0.0 )\n -0.0\n\n See Also\n --------\n base.floorf\n","base.ceiln":"\nbase.ceiln( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.ceiln( 3.14159, -2 )\n 3.15\n\n // If `n = 0`, standard round toward positive infinity behavior:\n > y = base.ceiln( 3.14159, 0 )\n 4.0\n\n // Round to nearest thousand:\n > y = base.ceiln( 12368.0, 3 )\n 13000.0\n\n\n See Also\n --------\n base.ceil, base.ceilb, base.floorn, base.roundn\n","base.ceilsd":"\nbase.ceilsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilsd( 3.14159, 5 )\n 3.1416\n > y = base.ceilsd( 3.14159, 1 )\n 4.0\n > y = base.ceilsd( 12368.0, 2 )\n 13000.0\n > y = base.ceilsd( 0.0313, 2, 2 )\n 0.046875\n\n See Also\n --------\n base.ceil, base.floorsd, base.roundsd, base.truncsd\n","base.cexp":"\nbase.cexp( z )\n Evaluates the exponential function for a double-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex number.\n\n Examples\n --------\n > var y = base.cexp( new Complex128( 0.0, 0.0 ) )\n \n > var re = real( y )\n 1.0\n > var im = imag( y )\n 0.0\n > y = base.cexp( new Complex128( 0.0, 1.0 ) )\n \n > re = real( y )\n ~0.540\n > im = imag( y )\n ~0.841\n\n","base.cflipsign":"\nbase.cflipsign( z, y )\n Returns a double-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\n \n > var re = real( v )\n 4.2\n > var im = imag( v )\n -5.5\n\n See Also\n --------\n base.cneg, base.csignum\n","base.cflipsignf":"\nbase.cflipsignf( z, y )\n Returns a single-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\n \n > var re = real( v )\n 4.0\n > var im = imag( v )\n -5.0\n\n See Also\n --------\n base.cnegf, base.cflipsign\n","base.cfloor":"\nbase.cfloor( z )\n Rounds a double-precision complex floating-point number toward negative\n infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\n \n > var re = real( v )\n 5.0\n > var im = imag( v )\n 3.0\n\n See Also\n --------\n base.cceil, base.cfloorn, base.cround\n","base.cfloorn":"\nbase.cfloorn( z, n )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n` toward negative infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n z: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\n \n > var re = real( v )\n 5.55\n > var im = imag( v )\n -3.34\n\n See Also\n --------\n base.cceiln, base.cfloor, base.croundn\n","base.cidentity":"\nbase.cidentity( z )\n Evaluates the identity function for a double-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex128\n Input value.\n\n Returns\n -------\n v: Complex128\n Input value.\n\n Examples\n --------\n > var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\n \n > var re = real( v )\n -1.0\n > var img = imag( v )\n 2.0\n\n See Also\n --------\n base.cidentityf, base.identity\n","base.cidentityf":"\nbase.cidentityf( z )\n Evaluates the identity function for a single-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex64\n Input value.\n\n Returns\n -------\n v: Complex64\n Input value.\n\n Examples\n --------\n > var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\n \n > var re = real( v )\n -1.0\n > var img = imag( v )\n 2.0\n\n See Also\n --------\n base.cidentity, base.identityf\n","base.cinv":"\nbase.cinv( z )\n Computes the inverse of a double-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cinv( new Complex128( 2.0, 4.0 ) )\n \n > var re = real( v )\n 0.1\n > var im = imag( v )\n -0.2\n\n See Also\n --------\n base.cdiv\n","base.clamp":"\nbase.clamp( v, min, max )\n Restricts a double-precision floating-point number to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clamp( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clamp( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clamp( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clamp( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clampf, base.wrap\n","base.clampf":"\nbase.clampf( v, min, max )\n Restricts a single-precision floating-point number to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clampf( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clampf( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clampf( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clampf( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clampf( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clampf( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clamp\n","base.cmul":"\nbase.cmul( z1, z2 )\n Multiplies two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( 5.0, 3.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var out = base.cmul( z1, z2 )\n \n > var re = real( out )\n -13.0\n > var im = imag( out )\n -1.0\n\n See Also\n --------\n base.cadd, base.cdiv, base.csub\n","base.cmulf":"\nbase.cmulf( z1, z2 )\n Multiplies two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z1 = new Complex64( 5.0, 3.0 )\n \n > var z2 = new Complex64( -2.0, 1.0 )\n \n > var out = base.cmulf( z1, z2 )\n \n > var re = realf( out )\n -13.0\n > var im = imagf( out )\n -1.0\n\n See Also\n --------\n base.caddf, base.cmul, base.csubf\n","base.cneg":"\nbase.cneg( z )\n Negates a double-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z = new Complex128( -4.2, 5.5 )\n \n > var v = base.cneg( z )\n \n > var re = real( v )\n 4.2\n > var im = imag( v )\n -5.5\n\n See Also\n --------\n base.cabs\n","base.cnegf":"\nbase.cnegf( z )\n Negates a single-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z = new Complex64( -4.0, 5.0 )\n \n > var v = base.cnegf( z )\n \n > var re = realf( v )\n 4.0\n > var im = imagf( v )\n -5.0\n\n See Also\n --------\n base.cneg, base.cabsf\n","base.continuedFraction":"\nbase.continuedFraction( generator[, options] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n\n `generator` can be either a function which returns an array with two\n elements, the `a` and `b` terms of the fraction, or an ES6 Generator object.\n\n By default, the function computes\n\n a1\n ---------------\n b1 + a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n To evaluate\n\n b0 +\t a1\n ---------------\n b1 +\t a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n set the `keep` option to `true`.\n\n Parameters\n ----------\n generator: Function\n Function returning terms of continued fraction expansion.\n\n options: Object (optional)\n Options.\n\n options.maxIter: integer (optional)\n Maximum number of iterations. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n current term times the tolerance. Default: `2.22e-16`.\n\n options.keep: boolean (optional)\n Boolean indicating whether to keep the `b0` term in the continued\n fraction. Default: `false`.\n\n Returns\n -------\n out: number\n Value of continued fraction.\n\n Examples\n --------\n // Continued fraction for (e-1)^(-1):\n > function closure() {\n ... var i = 0;\n ... return function() {\n ... i += 1;\n ... return [ i, i ];\n ... };\n ... };\n > var gen = closure();\n > var out = base.continuedFraction( gen )\n ~0.582\n\n // Using an ES6 generator:\n > function* generator() {\n ... var i = 0;\n ... while ( true ) {\n ... i += 1;\n ... yield [ i, i ];\n ... }\n ... };\n > gen = generator();\n > out = base.continuedFraction( gen )\n ~0.582\n\n // Set options:\n > out = base.continuedFraction( generator(), { 'keep': true } )\n ~1.718\n > out = base.continuedFraction( generator(), { 'maxIter': 10 } )\n ~0.582\n > out = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n ~0.579\n\n","base.copysign":"\nbase.copysign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysign( -3.14, 10.0 )\n 3.14\n > z = base.copysign( 3.14, -1.0 )\n -3.14\n > z = base.copysign( 1.0, -0.0 )\n -1.0\n > z = base.copysign( -3.14, -0.0 )\n -3.14\n > z = base.copysign( -0.0, 1.0 )\n 0.0\n\n See Also\n --------\n base.flipsign\n","base.copysignf":"\nbase.copysignf( x, y )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Single-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysignf( -3.0, 10.0 )\n 3.0\n > z = base.copysignf( 3.0, -1.0 )\n -3.0\n > z = base.copysignf( 1.0, -0.0 )\n -1.0\n > z = base.copysignf( -3.0, -0.0 )\n -3.0\n > z = base.copysignf( -0.0, 1.0 )\n 0.0\n\n See Also\n --------\n base.copysign, base.flipsignf\n","base.cos":"\nbase.cos( x )\n Computes the cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine.\n\n Examples\n --------\n > var y = base.cos( 0.0 )\n 1.0\n > y = base.cos( PI/4.0 )\n ~0.707\n > y = base.cos( -PI/6.0 )\n ~0.866\n > y = base.cos( NaN )\n NaN\n\n See Also\n --------\n base.cospi, base.cosm1, base.sin, base.tan\n","base.cosh":"\nbase.cosh( x )\n Computes the hyperbolic cosine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic cosine.\n\n Examples\n --------\n > var y = base.cosh( 0.0 )\n 1.0\n > y = base.cosh( 2.0 )\n ~3.762\n > y = base.cosh( -2.0 )\n ~3.762\n > y = base.cosh( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinh, base.tanh\n","base.cosm1":"\nbase.cosm1( x )\n Computes the cosine of a number minus one.\n\n This function should be used instead of manually calculating `cos(x)-1` when\n `x` is near unity.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine minus one.\n\n Examples\n --------\n > var y = base.cosm1( 0.0 )\n 0.0\n > y = base.cosm1( PI/4.0 )\n ~-0.293\n > y = base.cosm1( -PI/6.0 )\n ~-0.134\n > y = base.cosm1( NaN )\n NaN\n\n See Also\n --------\n base.cos\n","base.cospi":"\nbase.cospi( x )\n Computes the value of `cos(πx)`.\n\n This function computes `cos(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.cospi( 0.0 )\n 1.0\n > y = base.cospi( 0.5 )\n 0.0\n > y = base.cospi( 0.1 )\n ~0.951\n > y = base.cospi( NaN )\n NaN\n\n See Also\n --------\n base.cos\n","base.cot":"\nbase.cot( x )\n Computes the cotangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cotangent.\n\n Examples\n --------\n > var y = base.cot( 0.0 )\n Infinity\n > y = base.cot( -PI/4.0 )\n ~-1.0\n > y = base.cot( PI/4.0 )\n ~1.0\n > y = base.cot( NaN )\n NaN\n\n See Also\n --------\n base.tan\n","base.coth":"\nbase.coth( x )\n Computes the hyperbolic cotangent of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic cotangent.\n\n Examples\n --------\n > var y = base.coth( 0.0 )\n Infinity\n > y = base.coth( -0.0 )\n -Infinity\n > y = base.coth( 2.0 )\n ~1.0373\n > y = base.coth( -2.0 )\n ~-1.0373\n > y = base.coth( +Infinity )\n ~1\n > y = base.coth( -Infinity )\n ~-1\n > y = base.coth( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.cot, base.csch, base.tanh\n","base.covercos":"\nbase.covercos( x )\n Computes the coversed cosine.\n\n The coversed cosine is defined as `1 + sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed cosine.\n\n Examples\n --------\n > var y = base.covercos( 3.14 )\n ~1.0016\n > y = base.covercos( -4.2 )\n ~1.8716\n > y = base.covercos( -4.6 )\n ~1.9937\n > y = base.covercos( 9.5 )\n ~0.9248\n > y = base.covercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.coversin, base.vercos\n","base.coversin":"\nbase.coversin( x )\n Computes the coversed sine.\n\n The coversed sine is defined as `1 - sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed sine.\n\n Examples\n --------\n > var y = base.coversin( 3.14 )\n ~0.9984\n > y = base.coversin( -4.2 )\n ~0.1284\n > y = base.coversin( -4.6 )\n ~0.0063\n > y = base.coversin( 9.5 )\n ~1.0752\n > y = base.coversin( -0.0 )\n 1.0\n\n See Also\n --------\n base.covercos, base.versin\n","base.cphase":"\nbase.cphase( z )\n Computes the argument of a double-precision complex floating-point number\n in radians.\n\n The argument of a complex number, also known as the phase, is the angle of\n the radius extending from the origin to the complex number plotted in the\n complex plane and the positive real axis.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n phi: number\n Argument.\n\n Examples\n --------\n > var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n ~0.5404\n\n See Also\n --------\n base.cabs\n","base.cpolar":"\nbase.cpolar( z )\n Returns the absolute value and phase of a double-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Array\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n [ ~5.83, ~0.5404 ]\n\n\nbase.cpolar.assign( z, out, stride, offset )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n out: Array|TypedArray|Object\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs, base.cphase","base.cpolar.assign":"\nbase.cpolar.assign( z, out, stride, offset )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n out: Array|TypedArray|Object\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs, base.cphase","base.cround":"\nbase.cround( z )\n Rounds each component of a double-precision complex floating-point number\n to the nearest integer.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Rounded complex number.\n\n Examples\n --------\n > var v = base.cround( new Complex128( 5.5, 3.3 ) )\n \n > var re = real( v )\n 6.0\n > var im = imag( v )\n 3.0\n\n See Also\n --------\n base.cceil, base.cfloor, base.croundn\n","base.croundn":"\nbase.croundn( z, n )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\n \n > var re = real( v )\n 5.56\n > var im = imag( v )\n -3.34\n\n See Also\n --------\n base.cceiln, base.cfloorn, base.cround\n","base.csch":"\nbase.csch( x )\n Computes the hyperbolic cosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic cosecant.\n\n Examples\n --------\n > var y = base.csch( +0.0 )\n +Infinity\n > var y = base.csch( -0.0 )\n -Infinity\n > var y = base.csch( +Infinity )\n +0.0\n > var y = base.csch( -Infinity )\n -0.0\n > y = base.csch( 2.0 )\n ~0.2757\n > y = base.csch( -2.0 )\n ~-0.2757\n > y = base.csch( NaN )\n NaN\n\n See Also\n --------\n base.acsch, base.coth, base.sinh\n","base.csignum":"\nbase.csignum( z )\n Evaluates the signum function of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.csignum( new Complex128( -4.2, 5.5 ) )\n \n > var re = real( v )\n -0.6069136033622302\n > var im = imag( v )\n 0.79476781392673\n\n See Also\n --------\n base.signum\n","base.csub":"\nbase.csub( z1, z2 )\n Subtracts two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( 5.0, 3.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var out = base.csub( z1, z2 )\n \n > var re = real( out )\n 7.0\n > var im = imag( out )\n 2.0\n\n See Also\n --------\n base.cadd, base.cdiv, base.cmul\n","base.csubf":"\nbase.csubf( z1, z2 )\n Subtracts two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z1 = new Complex64( 5.0, 3.0 )\n \n > var z2 = new Complex64( -2.0, 1.0 )\n \n > var out = base.csubf( z1, z2 )\n \n > var re = realf( out )\n 7.0\n > var im = imagf( out )\n 2.0\n\n See Also\n --------\n base.caddf, base.cmulf, base.csub\n","base.deg2rad":"\nbase.deg2rad( x )\n Converts an angle from degrees to radians.\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2rad( 90.0 )\n ~1.571\n > r = base.deg2rad( -45.0 )\n ~-0.785\n > r = base.deg2rad( NaN )\n NaN\n\n See Also\n --------\n base.rad2deg\n","base.deg2radf":"\nbase.deg2radf( x )\n Converts an angle from degrees to radians (single-precision).\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2radf( 90.0 )\n ~1.571\n > r = base.deg2radf( -45.0 )\n ~-0.785\n > r = base.deg2radf( NaN )\n NaN\n\n See Also\n --------\n base.deg2rad\n","base.digamma":"\nbase.digamma( x )\n Evaluates the digamma function.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.digamma( -2.5 )\n ~1.103\n > y = base.digamma( 1.0 )\n ~-0.577\n > y = base.digamma( 10.0 )\n ~2.252\n > y = base.digamma( NaN )\n NaN\n > y = base.digamma( -1.0 )\n NaN\n\n See Also\n --------\n base.gamma, base.trigamma\n","base.diracDelta":"\nbase.diracDelta( x )\n Evaluates the Dirac delta function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.diracDelta( 3.14 )\n 0.0\n > y = base.diracDelta( 0.0 )\n Infinity\n\n See Also\n --------\n base.kroneckerDelta\n","base.div":"\nbase.div( x, y )\n Divides two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value (dividend).\n\n y: number\n Second input value (divisor).\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.div( -1.0, 5.0 )\n -0.2\n > v = base.div( 2.0, 5.0 )\n 0.4\n > v = base.div( 0.0, 5.0 )\n 0.0\n > v = base.div( -0.0, 5.0 )\n -0.0\n > v = base.div( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.mul, base.sub\n","base.divf":"\nbase.divf( x, y )\n Divides two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value (dividend).\n\n y: number\n Second input value (divisor).\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.divf( -1.0, 5.0 )\n ~-0.2\n > v = base.divf( 2.0, 5.0 )\n ~0.4\n > v = base.divf( 0.0, 5.0 )\n 0.0\n > v = base.divf( -0.0, 5.0 )\n -0.0\n > v = base.divf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.div, base.mulf, base.subf\n","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a, b] )\n Returns an arcsine distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be less than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n arcsine: Object\n Distribution instance.\n\n arcsine.a: number\n Minimum support. If set, the value must be less than `b`.\n\n arcsine.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n arcsine.entropy: number\n Read-only property which returns the differential entropy.\n\n arcsine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n arcsine.mean: number\n Read-only property which returns the expected value.\n\n arcsine.median: number\n Read-only property which returns the median.\n\n arcsine.mode: number\n Read-only property which returns the mode.\n\n arcsine.skewness: number\n Read-only property which returns the skewness.\n\n arcsine.stdev: number\n Read-only property which returns the standard deviation.\n\n arcsine.variance: number\n Read-only property which returns the variance.\n\n arcsine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n arcsine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n arcsine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n arcsine.pdf: Function\n Evaluates the probability density function (PDF).\n\n arcsine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\n > arcsine.a\n 0.0\n > arcsine.b\n 1.0\n > arcsine.entropy\n ~-0.242\n > arcsine.kurtosis\n -1.5\n > arcsine.mean\n 0.5\n > arcsine.median\n 0.5\n > arcsine.mode\n 0.0\n > arcsine.skewness\n 0.0\n > arcsine.stdev\n ~0.354\n > arcsine.variance\n 0.125\n > arcsine.cdf( 0.8 )\n ~0.705\n > arcsine.logcdf( 0.8 )\n ~-0.35\n > arcsine.logpdf( 0.4 )\n ~-0.431\n > arcsine.pdf( 0.8 )\n ~0.796\n > arcsine.quantile( 0.8 )\n ~0.905\n\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\n ~0.795\n > y = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\n ~0.333\n > y = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705\n\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a, b )\n Returns the differential entropy of an arcsine distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.arcsine.entropy( 0.0, 1.0 )\n ~-0.242\n > v = base.dists.arcsine.entropy( 4.0, 12.0 )\n ~1.838\n > v = base.dists.arcsine.entropy( 2.0, 8.0 )\n ~1.55\n\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a, b )\n Returns the excess kurtosis of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 4.0, 12.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n -1.5\n\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\n ~-0.229\n > y = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\n ~-1.1\n > y = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35\n\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\n ~-1.838\n > y = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\n ~-0.308\n > y = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity\n\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a, b )\n Returns the expected value of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.arcsine.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a, b )\n Returns the median of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.arcsine.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a, b )\n Returns the mode of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.arcsine.mode( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.mode( 4.0, 12.0 )\n 4.0\n > v = base.dists.arcsine.mode( 2.0, 8.0 )\n 2.0\n\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x, a, b )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\n ~0.159\n > y = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\n ~0.735\n > y = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n Infinity\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n Infinity\n > y = myPDF( 5.0 )\n 0.0","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p, a, b )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\n ~0.905\n > y = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\n ~5.0\n\n > y = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n ~3.618\n\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n ~3.618","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a, b )\n Returns the skewness of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.arcsine.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a, b )\n Returns the standard deviation of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.arcsine.stdev( 0.0, 1.0 )\n ~0.354\n > v = base.dists.arcsine.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.arcsine.stdev( 2.0, 8.0 )\n ~2.121\n\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a, b )\n Returns the variance of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.arcsine.variance( 0.0, 1.0 )\n ~0.125\n > v = base.dists.arcsine.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.variance( 2.0, 8.0 )\n ~4.5\n\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p] )\n Returns a Bernoulli distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n bernoulli: Object\n Distribution instance.\n\n bernoulli.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n bernoulli.entropy: number\n Read-only property which returns the differential entropy.\n\n bernoulli.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n bernoulli.mean: number\n Read-only property which returns the expected value.\n\n bernoulli.median: number\n Read-only property which returns the median.\n\n bernoulli.skewness: number\n Read-only property which returns the skewness.\n\n bernoulli.stdev: number\n Read-only property which returns the standard deviation.\n\n bernoulli.variance: number\n Read-only property which returns the variance.\n\n bernoulli.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n bernoulli.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n bernoulli.pmf: Function\n Evaluates the probability mass function (PMF).\n\n bernoulli.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\n > bernoulli.p\n 0.6\n > bernoulli.entropy\n ~0.673\n > bernoulli.kurtosis\n ~-1.833\n > bernoulli.mean\n 0.6\n > bernoulli.median\n 1.0\n > bernoulli.skewness\n ~-0.408\n > bernoulli.stdev\n ~0.49\n > bernoulli.variance\n ~0.24\n > bernoulli.cdf( 0.5 )\n 0.4\n > bernoulli.mgf( 3.0 )\n ~12.451\n > bernoulli.pmf( 0.0 )\n 0.4\n > bernoulli.quantile( 0.7 )\n 1.0\n\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\n 0.5\n > y = base.dists.bernoulli.cdf( 0.8, 0.1 )\n 0.9\n > y = base.dists.bernoulli.cdf( -1.0, 0.4 )\n 0.0\n > y = base.dists.bernoulli.cdf( 1.5, 0.4 )\n 1.0\n > y = base.dists.bernoulli.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.bernoulli.cdf( 0.0, NaN )\n NaN\n // Invalid probability:\n > y = base.dists.bernoulli.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.bernoulli.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 1.0\n > y = mycdf( 0.7 )\n 0.5\n\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 1.0\n > y = mycdf( 0.7 )\n 0.5","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.bernoulli.entropy( 0.1 )\n ~0.325\n > v = base.dists.bernoulli.entropy( 0.5 )\n ~0.693\n\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.bernoulli.kurtosis( 0.1 )\n ~5.111\n > v = base.dists.bernoulli.kurtosis( 0.5 )\n -2.0\n\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mean( 0.1 )\n 0.1\n > v = base.dists.bernoulli.mean( 0.5 )\n 0.5\n\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p )\n Returns the median of a Bernoulli distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.bernoulli.median( 0.1 )\n 0\n > v = base.dists.bernoulli.median( 0.8 )\n 1\n\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\n ~1.111\n > y = base.dists.bernoulli.mgf( 0.4, 0.5 )\n ~1.246\n > y = base.dists.bernoulli.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.bernoulli.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.855\n\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.855","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n\n For `p = 0.5`, the mode is either `0` or `1`. This implementation returns\n `0` for `p = 0.5`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mode( 0.1 )\n 0\n > v = base.dists.bernoulli.mode( 0.8 )\n 1\n\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x, p )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\n 0.3\n > y = base.dists.bernoulli.pmf( 0.0, 0.7 )\n 0.3\n > y = base.dists.bernoulli.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.bernoulli.pmf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.bernoulli.pmf( 0.0, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n > var y = mypmf( 1.0 )\n 0.5\n > y = mypmf( 0.0 )\n 0.5\n\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n > var y = mypmf( 1.0 )\n 0.5\n > y = mypmf( 0.0 )\n 0.5","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r, p )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\n 1\n > y = base.dists.bernoulli.quantile( 0.5, 0.4 )\n 0\n > y = base.dists.bernoulli.quantile( 0.9, 0.1 )\n 0\n\n > y = base.dists.bernoulli.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.bernoulli.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.bernoulli.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.quantile.factory( p )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 1\n > y = myquantile( 1.0 )\n 1\n\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 1\n > y = myquantile( 1.0 )\n 1","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.bernoulli.skewness( 0.1 )\n ~2.667\n > v = base.dists.bernoulli.skewness( 0.5 )\n 0.0\n\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.bernoulli.stdev( 0.1 )\n ~0.3\n > v = base.dists.bernoulli.stdev( 0.5 )\n 0.5\n\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.bernoulli.variance( 0.1 )\n ~0.09\n > v = base.dists.bernoulli.variance( 0.5 )\n 0.25\n\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α, β] )\n Returns a beta distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n beta: Object\n Distribution instance.\n\n beta.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n beta.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n beta.entropy: number\n Read-only property which returns the differential entropy.\n\n beta.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n beta.mean: number\n Read-only property which returns the expected value.\n\n beta.median: number\n Read-only property which returns the median.\n\n beta.mode: number\n Read-only property which returns the mode.\n\n beta.skewness: number\n Read-only property which returns the skewness.\n\n beta.stdev: number\n Read-only property which returns the standard deviation.\n\n beta.variance: number\n Read-only property which returns the variance.\n\n beta.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n beta.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n beta.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n beta.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n beta.pdf: Function\n Evaluates the probability density function (PDF).\n\n beta.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var beta = base.dists.beta.Beta( 1.0, 1.0 );\n > beta.alpha\n 1.0\n > beta.beta\n 1.0\n > beta.entropy\n 0.0\n > beta.kurtosis\n -1.2\n > beta.mean\n 0.5\n > beta.median\n 0.5\n > beta.mode\n NaN\n > beta.skewness\n 0.0\n > beta.stdev\n ~0.289\n > beta.variance\n ~0.0833\n > beta.cdf( 0.8 )\n 0.8\n > beta.logcdf( 0.8 )\n ~-0.223\n > beta.logpdf( 1.0 )\n 0.0\n > beta.mgf( 3.14 )\n ~7.0394\n > beta.pdf( 1.0 )\n 1.0\n > beta.quantile( 0.8 )\n 0.8\n\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\n ~0.813\n > y = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\n ~0.104\n > y = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\n ~0.967\n > y = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.705\n > y = mycdf( 0.3 )\n ~0.369\n\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.705\n > y = mycdf( 0.3 )\n ~0.369","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α, β )\n Returns the differential entropy of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.beta.entropy( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.entropy( 4.0, 12.0 )\n ~-0.869\n > v = base.dists.beta.entropy( 8.0, 2.0 )\n ~-0.795\n\n > v = base.dists.beta.entropy( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.entropy( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.entropy( 2.0, NaN )\n NaN\n > v = base.dists.beta.entropy( NaN, 2.0 )\n NaN\n\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α, β )\n Returns the excess kurtosis of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.beta.kurtosis( 1.0, 1.0 )\n -1.2\n > v = base.dists.beta.kurtosis( 4.0, 12.0 )\n ~0.082\n > v = base.dists.beta.kurtosis( 8.0, 2.0 )\n ~0.490\n\n > v = base.dists.beta.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.kurtosis( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.beta.kurtosis( NaN, 2.0 )\n NaN\n\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\n ~-0.208\n > y = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\n ~-2.263\n > y = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\n ~-0.034\n > y = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.35\n > y = mylogcdf( 0.3 )\n ~-0.997\n\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.35\n > y = mylogcdf( 0.3 )\n ~-0.997","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\n ~0.223\n > y = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\n ~-0.041\n > y = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\n ~-0.556\n > y = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-0.228\n > y = mylogpdf( 0.3 )\n ~-0.364\n\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-0.228\n > y = mylogpdf( 0.3 )\n ~-0.364","base.dists.beta.mean":"\nbase.dists.beta.mean( α, β )\n Returns the expected value of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.beta.mean( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.mean( 4.0, 12.0 )\n 0.25\n > v = base.dists.beta.mean( 8.0, 2.0 )\n 0.8\n\n","base.dists.beta.median":"\nbase.dists.beta.median( α, β )\n Returns the median of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.beta.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.median( 4.0, 12.0 )\n ~0.239\n > v = base.dists.beta.median( 8.0, 2.0 )\n ~0.820\n\n > v = base.dists.beta.median( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.median( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.median( 2.0, NaN )\n NaN\n > v = base.dists.beta.median( NaN, 2.0 )\n NaN\n\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\n ~1.297\n > y = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\n ~1.186\n > y = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\n ~5.575\n > y = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\n ~0.676\n\n > y = base.dists.beta.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n NaN\n\n\nbase.dists.beta.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n > var y = myMGF( 0.8 )\n ~1.552\n > y = myMGF( 0.3 )\n ~1.168\n\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n > var y = myMGF( 0.8 )\n ~1.552\n > y = myMGF( 0.3 )\n ~1.168","base.dists.beta.mode":"\nbase.dists.beta.mode( α, β )\n Returns the mode of a beta distribution.\n\n If `α <= 1` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.beta.mode( 4.0, 12.0 )\n ~0.214\n > v = base.dists.beta.mode( 8.0, 2.0 )\n ~0.875\n > v = base.dists.beta.mode( 1.0, 1.0 )\n NaN\n\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\n 1.25\n > y = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\n ~0.96\n > y = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\n ~0.573\n > y = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.796\n > y = mypdf( 0.3 )\n ~0.695\n\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.796\n > y = mypdf( 0.3 )\n ~0.695","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p, α, β )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\n ~0.894\n > y = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\n ~0.686\n > y = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.beta.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.beta.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n > y = myquantile( 0.8 )\n ~0.713\n > y = myquantile( 0.4 )\n ~0.433\n\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n > y = myquantile( 0.8 )\n ~0.713\n > y = myquantile( 0.4 )\n ~0.433","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α, β )\n Returns the skewness of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.beta.skewness( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.skewness( 4.0, 12.0 )\n ~0.529\n > v = base.dists.beta.skewness( 8.0, 2.0 )\n ~-0.829\n\n > v = base.dists.beta.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.skewness( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.skewness( 2.0, NaN )\n NaN\n > v = base.dists.beta.skewness( NaN, 2.0 )\n NaN\n\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α, β )\n Returns the standard deviation of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.beta.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.beta.stdev( 4.0, 12.0 )\n ~0.105\n > v = base.dists.beta.stdev( 8.0, 2.0 )\n ~0.121\n\n > v = base.dists.beta.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.stdev( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.stdev( 2.0, NaN )\n NaN\n > v = base.dists.beta.stdev( NaN, 2.0 )\n NaN\n\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α, β )\n Returns the variance of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.beta.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.beta.variance( 4.0, 12.0 )\n ~0.011\n > v = base.dists.beta.variance( 8.0, 2.0 )\n ~0.015\n\n > v = base.dists.beta.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.variance( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.variance( 2.0, NaN )\n NaN\n > v = base.dists.beta.variance( NaN, 2.0 )\n NaN\n\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α, β] )\n Returns a beta prime distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n betaprime: Object\n Distribution instance.\n\n betaprime.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n betaprime.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n betaprime.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n betaprime.mean: number\n Read-only property which returns the expected value.\n\n betaprime.mode: number\n Read-only property which returns the mode.\n\n betaprime.skewness: number\n Read-only property which returns the skewness.\n\n betaprime.stdev: number\n Read-only property which returns the standard deviation.\n\n betaprime.variance: number\n Read-only property which returns the variance.\n\n betaprime.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n betaprime.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n betaprime.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n betaprime.pdf: Function\n Evaluates the probability density function (PDF).\n\n betaprime.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\n > betaprime.alpha\n 6.0\n > betaprime.beta\n 5.0\n > betaprime.kurtosis\n 44.4\n > betaprime.mean\n 1.5\n > betaprime.mode\n ~0.833\n > betaprime.skewness\n ~3.578\n > betaprime.stdev\n ~1.118\n > betaprime.variance\n 1.25\n > betaprime.cdf( 0.8 )\n ~0.25\n > betaprime.logcdf( 0.8 )\n ~-1.387\n > betaprime.logpdf( 1.0 )\n ~-0.486\n > betaprime.pdf( 1.0 )\n ~0.615\n > betaprime.quantile( 0.8 )\n ~2.06\n\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\n ~0.333\n > y = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\n ~0.539\n > y = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\n ~0.074\n > y = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\n ~0.38\n > y = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.465\n > y = mycdf( 0.3 )\n ~0.319\n\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.465\n > y = mycdf( 0.3 )\n ~0.319","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α, β )\n Returns the excess kurtosis of a beta prime distribution.\n\n If `α <= 0` or `β <= 4`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\n ~26.143\n > v = base.dists.betaprime.kurtosis( 4.0, 12.0 )\n ~5.764\n > v = base.dists.betaprime.kurtosis( 8.0, 6.0 )\n ~19.962\n\n > v = base.dists.betaprime.kurtosis( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.kurtosis( -0.1, 5.0 )\n NaN\n\n > v = base.dists.betaprime.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.kurtosis( NaN, 6.0 )\n NaN\n\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\n ~-1.099\n > y = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\n ~-0.618\n > y = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\n ~-2.603\n > y = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\n ~-0.968\n > y = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.767\n > y = mylogcdf( 0.3 )\n ~-1.143\n\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.767\n > y = mylogcdf( 0.3 )\n ~-1.143","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\n ~-0.811\n > y = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\n ~-0.13\n > y = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\n ~-0.547\n > y = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\n ~-0.43\n > y = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-1.62\n > y = mylogpdf( 0.3 )\n ~-0.805\n\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-1.62\n > y = mylogpdf( 0.3 )\n ~-0.805","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α, β )\n Returns the expected value of a beta prime distribution.\n\n If `α <= 0` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.betaprime.mean( 1.0, 2.0 )\n 1.0\n > v = base.dists.betaprime.mean( 4.0, 12.0 )\n ~0.364\n > v = base.dists.betaprime.mean( 8.0, 2.0 )\n 8.0\n\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α, β )\n Returns the mode of a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.betaprime.mode( 1.0, 2.0 )\n 0.0\n > v = base.dists.betaprime.mode( 4.0, 12.0 )\n ~0.231\n > v = base.dists.betaprime.mode( 8.0, 2.0 )\n ~2.333\n\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\n ~0.444\n > y = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\n ~0.878\n > y = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\n ~0.579\n > y = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\n ~0.65\n > y = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.198\n > y = mypdf( 0.3 )\n ~0.447\n\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.198\n > y = mypdf( 0.3 )\n ~0.447","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p, α, β )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\n ~8.472\n > y = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\n ~2.187\n > y = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.betaprime.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n > y = myQuantile( 0.8 )\n ~2.483\n > y = myQuantile( 0.4 )\n ~0.763\n\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n > y = myQuantile( 0.8 )\n ~2.483\n > y = myQuantile( 0.4 )\n ~0.763","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α, β )\n Returns the skewness of a beta prime distribution.\n\n If `α <= 0` or `β <= 3`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.betaprime.skewness( 2.0, 4.0 )\n ~6.261\n > v = base.dists.betaprime.skewness( 4.0, 12.0 )\n ~1.724\n > v = base.dists.betaprime.skewness( 8.0, 4.0 )\n ~5.729\n\n > v = base.dists.betaprime.skewness( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.skewness( -0.1, 4.0 )\n NaN\n\n > v = base.dists.betaprime.skewness( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.skewness( NaN, 4.0 )\n NaN\n\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α, β )\n Returns the standard deviation of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.betaprime.stdev( 1.0, 2.5 )\n ~1.491\n > v = base.dists.betaprime.stdev( 4.0, 12.0 )\n ~0.223\n > v = base.dists.betaprime.stdev( 8.0, 2.5 )\n ~8.219\n\n > v = base.dists.betaprime.stdev( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.stdev( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.stdev( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.stdev( NaN, 3.0 )\n NaN\n\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α, β )\n Returns the variance of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.betaprime.variance( 1.0, 2.5 )\n ~2.222\n > v = base.dists.betaprime.variance( 4.0, 12.0 )\n ~0.05\n > v = base.dists.betaprime.variance( 8.0, 2.5 )\n ~67.556\n\n > v = base.dists.betaprime.variance( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.variance( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.variance( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.variance( NaN, 3.0 )\n NaN\n\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n, p] )\n Returns a binomial distribution object.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials. Must be a positive integer. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n binomial: Object\n Distribution instance.\n\n binomial.n: number\n Number of trials. If set, the value must be a positive integer.\n\n binomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n binomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n binomial.mean: number\n Read-only property which returns the expected value.\n\n binomial.median: number\n Read-only property which returns the median.\n\n binomial.mode: number\n Read-only property which returns the mode.\n\n binomial.skewness: number\n Read-only property which returns the skewness.\n\n binomial.stdev: number\n Read-only property which returns the standard deviation.\n\n binomial.variance: number\n Read-only property which returns the variance.\n\n binomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n binomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n binomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n binomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n binomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var binomial = base.dists.binomial.Binomial( 8, 0.5 );\n > binomial.n\n 8.0\n > binomial.p\n 0.5\n > binomial.kurtosis\n -0.25\n > binomial.mean\n 4.0\n > binomial.median\n 4.0\n > binomial.mode\n 4.0\n > binomial.skewness\n 0.0\n > binomial.stdev\n ~1.414\n > binomial.variance\n 2.0\n > binomial.cdf( 2.9 )\n ~0.145\n > binomial.logpmf( 3.0 )\n ~-1.52\n > binomial.mgf( 0.2 )\n ~2.316\n > binomial.pmf( 3.0 )\n ~0.219\n > binomial.quantile( 0.8 )\n 5.0\n\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x, n, p )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\n ~0.411\n > y = base.dists.binomial.cdf( 21.0, 20, 0.2 )\n 1.0\n > y = base.dists.binomial.cdf( 5.0, 10, 0.4 )\n ~0.834\n > y = base.dists.binomial.cdf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.cdf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.cdf.factory( n, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n > var y = mycdf( 3.0 )\n ~0.172\n > y = mycdf( 1.0 )\n ~0.011\n\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n > var y = mycdf( 3.0 )\n ~0.172\n > y = mycdf( 1.0 )\n ~0.011","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n, p )\n Returns the entropy of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.binomial.entropy( 100, 0.1 )\n ~2.511\n > v = base.dists.binomial.entropy( 20, 0.5 )\n ~2.223\n > v = base.dists.binomial.entropy( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.entropy( 20, 1.1 )\n NaN\n > v = base.dists.binomial.entropy( 20, NaN )\n NaN\n\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n, p )\n Returns the excess kurtosis of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.binomial.kurtosis( 100, 0.1 )\n ~0.051\n > v = base.dists.binomial.kurtosis( 20, 0.5 )\n ~-0.1\n > v = base.dists.binomial.kurtosis( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, 1.1 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, NaN )\n NaN\n\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x, n, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\n ~-1.583\n > y = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\n -Infinity\n > y = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\n ~-1.606\n > y = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\n ~-5.108\n > y = base.dists.binomial.logpmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.logpmf.factory( n, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.144\n > y = mylogpmf( 5.0 )\n ~-1.402\n\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.144\n > y = mylogpmf( 5.0 )\n ~-1.402","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n, p )\n Returns the expected value of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.binomial.mean( 100, 0.1 )\n 10.0\n > v = base.dists.binomial.mean( 20, 0.5 )\n 10.0\n > v = base.dists.binomial.mean( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mean( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mean( 20, NaN )\n NaN\n\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n, p )\n Returns the median of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.binomial.median( 100, 0.1 )\n 10\n > v = base.dists.binomial.median( 20, 0.5 )\n 10\n > v = base.dists.binomial.median( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.median( 20, 1.1 )\n NaN\n > v = base.dists.binomial.median( 20, NaN )\n NaN\n\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t, n, p )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\n ~11.471\n > y = base.dists.binomial.mgf( 5.0, 20, 0.2 )\n ~4.798e+29\n > y = base.dists.binomial.mgf( 0.9, 10, 0.4 )\n ~99.338\n > y = base.dists.binomial.mgf( 0.0, 10, 0.4 )\n 1.0\n\n > y = base.dists.binomial.mgf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, 20, NaN )\n NaN\n\n > y = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.mgf.factory( n, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n > var y = myMGF( 0.3 )\n ~5.013\n\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n > var y = myMGF( 0.3 )\n ~5.013","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n, p )\n Returns the mode of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.binomial.mode( 100, 0.1 )\n 10\n > v = base.dists.binomial.mode( 20, 0.5 )\n 10\n > v = base.dists.binomial.mode( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mode( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mode( 20, NaN )\n NaN\n\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x, n, p )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\n ~0.205\n > y = base.dists.binomial.pmf( 21.0, 20, 0.2 )\n 0.0\n > y = base.dists.binomial.pmf( 5.0, 10, 0.4 )\n ~0.201\n > y = base.dists.binomial.pmf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.pmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.pmf.factory( n, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n > var y = mypmf( 3.0 )\n ~0.117\n > y = mypmf( 5.0 )\n ~0.246\n\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n > var y = mypmf( 3.0 )\n ~0.117\n > y = mypmf( 5.0 )\n ~0.246","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r, n, p )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\n 3\n > y = base.dists.binomial.quantile( 0.8, 20, 0.2 )\n 5\n > y = base.dists.binomial.quantile( 0.5, 10, 0.4 )\n 4\n > y = base.dists.binomial.quantile( 0.0, 10, 0.4 )\n 0\n > y = base.dists.binomial.quantile( 1.0, 10, 0.4 )\n 10\n\n > y = base.dists.binomial.quantile( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, 20, NaN )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 20, -1.0 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.quantile.factory( n, p )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n > var y = myquantile( 0.1 )\n 3\n > y = myquantile( 0.9 )\n 7\n\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n, p )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n > var y = myquantile( 0.1 )\n 3\n > y = myquantile( 0.9 )\n 7","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n, p )\n Returns the skewness of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.binomial.skewness( 100, 0.1 )\n ~0.267\n > v = base.dists.binomial.skewness( 20, 0.5 )\n 0.0\n > v = base.dists.binomial.skewness( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.skewness( 20, 1.1 )\n NaN\n > v = base.dists.binomial.skewness( 20, NaN )\n NaN\n\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n, p )\n Returns the standard deviation of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.binomial.stdev( 100, 0.1 )\n 3.0\n > v = base.dists.binomial.stdev( 20, 0.5 )\n ~2.236\n > v = base.dists.binomial.stdev( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.stdev( 20, 1.1 )\n NaN\n > v = base.dists.binomial.stdev( 20, NaN )\n NaN\n\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n, p )\n Returns the variance of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.binomial.variance( 100, 0.1 )\n 9\n > v = base.dists.binomial.variance( 20, 0.5 )\n 5\n > v = base.dists.binomial.variance( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.variance( 20, 1.1 )\n NaN\n > v = base.dists.binomial.variance( 20, NaN )\n NaN\n\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0, Ɣ] )\n Returns a Cauchy distribution object.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter. Default: `0.0`.\n\n Ɣ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cauchy: Object\n Distribution instance.\n\n cauchy.x0: number\n Location parameter.\n\n cauchy.gamma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cauchy.entropy: number\n Read-only property which returns the differential entropy.\n\n cauchy.median: number\n Read-only property which returns the median.\n\n cauchy.mode: number\n Read-only property which returns the mode.\n\n cauchy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cauchy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cauchy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cauchy.pdf: Function\n Evaluates the probability density function (PDF).\n\n cauchy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\n > cauchy.x0\n 0.0\n > cauchy.gamma\n 1.0\n > cauchy.entropy\n ~2.531\n > cauchy.median\n 0.0\n > cauchy.mode\n 0.0\n > cauchy.cdf( 0.8 )\n ~0.715\n > cauchy.logcdf( 1.0 )\n ~-0.288\n > cauchy.logpdf( 1.0 )\n ~-1.838\n > cauchy.pdf( 1.0 )\n ~0.159\n > cauchy.quantile( 0.8 )\n ~1.376\n\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x, x0, Ɣ )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\n ~0.852\n > y = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\n ~0.648\n > y = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\n 0.25\n > y = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n > var y = myCDF( 1.0 )\n ~0.447\n\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n > var y = myCDF( 1.0 )\n ~0.447","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0, Ɣ )\n Returns the differential entropy of a Cauchy distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.cauchy.entropy( 10.0, 7.0 )\n ~4.477\n > v = base.dists.cauchy.entropy( 22.0, 0.5 )\n ~1.838\n > v = base.dists.cauchy.entropy( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\n ~-0.16\n > y = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\n ~-0.435\n > y = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\n ~-1.386\n > y = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of CDF.\n\n Examples\n --------\n > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n > var y = mylogCDF( 1.0 )\n ~-0.804\n\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of CDF.\n\n Examples\n --------\n > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n > var y = mylogCDF( 1.0 )\n ~-0.804","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\n ~-1.838\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\n ~-3.457\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\n ~-2.349\n > y = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.838\n\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.838","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0, Ɣ )\n Returns the median of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.cauchy.median( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.median( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.median( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0, Ɣ )\n Returns the mode of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.cauchy.mode( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.mode( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.mode( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x, x0, Ɣ )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\n ~0.159\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\n ~0.0315\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\n ~0.095\n > y = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.159\n\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.159","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p, x0, Ɣ )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\n ~0.547\n > y = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\n ~12.753\n > y = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\n ~3.845\n\n > y = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chi.cdf( 2.0, 3.0 )\n ~0.739\n > y = base.dists.chi.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chi.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chi.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chi.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chi.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chi.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chi.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.954\n > y = mycdf( 1.2 )\n ~0.77\n\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.954\n > y = mycdf( 1.2 )\n ~0.77","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k] )\n Returns a chi distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chi: Object\n Distribution instance.\n\n chi.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chi.entropy: number\n Read-only property which returns the differential entropy.\n\n chi.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chi.mean: number\n Read-only property which returns the expected value.\n\n chi.mode: number\n Read-only property which returns the mode.\n\n chi.skewness: number\n Read-only property which returns the skewness.\n\n chi.stdev: number\n Read-only property which returns the standard deviation.\n\n chi.variance: number\n Read-only property which returns the variance.\n\n chi.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chi.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n chi.pdf: Function\n Evaluates the probability density function (PDF).\n\n chi.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chi = base.dists.chi.Chi( 6.0 );\n > chi.k\n 6.0\n > chi.entropy\n ~1.04\n > chi.kurtosis\n ~0.025\n > chi.mean\n ~2.35\n > chi.mode\n ~2.236\n > chi.skewness\n ~0.318\n > chi.stdev\n ~0.691\n > chi.variance\n ~0.478\n > chi.cdf( 1.0 )\n ~0.014\n > chi.logpdf( 1.5 )\n ~-1.177\n > chi.pdf( 1.5 )\n ~0.308\n > chi.quantile( 0.5 )\n ~2.313\n\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k )\n Returns the differential entropy of a chi distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chi.entropy( 11.0 )\n ~1.056\n > v = base.dists.chi.entropy( 1.5 )\n ~0.878\n\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k )\n Returns the excess kurtosis of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chi.kurtosis( 9.0 )\n ~0.011\n > v = base.dists.chi.kurtosis( 1.5 )\n ~0.424\n\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chi.logpdf( 0.3, 4.0 )\n ~-4.35\n > y = base.dists.chi.logpdf( 0.7, 0.7 )\n ~-0.622\n > y = base.dists.chi.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n > var y = mylogPDF( 3.0 )\n ~-1.086\n\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n > var y = mylogPDF( 3.0 )\n ~-1.086","base.dists.chi.mean":"\nbase.dists.chi.mean( k )\n Returns the expected value of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chi.mean( 11.0 )\n ~3.242\n > v = base.dists.chi.mean( 4.5 )\n ~2.008\n\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k )\n Returns the mode of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chi.mode( 11.0 )\n ~3.162\n > v = base.dists.chi.mode( 1.5 )\n ~0.707\n\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chi.pdf( 0.3, 4.0 )\n ~0.013\n > y = base.dists.chi.pdf( 0.7, 0.7 )\n ~0.537\n > y = base.dists.chi.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.337\n\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.337","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p, k )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chi.quantile( 0.8, 1.0 )\n ~1.282\n > y = base.dists.chi.quantile( 0.5, 4.0 )\n ~1.832\n > y = base.dists.chi.quantile( 0.8, 0.1 )\n ~0.116\n > y = base.dists.chi.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chi.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chi.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chi.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chi.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chi.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.845\n > y = myquantile( 0.7 )\n ~1.552\n\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.845\n > y = myquantile( 0.7 )\n ~1.552","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k )\n Returns the skewness of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chi.skewness( 11.0 )\n ~0.225\n > v = base.dists.chi.skewness( 1.5 )\n ~0.763\n\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k )\n Returns the standard deviation of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chi.stdev( 11.0 )\n ~0.699\n > v = base.dists.chi.stdev( 1.5 )\n ~0.637\n\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k )\n Returns the variance of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chi.variance( 11.0 )\n ~0.488\n > v = base.dists.chi.variance( 1.5 )\n ~0.406\n\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.cdf( 2.0, 3.0 )\n ~0.428\n > y = base.dists.chisquare.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chisquare.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chisquare.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chisquare.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chisquare.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chisquare.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.843\n > y = mycdf( 1.2 )\n ~0.727\n\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.843\n > y = mycdf( 1.2 )\n ~0.727","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k] )\n Returns a chi-squared distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chisquare: Object\n Distribution instance.\n\n chisquare.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chisquare.entropy: number\n Read-only property which returns the differential entropy.\n\n chisquare.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chisquare.mean: number\n Read-only property which returns the expected value.\n\n chisquare.median: number\n Read-only property which returns the median.\n\n chisquare.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n chisquare.mode: number\n Read-only property which returns the mode.\n\n chisquare.skewness: number\n Read-only property which returns the skewness.\n\n chisquare.stdev: number\n Read-only property which returns the standard deviation.\n\n chisquare.variance: number\n Read-only property which returns the variance.\n\n chisquare.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chisquare.pdf: Function\n Evaluates the probability density function (PDF).\n\n chisquare.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\n > chisquare.k\n 6.0\n > chisquare.entropy\n ~2.541\n > chisquare.kurtosis\n 2.0\n > chisquare.mean\n 6.0\n > chisquare.median\n ~5.348\n > chisquare.mode\n 4.0\n > chisquare.skewness\n ~1.155\n > chisquare.stdev\n ~3.464\n > chisquare.variance\n 12.0\n > chisquare.cdf( 3.0 )\n ~0.191\n > chisquare.mgf( 0.2 )\n ~4.63\n > chisquare.pdf( 1.5 )\n ~0.066\n > chisquare.quantile( 0.5 )\n ~5.348\n\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k )\n Returns the differential entropy of a chi-squared distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chisquare.entropy( 11.0 )\n ~2.901\n > v = base.dists.chisquare.entropy( 1.5 )\n ~1.375\n\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k )\n Returns the excess kurtosis of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chisquare.kurtosis( 9.0 )\n ~1.333\n > v = base.dists.chisquare.kurtosis( 1.5 )\n 8.0\n\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\n ~-2.74\n > y = base.dists.chisquare.logpdf( 0.7, 0.7 )\n ~-1.295\n > y = base.dists.chisquare.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n > var y = myLogPDF( 3.0 )\n ~-2.075\n\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n > var y = myLogPDF( 3.0 )\n ~-2.075","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k )\n Returns the expected value of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chisquare.mean( 11.0 )\n 11.0\n > v = base.dists.chisquare.mean( 4.5 )\n 4.5\n\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k )\n Returns the median of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var k = base.dists.chisquare.median( 9.0 )\n ~8.343\n > k = base.dists.chisquare.median( 2.0 )\n ~1.386\n\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t, k )\n Evaluates the moment-generating function (MGF) for a chi-squared\n distribution with degrees of freedom `k` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.chisquare.mgf( 0.4, 2 )\n ~5.0\n > y = base.dists.chisquare.mgf( -1.0, 5.0 )\n ~0.0642\n > y = base.dists.chisquare.mgf( 0.0, 10.0 )\n 1.0\n\n\nbase.dists.chisquare.mgf.factory( k )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n > var y = mymgf( 0.2 )\n ~1.291\n > y = mymgf( 0.4 )\n ~2.236\n\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n > var y = mymgf( 0.2 )\n ~1.291\n > y = mymgf( 0.4 )\n ~2.236","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k )\n Returns the mode of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chisquare.mode( 11.0 )\n 9.0\n > v = base.dists.chisquare.mode( 1.5 )\n 0.0\n\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.pdf( 0.3, 4.0 )\n ~0.065\n > y = base.dists.chisquare.pdf( 0.7, 0.7 )\n ~0.274\n > y = base.dists.chisquare.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.126\n\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.126","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p, k )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chisquare.quantile( 0.8, 1.0 )\n ~1.642\n > y = base.dists.chisquare.quantile( 0.5, 4.0 )\n ~3.357\n > y = base.dists.chisquare.quantile( 0.8, 0.1 )\n ~0.014\n > y = base.dists.chisquare.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chisquare.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chisquare.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.713\n > y = myquantile( 0.7 )\n ~2.408\n\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.713\n > y = myquantile( 0.7 )\n ~2.408","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k )\n Returns the skewness of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chisquare.skewness( 11.0 )\n ~0.853\n > v = base.dists.chisquare.skewness( 1.5 )\n ~2.309\n\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k )\n Returns the standard deviation of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chisquare.stdev( 11.0 )\n ~4.69\n > v = base.dists.chisquare.stdev( 1.5 )\n ~1.732\n\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k )\n Returns the variance of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chisquare.variance( 11.0 )\n 22.0\n > v = base.dists.chisquare.variance( 1.5 )\n 3.0\n\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\n ~0.971\n > y = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\n ~0.196\n\n > y = base.dists.cosine.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.cosine.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.9 )\n ~0.015\n\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.9 )\n ~0.015","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ, s] )\n Returns a raised cosine distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cosine: Object\n Distribution instance.\n\n cosine.mu: number\n Location parameter.\n\n cosine.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cosine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n cosine.mean: number\n Read-only property which returns the expected value.\n\n cosine.median: number\n Read-only property which returns the median.\n\n cosine.mode: number\n Read-only property which returns the mode.\n\n cosine.skewness: number\n Read-only property which returns the skewness.\n\n cosine.stdev: number\n Read-only property which returns the standard deviation.\n\n cosine.variance: number\n Read-only property which returns the variance.\n\n cosine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cosine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cosine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cosine.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n cosine.pdf: Function\n Evaluates the probability density function (PDF).\n\n cosine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\n > cosine.mu\n -2.0\n > cosine.s\n 3.0\n > cosine.kurtosis\n ~-0.594\n > cosine.mean\n -2.0\n > cosine.median\n -2.0\n > cosine.mode\n -2.0\n > cosine.skewness\n 0.0\n > cosine.stdev\n ~1.085\n > cosine.variance\n ~1.176\n > cosine.cdf( 0.5 )\n ~0.996\n > cosine.logcdf( 0.5 )\n ~-0.004\n > cosine.logpdf( -1.0 )\n ~-1.386\n > cosine.mgf( 0.2 )\n ~0.686\n > cosine.pdf( -2.0 )\n ~0.333\n > cosine.quantile( 0.9 )\n ~-0.553\n\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ, s )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( 4.0, 2.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x, μ, s )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\n ~-0.029\n > y = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\n ~-1.632\n\n > y = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n 0.0\n\n\nbase.dists.cosine.logcdf.factory( μ, s )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.9 )\n ~-4.2\n\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ, s )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.9 )\n ~-4.2","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\n ~-2.485\n > y = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\n ~-3.307\n > y = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-0.693\n\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-0.693","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ, s )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.cosine.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mean( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mean( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ, s )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.cosine.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.median( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.median( 0.0, NaN )\n NaN\n > y = base.dists.cosine.median( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\n ~7.234\n > y = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\n ~1.606e+47\n\n > y = base.dists.cosine.mgf( 0.5, 0.0, NaN )\n NaN\n > y = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.cosine.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n > var y = mymgf( 1.9 )\n ~495.57\n\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n > var y = mymgf( 1.9 )\n ~495.57","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ, s )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.cosine.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mode( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mode( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\n ~0.083\n > y = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\n ~0.048\n > y = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n > var y = myPDF( 2.0 )\n ~0.083\n\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n > var y = myPDF( 2.0 )\n ~0.083","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p, μ, s )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\n ~0.327\n > y = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\n ~4.0\n\n > y = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cosine.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.3 )\n ~9.586\n\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.3 )\n ~9.586","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ, s )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.cosine.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.cosine.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.skewness( 0.0, NaN )\n NaN\n > y = base.dists.cosine.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ, s )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.cosine.stdev( 0.0, 1.0 )\n ~0.362\n > y = base.dists.cosine.stdev( 4.0, 2.0 )\n ~0.723\n > y = base.dists.cosine.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.stdev( 0.0, NaN )\n NaN\n > y = base.dists.cosine.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ, s )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.cosine.variance( 0.0, 1.0 )\n ~0.131\n > y = base.dists.cosine.variance( 4.0, 2.0 )\n ~0.523\n > y = base.dists.cosine.variance( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.variance( 0.0, NaN )\n NaN\n > y = base.dists.cosine.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x, μ )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.cdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.cdf( 4.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.cdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.cdf.factory( μ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n > var y = myCDF( 3.0 )\n 0.0\n > y = myCDF( 6.0 )\n 1.0\n\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n > var y = myCDF( 3.0 )\n 0.0\n > y = myCDF( 6.0 )\n 1.0","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ] )\n Returns a degenerate distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Constant value of distribution.\n\n Returns\n -------\n degenerate: Object\n Distribution instance.\n\n degenerate.mu: number\n Constant value of distribution.\n\n degenerate.entropy: number\n Read-only property which returns the differential entropy.\n\n degenerate.mean: number\n Read-only property which returns the expected value.\n\n degenerate.median: number\n Read-only property which returns the median.\n\n degenerate.stdev: number\n Read-only property which returns the standard deviation.\n\n degenerate.variance: number\n Read-only property which returns the variance.\n\n degenerate.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n degenerate.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n degenerate.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n degenerate.logpmf: Function\n Evaluates the natural logarithm of the probability mass function\n (PMF).\n\n degenerate.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n degenerate.pmf: Function\n Evaluates the probability mass function (PMF).\n\n degenerate.pdf: Function\n Evaluates the probability density function (PDF).\n\n degenerate.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var degenerate = base.dists.degenerate.Degenerate( 2.0 );\n > degenerate.mu\n 2.0\n > degenerate.entropy\n 0.0\n > degenerate.mean\n 2.0\n > degenerate.mode\n 2.0\n > degenerate.median\n 2.0\n > degenerate.stdev\n 0.0\n > degenerate.variance\n 0.0\n > degenerate.cdf( 0.5 )\n 0.0\n > degenerate.logcdf( 2.5 )\n 0.0\n > degenerate.logpdf( 0.5 )\n -Infinity\n > degenerate.logpmf( 2.5 )\n -Infinity\n > degenerate.mgf( 0.2 )\n ~1.492\n > degenerate.pdf( 2.0 )\n +Infinity\n > degenerate.pmf( 2.0 )\n 1.0\n > degenerate.quantile( 0.7 )\n 2.0\n\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.degenerate.entropy( 20.0 )\n 0.0\n > v = base.dists.degenerate.entropy( -10.0 )\n 0.0\n\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x, μ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logcdf( 4.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( 3.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logcdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logcdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of cumulative distribution\n function (logCDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n > var y = mylogcdf( 3.0 )\n -Infinity\n > y = mylogcdf( 6.0 )\n 0\n\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of cumulative distribution\n function (logCDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n > var y = mylogcdf( 3.0 )\n -Infinity\n > y = mylogcdf( 6.0 )\n 0","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x, μ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.logpdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n > var y = mylogPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n > var y = mylogPDF( 10.0 )\n Infinity","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x, μ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpmf( 3.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.logpmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpmf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n > var y = mylogPMF( 10.0 )\n 0.0\n\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n > var y = mylogPMF( 10.0 )\n 0.0","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.degenerate.mean( 20.0 )\n 20.0\n > v = base.dists.degenerate.mean( -10.0 )\n -10.0\n\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ )\n Returns the median of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.degenerate.median( 20.0 )\n 20.0\n > v = base.dists.degenerate.median( -10.0 )\n -10.0\n\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x, μ )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.degenerate.mgf( 1.0, 1.0 )\n ~2.718\n > y = base.dists.degenerate.mgf( 2.0, 3.0 )\n ~403.429\n > y = base.dists.degenerate.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.mgf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.mgf.factory( μ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n > var y = myMGF( 0.1 )\n ~2.718\n\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n > var y = myMGF( 0.1 )\n ~2.718","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ )\n Returns the mode of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.degenerate.mode( 20.0 )\n 20.0\n > v = base.dists.degenerate.mode( -10.0 )\n -10.0\n\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x, μ )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.pdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pdf.factory( μ )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n > var y = myPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n > var y = myPDF( 10.0 )\n Infinity","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x, μ )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pmf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pmf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.pmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pmf.factory( μ )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n > var y = myPMF( 10.0 )\n 1.0\n\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n > var y = myPMF( 10.0 )\n 1.0","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p, μ )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.degenerate.quantile( 0.5, 2.0 )\n 2.0\n > y = base.dists.degenerate.quantile( 0.9, 4.0 )\n 4.0\n > y = base.dists.degenerate.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( -0.2, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.degenerate.stdev( 20.0 )\n 0.0\n > v = base.dists.degenerate.stdev( -10.0 )\n 0.0\n\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ )\n Returns the variance of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.degenerate.variance( 20.0 )\n 0.0\n > v = base.dists.degenerate.variance( -10.0 )\n 0.0\n\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\n ~0.909\n > y = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\n ~0.333\n > y = base.dists.discreteUniform.cdf( PINF, 2, 4 )\n 1.0\n > y = base.dists.discreteUniform.cdf( NINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.cdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818\n\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a, b] )\n Returns a discrete uniform distribution object.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support. Must be an integer smaller than `b`. Default: `0`.\n\n b: integer (optional)\n Maximum support. Must be an integer greater than `a`. Default: `1`.\n\n Returns\n -------\n discreteUniform: Object\n Distribution instance.\n\n discreteUniform.a: integer\n Minimum support. If set, the value must be an integer smaller than or\n equal to `b`.\n\n discreteUniform.b: integer\n Maximum support. If set, the value must be an integer greater than or\n equal to `a`.\n\n discreteUniform.entropy: number\n Read-only property which returns the entropy.\n\n discreteUniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n discreteUniform.mean: number\n Read-only property which returns the expected value.\n\n discreteUniform.median: number\n Read-only property which returns the median.\n\n discreteUniform.skewness: number\n Read-only property which returns the skewness.\n\n discreteUniform.stdev: number\n Read-only property which returns the standard deviation.\n\n discreteUniform.variance: number\n Read-only property which returns the variance.\n\n discreteUniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n discreteUniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n discreteUniform.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n discreteUniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n discreteUniform.pmf: Function\n Evaluates the probability mass function (PMF).\n\n discreteUniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\n > discreteUniform.a\n -2\n > discreteUniform.b\n 2\n > discreteUniform.entropy\n ~1.609\n > discreteUniform.kurtosis\n -1.3\n > discreteUniform.mean\n 0.0\n > discreteUniform.median\n 0.0\n > discreteUniform.skewness\n 0.0\n > discreteUniform.stdev\n ~1.414\n > discreteUniform.variance\n 2.0\n > discreteUniform.cdf( 0.8 )\n 0.6\n > discreteUniform.logcdf( 0.5 )\n ~-0.511\n > discreteUniform.logpmf( 1.0 )\n ~-1.609\n > discreteUniform.mgf( 0.8 )\n ~1.766\n > discreteUniform.pmf( 0.0 )\n 0.2\n > discreteUniform.quantile( 0.8 )\n 2.0\n\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a, b )\n Returns the excess kurtosis of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.kurtosis( 0, 1 )\n -2.0\n > v = base.dists.discreteUniform.kurtosis( 4, 12 )\n ~-1.23\n > v = base.dists.discreteUniform.kurtosis( -4, 8 )\n ~-1.214\n\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\n ~-0.095\n > y = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\n ~-1.099\n > y = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201\n\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x, a, b )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\n ~-1.609\n > y = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\n ~-2.197\n > y = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity\n\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a, b )\n Returns the expected value of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.mean( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.mean( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.mean( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a, b )\n Returns the median of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.median( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.median( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.median( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\n ~689.475\n > y = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\n ~0.697\n > y = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\n ~4.195\n > y = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\n NaN\n > y = base.dists.discreteUniform.mgf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n NaN\n\n\nbase.dists.discreteUniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n > var y = mymgf( 0.1 )\n ~1.918\n > y = mymgf( 1.1 )\n ~1471.722\n\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n > var y = mymgf( 0.1 )\n ~1.918\n > y = mymgf( 1.1 )\n ~1471.722","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x, a, b )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\n ~0.2\n > y = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\n 0.0\n > y = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\n ~0.111\n > y = base.dists.discreteUniform.pmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.pmf.factory( a, b )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n > var y = myPMF( 7.0 )\n 0.5\n > y = myPMF( 5.0 )\n 0.0\n\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a, b )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n > var y = myPMF( 7.0 )\n 0.5\n > y = myPMF( 5.0 )\n 0.0","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p, a, b )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n If provided `a > b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\n 1\n > y = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\n 5\n\n > y = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\n NaN\n > y = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\n NaN\n\n > y = base.dists.discreteUniform.quantile( NaN, -2, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\n NaN\n\n > y = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n NaN\n\n\nbase.dists.discreteUniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n > var y = myQuantile( 0.8 )\n 4\n\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n > var y = myQuantile( 0.8 )\n 4","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a, b )\n Returns the skewness of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.skewness( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 4, 12 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 2, 8 )\n 0.0\n\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a, b )\n Returns the standard deviation of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.stdev( 0, 1 )\n ~0.5\n > v = base.dists.discreteUniform.stdev( 4, 12 )\n ~2.582\n > v = base.dists.discreteUniform.stdev( 2, 8 )\n 2.0\n\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a, b )\n Returns the variance of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.variance( 0, 1 )\n ~0.25\n > v = base.dists.discreteUniform.variance( 4, 12 )\n ~6.667\n > v = base.dists.discreteUniform.variance( 2, 8 )\n 4.0\n\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\n ~0.865\n > y = base.dists.erlang.cdf( 2.0, 3, 1.0 )\n ~0.323\n > y = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( -1.0, 2, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( PINF, 4, 2.0 )\n 1.0\n > y = base.dists.erlang.cdf( NINF, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( NaN, 0, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.erlang.cdf( 2.0, -1, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264\n\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k, λ )\n Returns the differential entropy of an Erlang distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.erlang.entropy( 1, 1.0 )\n ~1.0\n > v = base.dists.erlang.entropy( 4, 12.0 )\n ~-0.462\n > v = base.dists.erlang.entropy( 8, 2.0 )\n ~1.723\n\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k, λ] )\n Returns an Erlang distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be a positive integer. Default: `1.0`.\n\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n erlang: Object\n Distribution instance.\n\n erlang.k: number\n Shape parameter. If set, the value must be a positive integer.\n\n erlang.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n erlang.entropy: number\n Read-only property which returns the differential entropy.\n\n erlang.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n erlang.mean: number\n Read-only property which returns the expected value.\n\n erlang.mode: number\n Read-only property which returns the mode.\n\n erlang.skewness: number\n Read-only property which returns the skewness.\n\n erlang.stdev: number\n Read-only property which returns the standard deviation.\n\n erlang.variance: number\n Read-only property which returns the variance.\n\n erlang.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n erlang.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n erlang.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n erlang.pdf: Function\n Evaluates the probability density function (PDF).\n\n erlang.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var erlang = base.dists.erlang.Erlang( 6, 5.0 );\n > erlang.k\n 6\n > erlang.lambda\n 5.0\n > erlang.entropy\n ~0.647\n > erlang.kurtosis\n 1.0\n > erlang.mean\n 1.2\n > erlang.mode\n 1.0\n > erlang.skewness\n ~0.816\n > erlang.stdev\n ~0.49\n > erlang.variance\n 0.24\n > erlang.cdf( 3.0 )\n ~0.997\n > erlang.logpdf( 3.0 )\n ~-4.638\n > erlang.mgf( -0.5 )\n ~0.564\n > erlang.pdf( 3.0 )\n ~0.01\n > erlang.quantile( 0.8 )\n ~1.581\n\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k, λ )\n Returns the excess kurtosis of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.erlang.kurtosis( 1, 1.0 )\n 6.0\n > v = base.dists.erlang.kurtosis( 4, 12.0 )\n 1.5\n > v = base.dists.erlang.kurtosis( 8, 2.0 )\n 0.75\n\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x, k, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\n ~-0.1\n > y = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\n ~-0.111\n > y = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.logpdf.factory( k, λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n > y = myLogPDF( 7.0 )\n ~-32.382\n\n\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k, λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n > y = myLogPDF( 7.0 )\n ~-32.382","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k, λ )\n Returns the expected value of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.erlang.mean( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.mean( 4, 12.0 )\n ~0.333\n > v = base.dists.erlang.mean( 8, 2.0 )\n 4.0\n\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t, k, λ )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\n ~1.429\n > y = base.dists.erlang.mgf( 2.0, 2, 3.0 )\n ~9.0\n > y = base.dists.erlang.mgf( -1.0, 2, 2.0 )\n ~0.444\n\n > y = base.dists.erlang.mgf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, 1, NaN )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, -2, 0.5 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, 1, 0.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n NaN\n\n\nbase.dists.erlang.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n > var y = myMGF( 0.2 )\n ~2.778\n > y = myMGF( -0.5 )\n 0.25\n\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n > var y = myMGF( 0.2 )\n ~2.778\n > y = myMGF( -0.5 )\n 0.25","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k, λ )\n Returns the mode of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.erlang.mode( 1, 1.0 )\n 0.0\n > v = base.dists.erlang.mode( 4, 12.0 )\n 0.25\n > v = base.dists.erlang.mode( 8, 2.0 )\n 3.5\n\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\n ~0.905\n > y = base.dists.erlang.pdf( 0.5, 2, 2.5 )\n ~0.895\n > y = base.dists.erlang.pdf( -1.0, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.pdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.pdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n > y = myPDF( 7.0 )\n ~8.639e-15\n\n\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n > y = myPDF( 7.0 )\n ~8.639e-15","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p, k, λ )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive number for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\n ~2.994\n > y = base.dists.erlang.quantile( 0.5, 4, 2.0 )\n ~1.836\n\n > y = base.dists.erlang.quantile( 1.1, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( -0.2, 1, 1.0 )\n NaN\n\n > y = base.dists.erlang.quantile( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, 1, NaN )\n NaN\n\n // Non-integer shape parameter:\n > y = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\n NaN\n // Non-positive shape parameter:\n > y = base.dists.erlang.quantile( 0.5, -1, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n > var y = myQuantile( 0.4 )\n ~4.452\n\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n > var y = myQuantile( 0.4 )\n ~4.452","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k, λ )\n Returns the skewness of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.erlang.skewness( 1, 1.0 )\n 2.0\n > v = base.dists.erlang.skewness( 4, 12.0 )\n 1.0\n > v = base.dists.erlang.skewness( 8, 2.0 )\n ~0.707\n\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k, λ )\n Returns the standard deviation of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.erlang.stdev( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.stdev( 4, 12.0 )\n ~0.167\n > v = base.dists.erlang.stdev( 8, 2.0 )\n ~1.414\n\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k, λ )\n Returns the variance of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.erlang.variance( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.variance( 4, 12.0 )\n ~0.028\n > v = base.dists.erlang.variance( 8, 2.0 )\n 2.0\n\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.exponential.cdf( 2.0, 0.1 )\n ~0.181\n > y = base.dists.exponential.cdf( 1.0, 2.0 )\n ~0.865\n > y = base.dists.exponential.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.exponential.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.cdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.cdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n > var y = myCDF( 3.0 )\n ~0.777\n\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n > var y = myCDF( 3.0 )\n ~0.777","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ )\n Returns the differential entropy of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.exponential.entropy( 11.0 )\n ~-1.398\n > v = base.dists.exponential.entropy( 4.5 )\n ~-0.504\n\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ] )\n Returns an exponential distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n exponential: Object\n Distribution instance.\n\n exponential.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n exponential.entropy: number\n Read-only property which returns the differential entropy.\n\n exponential.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n exponential.mean: number\n Read-only property which returns the expected value.\n\n exponential.median: number\n Read-only property which returns the median.\n\n exponential.mode: number\n Read-only property which returns the mode.\n\n exponential.skewness: number\n Read-only property which returns the skewness.\n\n exponential.stdev: number\n Read-only property which returns the standard deviation.\n\n exponential.variance: number\n Read-only property which returns the variance.\n\n exponential.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n exponential.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n exponential.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n exponential.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n exponential.pdf: Function\n Evaluates the probability density function (PDF).\n\n exponential.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var exponential = base.dists.exponential.Exponential( 6.0 );\n > exponential.lambda\n 6.0\n > exponential.entropy\n ~-0.792\n > exponential.kurtosis\n 6.0\n > exponential.mean\n ~0.167\n > exponential.median\n ~0.116\n > exponential.mode\n 0.0\n > exponential.skewness\n 2.0\n > exponential.stdev\n ~0.167\n > exponential.variance\n ~0.028\n > exponential.cdf( 1.0 )\n ~0.998\n > exponential.logcdf( 1.0 )\n ~-0.002\n > exponential.logpdf( 1.5 )\n ~-7.208\n > exponential.mgf( -0.5 )\n ~0.923\n > exponential.pdf( 1.5 )\n ~0.001\n > exponential.quantile( 0.5 )\n ~0.116\n\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ )\n Returns the excess kurtosis of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.exponential.kurtosis( 11.0 )\n 6.0\n > v = base.dists.exponential.kurtosis( 4.5 )\n 6.0\n\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x, λ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logcdf( 2.0, 0.1 )\n ~-1.708\n > y = base.dists.exponential.logcdf( 1.0, 2.0 )\n ~-0.145\n > y = base.dists.exponential.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.exponential.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.logcdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.logcdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logcdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n > var y = mylogCDF( 3.0 )\n ~-0.252\n\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n > var y = mylogCDF( 3.0 )\n ~-0.252","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logpdf( 0.3, 4.0 )\n ~0.186\n > y = base.dists.exponential.logpdf( 2.0, 0.7 )\n ~-1.757\n > y = base.dists.exponential.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.exponential.logpdf( 0, NaN )\n NaN\n > y = base.dists.exponential.logpdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.logpdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logpdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n > var y = mylogpdf( 3.0 )\n ~-2.193\n\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n > var y = mylogpdf( 3.0 )\n ~-2.193","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ )\n Returns the expected value of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.exponential.mean( 11.0 )\n ~0.091\n > v = base.dists.exponential.mean( 4.5 )\n ~0.222\n\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ )\n Returns the median of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.exponential.median( 11.0 )\n ~0.063\n > v = base.dists.exponential.median( 4.5 )\n ~0.154\n\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t, λ )\n Evaluates the moment-generating function (MGF) for an exponential\n distribution with rate parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var v = base.dists.exponential.mgf( 2.0, 3.0 )\n 3.0\n > v = base.dists.exponential.mgf( 0.4, 1.2 )\n 1.5\n > v = base.dists.exponential.mgf( 0.8, 1.6 )\n 2.0\n > v = base.dists.exponential.mgf( 4.0, 3.0 )\n NaN\n > v = base.dists.exponential.mgf( NaN, 3.0 )\n NaN\n > v = base.dists.exponential.mgf( 2.0, NaN )\n NaN\n\n\nbase.dists.exponential.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n mg: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n > var y = myMGF( 3.0 )\n 4.0\n > y = myMGF( 0.5 )\n ~1.143\n\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n mg: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n > var y = myMGF( 3.0 )\n 4.0\n > y = myMGF( 0.5 )\n ~1.143","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ )\n Returns the mode of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.exponential.mode( 11.0 )\n 0.0\n > v = base.dists.exponential.mode( 4.5 )\n 0.0\n\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x, λ )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.exponential.pdf( 0.3, 4.0 )\n ~1.205\n > y = base.dists.exponential.pdf( 2.0, 0.7 )\n ~0.173\n > y = base.dists.exponential.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.exponential.pdf( 0, NaN )\n NaN\n > y = base.dists.exponential.pdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.pdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.pdf.factory( λ )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n > var y = myPDF( 3.0 )\n ~0.112\n\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n > var y = myPDF( 3.0 )\n ~0.112","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p, λ )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.exponential.quantile( 0.8, 1.0 )\n ~1.609\n > y = base.dists.exponential.quantile( 0.5, 4.0 )\n ~0.173\n > y = base.dists.exponential.quantile( 0.5, 0.1 )\n ~6.931\n\n > y = base.dists.exponential.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.exponential.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.quantile( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.exponential.quantile.factory( λ )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~1.277\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~1.277\n > y = myQuantile( 1.0 )\n Infinity","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ )\n Returns the skewness of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.exponential.skewness( 11.0 )\n 2.0\n > v = base.dists.exponential.skewness( 4.5 )\n 2.0\n\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ )\n Returns the standard deviation of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.exponential.stdev( 9.0 )\n ~0.11\n > v = base.dists.exponential.stdev( 1.0 )\n 1.0\n\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ )\n Returns the variance of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.exponential.variance( 9.0 )\n ~0.012\n > v = base.dists.exponential.variance( 1.0 )\n 1.0\n\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x, d1, d2 )\n Evaluates the cumulative distribution function (CDF) for an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\n ~0.608\n > var y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\n ~0.737\n > var y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > var y = base.dists.f.cdf( PINF, 4.0, 2.0 )\n 1.0\n > var y = base.dists.f.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > var y = base.dists.f.cdf( NaN, 1.0, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, NaN, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, 1.0, NaN )\n NaN\n\n > var y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\n NaN\n > var y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884\n\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884","base.dists.f.entropy":"\nbase.dists.f.entropy( d1, d2 )\n Returns the differential entropy of an F distribution (in nats).\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.f.entropy( 3.0, 7.0 )\n ~1.298\n > v = base.dists.f.entropy( 4.0, 12.0 )\n ~1.12\n > v = base.dists.f.entropy( 8.0, 2.0 )\n ~2.144\n\n","base.dists.f.F":"\nbase.dists.f.F( [d1, d2] )\n Returns an F distribution object.\n\n Parameters\n ----------\n d1: number (optional)\n Numerator degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n d2: number (optional)\n Denominator degrees of freedom. Must be greater than `0`.\n Default: `1.0`.\n\n Returns\n -------\n f: Object\n Distribution instance.\n\n f.d1: number\n Numerator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.d2: number\n Denominator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.entropy: number\n Read-only property which returns the differential entropy.\n\n f.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n f.mean: number\n Read-only property which returns the expected value.\n\n f.mode: number\n Read-only property which returns the mode.\n\n f.skewness: number\n Read-only property which returns the skewness.\n\n f.stdev: number\n Read-only property which returns the standard deviation.\n\n f.variance: number\n Read-only property which returns the variance.\n\n f.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n f.pdf: Function\n Evaluates the probability density function (PDF).\n\n f.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var f = base.dists.f.F( 6.0, 9.0 );\n > f.d1\n 6.0\n > f.d2\n 9.0\n > f.entropy\n ~1.134\n > f.kurtosis\n ~104.564\n > f.mean\n ~1.286\n > f.mode\n ~0.545\n > f.skewness\n ~4.535\n > f.stdev\n ~1.197\n > f.variance\n ~1.433\n > f.cdf( 3.0 )\n ~0.932\n > f.pdf( 2.5 )\n ~0.095\n > f.quantile( 0.8 )\n ~1.826\n\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1, d2 )\n Returns the excess kurtosis of an F distribution.\n\n If `d1 <= 0` or `d2 <= 8`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.f.kurtosis( 3.0, 9.0 )\n ~124.667\n > v = base.dists.f.kurtosis( 4.0, 12.0 )\n ~26.143\n > v = base.dists.f.kurtosis( 8.0, 9.0 )\n ~100.167\n\n","base.dists.f.mean":"\nbase.dists.f.mean( d1, d2 )\n Returns the expected value of an F distribution.\n\n If `d1 <= 0` or `d2 <= 2`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.f.mean( 3.0, 5.0 )\n ~1.667\n > v = base.dists.f.mean( 4.0, 12.0 )\n ~1.2\n > v = base.dists.f.mean( 8.0, 4.0 )\n 2.0\n\n","base.dists.f.mode":"\nbase.dists.f.mode( d1, d2 )\n Returns the mode of an F distribution.\n\n If `d1 <= 2` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.f.mode( 3.0, 5.0 )\n ~0.238\n > v = base.dists.f.mode( 4.0, 12.0 )\n ~0.429\n > v = base.dists.f.mode( 8.0, 4.0 )\n 0.5\n\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x, d1, d2 )\n Evaluates the probability density function (PDF) for an F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\n ~0.057\n > y = base.dists.f.pdf( 0.1, 1.0, 1.0 )\n ~0.915\n > y = base.dists.f.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.f.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.f.pdf( 2.0, 1.0, -1.0 )\n NaN\n > y = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.pdf.factory( d1, d2 )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n ~0.004\n > y = myPDF( 2.0 )\n ~0.166\n\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1, d2 )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n ~0.004\n > y = myPDF( 2.0 )\n ~0.166","base.dists.f.quantile":"\nbase.dists.f.quantile( p, d1, d2 )\n Evaluates the quantile function for an F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\n ~9.472\n > y = base.dists.f.quantile( 0.5, 4.0, 2.0 )\n ~1.207\n\n > y = base.dists.f.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.f.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.f.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.f.quantile.factory( d1, d2 )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~0.527\n > y = myQuantile( 0.8 )\n ~4.382\n\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1, d2 )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~0.527\n > y = myQuantile( 0.8 )\n ~4.382","base.dists.f.skewness":"\nbase.dists.f.skewness( d1, d2 )\n Returns the skewness of an F distribution.\n\n If `d1 <= 0` or `d2 <= 6`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.f.skewness( 3.0, 7.0 )\n 11.0\n > v = base.dists.f.skewness( 4.0, 12.0 )\n ~3.207\n > v = base.dists.f.skewness( 8.0, 7.0 )\n ~10.088\n\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1, d2 )\n Returns the standard deviation of an F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.f.stdev( 3.0, 5.0 )\n ~3.333\n > v = base.dists.f.stdev( 4.0, 12.0 )\n ~1.122\n > v = base.dists.f.stdev( 8.0, 5.0 )\n ~2.764\n\n","base.dists.f.variance":"\nbase.dists.f.variance( d1, d2 )\n Returns the variance of an F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.f.variance( 3.0, 5.0 )\n ~11.111\n > v = base.dists.f.variance( 4.0, 12.0 )\n ~1.26\n > v = base.dists.f.variance( 8.0, 5.0 )\n ~7.639\n\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x, α, s, m )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\n ~0.914\n > y = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\n ~0.105\n > y = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\n ~0.018\n > y = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.cdf.factory( α, s, m )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n > var y = myCDF( 10.0 )\n ~0.806\n > y = myCDF( 7.0 )\n ~0.034\n\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α, s, m )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n > var y = myCDF( 10.0 )\n ~0.806\n > y = myCDF( 7.0 )\n ~0.034","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α, s, m )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\n ~2.154\n > y = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\n ~1.028\n > y = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α, s, m] )\n Returns a Fréchet distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n m: number (optional)\n Location parameter. Default: `0.0`.\n\n Returns\n -------\n frechet: Object\n Distribution instance.\n\n frechet.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n frechet.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n frechet.m: number\n Location parameter.\n\n frechet.entropy: number\n Read-only property which returns the differential entropy.\n\n frechet.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n frechet.mean: number\n Read-only property which returns the expected value.\n\n frechet.median: number\n Read-only property which returns the median.\n\n frechet.mode: number\n Read-only property which returns the mode.\n\n frechet.skewness: number\n Read-only property which returns the skewness.\n\n frechet.stdev: number\n Read-only property which returns the standard deviation.\n\n frechet.variance: number\n Read-only property which returns the variance.\n\n frechet.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n frechet.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n frechet.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n frechet.pdf: Function\n Evaluates the probability density function (PDF).\n\n frechet.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\n > frechet.alpha\n 1.0\n > frechet.s\n 1.0\n > frechet.m\n 0.0\n > frechet.entropy\n ~2.154\n > frechet.kurtosis\n Infinity\n > frechet.mean\n Infinity\n > frechet.median\n ~1.443\n > frechet.mode\n 0.5\n > frechet.skewness\n Infinity\n > frechet.stdev\n Infinity\n > frechet.variance\n Infinity\n > frechet.cdf( 0.8 )\n ~0.287\n > frechet.logcdf( 0.8 )\n -1.25\n > frechet.logpdf( 0.8 )\n ~-0.804\n > frechet.pdf( 0.8 )\n ~0.448\n > frechet.quantile( 0.8 )\n ~4.481\n\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α, s, m )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 4` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\n ~45.092\n > var y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\n ~45.092\n > y = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x, α, s, m )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\n ~-0.09\n > y = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\n ~-2.25\n > y = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\n -4.0\n > y = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.logcdf.factory( α, s, m )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.216\n > y = mylogcdf( 7.0 )\n ~-3.375\n\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α, s, m )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.216\n > y = mylogcdf( 7.0 )\n ~-3.375","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x, α, s, m )\n Evaluates the logarithm of the probability density function (PDF) for a\n Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\n ~-2.72\n > y = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\n ~-1.901\n > y = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\n ~-0.307\n > y = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.logpdf.factory( α, s, m )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n > var y = mylogPDF( 10.0 )\n ~-3.812\n > y = mylogPDF( 2.0 )\n ~-6.11\n\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α, s, m )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n > var y = mylogPDF( 10.0 )\n ~-3.812\n > y = mylogPDF( 2.0 )\n ~-6.11","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α, s, m )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 1` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\n ~3.451\n > y = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.mean( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α, s, m )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\n ~3.192\n > var y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\n ~-0.808\n > y = base.dists.frechet.median( 0.5, 2.0, 1.0 )\n ~5.163\n > y = base.dists.frechet.median( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α, s, m )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\n ~2.891\n > var y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\n ~-1.109\n > y = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\n ~1.222\n > y = base.dists.frechet.mode( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x, α, s, m )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.pdf.factory( α, s, m )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n > var y = myPDF( 10.0 )\n ~0.933\n > y = myPDF( 2.0 )\n ~0.368\n\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α, s, m )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n > var y = myPDF( 10.0 )\n ~0.933\n > y = myPDF( 2.0 )\n ~0.368","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p, α, s, m )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\n ~4.963\n > y = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\n ~5.56\n > y = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\n ~6.491\n > y = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.quantile.factory( α, s, m )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~5.402\n > y = myQuantile( 0.2 )\n ~4.576\n\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α, s, m )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~5.402\n > y = myQuantile( 0.2 )\n ~4.576","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α, s, m )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 3` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\n ~5.605\n > var y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\n ~5.605\n > y = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α, s, m )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\n ~1.041\n > var y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\n ~1.041\n > y = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α, s, m )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\n ~1.083\n > var y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\n ~1.083\n > y = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.variance( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\n ~0.323\n > y = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0` when `α = 0.0`:\n > y = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264\n\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α, β )\n Returns the differential entropy of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.gamma.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.entropy( 4.0, 12.0 )\n ~-0.462\n > v = base.dists.gamma.entropy( 8.0, 2.0 )\n ~1.723\n\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α, β] )\n Returns a gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gamma: Object\n Distribution instance.\n\n gamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n gamma.beta: number\n Rate parameter. If set, the value must be greater than `0`.\n\n gamma.entropy: number\n Read-only property which returns the differential entropy.\n\n gamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gamma.mean: number\n Read-only property which returns the expected value.\n\n gamma.mode: number\n Read-only property which returns the mode.\n\n gamma.skewness: number\n Read-only property which returns the skewness.\n\n gamma.stdev: number\n Read-only property which returns the standard deviation.\n\n gamma.variance: number\n Read-only property which returns the variance.\n\n gamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gamma.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n gamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gamma.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n gamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\n > gamma.alpha\n 6.0\n > gamma.beta\n 5.0\n > gamma.entropy\n ~0.647\n > gamma.kurtosis\n 1.0\n > gamma.mean\n 1.2\n > gamma.mode\n 1.0\n > gamma.skewness\n ~0.816\n > gamma.stdev\n ~0.49\n > gamma.variance\n 0.24\n > gamma.cdf( 0.8 )\n ~0.215\n > gamma.logcdf( 0.8 )\n ~-1.538\n > gamma.logpdf( 1.0 )\n ~-0.131\n > gamma.mgf( -0.5 )\n ~0.564\n > gamma.pdf( 1.0 )\n ~0.877\n > gamma.quantile( 0.8 )\n ~1.581\n\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α, β )\n Returns the excess kurtosis of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.gamma.kurtosis( 4.0, 12.0 )\n 1.5\n > v = base.dists.gamma.kurtosis( 8.0, 2.0 )\n 0.75\n\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x, α, β )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\n ~-0.047\n > y = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\n ~-2.352\n > y = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.gamma.logcdf.factory( α, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n > var y = mylogCDF( 2.0 )\n ~-0.006\n\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n > var y = mylogCDF( 2.0 )\n ~-0.006","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x, α, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.919\n > y = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.logpdf.factory( α, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-3.646\n\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-3.646","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α, β )\n Returns the expected value of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.gamma.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.mean( 4.0, 12.0 )\n ~0.333\n > v = base.dists.gamma.mean( 8.0, 2.0 )\n 4.0\n\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\n ~1.414\n > y = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\n ~1.111\n > y = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\n ~0.198\n\n > y = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.gamma.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n > var y = myMGF( 1.0 )\n ~27.0\n > y = myMGF( 0.5 )\n ~3.375\n\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n > var y = myMGF( 1.0 )\n ~27.0\n > y = myMGF( 0.5 )\n ~3.375","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α, β )\n Returns the mode of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.gamma.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.gamma.mode( 4.0, 12.0 )\n 0.25\n > v = base.dists.gamma.mode( 8.0, 2.0 )\n 3.5\n\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\n ~0.054\n > y = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.026\n\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.026","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p, α, β )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\n ~2.994\n > y = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\n ~1.836\n\n > y = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~1.497\n > y = myQuantile( 0.4 )\n ~0.688\n\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~1.497\n > y = myQuantile( 0.4 )\n ~0.688","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α, β )\n Returns the skewness of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.gamma.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.gamma.skewness( 4.0, 12.0 )\n 1.0\n > v = base.dists.gamma.skewness( 8.0, 2.0 )\n ~0.707\n\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α, β )\n Returns the standard deviation of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.gamma.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.stdev( 4.0, 12.0 )\n ~0.167\n > v = base.dists.gamma.stdev( 8.0, 2.0 )\n ~1.414\n\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α, β )\n Returns the variance of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.gamma.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.variance( 4.0, 12.0 )\n ~0.028\n > v = base.dists.gamma.variance( 8.0, 2.0 )\n 2.0\n\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.geometric.cdf( 2.0, 0.5 )\n 0.875\n > y = base.dists.geometric.cdf( 2.0, 0.1 )\n ~0.271\n > y = base.dists.geometric.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.geometric.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.cdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 0.9375\n > y = mycdf( 1.0 )\n 0.75\n\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 0.9375\n > y = mycdf( 1.0 )\n 0.75","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.geometric.entropy( 0.1 )\n ~3.251\n > v = base.dists.geometric.entropy( 0.5 )\n ~1.386\n\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p] )\n Returns a geometric distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n geometric: Object\n Distribution instance.\n\n geometric.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n geometric.entropy: number\n Read-only property which returns the differential entropy.\n\n geometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n geometric.mean: number\n Read-only property which returns the expected value.\n\n geometric.median: number\n Read-only property which returns the median.\n\n geometric.mode: number\n Read-only property which returns the mode.\n\n geometric.skewness: number\n Read-only property which returns the skewness.\n\n geometric.stdev: number\n Read-only property which returns the standard deviation.\n\n geometric.variance: number\n Read-only property which returns the variance.\n\n geometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n geometric.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n geometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n geometric.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n geometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n geometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var geometric = base.dists.geometric.Geometric( 0.6 );\n > geometric.p\n 0.6\n > geometric.entropy\n ~1.122\n > geometric.kurtosis\n ~6.9\n > geometric.mean\n ~0.667\n > geometric.median\n 0.0\n > geometric.mode\n 0.0\n > geometric.skewness\n ~2.214\n > geometric.stdev\n ~1.054\n > geometric.variance\n ~1.111\n > geometric.cdf( 3.0 )\n ~0.974\n > geometric.logcdf( 3.0 )\n ~-0.026\n > geometric.logpmf( 4.0 )\n ~-4.176\n > geometric.mgf( 0.5 )\n ~2.905\n > geometric.pmf( 2.0 )\n ~0.096\n > geometric.quantile( 0.7 )\n 1.0\n\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.geometric.kurtosis( 0.1 )\n ~6.011\n > v = base.dists.geometric.kurtosis( 0.5 )\n 6.5\n\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x, p )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.geometric.logcdf( 2.0, 0.5 )\n ~-0.134\n > y = base.dists.geometric.logcdf( 2.0, 0.1 )\n ~-1.306\n > y = base.dists.geometric.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.geometric.logcdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.logcdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.logcdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.logcdf.factory( p )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.065\n > y = mylogcdf( 1.0 )\n ~-0.288\n\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.065\n > y = mylogcdf( 1.0 )\n ~-0.288","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x, p )\n Evaluates the logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.geometric.logpmf( 4.0, 0.3 )\n ~-2.631\n > y = base.dists.geometric.logpmf( 2.0, 0.7 )\n ~-2.765\n > y = base.dists.geometric.logpmf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.geometric.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.logpmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.logpmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.logpmf.factory( p )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.773\n > y = mylogpmf( 1.0 )\n ~-1.386\n\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.773\n > y = mylogpmf( 1.0 )\n ~-1.386","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.geometric.mean( 0.1 )\n 9.0\n > v = base.dists.geometric.mean( 0.5 )\n 1.0\n\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p )\n Returns the median of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.geometric.median( 0.1 )\n 6\n > v = base.dists.geometric.median( 0.5 )\n 0\n\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `t >= -ln(1-p)`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.geometric.mgf( 0.2, 0.5 )\n ~1.569\n > y = base.dists.geometric.mgf( 0.4, 0.5 )\n ~2.936\n // Case: t >= -ln(1-p)\n > y = base.dists.geometric.mgf( 0.8, 0.5 )\n NaN\n > y = base.dists.geometric.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.geometric.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.783\n\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.783","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p )\n Returns the mode of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.geometric.mode( 0.1 )\n 0\n > v = base.dists.geometric.mode( 0.5 )\n 0\n\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x, p )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.geometric.pmf( 4.0, 0.3 )\n ~0.072\n > y = base.dists.geometric.pmf( 2.0, 0.7 )\n ~0.063\n > y = base.dists.geometric.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.geometric.pmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.pmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n > var y = mypmf( 3.0 )\n 0.0625\n > y = mypmf( 1.0 )\n 0.25\n\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n > var y = mypmf( 3.0 )\n 0.0625\n > y = mypmf( 1.0 )\n 0.25","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r, p )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.geometric.quantile( 0.8, 0.4 )\n 3\n > y = base.dists.geometric.quantile( 0.5, 0.4 )\n 1\n > y = base.dists.geometric.quantile( 0.9, 0.1 )\n 21\n\n > y = base.dists.geometric.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.geometric.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.geometric.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.geometric.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.geometric.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.geometric.quantile.factory( p )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 3\n > y = myquantile( 1.0 )\n Infinity\n\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 3\n > y = myquantile( 1.0 )\n Infinity","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.geometric.skewness( 0.1 )\n ~2.003\n > v = base.dists.geometric.skewness( 0.5 )\n ~2.121\n\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.geometric.stdev( 0.1 )\n ~9.487\n > v = base.dists.geometric.stdev( 0.5 )\n ~1.414\n\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p )\n Returns the variance of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.geometric.variance( 0.1 )\n ~90.0\n > v = base.dists.geometric.variance( 0.5 )\n 2.0\n\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x, μ, β )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.cdf.factory( μ, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.933\n > y = myCDF( 2.0 )\n ~0.368\n\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.933\n > y = myCDF( 2.0 )\n ~0.368","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ, β )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.gumbel.entropy( 0.0, 1.0 )\n ~1.577\n > y = base.dists.gumbel.entropy( 4.0, 2.0 )\n ~2.27\n > y = base.dists.gumbel.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ, β] )\n Returns a Gumbel distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gumbel: Object\n Distribution instance.\n\n gumbel.mu: number\n Location parameter.\n\n gumbel.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n gumbel.entropy: number\n Read-only property which returns the differential entropy.\n\n gumbel.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gumbel.mean: number\n Read-only property which returns the expected value.\n\n gumbel.median: number\n Read-only property which returns the median.\n\n gumbel.mode: number\n Read-only property which returns the mode.\n\n gumbel.skewness: number\n Read-only property which returns the skewness.\n\n gumbel.stdev: number\n Read-only property which returns the standard deviation.\n\n gumbel.variance: number\n Read-only property which returns the variance.\n\n gumbel.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gumbel.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n gumbel.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gumbel.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gumbel.pdf: Function\n Evaluates the probability density function (PDF).\n\n gumbel.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\n > gumbel.mu\n -2.0\n > gumbel.beta\n 3.0\n > gumbel.entropy\n ~2.676\n > gumbel.kurtosis\n 2.4\n > gumbel.mean\n ~-0.268\n > gumbel.median\n ~-0.9\n > gumbel.mode\n -2.0\n > gumbel.skewness\n ~1.14\n > gumbel.stdev\n ~3.848\n > gumbel.variance\n ~14.804\n > gumbel.cdf( 0.8 )\n ~0.675\n > gumbel.logcdf( 0.8 )\n ~-0.393\n > gumbel.logpdf( 1.0 )\n ~-2.466\n > gumbel.mgf( 0.2 )\n ~1.487\n > gumbel.pdf( 1.0 )\n ~0.085\n > gumbel.quantile( 0.8 )\n ~2.5\n\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ, β )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( 4.0, 2.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x, μ, β )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\n ~-0.036\n > y = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\n ~-1.948\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\n ~-1.0\n > y = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logcdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n > var y = myLCDF( 10.0 )\n ~-0.069\n > y = myLCDF( 2.0 )\n ~-1.0\n\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n > var y = myLCDF( 10.0 )\n ~-0.069\n > y = myLCDF( 2.0 )\n ~-1.0","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x, μ, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\n ~-1.693\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\n ~-1\n > y = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\n ~-2.411\n > y = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logpdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-1.693\n > y = mylogpdf( 12.0 )\n ~-2.061\n\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-1.693\n > y = mylogpdf( 12.0 )\n ~-2.061","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ, β )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.gumbel.mean( 0.0, 1.0 )\n ~0.577\n > y = base.dists.gumbel.mean( 4.0, 2.0 )\n ~5.154\n > y = base.dists.gumbel.mean( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mean( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ, β )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.gumbel.median( 0.0, 1.0 )\n ~0.367\n > y = base.dists.gumbel.median( 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.median( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.median( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.median( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t, μ, β )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\n 6.0\n > y = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\n ~1.298\n\n > y = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\n NaN\n\n // Case: `t >= 1/beta`\n > y = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\n NaN\n\n // Non-positive scale parameter:\n > y = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.mgf.factory( μ, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n > var y = myMGF( -1.5 )\n ~52.343\n > y = myMGF( -1.0 )\n 6.0\n\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n > var y = myMGF( -1.5 )\n ~52.343\n > y = myMGF( -1.0 )\n 6.0","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ, β )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.gumbel.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.gumbel.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.gumbel.mode( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mode( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x, μ, β )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\n ~0.184\n > y = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\n ~0.09\n > y = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.pdf.factory( μ, β )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.184\n > y = myPDF( 12.0 )\n ~0.127\n\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ, β )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.184\n > y = myPDF( 12.0 )\n ~0.127","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p, μ, β )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\n ~1.5\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\n ~5.466\n\n > y = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.quantile.factory( μ, β )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~8.733\n > y = myQuantile( 0.7 )\n ~10.062\n\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ, β )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~8.733\n > y = myQuantile( 0.7 )\n ~10.062","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ, β )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.gumbel.skewness( 0.0, 1.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( 4.0, 2.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ, β )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.gumbel.stdev( 0.0, 1.0 )\n ~1.283\n > y = base.dists.gumbel.stdev( 4.0, 2.0 )\n ~2.565\n > y = base.dists.gumbel.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ, β )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.gumbel.variance( 0.0, 1.0 )\n ~1.645\n > y = base.dists.gumbel.variance( 4.0, 2.0 )\n ~6.58\n > y = base.dists.gumbel.variance( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.variance( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x, N, K, n )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceeds population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\n 1.0\n > y = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\n ~0.214\n\n > y = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n > var y = myCDF( 4.0 )\n ~0.891\n > y = myCDF( 1.0 )\n ~0.031\n\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n > var y = myCDF( 4.0 )\n ~0.891\n > y = myCDF( 1.0 )\n ~0.031","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N, K, n] )\n Returns a hypergeometric distribution object.\n\n Parameters\n ----------\n N: integer (optional)\n Population size. Must be a nonnegative integer larger than or equal to\n `K` and `n`.\n\n K: integer (optional)\n Subpopulation size. Must be a nonnegative integer smaller than or equal\n to `N`.\n\n n: integer (optional)\n Number of draws. Must be a nonnegative integer smaller than or equal to\n `N`.\n\n Returns\n -------\n hypergeometric: Object\n Distribution instance.\n\n hypergeometric.N: number\n Population size. If set, the value must be a nonnegative integer larger\n than or equal to `K` and `n`.\n\n hypergeometric.K: number\n Subpopulation size. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.n: number\n Number of draws. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n hypergeometric.mean: number\n Read-only property which returns the expected value.\n\n hypergeometric.mode: number\n Read-only property which returns the mode.\n\n hypergeometric.skewness: number\n Read-only property which returns the skewness.\n\n hypergeometric.stdev: number\n Read-only property which returns the standard deviation.\n\n hypergeometric.variance: number\n Read-only property which returns the variance.\n\n hypergeometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n hypergeometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n hypergeometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n hypergeometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\n > hypergeometric.N\n 100.0\n > hypergeometric.K\n 70.0\n > hypergeometric.n\n 20.0\n > hypergeometric.kurtosis\n ~-0.063\n > hypergeometric.mean\n 14.0\n > hypergeometric.mode\n 14.0\n > hypergeometric.skewness\n ~-0.133\n > hypergeometric.stdev\n ~1.842\n > hypergeometric.variance\n ~3.394\n > hypergeometric.cdf( 2.9 )\n ~0.0\n > hypergeometric.logpmf( 10 )\n ~-3.806\n > hypergeometric.pmf( 10 )\n ~0.022\n > hypergeometric.quantile( 0.8 )\n 16.0\n\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N, K, n )\n Returns the excess kurtosis of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceed population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\n ~-0.326\n > v = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x, N, K, n )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K`, or draws `n`\n which is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\n ~-0.56\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\n -Infinity\n\n > y = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n > var y = mylogPMF( 4.0 )\n ~-1.079\n > y = mylogPMF( 1.0 )\n ~-3.524\n\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n > var y = mylogPMF( 4.0 )\n ~-1.079\n > y = mylogPMF( 1.0 )\n ~-3.524","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N, K, n )\n Returns the expected value of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mean( 16, 11, 4 )\n 2.75\n > v = base.dists.hypergeometric.mean( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.mean( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mean( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mean( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N, K, n )\n Returns the mode of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mode( 16, 11, 4 )\n 3\n > v = base.dists.hypergeometric.mode( 2, 1, 1 )\n 1\n\n > v = base.dists.hypergeometric.mode( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mode( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mode( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x, N, K, n )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\n ~0.571\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\n 0.0\n\n > y = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n > var y = myPMF( 4.0 )\n ~0.34\n > y = myPMF( 1.0 )\n ~0.029\n\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n > var y = myPMF( 4.0 )\n ~0.34\n > y = myPMF( 1.0 )\n ~0.029","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p, N, K, n )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\n 5\n > y = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\n 15\n > y = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\n 1\n > y = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\n 0\n > y = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\n 20\n\n > y = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n NaN\n\n\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n > var y = myQuantile( 0.2 )\n 1\n > y = myQuantile( 0.9 )\n 4\n\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n > var y = myQuantile( 0.2 )\n 1\n > y = myQuantile( 0.9 )\n 4","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N, K, n )\n Returns the skewness of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\n ~-0.258\n > v = base.dists.hypergeometric.skewness( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.skewness( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.skewness( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N, K, n )\n Returns the standard deviation of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\n ~0.829\n > v = base.dists.hypergeometric.stdev( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.stdev( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.stdev( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N, K, n )\n Returns the variance of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.variance( 16, 11, 4 )\n ~0.688\n > v = base.dists.hypergeometric.variance( 2, 1, 1 )\n 0.25\n\n > v = base.dists.hypergeometric.variance( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.variance( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.variance( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, 10, NaN )\n NaN\n\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\n ~0.607\n > y = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\n ~0.986\n > y = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974\n\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α, β )\n Returns the differential entropy of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.invgamma.entropy( 1.0, 1.0 )\n ~2.154\n > v = base.dists.invgamma.entropy( 4.0, 12.0 )\n ~1.996\n > v = base.dists.invgamma.entropy( 8.0, 2.0 )\n ~-0.922\n\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α, β] )\n Returns an inverse gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n invgamma: Object\n Distribution instance.\n\n invgamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n invgamma.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n invgamma.entropy: number\n Read-only property which returns the differential entropy.\n\n invgamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n invgamma.mean: number\n Read-only property which returns the expected value.\n\n invgamma.mode: number\n Read-only property which returns the mode.\n\n invgamma.skewness: number\n Read-only property which returns the skewness.\n\n invgamma.stdev: number\n Read-only property which returns the standard deviation.\n\n invgamma.variance: number\n Read-only property which returns the variance.\n\n invgamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n invgamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n invgamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n invgamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\n > invgamma.alpha\n 6.0\n > invgamma.beta\n 5.0\n > invgamma.entropy\n ~0.454\n > invgamma.kurtosis\n 19.0\n > invgamma.mean\n 1.0\n > invgamma.mode\n ~0.714\n > invgamma.skewness\n ~2.667\n > invgamma.stdev\n 0.5\n > invgamma.variance\n 0.25\n > invgamma.cdf( 0.8 )\n ~0.406\n > invgamma.pdf( 1.0 )\n ~0.877\n > invgamma.logpdf( 1.0 )\n ~-0.131\n > invgamma.quantile( 0.8 )\n ~1.281\n\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α, β )\n Returns the excess kurtosis of an inverse gamma distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\n 12.0\n > v = base.dists.invgamma.kurtosis( 6.0, 12.0 )\n 19.0\n > v = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n ~8.7\n\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.112\n > y = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\n ~-1.781\n > y = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-1.464\n\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-1.464","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α, β )\n Returns the expected value of an inverse gamma distribution.\n\n If `α <= 1` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.invgamma.mean( 4.0, 12.0 )\n 4.0\n > v = base.dists.invgamma.mean( 8.0, 2.0 )\n ~0.286\n\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α, β )\n Returns the mode of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.invgamma.mode( 1.0, 1.0 )\n 0.5\n > v = base.dists.invgamma.mode( 4.0, 12.0 )\n 2.4\n > v = base.dists.invgamma.mode( 8.0, 2.0 )\n ~0.222\n\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\n ~0.121\n > y = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\n ~0.168\n > y = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.231\n\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.231","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p, α, β )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\n ~1.213\n > y = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\n ~0.545\n > y = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n\n // Non-positive rate parameter:\n > y = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~2.426\n > y = myQuantile( 0.4 )\n ~0.989\n\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~2.426\n > y = myQuantile( 0.4 )\n ~0.989","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α, β )\n Returns the skewness of an inverse gamma distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.invgamma.skewness( 4.0, 12.0 )\n ~5.657\n > v = base.dists.invgamma.skewness( 8.0, 2.0 )\n ~1.96\n\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α, β )\n Returns the standard deviation of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.invgamma.stdev( 5.0, 7.0 )\n ~1.01\n > v = base.dists.invgamma.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.invgamma.stdev( 8.0, 2.0 )\n ~0.117\n\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α, β )\n Returns the variance of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.invgamma.variance( 5.0, 7.0 )\n ~1.021\n > v = base.dists.invgamma.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.invgamma.variance( 8.0, 2.0 )\n ~0.014\n\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\n ~0.5\n > y = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\n ~0.684\n > y = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\n ~0.078\n > y = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\n ~0.878\n > y = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n > var y = mycdf( 0.8 )\n ~0.894\n > y = mycdf( 0.3 )\n ~0.548\n\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n > var y = mycdf( 0.8 )\n ~0.894\n > y = mycdf( 0.3 )\n ~0.548","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a, b] )\n Returns a Kumaraswamy's double bounded distribution object.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n b: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n kumaraswamy: Object\n Distribution instance.\n\n kumaraswamy.a: number\n First shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.b: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n kumaraswamy.mean: number\n Read-only property which returns the expected value.\n\n kumaraswamy.mode: number\n Read-only property which returns the mode.\n\n kumaraswamy.skewness: number\n Read-only property which returns the skewness.\n\n kumaraswamy.stdev: number\n Read-only property which returns the standard deviation.\n\n kumaraswamy.variance: number\n Read-only property which returns the variance.\n\n kumaraswamy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n kumaraswamy.pdf: Function\n Evaluates the probability density function (PDF).\n\n kumaraswamy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\n > kumaraswamy.a\n 6.0\n > kumaraswamy.b\n 5.0\n > kumaraswamy.kurtosis\n ~3.194\n > kumaraswamy.mean\n ~0.696\n > kumaraswamy.mode\n ~0.746\n > kumaraswamy.skewness\n ~-0.605\n > kumaraswamy.stdev\n ~0.126\n > kumaraswamy.variance\n ~0.016\n > kumaraswamy.cdf( 0.8 )\n ~0.781\n > kumaraswamy.pdf( 1.0 )\n ~0.0\n > kumaraswamy.quantile( 0.8 )\n ~0.807\n\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a, b )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\n ~1.8\n > v = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\n ~2.704\n > v = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n ~4.311\n\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\n ~-0.38\n > y = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\n ~-2.546\n > y = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\n ~-0.13\n > y = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n > var y = mylogcdf( 0.8 )\n ~-0.112\n > y = mylogcdf( 0.3 )\n ~-0.602\n\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n > var y = mylogcdf( 0.8 )\n ~-0.112\n > y = mylogcdf( 0.3 )\n ~-0.602","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x, a, b )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\n ~0.523\n > y = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\n ~-0.264\n > y = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\n ~0.522\n > y = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n > var y = mylogpdf( 0.8 )\n ~-0.582\n > y = mylogpdf( 0.3 )\n ~-0.091\n\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n > var y = mylogpdf( 0.8 )\n ~-0.582\n > y = mylogpdf( 0.3 )\n ~-0.091","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a, b )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\n ~0.512\n > v = base.dists.kumaraswamy.mean( 4.0, 12.0 )\n ~0.481\n > v = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n ~0.846\n\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a, b )\n Returns the median of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.kumaraswamy.median( 4.0, 12.0 )\n ~0.487\n > v = base.dists.kumaraswamy.median( 16.0, 8.0 )\n ~0.856\n\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a, b )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a < 1`, `b < 1`, or `a = b = 1`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\n ~0.543\n > v = base.dists.kumaraswamy.mode( 4.0, 12.0 )\n ~0.503\n > v = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n ~0.875\n\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x, a, b )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\n ~1.688\n > y = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\n ~0.768\n > y = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\n ~1.686\n > y = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n > var y = mypdf( 0.8 )\n ~0.559\n > y = mypdf( 0.3 )\n ~0.913\n\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n > var y = mypdf( 0.8 )\n ~0.559\n > y = mypdf( 0.3 )\n ~0.913","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p, a, b )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\n ~0.399\n > y = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\n ~0.325\n > y = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\n ~0.759\n\n > y = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n > var y = myQuantile( 0.8 )\n ~0.64\n > y = myQuantile( 0.3 )\n ~0.09\n\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n > var y = myQuantile( 0.8 )\n ~0.64\n > y = myQuantile( 0.3 )\n ~0.09","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a, b )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\n ~1.154e-15\n > v = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\n ~-0.201\n > v = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n ~-0.94\n\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a, b )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\n ~0.13\n > v = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n ~0.062\n\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a, b )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.kumaraswamy.variance( 4.0, 12.0 )\n ~0.017\n > v = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n ~0.004\n\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x, μ, b )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\n ~0.932\n > y = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\n ~0.094\n > y = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.cdf.factory( μ, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.965\n > y = myCDF( 2.0 )\n 0.5\n\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.965\n > y = myCDF( 2.0 )\n 0.5","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ, b )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.laplace.entropy( 0.0, 1.0 )\n ~1.693\n > y = base.dists.laplace.entropy( 4.0, 2.0 )\n ~2.386\n > y = base.dists.laplace.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.entropy( 0.0, NaN )\n NaN\n > y = base.dists.laplace.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ, b )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( 4.0, 2.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ, b] )\n Returns a Laplace distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n b: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n laplace: Object\n Distribution instance.\n\n laplace.mu: number\n Location parameter.\n\n laplace.b: number\n Scale parameter. If set, the value must be greater than `0`.\n\n laplace.entropy: number\n Read-only property which returns the differential entropy.\n\n laplace.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n laplace.mean: number\n Read-only property which returns the expected value.\n\n laplace.median: number\n Read-only property which returns the median.\n\n laplace.mode: number\n Read-only property which returns the mode.\n\n laplace.skewness: number\n Read-only property which returns the skewness.\n\n laplace.stdev: number\n Read-only property which returns the standard deviation.\n\n laplace.variance: number\n Read-only property which returns the variance.\n\n laplace.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n laplace.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n laplace.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n laplace.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n laplace.pdf: Function\n Evaluates the probability density function (PDF).\n\n laplace.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\n > laplace.mu\n -2.0\n > laplace.b\n 3.0\n > laplace.entropy\n ~2.792\n > laplace.kurtosis\n 3.0\n > laplace.mean\n -2.0\n > laplace.median\n -2.0\n > laplace.mode\n -2.0\n > laplace.skewness\n 0.0\n > laplace.stdev\n ~4.243\n > laplace.variance\n 18.0\n > laplace.cdf( 0.8 )\n ~0.803\n > laplace.logcdf( 0.8 )\n ~-0.219\n > laplace.logpdf( 1.0 )\n ~-2.792\n > laplace.mgf( 0.2 )\n ~1.047\n > laplace.pdf( 2.0 )\n ~0.044\n > laplace.quantile( 0.9 )\n ~2.828\n\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x, μ, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\n ~-0.07\n > y = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\n ~-2.36\n > y = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logcdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.035\n > y = mylogcdf( 2.0 )\n ~-0.693\n\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.035\n > y = mylogcdf( 2.0 )\n ~-0.693","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x, μ, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\n ~-2.693\n > y = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\n ~-2.792\n > y = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\n ~-1.958\n > y = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logpdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.386\n\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.386","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ, b )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.laplace.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mean( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mean( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ, b )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.laplace.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.median( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.median( 0.0, NaN )\n NaN\n > y = base.dists.laplace.median( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t, μ, b )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\n ~1.333\n > y = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\n ~0.019\n > y = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\n NaN\n > y = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.mgf.factory( μ, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n > var y = mymgf( 0.2 )\n ~2.649\n > y = mymgf( 0.4 )\n ~13.758\n\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n > var y = mymgf( 0.2 )\n ~2.649\n > y = mymgf( 0.4 )\n ~13.758","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ, b )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.laplace.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mode( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mode( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x, μ, b )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\n ~0.068\n > y = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\n ~0.061\n > y = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\n ~0.141\n > y = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.pdf.factory( μ, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.25\n\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.25","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p, μ, b )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\n ~0.916\n > y = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\n 4.0\n\n > y = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.quantile.factory( μ, b )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n > y = myQuantile( 0.8 )\n ~11.833\n\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ, b )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n > y = myQuantile( 0.8 )\n ~11.833","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ, b )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.laplace.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.laplace.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.skewness( 0.0, NaN )\n NaN\n > y = base.dists.laplace.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ, b )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.laplace.stdev( 0.0, 1.0 )\n ~1.414\n > y = base.dists.laplace.stdev( 4.0, 2.0 )\n ~2.828\n > y = base.dists.laplace.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.stdev( 0.0, NaN )\n NaN\n > y = base.dists.laplace.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ, b )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.laplace.variance( 0.0, 1.0 )\n 2.0\n > y = base.dists.laplace.variance( 4.0, 2.0 )\n 8.0\n > y = base.dists.laplace.variance( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.variance( 0.0, NaN )\n NaN\n > y = base.dists.laplace.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x, μ, c )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\n ~0.48\n > y = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\n ~0.221\n > y = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\n 0.0\n > y = base.dists.levy.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0\n\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ, c )\n Returns the entropy of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.levy.entropy( 0.0, 1.0 )\n ~3.324\n > y = base.dists.levy.entropy( 4.0, 2.0 )\n ~4.018\n > y = base.dists.levy.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.levy.entropy( 0.0, NaN )\n NaN\n > y = base.dists.levy.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ, c] )\n Returns a Lévy distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n c: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n levy: Object\n Distribution instance.\n\n levy.mu: number\n Location parameter.\n\n levy.c: number\n Scale parameter. If set, the value must be greater than `0`.\n\n levy.entropy: number\n Read-only property which returns the differential entropy.\n\n levy.mean: number\n Read-only property which returns the expected value.\n\n levy.median: number\n Read-only property which returns the median.\n\n levy.mode: number\n Read-only property which returns the mode.\n\n levy.stdev: number\n Read-only property which returns the standard deviation.\n\n levy.variance: number\n Read-only property which returns the variance.\n\n levy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n levy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n levy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n levy.pdf: Function\n Evaluates the probability density function (PDF).\n\n levy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var levy = base.dists.levy.Levy( -2.0, 3.0 );\n > levy.mu\n -2.0\n > levy.c\n 3.0\n > levy.entropy\n ~4.423\n > levy.mean\n Infinity\n > levy.median\n ~4.594\n > levy.mode\n -1.0\n > levy.stdev\n Infinity\n > levy.variance\n Infinity\n > levy.cdf( 0.8 )\n ~0.3\n > levy.logcdf( 0.8 )\n ~-1.2\n > levy.logpdf( 1.0 )\n ~-2.518\n > levy.pdf( 1.0 )\n ~0.081\n > levy.quantile( 0.8 )\n ~44.74\n\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x, μ, c )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Lévy distribution with location parameter `μ` and scale parameter `c` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\n ~-0.735\n > y = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\n ~-1.51\n > y = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\n -Infinity\n > y = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity\n\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x, μ, c )\n Evaluates the logarithm of the probability density function (PDF) for a Lévy\n distribution with location parameter `μ` and scale parameter `c` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\n ~-2.209\n > y = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logpdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 11.0 )\n ~-1.572\n\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 11.0 )\n ~-1.572","base.dists.levy.mean":"\nbase.dists.levy.mean( μ, c )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.levy.mean( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.mean( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.mean( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mean( 0.0, NaN )\n NaN\n > y = base.dists.levy.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.median":"\nbase.dists.levy.median( μ, c )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.levy.median( 0.0, 1.0 )\n ~2.198\n > y = base.dists.levy.median( 4.0, 3.0 )\n ~10.594\n > y = base.dists.levy.median( NaN, 1.0 )\n NaN\n > y = base.dists.levy.median( 0.0, NaN )\n NaN\n > y = base.dists.levy.median( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ, c )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.levy.mode( 0.0, 1.0 )\n ~0.333\n > y = base.dists.levy.mode( 4.0, 3.0 )\n 5.0\n > y = base.dists.levy.mode( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mode( 0.0, NaN )\n NaN\n > y = base.dists.levy.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x, μ, c )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\n ~0.11\n > y = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.levy.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.pdf.factory( μ, c )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 11.0 )\n ~0.208\n\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ, c )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 11.0 )\n ~0.208","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p, μ, c )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\n ~15.58\n > y = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\n ~8.396\n\n > y = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.levy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.quantile.factory( μ, c )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~14.396\n\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ, c )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~14.396","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ, c )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.levy.stdev( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.stdev( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.levy.stdev( 0.0, NaN )\n NaN\n > y = base.dists.levy.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ, c )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.levy.variance( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.variance( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.variance( NaN, 1.0 )\n NaN\n > y = base.dists.levy.variance( 0.0, NaN )\n NaN\n > y = base.dists.levy.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\n ~0.881\n > y = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\n ~0.159\n\n > y = base.dists.logistic.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209\n\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ, s )\n Returns the entropy of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.logistic.entropy( 0.0, 1.0 )\n 2.0\n > y = base.dists.logistic.entropy( 4.0, 2.0 )\n ~2.693\n > y = base.dists.logistic.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.entropy( 0.0, NaN )\n NaN\n > y = base.dists.logistic.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ, s )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( 4.0, 2.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, 0.0 )\n NaN\n\n\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x, μ, s )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\n ~-0.127\n > y = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\n ~-1.84\n > y = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567\n\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ, s] )\n Returns a logistic distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n logistic: Object\n Distribution instance.\n\n logistic.mu: number\n Location parameter.\n\n logistic.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n logistic.entropy: number\n Read-only property which returns the differential entropy.\n\n logistic.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n logistic.mean: number\n Read-only property which returns the expected value.\n\n logistic.median: number\n Read-only property which returns the median.\n\n logistic.mode: number\n Read-only property which returns the mode.\n\n logistic.skewness: number\n Read-only property which returns the skewness.\n\n logistic.stdev: number\n Read-only property which returns the standard deviation.\n\n logistic.variance: number\n Read-only property which returns the variance.\n\n logistic.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n logistic.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n logistic.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n logistic.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n logistic.pdf: Function\n Evaluates the probability density function (PDF).\n\n logistic.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\n > logistic.mu\n -2.0\n > logistic.s\n 3.0\n > logistic.entropy\n ~3.1\n > logistic.kurtosis\n 1.2\n > logistic.mean\n -2.0\n > logistic.median\n -2.0\n > logistic.mode\n -2.0\n > logistic.skewness\n 0.0\n > logistic.stdev\n ~5.441\n > logistic.variance\n ~29.609\n > logistic.cdf( 0.8 )\n ~0.718\n > logistic.logcdf( 0.8 )\n ~-0.332\n > logistic.logpdf( 2.0 )\n ~-2.9\n > logistic.mgf( 0.2 )\n ~1.329\n > logistic.pdf( 2.0 )\n ~0.055\n > logistic.quantile( 0.9 )\n ~4.592\n\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\n ~-2.254\n > y = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\n ~-3.351\n > y = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-2.079\n\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-2.079","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ, s )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.logistic.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mean( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mean( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ, s )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.logistic.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.median( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.median( 0.0, NaN )\n NaN\n > y = base.dists.logistic.median( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\n ~9.15\n > y = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\n ~1.971\n > y = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\n ~1.921\n > y = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\n Infinity\n > y = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.logistic.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n > var y = mymgf( 0.5 )\n ~164.846\n > y = mymgf( 2.0 )\n Infinity\n\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n > var y = mymgf( 0.5 )\n ~164.846\n > y = mymgf( 2.0 )\n Infinity","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ, s )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.logistic.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mode( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mode( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\n ~0.105\n > y = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\n ~0.035\n > y = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.125\n\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.125","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p, μ, s )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\n ~1.386\n > y = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.logistic.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ, s )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.logistic.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.logistic.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.skewness( 0.0, NaN )\n NaN\n > y = base.dists.logistic.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ, s )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.logistic.stdev( 0.0, 1.0 )\n ~1.814\n > y = base.dists.logistic.stdev( 4.0, 2.0 )\n ~3.628\n > y = base.dists.logistic.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.stdev( 0.0, NaN )\n NaN\n > y = base.dists.logistic.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ, s )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.logistic.variance( 0.0, 1.0 )\n ~3.29\n > y = base.dists.logistic.variance( 4.0, 2.0 )\n ~13.159\n > y = base.dists.logistic.variance( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.variance( 0.0, NaN )\n NaN\n > y = base.dists.logistic.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\n ~0.756\n > y = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\n ~0.003\n\n > y = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n > var y = myCDF( 1.0 )\n ~0.023\n > y = myCDF( 4.0 )\n ~0.141\n\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n > var y = myCDF( 1.0 )\n ~0.023\n > y = myCDF( 4.0 )\n ~0.141","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ, σ )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.lognormal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.lognormal.entropy( 5.0, 2.0 )\n ~7.112\n > y = base.dists.lognormal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ, σ )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\n ~110.936\n > y = base.dists.lognormal.kurtosis( 5.0, 2.0 )\n ~9220556.977\n > y = base.dists.lognormal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ, σ] )\n Returns a lognormal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n lognormal: Object\n Distribution instance.\n\n lognormal.mu: number\n Location parameter.\n\n lognormal.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n lognormal.entropy: number\n Read-only property which returns the differential entropy.\n\n lognormal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n lognormal.mean: number\n Read-only property which returns the expected value.\n\n lognormal.median: number\n Read-only property which returns the median.\n\n lognormal.mode: number\n Read-only property which returns the mode.\n\n lognormal.skewness: number\n Read-only property which returns the skewness.\n\n lognormal.stdev: number\n Read-only property which returns the standard deviation.\n\n lognormal.variance: number\n Read-only property which returns the variance.\n\n lognormal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n lognormal.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n lognormal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n lognormal.pdf: Function\n Evaluates the probability density function (PDF).\n\n lognormal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\n > lognormal.mu\n -2.0\n > lognormal.sigma\n 3.0\n > lognormal.entropy\n ~0.518\n > lognormal.kurtosis\n 4312295840576300\n > lognormal.mean\n ~12.182\n > lognormal.median\n ~0.135\n > lognormal.mode\n ~0.0\n > lognormal.skewness\n ~729551.383\n > lognormal.stdev\n ~1096.565\n > lognormal.variance\n ~1202455.871\n > lognormal.cdf( 0.8 )\n ~0.723\n > lognormal.logcdf( 0.8 )\n ~-4.334\n > lognormal.logpdf( 2.0 )\n ~-3.114\n > lognormal.pdf( 2.0 )\n ~0.044\n > lognormal.quantile( 0.9 )\n ~6.326\n\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x, μ, σ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a lognormal distribution with mean `μ` and standard deviation `σ`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logcdf.\n\n Examples\n --------\n > var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\n ~-0.2799\n > y = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\n ~-1.442\n > y = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n -Infinity\n\n\nbase.dists.lognormal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-9.732\n\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-9.732","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\n ~-1.852\n > y = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\n ~-0.919\n > y = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\n ~-5.419\n > y = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-4.275\n > y = mylogPDF( 2.0 )\n ~-3.672\n\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-4.275\n > y = mylogPDF( 2.0 )\n ~-3.672","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ, σ )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.lognormal.mean( 0.0, 1.0 )\n ~1.649\n > y = base.dists.lognormal.mean( 4.0, 2.0 )\n ~403.429\n > y = base.dists.lognormal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mean( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ, σ )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.lognormal.median( 0.0, 1.0 )\n 1.0\n > y = base.dists.lognormal.median( 5.0, 2.0 )\n ~148.413\n > y = base.dists.lognormal.median( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.median( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ, σ )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.lognormal.mode( 0.0, 1.0 )\n ~0.368\n > y = base.dists.lognormal.mode( 5.0, 2.0 )\n ~2.718\n > y = base.dists.lognormal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mode( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\n ~0.157\n > y = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\n ~0.399\n > y = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\n ~0.004\n > y = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.014\n > y = myPDF( 2.0 )\n ~0.025\n\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.014\n > y = myPDF( 2.0 )\n ~0.025","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p, μ, σ )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\n ~2.32\n > y = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\n ~54.598\n > y = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~10.143\n > y = myQuantile( 0.8 )\n ~293.901\n\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~10.143\n > y = myQuantile( 0.8 )\n ~293.901","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ, σ )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.lognormal.skewness( 0.0, 1.0 )\n ~6.185\n > y = base.dists.lognormal.skewness( 5.0, 2.0 )\n ~414.359\n > y = base.dists.lognormal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ, σ )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.lognormal.stdev( 0.0, 1.0 )\n ~2.161\n > y = base.dists.lognormal.stdev( 4.0, 2.0 )\n ~2953.533\n > y = base.dists.lognormal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ, σ )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.lognormal.variance( 0.0, 1.0 )\n ~4.671\n > y = base.dists.lognormal.variance( 4.0, 2.0 )\n ~8723355.729\n > y = base.dists.lognormal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.variance( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x, r, p )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\n ~0.617\n > y = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\n ~0.622\n > y = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\n ~0.034\n > y = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\n ~0.859\n > y = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\n ~0.131\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.cdf.factory( r, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n > var y = myCDF( 3.0 )\n ~0.046\n > y = myCDF( 11.0 )\n ~0.668\n\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n > var y = myCDF( 3.0 )\n ~0.046\n > y = myCDF( 11.0 )\n ~0.668","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r, p )\n Returns the excess kurtosis of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\n ~0.061\n > v = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n ~0.325\n\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x, r, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\n ~-1.853\n > y = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\n ~-2.818\n > y = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\n ~-4.115\n > y = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\n ~-1.054\n > y = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\n ~-3.292\n > y = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\n ~-2.976\n\n > y = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n > var y = mylogPMF( 3.0 )\n ~-3.617\n > y = mylogPMF( 5.0 )\n ~-2.795\n\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n > var y = mylogPMF( 3.0 )\n ~-3.617\n > y = mylogPMF( 5.0 )\n ~-2.795","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r, p )\n Returns the expected value of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mean( 100, 0.2 )\n 400\n > v = base.dists.negativeBinomial.mean( 20, 0.5 )\n 20\n\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x, r, p )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\n ~267.839\n > y = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\n ~9.347\n > y = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\n ~42822.023\n\n > y = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.mgf.factory( r, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n > var y = myMGF( 0.2 )\n ~4.696\n > y = myMGF( 0.4 )\n ~30.83\n\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n > var y = myMGF( 0.2 )\n ~4.696\n > y = myMGF( 0.4 )\n ~30.83","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r, p )\n Returns the mode of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mode( 100, 0.2 )\n 396\n > v = base.dists.negativeBinomial.mode( 20, 0.5 )\n 19\n\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r, p] )\n Returns a negative binomial distribution object.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped. Must be a positive\n number. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n nbinomial: Object\n Distribution instance.\n\n nbinomial.r: number\n Number of trials. If set, the value must be a positive number.\n\n nbinomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n nbinomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n nbinomial.mean: number\n Read-only property which returns the expected value.\n\n nbinomial.mode: number\n Read-only property which returns the mode.\n\n nbinomial.skewness: number\n Read-only property which returns the skewness.\n\n nbinomial.stdev: number\n Read-only property which returns the standard deviation.\n\n nbinomial.variance: number\n Read-only property which returns the variance.\n\n nbinomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n nbinomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n nbinomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n nbinomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n nbinomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\n > nbinomial.r\n 8.0\n > nbinomial.p\n 0.5\n > nbinomial.kurtosis\n 0.8125\n > nbinomial.mean\n 8.0\n > nbinomial.mode\n 7.0\n > nbinomial.skewness\n 0.75\n > nbinomial.stdev\n 4.0\n > nbinomial.variance\n 16.0\n > nbinomial.cdf( 2.9 )\n ~0.055\n > nbinomial.logpmf( 3.0 )\n ~-2.837\n > nbinomial.mgf( 0.2 )\n ~36.675\n > nbinomial.pmf( 3.0 )\n ~0.059\n > nbinomial.quantile( 0.8 )\n 11.0\n\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x, r, p )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\n ~0.157\n > y = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\n ~0.06\n > y = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\n ~0.016\n > y = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\n ~0.037\n > y = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\n ~0.051\n\n > y = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.pmf.factory( r, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n > var y = myPMF( 3.0 )\n ~0.027\n > y = myPMF( 5.0 )\n ~0.061\n\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n > var y = myPMF( 3.0 )\n ~0.027\n > y = myPMF( 5.0 )\n ~0.061","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k, r, p )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n\n If provided a `k` outside of `[0,1]`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n k: number\n Input probability.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\n 106\n > y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\n 8\n > y = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\n 14\n > y = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\n 0\n\n > y = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\n 12\n > y = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\n 10\n\n > y = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.quantile.factory( r, p )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n > var y = myQuantile( 0.1 )\n 5\n > y = myQuantile( 0.9 )\n 16\n\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r, p )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n > var y = myQuantile( 0.1 )\n 5\n > y = myQuantile( 0.9 )\n 16","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r, p )\n Returns the skewness of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\n ~0.201\n > v = base.dists.negativeBinomial.skewness( 20, 0.5 )\n ~0.474\n\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r, p )\n Returns the standard deviation of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\n ~44.721\n > v = base.dists.negativeBinomial.stdev( 20, 0.5 )\n ~6.325\n\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r, p )\n Returns the variance of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.variance( 100, 0.2 )\n 2000.0\n > v = base.dists.negativeBinomial.variance( 20, 0.5 )\n 40.0\n\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\n ~0.977\n > y = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\n 0.5\n > y = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\n ~0.006\n > y = base.dists.normal.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.normal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n 0.5\n\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n 0.5","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ, σ )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.normal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.normal.entropy( 4.0, 3.0 )\n ~2.518\n > y = base.dists.normal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.normal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.normal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ, σ )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.normal.kurtosis( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.kurtosis( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x, μ, σ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logcdf.\n\n Examples\n --------\n > var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\n ~-0.023\n > y = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\n ~-5.082\n > y = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.logcdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n 0.0\n\n\nbase.dists.normal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.693\n\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.693","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\n ~-2.919\n > y = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\n ~-4.737\n > y = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.normal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n > var y = myLogPDF( 10.0 )\n ~-1.612\n\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n > var y = myLogPDF( 10.0 )\n ~-1.612","base.dists.normal.mean":"\nbase.dists.normal.mean( μ, σ )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.normal.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mean( 0.0, NaN )\n NaN\n > y = base.dists.normal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.median":"\nbase.dists.normal.median( μ, σ )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.normal.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.median( NaN, 1.0 )\n NaN\n > y = base.dists.normal.median( 0.0, NaN )\n NaN\n > y = base.dists.normal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x, μ, σ )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\n ~7.389\n > y = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\n ~0.1353\n > y = base.dists.normal.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.normal.mgf.factory( μ, σ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n > var y = myMGF( 1.0 )\n ~403.429\n > y = myMGF( 0.5 )\n ~12.182\n\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ, σ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n > var y = myMGF( 1.0 )\n ~403.429\n > y = myMGF( 0.5 )\n ~12.182","base.dists.normal.mode":"\nbase.dists.normal.mode( μ, σ )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.normal.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mode( 0.0, NaN )\n NaN\n > y = base.dists.normal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ, σ] )\n Returns a normal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Mean parameter. Default: `0.0`.\n\n σ: number (optional)\n Standard deviation. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n normal: Object\n Distribution instance.\n\n normal.mu: number\n Mean parameter.\n\n normal.sigma: number\n Standard deviation. If set, the value must be greater than `0`.\n\n normal.entropy: number\n Read-only property which returns the differential entropy.\n\n normal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n normal.mean: number\n Read-only property which returns the expected value.\n\n normal.median: number\n Read-only property which returns the median.\n\n normal.mode: number\n Read-only property which returns the mode.\n\n normal.skewness: number\n Read-only property which returns the skewness.\n\n normal.stdev: number\n Read-only property which returns the standard deviation.\n\n normal.variance: number\n Read-only property which returns the variance.\n\n normal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n normal.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n normal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n normal.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n normal.pdf: Function\n Evaluates the probability density function (PDF).\n\n normal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var normal = base.dists.normal.Normal( -2.0, 3.0 );\n > normal.mu\n -2.0\n > normal.sigma\n 3.0\n > normal.entropy\n ~2.518\n > normal.kurtosis\n 0.0\n > normal.mean\n -2.0\n > normal.median\n -2.0\n > normal.mode\n -2.0\n > normal.skewness\n 0.0\n > normal.stdev\n 3.0\n > normal.variance\n 9.0\n > normal.cdf( 0.8 )\n ~0.825\n > normal.logcdf( 0.8 )\n ~-0.193\n > normal.logpdf( 2.0 )\n ~-2.9\n > normal.mgf( 0.2 )\n ~0.803\n > normal.pdf( 2.0 )\n ~0.055\n > normal.quantile( 0.9 )\n ~1.845\n\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\n ~0.054\n > y = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\n ~0.009\n > y = base.dists.normal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n infinity\n\n\nbase.dists.normal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.199\n\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.199","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p, μ, σ )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\n ~0.842\n > y = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.normal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\n 8.0\n > y = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n 8.0\n\n\nbase.dists.normal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ, σ )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.normal.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.skewness( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.normal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.normal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ, σ )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.normal.stdev( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.stdev( 4.0, 3.0 )\n 3.0\n > y = base.dists.normal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.normal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.normal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ, σ )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.normal.variance( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.variance( 4.0, 3.0 )\n 9.0\n > y = base.dists.normal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.normal.variance( 0.0, NaN )\n NaN\n > y = base.dists.normal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\n 0.5\n > y = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\n ~0.36\n > y = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\n 0.75\n > y = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893\n\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α, β )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.pareto1.entropy( 0.8, 1.0 )\n ~2.473\n > v = base.dists.pareto1.entropy( 4.0, 12.0 )\n ~2.349\n > v = base.dists.pareto1.entropy( 8.0, 2.0 )\n ~-0.261\n\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α, β )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\n ~70.8\n > v = base.dists.pareto1.kurtosis( 4.5, 12.0 )\n ~146.444\n > v = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n ~19.725\n\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\n ~-1.022\n > y = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\n ~-0.288\n > y = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114\n\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\n ~-2.773\n > y = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\n ~-3.689\n > y = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\n ~-1.561\n > y = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\n ~-5.238\n > y = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079\n\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α, β )\n Returns the expected value of a Pareto (Type I) distribution.\n\n If `0 < α <= 1`, the function returns `Infinity`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.pareto1.mean( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.mean( 4.0, 12.0 )\n 16.0\n > v = base.dists.pareto1.mean( 8.0, 2.0 )\n ~2.286\n\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α, β )\n Returns the median of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.pareto1.median( 0.8, 1.0 )\n ~2.378\n > v = base.dists.pareto1.median( 4.0, 12.0 )\n ~14.27\n > v = base.dists.pareto1.median( 8.0, 2.0 )\n ~2.181\n\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α, β )\n Returns the mode of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.pareto1.mode( 0.8, 1.0 )\n 1.0\n > v = base.dists.pareto1.mode( 4.0, 12.0 )\n 12.0\n > v = base.dists.pareto1.mode( 8.0, 2.0 )\n 2.0\n\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α, β] )\n Returns a Pareto (Type I) distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n pareto1: Object\n Distribution instance.\n\n pareto1.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n pareto1.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n pareto1.entropy: number\n Read-only property which returns the differential entropy.\n\n pareto1.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n pareto1.mean: number\n Read-only property which returns the expected value.\n\n pareto1.median: number\n Read-only property which returns the median.\n\n pareto1.mode: number\n Read-only property which returns the mode.\n\n pareto1.skewness: number\n Read-only property which returns the skewness.\n\n pareto1.variance: number\n Read-only property which returns the variance.\n\n pareto1.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n pareto1.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF).\n\n pareto1.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (logPDF).\n\n pareto1.pdf: Function\n Evaluates the probability density function (PDF).\n\n pareto1.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\n > pareto1.alpha\n 6.0\n > pareto1.beta\n 5.0\n > pareto1.entropy\n ~0.984\n > pareto1.kurtosis\n ~35.667\n > pareto1.mean\n 6.0\n > pareto1.median\n ~5.612\n > pareto1.mode\n 5.0\n > pareto1.skewness\n ~3.81\n > pareto1.variance\n 1.5\n > pareto1.cdf( 7.0 )\n ~0.867\n > pareto1.logcdf( 7.0 )\n ~-0.142\n > pareto1.logpdf( 5.0 )\n ~0.182\n > pareto1.pdf( 5.0 )\n 1.2\n > pareto1.quantile( 0.8 )\n ~6.538\n\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\n ~0.063\n > y = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\n 0.025\n > y = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\n ~0.21\n > y = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\n ~0.005\n > y = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n > var y = myPDF( 0.8 )\n ~0.494\n > y = myPDF( 2.0 )\n ~0.125\n\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n > var y = myPDF( 0.8 )\n ~0.494\n > y = myPDF( 2.0 )\n ~0.125","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p, α, β )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\n ~2.236\n > y = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\n ~50.0\n > y = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\n ~11.111\n\n > y = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.pareto1.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n > var y = myQuantile( 0.5 )\n ~0.66\n > y = myQuantile( 0.8 )\n ~0.952\n\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n > var y = myQuantile( 0.5 )\n ~0.66\n > y = myQuantile( 0.8 )\n ~0.952","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α, β )\n Returns the skewness of a Pareto (Type I) distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.pareto1.skewness( 3.5, 1.0 )\n ~11.784\n > v = base.dists.pareto1.skewness( 4.0, 12.0 )\n ~7.071\n > v = base.dists.pareto1.skewness( 8.0, 2.0 )\n ~3.118\n\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α, β )\n Returns the standard deviation of a Pareto (Type I) distribution.\n\n If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.pareto1.stdev( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.stdev( 4.0, 12.0 )\n ~5.657\n > v = base.dists.pareto1.stdev( 8.0, 2.0 )\n ~0.33\n\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α, β )\n Returns the variance of a Pareto (Type I) distribution.\n\n If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.pareto1.variance( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.variance( 4.0, 12.0 )\n 32.0\n > v = base.dists.pareto1.variance( 8.0, 2.0 )\n ~0.109\n\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.poisson.cdf( 2.0, 0.5 )\n ~0.986\n > y = base.dists.poisson.cdf( 2.0, 10.0 )\n ~0.003\n > y = base.dists.poisson.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.poisson.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.poisson.cdf( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.poisson.cdf( 10.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n > var y = mycdf( 3.0 )\n ~0.265\n > y = mycdf( 8.0 )\n ~0.932\n\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n > var y = mycdf( 3.0 )\n ~0.265\n > y = mycdf( 8.0 )\n ~0.932","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ )\n Returns the entropy of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.poisson.entropy( 11.0 )\n ~2.61\n > v = base.dists.poisson.entropy( 4.5 )\n ~2.149\n\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ )\n Returns the excess kurtosis of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.poisson.kurtosis( 11.0 )\n ~0.091\n > v = base.dists.poisson.kurtosis( 4.5 )\n ~0.222\n\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x, λ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.poisson.logpmf( 4.0, 3.0 )\n ~-1.784\n > y = base.dists.poisson.logpmf( 1.0, 3.0 )\n ~-1.901\n > y = base.dists.poisson.logpmf( -1.0, 2.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.logpmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.logpmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.logpmf( 2.0, 0.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, 0.0 )\n 0.0\n\n\nbase.dists.poisson.logpmf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n > var y = mylogpmf( 3.0 )\n ~-2.792\n > y = mylogpmf( 1.0 )\n ~-1.0\n\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n > var y = mylogpmf( 3.0 )\n ~-2.792\n > y = mylogpmf( 1.0 )\n ~-1.0","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ )\n Returns the expected value of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.poisson.mean( 11.0 )\n 11.0\n > v = base.dists.poisson.mean( 4.5 )\n 4.5\n\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ )\n Returns the median of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.poisson.median( 11.0 )\n 11\n > v = base.dists.poisson.median( 4.5 )\n 4\n\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x, λ )\n Evaluates the moment-generating function (MGF) for a Poisson distribution\n with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.poisson.mgf( 1.0, 1.5 )\n ~13.163\n > y = base.dists.poisson.mgf( 0.5, 0.5 )\n ~1.383\n > y = base.dists.poisson.mgf( NaN, 0.5 )\n NaN\n > y = base.dists.poisson.mgf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.mgf( -2.0, -1.0 )\n NaN\n\n\nbase.dists.poisson.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n > var y = myMGF( 0.1 )\n ~1.234\n\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n > var y = myMGF( 0.1 )\n ~1.234","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ )\n Returns the mode of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.poisson.mode( 11.0 )\n 11\n > v = base.dists.poisson.mode( 4.5 )\n 4\n\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x, λ )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.poisson.pmf( 4.0, 3.0 )\n ~0.168\n > y = base.dists.poisson.pmf( 1.0, 3.0 )\n ~0.149\n > y = base.dists.poisson.pmf( -1.0, 2.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.pmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.pmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.pmf( 2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.pmf.factory( λ )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n > var y = mypmf( 3.0 )\n ~0.061\n > y = mypmf( 1.0 )\n ~0.368\n\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n > var y = mypmf( 3.0 )\n ~0.061\n > y = mypmf( 1.0 )\n ~0.368","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ] )\n Returns a Poisson distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Mean parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n poisson: Object\n Distribution instance.\n\n poisson.lambda: number\n Mean parameter. If set, the value must be greater than `0`.\n\n poisson.entropy: number\n Read-only property which returns the differential entropy.\n\n poisson.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n poisson.mean: number\n Read-only property which returns the expected value.\n\n poisson.median: number\n Read-only property which returns the median.\n\n poisson.mode: number\n Read-only property which returns the mode.\n\n poisson.skewness: number\n Read-only property which returns the skewness.\n\n poisson.stdev: number\n Read-only property which returns the standard deviation.\n\n poisson.variance: number\n Read-only property which returns the variance.\n\n poisson.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n poisson.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n poisson.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n poisson.pmf: Function\n Evaluates the probability mass function (PMF).\n\n poisson.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var poisson = base.dists.poisson.Poisson( 6.0 );\n > poisson.lambda\n 6.0\n > poisson.entropy\n ~2.3\n > poisson.kurtosis\n ~0.167\n > poisson.mean\n 6.0\n > poisson.median\n 6.0\n > poisson.mode\n 6.0\n > poisson.skewness\n ~0.408\n > poisson.stdev\n ~2.449\n > poisson.variance\n 6.0\n > poisson.cdf( 4.0 )\n ~0.285\n > poisson.logpmf( 2.0 )\n ~-3.11\n > poisson.mgf( 0.5 )\n ~49.025\n > poisson.pmf( 2.0 )\n ~0.045\n > poisson.quantile( 0.5 )\n 6.0\n\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p, λ )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.poisson.quantile( 0.5, 2.0 )\n 2\n > y = base.dists.poisson.quantile( 0.9, 4.0 )\n 7\n > y = base.dists.poisson.quantile( 0.1, 200.0 )\n 182\n\n > y = base.dists.poisson.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.poisson.quantile( -0.2, 0.0 )\n NaN\n\n > y = base.dists.poisson.quantile( NaN, 0.5 )\n NaN\n > y = base.dists.poisson.quantile( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.quantile( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.quantile( 0.1, 0.0 )\n 0.0\n > y = base.dists.poisson.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.poisson.quantile.factory( λ )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n 0.0\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n 0.0\n > y = myQuantile( 1.0 )\n Infinity","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ )\n Returns the skewness of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.poisson.skewness( 11.0 )\n ~0.302\n > v = base.dists.poisson.skewness( 4.5 )\n ~0.471\n\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ )\n Returns the standard deviation of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.poisson.stdev( 11.0 )\n ~3.317\n > v = base.dists.poisson.stdev( 4.5 )\n ~2.121\n\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ )\n Returns the variance of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.poisson.variance( 11.0 )\n 11.0\n > v = base.dists.poisson.variance( 4.5 )\n 4.5\n\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x, sigma )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\n ~0.199\n > y = base.dists.rayleigh.cdf( 1.0, 2.0 )\n ~0.118\n > y = base.dists.rayleigh.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.cdf( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.rayleigh.cdf( 2.0, 0.0 )\n 1.0\n\n\nbase.dists.rayleigh.cdf.factory( sigma )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n > var y = myCDF( 1.0 )\n ~0.865\n > y = myCDF( 0.5 )\n ~0.393\n\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n > var y = myCDF( 1.0 )\n ~0.865\n > y = myCDF( 0.5 )\n ~0.393","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ )\n Returns the differential entropy of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.rayleigh.entropy( 11.0 )\n ~3.34\n > v = base.dists.rayleigh.entropy( 4.5 )\n ~2.446\n\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ )\n Returns the excess kurtosis of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.rayleigh.kurtosis( 11.0 )\n ~0.245\n > v = base.dists.rayleigh.kurtosis( 4.5 )\n ~0.245\n\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x, sigma )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\n ~-1.613\n > y = base.dists.rayleigh.logcdf( 1.0, 2.0 )\n ~-2.141\n > y = base.dists.rayleigh.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.rayleigh.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.logcdf( 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logcdf.factory( sigma )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n > var y = mylogcdf( 1.0 )\n ~-0.145\n > y = mylogcdf( 0.5 )\n ~-0.933\n\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n > var y = mylogcdf( 1.0 )\n ~-0.145\n > y = mylogcdf( 0.5 )\n ~-0.933","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x, sigma )\n Evaluates the logarithm of the probability density function (PDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\n ~-1.249\n > y = base.dists.rayleigh.logpdf( 2.0, 0.8 )\n ~-1.986\n > y = base.dists.rayleigh.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.rayleigh.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.logpdf( NaN, 2.0 )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logpdf.factory( sigma )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n > var y = mylogpdf( 6.0 )\n ~-2.106\n > y = mylogpdf( 4.0 )\n ~-1.886\n\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n > var y = mylogpdf( 6.0 )\n ~-2.106\n > y = mylogpdf( 4.0 )\n ~-1.886","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ )\n Returns the expected value of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mean( 11.0 )\n ~13.786\n > v = base.dists.rayleigh.mean( 4.5 )\n ~5.64\n\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ )\n Returns the median of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.rayleigh.median( 11.0 )\n ~12.952\n > v = base.dists.rayleigh.median( 4.5 )\n ~5.298\n\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t, sigma )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\n ~678.508\n > y = base.dists.rayleigh.mgf( 1.0, 2.0 )\n ~38.65\n > y = base.dists.rayleigh.mgf( -1.0, 4.0 )\n ~-0.947\n > y = base.dists.rayleigh.mgf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.mgf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.mgf( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.mgf.factory( sigma )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n > var y = myMGF( 1.0 )\n ~2.715\n > y = myMGF( 0.5 )\n ~1.888\n\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n > var y = myMGF( 1.0 )\n ~2.715\n > y = myMGF( 0.5 )\n ~1.888","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ )\n Returns the mode of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mode( 11.0 )\n 11.0\n > v = base.dists.rayleigh.mode( 4.5 )\n 4.5\n\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x, sigma )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\n ~0.287\n > y = base.dists.rayleigh.pdf( 2.0, 0.8 )\n ~0.137\n > y = base.dists.rayleigh.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.pdf( NaN, 2.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.pdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, 0.0 )\n Infinity\n > y = base.dists.rayleigh.pdf( 2.0, 0.0 )\n 0.0\n\n\nbase.dists.rayleigh.pdf.factory( sigma )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n > var y = myPDF( 6.0 )\n ~0.122\n > y = myPDF( 4.0 )\n ~0.152\n\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n > var y = myPDF( 6.0 )\n ~0.122\n > y = myPDF( 4.0 )\n ~0.152","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p, sigma )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative probability for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\n ~1.794\n > y = base.dists.rayleigh.quantile( 0.5, 4.0 )\n ~4.71\n\n > y = base.dists.rayleigh.quantile( 1.1, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( -0.2, 1.0 )\n NaN\n\n > y = base.dists.rayleigh.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.quantile.factory( sigma )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~0.404\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~0.404\n > y = myQuantile( 1.0 )\n Infinity","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ] )\n Returns a Rayleigh distribution object.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n rayleigh: Object\n Distribution instance.\n\n rayleigh.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n rayleigh.entropy: number\n Read-only property which returns the differential entropy.\n\n rayleigh.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n rayleigh.mean: number\n Read-only property which returns the expected value.\n\n rayleigh.median: number\n Read-only property which returns the median.\n\n rayleigh.mode: number\n Read-only property which returns the mode.\n\n rayleigh.skewness: number\n Read-only property which returns the skewness.\n\n rayleigh.stdev: number\n Read-only property which returns the standard deviation.\n\n rayleigh.variance: number\n Read-only property which returns the variance.\n\n rayleigh.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n rayleigh.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n rayleigh.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n rayleigh.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n rayleigh.pdf: Function\n Evaluates the probability density function (PDF).\n\n rayleigh.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\n > rayleigh.sigma\n 6.0\n > rayleigh.entropy\n ~2.734\n > rayleigh.kurtosis\n ~0.245\n > rayleigh.mean\n ~7.52\n > rayleigh.median\n ~7.064\n > rayleigh.mode\n 6.0\n > rayleigh.skewness\n ~0.631\n > rayleigh.stdev\n ~3.931\n > rayleigh.variance\n ~15.451\n > rayleigh.cdf( 1.0 )\n ~0.014\n > rayleigh.logcdf( 1.0 )\n ~-4.284\n > rayleigh.logpdf( 1.5 )\n ~-3.209\n > rayleigh.mgf( -0.5 )\n ~-0.91\n > rayleigh.pdf( 1.5 )\n ~0.04\n > rayleigh.quantile( 0.5 )\n ~7.064\n\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ )\n Returns the skewness of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.rayleigh.skewness( 11.0 )\n ~0.631\n > v = base.dists.rayleigh.skewness( 4.5 )\n ~0.631\n\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ )\n Returns the standard deviation of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.rayleigh.stdev( 9.0 )\n ~5.896\n > v = base.dists.rayleigh.stdev( 4.5 )\n ~2.948\n\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ )\n Returns the variance of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.rayleigh.variance( 9.0 )\n ~34.765\n > v = base.dists.rayleigh.variance( 4.5 )\n ~8.691\n\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x, n )\n Evaluates the cumulative distribution function (CDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `x`, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.signrank.cdf( 3, 7 )\n ~0.039\n > y = base.dists.signrank.cdf( 1.8, 3 )\n ~0.375\n > y = base.dists.signrank.cdf( -1.0, 40 )\n 0.0\n > y = base.dists.signrank.cdf( NaN, 10 )\n NaN\n > y = base.dists.signrank.cdf( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.cdf.factory( n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.signrank.cdf.factory( 8 );\n > var y = myCDF( 5.7 )\n ~0.055\n > y = myCDF( 2.2 )\n ~0.012\n\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.signrank.cdf.factory( 8 );\n > var y = myCDF( 5.7 )\n ~0.055\n > y = myCDF( 2.2 )\n ~0.012","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x, n )\n Evaluates the probability density function (PDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `x`, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.signrank.pdf( 3, 7 )\n ~0.0156\n > y = base.dists.signrank.pdf( 1.8, 3 )\n 0.0\n > y = base.dists.signrank.pdf( -1.0, 40 )\n 0.0\n > y = base.dists.signrank.pdf( NaN, 10 )\n NaN\n > y = base.dists.signrank.pdf( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.pdf.factory( n )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.signrank.pdf.factory( 8 );\n > var y = myPDF( 6.0 )\n ~0.0156\n > y = myPDF( 2.0 )\n ~0.0039\n\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.signrank.pdf.factory( 8 );\n > var y = myPDF( 6.0 )\n ~0.0156\n > y = myPDF( 2.0 )\n ~0.0039","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p, n )\n Evaluates the quantile function for the Wilcoxon signed rank test statistic\n with `n` observations at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.signrank.quantile( 0.8, 5 )\n 11\n > y = base.dists.signrank.quantile( 0.5, 4 )\n 5\n\n > y = base.dists.signrank.quantile( 1.1, 5 )\n NaN\n > y = base.dists.signrank.quantile( -0.2, 5 )\n NaN\n\n > y = base.dists.signrank.quantile( NaN, 5 )\n NaN\n > y = base.dists.signrank.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.quantile.factory( n )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n > var y = myQuantile( 0.4 )\n 16\n > y = myQuantile( 1.0 )\n 36\n\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n > var y = myQuantile( 0.4 )\n 16\n > y = myQuantile( 1.0 )\n 36","base.dists.t.cdf":"\nbase.dists.t.cdf( x, v )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.t.cdf( 2.0, 0.1 )\n ~0.611\n > y = base.dists.t.cdf( 1.0, 2.0 )\n ~0.789\n > y = base.dists.t.cdf( -1.0, 4.0 )\n ~0.187\n > y = base.dists.t.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.t.cdf( 0.0, NaN )\n NaN\n > y = base.dists.t.cdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.cdf.factory( v )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.t.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n ~0.816\n > y = mycdf( 1.0 )\n ~0.699\n\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.t.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n ~0.816\n > y = mycdf( 1.0 )\n ~0.699","base.dists.t.entropy":"\nbase.dists.t.entropy( v )\n Returns the differential entropy of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.t.entropy( 11.0 )\n ~1.512\n > v = base.dists.t.entropy( 4.5 )\n ~1.652\n\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v )\n Returns the excess kurtosis of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 2`, the function returns `NaN`.\n\n If provided `2 < v <= 4`, the function returns positive infinity.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.t.kurtosis( 11.0 )\n ~0.857\n > v = base.dists.t.kurtosis( 4.5 )\n 12.0\n\n","base.dists.t.mean":"\nbase.dists.t.mean( v )\n Returns the expected value of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.t.mean( 11.0 )\n 0.0\n > v = base.dists.t.mean( 4.5 )\n 0.0\n\n","base.dists.t.median":"\nbase.dists.t.median( v )\n Returns the median of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.t.median( 11.0 )\n 0.0\n > v = base.dists.t.median( 4.5 )\n 0.0\n\n","base.dists.t.mode":"\nbase.dists.t.mode( v )\n Returns the mode of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.t.mode( 11.0 )\n 0.0\n > v = base.dists.t.mode( 4.5 )\n 0.0\n\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x, v )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.t.pdf( 0.3, 4.0 )\n ~0.355\n > y = base.dists.t.pdf( 2.0, 0.7 )\n ~0.058\n > y = base.dists.t.pdf( -1.0, 0.5 )\n ~0.118\n > y = base.dists.t.pdf( 0.0, NaN )\n NaN\n > y = base.dists.t.pdf( NaN, 2.0 )\n NaN\n > y = base.dists.t.pdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.pdf.factory( v )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.t.pdf.factory( 3.0 );\n > var y = myPDF( 1.0 )\n ~0.207\n\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.t.pdf.factory( 3.0 );\n > var y = myPDF( 1.0 )\n ~0.207","base.dists.t.quantile":"\nbase.dists.t.quantile( p, v )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.t.quantile( 0.8, 1.0 )\n ~1.376\n > y = base.dists.t.quantile( 0.1, 1.0 )\n ~-3.078\n > y = base.dists.t.quantile( 0.5, 0.1 )\n 0.0\n\n > y = base.dists.t.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.t.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.t.quantile( 0.0, NaN )\n NaN\n\n > y = base.dists.t.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.t.quantile.factory( v )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n > var y = myQuantile( 0.2 )\n ~-0.941\n > y = myQuantile( 0.9 )\n ~1.533\n\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n > var y = myQuantile( 0.2 )\n ~-0.941\n > y = myQuantile( 0.9 )\n ~1.533","base.dists.t.skewness":"\nbase.dists.t.skewness( v )\n Returns the skewness of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 3`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.t.skewness( 11.0 )\n 0.0\n > v = base.dists.t.skewness( 4.5 )\n 0.0\n\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v )\n Returns the standard deviation of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.t.stdev( 9.0 )\n ~1.134\n > v = base.dists.t.stdev( 4.5 )\n ~1.342\n\n","base.dists.t.T":"\nbase.dists.t.T( [v] )\n Returns a Student's t distribution object.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n t: Object\n Distribution instance.\n\n t.v: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n t.entropy: number\n Read-only property which returns the differential entropy.\n\n t.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n t.mean: number\n Read-only property which returns the expected value.\n\n t.median: number\n Read-only property which returns the median.\n\n t.mode: number\n Read-only property which returns the mode.\n\n t.skewness: number\n Read-only property which returns the skewness.\n\n t.stdev: number\n Read-only property which returns the standard deviation.\n\n t.variance: number\n Read-only property which returns the variance.\n\n t.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n t.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n t.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n t.pdf: Function\n Evaluates the probability density function (PDF).\n\n t.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var t = base.dists.t.T( 6.0 );\n > t.v\n 6.0\n > t.entropy\n ~1.592\n > t.kurtosis\n 3.0\n > t.mean\n 0.0\n > t.median\n 0.0\n > t.mode\n 0.0\n > t.skewness\n 0.0\n > t.stdev\n ~1.225\n > t.variance\n 1.5\n > t.cdf( 1.0 )\n ~0.822\n > t.logcdf( 1.0 )\n ~-0.196\n > t.logpdf( 1.5 )\n ~-2.075\n > t.pdf( 1.5 )\n ~0.126\n > t.quantile( 0.8 )\n ~0.906\n\n","base.dists.t.variance":"\nbase.dists.t.variance( v )\n Returns the variance of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.t.variance( 9.0 )\n ~1.286\n > v = base.dists.t.variance( 4.5 )\n ~1.8\n\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x, a, b, c )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\n 0.875\n > y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\n 0.75\n > y = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.278\n > y = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.cdf.factory( a, b, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n > var y = mycdf( 0.5 )\n 0.0125\n > y = mycdf( 8.0 )\n 0.95\n\n\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a, b, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n > var y = mycdf( 0.5 )\n 0.0125\n > y = mycdf( 8.0 )\n 0.95","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a, b, c )\n Returns the differential entropy of a triangular distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\n ~-0.193\n > v = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\n ~1.886\n > v = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n ~1.599\n\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a, b, c )\n Returns the excess kurtosis of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\n -0.6\n > v = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\n -0.6\n > v = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n -0.6\n\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x, a, b, c )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.134\n > y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\n ~-0.288\n > y = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\n ~-1.281\n > y = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logcdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n > var y = mylogcdf( 0.5 )\n ~-4.382\n > y = mylogcdf( 8.0 )\n ~-0.051\n\n\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n > var y = mylogcdf( 0.5 )\n ~-4.382\n > y = mylogcdf( 8.0 )\n ~-0.051","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x, a, b, c )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.693\n > y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\n 0.0\n > y = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\n ~-2.89\n > y = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logpdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n > var y = mylogpdf( 2.0 )\n ~-2.526\n > y = mylogpdf( 12.0 )\n -Infinity\n\n\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n > var y = mylogpdf( 2.0 )\n ~-2.526\n > y = mylogpdf( 12.0 )\n -Infinity","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a, b, c )\n Returns the expected value of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\n ~0.6\n > v = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\n 7.0\n > v = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a, b, c )\n Returns the median of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\n ~0.632\n > v = base.dists.triangular.median( 4.0, 12.0, 5.0 )\n ~6.708\n > v = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t, a, b, c )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\n ~1.021\n > y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\n ~1.111\n > y = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\n ~24.334\n > y = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\n ~1.381\n > y = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.mgf.factory( a, b, c )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n > var y = mymgf( -1.0 )\n ~0.3996\n > y = mymgf( 2.0 )\n ~10.205\n\n\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a, b, c )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n > var y = mymgf( -1.0 )\n ~0.3996\n > y = mymgf( 2.0 )\n ~10.205","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a, b, c )\n Returns the mode of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\n 0.8\n > v = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\n 5.0\n > v = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x, a, b, c )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\n 0.5\n > y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\n 1.0\n > y = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.056\n > y = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.pdf.factory( a, b, c )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n > var y = mypdf( 2.0 )\n 0.08\n > y = mypdf( 12.0 )\n 0.0\n\n\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a, b, c )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n > var y = mypdf( 2.0 )\n 0.08\n > y = mypdf( 12.0 )\n 0.0","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p, a, b, c )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\n ~0.553\n > y = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\n ~-0.452\n > y = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\n -14.0\n > y = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\n ~11.056\n\n > y = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\n NaN\n\n > y = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\n NaN\n\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.quantile.factory( a, b, c )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n > var y = myquantile( 0.4 )\n ~2.658\n > y = myquantile( 0.8 )\n ~3.225\n\n\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a, b, c )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n > var y = myquantile( 0.4 )\n ~2.658\n > y = myquantile( 0.8 )\n ~3.225","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a, b, c )\n Returns the skewness of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\n ~-0.476\n > v = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\n ~0.532\n > v = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n 0.0\n\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a, b, c )\n Returns the standard deviation of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\n ~0.216\n > v = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\n ~1.78\n > v = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n ~1.225\n\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a, b, c] )\n Returns a triangular distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b` and `c`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a` and `c`. Default: `1.0`.\n\n c: number (optional)\n Mode. Must be greater than `a` and smaller than `b`. Default: `0.5`.\n\n Returns\n -------\n triangular: Object\n Distribution instance.\n\n triangular.a: number\n Minimum support. If set, the value must be smaller or equal to `b` and\n `c`.\n\n triangular.b: number\n Maximum support. If set, the value must be greater than or equal to `a`\n and `c`.\n\n triangular.c: number\n Mode. If set, the value must be greater than or equal to `a` and smaller\n than or equal to `b`.\n\n triangular.entropy: number\n Read-only property which returns the differential entropy.\n\n triangular.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n triangular.mean: number\n Read-only property which returns the expected value.\n\n triangular.median: number\n Read-only property which returns the median.\n\n triangular.mode: number\n Read-only property which returns the mode.\n\n triangular.skewness: number\n Read-only property which returns the skewness.\n\n triangular.stdev: number\n Read-only property which returns the standard deviation.\n\n triangular.variance: number\n Read-only property which returns the variance.\n\n triangular.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n triangular.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n triangular.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n triangular.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n triangular.pdf: Function\n Evaluates the probability density function (PDF).\n\n triangular.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\n > triangular.a\n 0.0\n > triangular.b\n 1.0\n > triangular.c\n 0.5\n > triangular.entropy\n ~-0.193\n > triangular.kurtosis\n -0.6\n > triangular.mean\n 0.5\n > triangular.median\n 0.5\n > triangular.mode\n 0.5\n > triangular.skewness\n 0.0\n > triangular.stdev\n ~0.204\n > triangular.variance\n ~0.042\n > triangular.cdf( 0.8 )\n 0.92\n > triangular.logcdf( 0.8 )\n ~-0.083\n > triangular.logpdf( 0.8 )\n ~-0.223\n > triangular.mgf( 0.8 )\n ~1.512\n > triangular.pdf( 0.8 )\n ~0.8\n > triangular.quantile( 0.8 )\n ~0.684\n\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a, b, c )\n Returns the variance of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\n ~0.047\n > v = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\n ~3.167\n > v = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n ~1.5\n\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\n 0.9\n > y = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\n 0.25\n > y = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8\n\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a, b )\n Returns the differential entropy of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.uniform.entropy( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.entropy( 4.0, 12.0 )\n ~2.079\n > v = base.dists.uniform.entropy( 2.0, 8.0 )\n ~1.792\n\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a, b )\n Returns the excess kurtosis of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 4.0, 12.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 2.0, 8.0 )\n -1.2\n\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\n ~-0.105\n > y = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\n ~-1.386\n > y = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223\n\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\n ~-1.386\n > y = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\n -infinity\n > y = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\n 0.0\n > y = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -infinity\n\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -infinity","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a, b )\n Returns the expected value of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.uniform.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a, b )\n Returns the median of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.uniform.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\n ~372.495\n > y = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\n ~0.688\n > y = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\n ~3.195\n > y = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\n NaN\n > y = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.uniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n > var y = mymgf( 0.1 )\n ~1.916\n > y = mymgf( 1.1 )\n ~1339.321\n\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n > var y = mymgf( 0.1 )\n ~1.916\n > y = mymgf( 1.1 )\n ~1339.321","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x, a, b )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\n 0.25\n > y = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\n 1.0\n > y = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n 1.0\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n 1.0\n > y = myPDF( 5.0 )\n 0.0","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p, a, b )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\n 0.8\n > y = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\n 5.0\n\n > y = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n 3.2\n\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n 3.2","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a, b )\n Returns the skewness of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.uniform.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.uniform.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a, b )\n Returns the standard deviation of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.uniform.stdev( 0.0, 1.0 )\n ~0.289\n > v = base.dists.uniform.stdev( 4.0, 12.0 )\n ~2.309\n > v = base.dists.uniform.stdev( 2.0, 8.0 )\n ~1.732\n\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a, b] )\n Returns a uniform distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n uniform: Object\n Distribution instance.\n\n uniform.a: number\n Minimum support. If set, the value must be smaller than `b`.\n\n uniform.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n uniform.entropy: number\n Read-only property which returns the differential entropy.\n\n uniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n uniform.mean: number\n Read-only property which returns the expected value.\n\n uniform.median: number\n Read-only property which returns the median.\n\n uniform.skewness: number\n Read-only property which returns the skewness.\n\n uniform.stdev: number\n Read-only property which returns the standard deviation.\n\n uniform.variance: number\n Read-only property which returns the variance.\n\n uniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n uniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n uniform.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n uniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n uniform.pdf: Function\n Evaluates the probability density function (PDF).\n\n uniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\n > uniform.a\n 0.0\n > uniform.b\n 1.0\n > uniform.entropy\n 0.0\n > uniform.kurtosis\n -1.2\n > uniform.mean\n 0.5\n > uniform.median\n 0.5\n > uniform.skewness\n 0.0\n > uniform.stdev\n ~0.289\n > uniform.variance\n ~0.083\n > uniform.cdf( 0.8 )\n 0.8\n > uniform.logcdf( 0.5 )\n ~-0.693\n > uniform.logpdf( 1.0 )\n ~-0.0\n > uniform.mgf( 0.8 )\n ~1.532\n > uniform.pdf( 0.8 )\n 1.0\n > uniform.quantile( 0.8 )\n 0.8\n\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a, b )\n Returns the variance of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.uniform.variance( 0.0, 1.0 )\n ~0.083\n > v = base.dists.uniform.variance( 4.0, 12.0 )\n ~5.333\n > v = base.dists.uniform.variance( 2.0, 8.0 )\n 3.0\n\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763\n\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k, λ )\n Returns the differential entropy of a Weibull distribution (in nats).\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.weibull.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.entropy( 4.0, 12.0 )\n ~2.532\n > v = base.dists.weibull.entropy( 8.0, 2.0 )\n ~0.119\n\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k, λ )\n Returns the excess kurtosis of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.weibull.kurtosis( 4.0, 12.0 )\n ~-0.252\n > v = base.dists.weibull.kurtosis( 8.0, 2.0 )\n ~0.328\n\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x, k, λ )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\n ~-0.145\n > y = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27\n\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x, k, λ )\n Evaluates the logarithm of the probability density function (PDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\n ~-3.307\n > y = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863\n\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k, λ )\n Returns the expected value of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.weibull.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.mean( 4.0, 12.0 )\n ~10.877\n > v = base.dists.weibull.mean( 8.0, 2.0 )\n ~1.883\n\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k, λ )\n Returns the median of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.weibull.median( 1.0, 1.0 )\n ~0.693\n > v = base.dists.weibull.median( 4.0, 12.0 )\n ~10.949\n > v = base.dists.weibull.median( 8.0, 2.0 )\n ~1.91\n\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x, k, λ )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\n ~2.0\n > y = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\n ~0.019\n\n > y = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n NaN\n\n\nbase.dists.weibull.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n > var y = myMGF( 0.8 )\n ~3150.149\n > y = myMGF( 0.08 )\n ~2.137\n\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n > var y = myMGF( 0.8 )\n ~3150.149\n > y = myMGF( 0.08 )\n ~2.137","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k, λ )\n Returns the mode of a Weibull distribution.\n\n If `0 < k <= 1`, the function returns `0.0`.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.weibull.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.weibull.mode( 4.0, 12.0 )\n ~11.167\n > v = base.dists.weibull.mode( 8.0, 2.0 )\n ~1.967\n\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\n ~0.037\n > y = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n > var y = myPDF( 7.0 )\n ~0.155\n\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n > var y = myPDF( 7.0 )\n ~0.155","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p, k, λ )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\n ~1.609\n > y = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\n ~3.33\n\n > y = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n > var y = myQuantile( 0.4 )\n ~7.147\n\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n > var y = myQuantile( 0.4 )\n ~7.147","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k, λ )\n Returns the skewness of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.weibull.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.weibull.skewness( 4.0, 12.0 )\n ~-0.087\n > v = base.dists.weibull.skewness( 8.0, 2.0 )\n ~-0.534\n\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k, λ )\n Returns the standard deviation of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.weibull.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.stdev( 4.0, 12.0 )\n ~3.051\n > v = base.dists.weibull.stdev( 8.0, 2.0 )\n ~0.279\n\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k, λ )\n Returns the variance of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.weibull.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.variance( 4.0, 12.0 )\n ~9.311\n > v = base.dists.weibull.variance( 8.0, 2.0 )\n ~0.078\n\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k, λ] )\n Returns a Weibull distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n λ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n weibull: Object\n Distribution instance.\n\n weibull.k: number\n Shape parameter. If set, the value must be greater than `0`.\n\n weibull.lambda: number\n Scale parameter. If set, the value must be greater than `0`.\n\n weibull.entropy: number\n Read-only property which returns the differential entropy.\n\n weibull.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n weibull.mean: number\n Read-only property which returns the expected value.\n\n weibull.median: number\n Read-only property which returns the median.\n\n weibull.mode: number\n Read-only property which returns the mode.\n\n weibull.skewness: number\n Read-only property which returns the skewness.\n\n weibull.stdev: number\n Read-only property which returns the standard deviation.\n\n weibull.variance: number\n Read-only property which returns the variance.\n\n weibull.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n weibull.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n weibull.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n weibull.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n weibull.pdf: Function\n Evaluates the probability density function (PDF).\n\n weibull.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\n > weibull.k\n 6.0\n > weibull.lambda\n 5.0\n > weibull.entropy\n ~1.299\n > weibull.kurtosis\n ~0.035\n > weibull.mean\n ~4.639\n > weibull.median\n ~4.704\n > weibull.mode\n ~4.85\n > weibull.skewness\n ~-0.373\n > weibull.stdev\n ~0.899\n > weibull.variance\n ~0.808\n > weibull.cdf( 3.0 )\n ~0.046\n > weibull.logcdf( 3.0 )\n ~-3.088\n > weibull.logpdf( 1.0 )\n ~-7.865\n > weibull.mgf( -0.5 )\n ~0.075\n > weibull.pdf( 3.0 )\n ~0.089\n > weibull.quantile( 0.8 )\n ~5.413\n\n","base.ellipe":"\nbase.ellipe( m )\n Computes the complete elliptic integral of the second kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipe( 0.5 )\n ~1.351\n > y = base.ellipe( -1.0 )\n ~1.910\n > y = base.ellipe( 2.0 )\n NaN\n > y = base.ellipe( PINF )\n NaN\n > y = base.ellipe( NINF )\n NaN\n > y = base.ellipe( NaN )\n NaN\n\n See Also\n --------\n base.ellipj, base.ellipk\n","base.ellipj":"\nbase.ellipj( u, m )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: Array\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var v = base.ellipj( 0.3, 0.5 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > v = base.ellipj( 0.0, 0.0 )\n [ ~0.0, ~1.0, ~1.0, ~0.0 ]\n > v = base.ellipj( Infinity, 1.0 )\n [ ~1.0, ~0.0, ~0.0, ~1.571 ]\n > v = base.ellipj( 0.0, -2.0)\n [ ~0.0, ~1.0, ~1.0, NaN ]\n > v = base.ellipj( NaN, NaN )\n [ NaN, NaN, NaN, NaN ]\n\n\nbase.ellipj.assign( u, m, out, stride, offset )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var out = new Float64Array( 4 );\n > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > var bool = ( v === out )\n true\n\n\nbase.ellipj.sn( u, m )\n Computes the Jacobi elliptic function sn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function sn.\n\n Examples\n --------\n > var v = base.ellipj.sn( 0.3, 0.5 )\n ~0.293\n\n\nbase.ellipj.cn( u, m )\n Computes the Jacobi elliptic functions cn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function cn.\n\n Examples\n --------\n > var v = base.ellipj.cn( 0.3, 0.5 )\n ~0.956\n\n\nbase.ellipj.dn( u, m )\n Computes the Jacobi elliptic function dn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function dn.\n\n Examples\n --------\n > var v = base.ellipj.dn( 0.3, 0.5 )\n ~0.978\n\n\nbase.ellipj.am( u, m )\n Computes the Jacobi amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function am.\n\n Examples\n --------\n > var v = base.ellipj.am( 0.3, 0.5 )\n ~0.298\n\n See Also\n --------\n base.ellipe, base.ellipk","base.ellipj.assign":"\nbase.ellipj.assign( u, m, out, stride, offset )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var out = new Float64Array( 4 );\n > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > var bool = ( v === out )\n true","base.ellipj.sn":"\nbase.ellipj.sn( u, m )\n Computes the Jacobi elliptic function sn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function sn.\n\n Examples\n --------\n > var v = base.ellipj.sn( 0.3, 0.5 )\n ~0.293","base.ellipj.cn":"\nbase.ellipj.cn( u, m )\n Computes the Jacobi elliptic functions cn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function cn.\n\n Examples\n --------\n > var v = base.ellipj.cn( 0.3, 0.5 )\n ~0.956","base.ellipj.dn":"\nbase.ellipj.dn( u, m )\n Computes the Jacobi elliptic function dn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function dn.\n\n Examples\n --------\n > var v = base.ellipj.dn( 0.3, 0.5 )\n ~0.978","base.ellipj.am":"\nbase.ellipj.am( u, m )\n Computes the Jacobi amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function am.\n\n Examples\n --------\n > var v = base.ellipj.am( 0.3, 0.5 )\n ~0.298\n\n See Also\n --------\n base.ellipe, base.ellipk","base.ellipk":"\nbase.ellipk( m )\n Computes the complete elliptic integral of the first kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipk( 0.5 )\n ~1.854\n > y = base.ellipk( -1.0 )\n ~1.311\n > y = base.ellipk( 2.0 )\n NaN\n > y = base.ellipk( PINF )\n NaN\n > y = base.ellipk( NINF )\n NaN\n > y = base.ellipk( NaN )\n NaN\n\n See Also\n --------\n base.ellipe, base.ellipj\n","base.epsdiff":"\nbase.epsdiff( x, y[, scale] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If computing the relative difference in units of epsilon will result in\n overflow, the function returns the maximum double-precision floating-point\n number.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference in units of double-precision floating-point epsilon.\n\n Examples\n --------\n > var d = base.epsdiff( 12.15, 12.149999999999999 )\n ~0.658\n > d = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n ~64761.512\n\n // Custom scale function:\n > function scale( x, y ) { return ( x > y ) ? y : x; };\n > d = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n ~44\n\n See Also\n --------\n base.absdiff, base.reldiff\n","base.erf":"\nbase.erf( x )\n Evaluates the error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the error function is an odd function (i.e., `erf(-x) == -erf(x)`), if\n provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erf( 2.0 )\n ~0.9953\n > y = base.erf( -1.0 )\n ~-0.8427\n > y = base.erf( -0.0 )\n -0.0\n > y = base.erf( NaN )\n NaN\n\n See Also\n --------\n base.erfc, base.erfinv, base.erfcinv\n","base.erfc":"\nbase.erfc( x )\n Evaluates the complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfc( 2.0 )\n ~0.0047\n > y = base.erfc( -1.0 )\n ~1.8427\n > y = base.erfc( 0.0 )\n 1.0\n > y = base.erfc( PINF )\n 0.0\n > y = base.erfc( NINF )\n 2.0\n > y = base.erfc( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfinv, base.erfcinv, base.erfcx\n","base.erfcinv":"\nbase.erfcinv( x )\n Evaluates the inverse complementary error function.\n\n The domain of `x` is restricted to `[0,2]`. If `x` is outside this interval,\n the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcinv( 0.5 )\n ~0.4769\n > y = base.erfcinv( 0.8 )\n ~0.1791\n > y = base.erfcinv( 0.0 )\n Infinity\n > y = base.erfcinv( 2.0 )\n -Infinity\n > y = base.erfcinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfinv, base.erfcx\n","base.erfcx":"\nbase.erfcx( x )\n Evaluates the scaled complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcx( 1.0 )\n ~0.4276\n > y = base.erfcx( -1.0 )\n ~5.01\n > y = base.erfcx( 0.0 )\n 1.0\n > y = base.erfcx( NaN )\n NaN\n\n See Also\n --------\n base.erfc, base.erfcinv, base.erf, base.erfinv","base.erfinv":"\nbase.erfinv( x )\n Evaluates the inverse error function.\n\n If `|x| > 1`, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the inverse error function is an odd function (i.e., `erfinv(-x) ==\n -erfinv(x)`), if provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfinv( 0.5 )\n ~0.4769\n > y = base.erfinv( 0.8 )\n ~0.9062\n > y = base.erfinv( 0.0 )\n 0.0\n > y = base.erfinv( -0.0 )\n -0.0\n > y = base.erfinv( -1.0 )\n -Infinity\n > y = base.erfinv( 1.0 )\n Infinity\n > y = base.erfinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfcinv\n","base.eta":"\nbase.eta( s )\n Evaluates the Dirichlet eta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.eta( 0.0 )\n 0.5\n > y = base.eta( -1.0 )\n 0.25\n > y = base.eta( 1.0 )\n ~0.6931\n > y = base.eta( 3.14 )\n ~0.9096\n > y = base.eta( NaN )\n NaN\n\n","base.evalpoly":"\nbase.evalpoly( c, x )\n Evaluates a polynomial.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n out: number\n Evaluated polynomial.\n\n Examples\n --------\n > var arr = [ 3.0, 2.0, 1.0 ];\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = base.evalpoly( arr, 10.0 )\n 123.0\n\n\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var polyval = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = polyval( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = polyval( 5.0 )\n 38.0\n\n See Also\n --------\n base.evalrational\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var polyval = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = polyval( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = polyval( 5.0 )\n 38.0\n\n See Also\n --------\n base.evalrational","base.evalrational":"\nbase.evalrational( P, Q, x )\n Evaluates a rational function.\n\n A rational function `f(x)` is defined as\n\n P(x)\n f(x) = ----\n Q(x)\n\n where both `P(x)` and `Q(x)` are polynomials in `x`.\n\n The coefficients for both `P` and `Q` should be sorted in ascending degree.\n\n For polynomials of different degree, the coefficient array for the lower\n degree polynomial should be padded with zeros.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the rational function.\n\n Returns\n -------\n out: number\n Evaluated rational function.\n\n Examples\n --------\n // 2x^3 + 4x^2 - 5x^1 - 6x^0\n > var P = [ -6.0, -5.0, 4.0, 2.0 ];\n\n // 0.5x^1 + 3x^0\n > var Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n // Evaluate the rational function:\n > var v = base.evalrational( P, Q, 6.0 )\n 90.0\n\n\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var rational = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = rational( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = rational( 2.0 )\n 1.5\n\n See Also\n --------\n base.evalpoly\n","base.evalrational.factory":"\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var rational = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = rational( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = rational( 2.0 )\n 1.5\n\n See Also\n --------\n base.evalpoly","base.exp":"\nbase.exp( x )\n Evaluates the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp( 4.0 )\n ~54.5982\n > y = base.exp( -9.0 )\n ~1.234e-4\n > y = base.exp( 0.0 )\n 1.0\n > y = base.exp( NaN )\n NaN\n\n See Also\n --------\n base.exp10, base.exp2, base.expm1, base.ln\n","base.exp2":"\nbase.exp2( x )\n Evaluates the base 2 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp2( 3.0 )\n 8.0\n > y = base.exp2( -9.0 )\n ~0.002\n > y = base.exp2( 0.0 )\n 1.0\n > y = base.exp2( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp10, base.log2\n","base.exp10":"\nbase.exp10( x )\n Evaluates the base 10 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp10( 3.0 )\n 1000\n > y = base.exp10( -9.0 )\n 1.0e-9\n > y = base.exp10( 0.0 )\n 1.0\n > y = base.exp10( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp2, base.log10\n","base.expit":"\nbase.expit( x )\n Evaluates the standard logistic function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expit( 0.0 )\n 0.5\n > y = base.expit( 1.0 )\n ~0.731\n > y = base.expit( -1.0 )\n ~0.269\n > y = base.expit( Infinity )\n 1.0\n > y = base.expit( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.logit","base.expm1":"\nbase.expm1( x )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1( 0.2 )\n ~0.221\n > y = base.expm1( -9.0 )\n ~-1.0\n > y = base.expm1( 0.0 )\n 0.0\n > y = base.expm1( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.expm1rel\n","base.expm1rel":"\nbase.expm1rel( x )\n Relative error exponential.\n\n When `x` is near zero,\n\n e^x - 1\n\n can suffer catastrophic cancellation (i.e., significant loss of precision).\n This function avoids the loss of precision when `x` is near zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1rel( 0.0 )\n 1.0\n > y = base.expm1rel( 1.0 )\n ~1.718\n > y = base.expm1rel( -1.0 )\n ~0.632\n > y = base.expm1rel( NaN )\n NaN\n\t\n See Also\n --------\n base.exp, base.expm1\n","base.exponent":"\nbase.exponent( x )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponent( 3.14e-307 )\n -1019\n > exponent = base.exponent( -3.14 )\n 1\n > exponent = base.exponent( 0.0 )\n -1023\n > exponent = base.exponent( NaN )\n 1024\n\n See Also\n --------\n base.exponentf\n","base.exponentf":"\nbase.exponentf( x )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\n 114\n > exponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\n -112\n > exponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\n 1\n > exponent = base.exponentf( 0.0 )\n -127\n > exponent = base.exponentf( NaN )\n 128\n\n See Also\n --------\n base.exponent\n","base.factorial":"\nbase.factorial( x )\n Evaluates the factorial of `x`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Factorial.\n\n Examples\n --------\n > var y = base.factorial( 3.0 )\n 6.0\n > y = base.factorial( -1.5 )\n ~-3.545\n > y = base.factorial( -0.5 )\n ~1.772\n > y = base.factorial( 0.5 )\n ~0.886\n > y = base.factorial( -10.0 )\n NaN\n > y = base.factorial( 171.0 )\n Infinity\n > y = base.factorial( NaN )\n NaN\n\n See Also\n --------\n base.factorialln\n","base.factorial2":"\nbase.factorial2( n )\n Evaluates the double factorial of `n`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: number\n Input value.\n\n Returns\n -------\n y: number\n Double factorial.\n\n Examples\n --------\n > var y = base.factorial2( 3 )\n 3\n > y = base.factorial2( 5 )\n 15\n > y = base.factorial2( 6 )\n 48\n > y = base.factorial2( 301 )\n Infinity\n > y = base.factorial2( NaN )\n NaN\n\n See Also\n --------\n base.factorial\n","base.factorialln":"\nbase.factorialln( x )\n Evaluates the natural logarithm of the factorial of `x`.\n\n For input values other than negative integers, the function returns\n\n ln( x! ) = ln( Γ(x+1) )\n\n where `Γ` is the Gamma function. For negative integers, the function returns\n `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the factorial of `x`.\n\n Examples\n --------\n > var y = base.factorialln( 3.0 )\n ~1.792\n > y = base.factorialln( 2.4 )\n ~1.092\n > y = base.factorialln( -1.0 )\n NaN\n > y = base.factorialln( -1.5 )\n ~1.266\n > y = base.factorialln( NaN )\n NaN\n\n See Also\n --------\n base.factorial\n","base.fallingFactorial":"\nbase.fallingFactorial( x, n )\n Computes the falling factorial of `x` and `n`.\n\n If not provided a nonnegative integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.fallingFactorial( 0.9, 5 )\n ~0.644\n > v = base.fallingFactorial( -9.0, 3 )\n -990.0\n > v = base.fallingFactorial( 0.0, 2 )\n 0.0\n > v = base.fallingFactorial( 3.0, -2 )\n NaN\n\n See Also\n --------\n base.risingFactorial\n","base.fibonacci":"\nbase.fibonacci( n )\n Computes the nth Fibonacci number.\n\n Fibonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2}\n\n with seed values F_0 = 0 and F_1 = 1.\n\n If `n` is greater than `78`, the function returns `NaN`, as larger Fibonacci\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Fibonacci number.\n\n Examples\n --------\n > var y = base.fibonacci( 0 )\n 0\n > y = base.fibonacci( 1 )\n 1\n > y = base.fibonacci( 2 )\n 1\n > y = base.fibonacci( 3 )\n 2\n > y = base.fibonacci( 4 )\n 3\n > y = base.fibonacci( 79 )\n NaN\n > y = base.fibonacci( NaN )\n NaN\n\n See Also\n --------\n base.binet, base.fibonacciIndex, base.lucas, base.negafibonacci\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F )\n Computes the Fibonacci number index.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `F <= 1` or `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n F: integer\n Fibonacci number.\n\n Returns\n -------\n n: number\n Fibonacci number index.\n\n Examples\n --------\n > var n = base.fibonacciIndex( 2 )\n 3\n > n = base.fibonacciIndex( 3 )\n 4\n > n = base.fibonacciIndex( 5 )\n 5\n > n = base.fibonacciIndex( NaN )\n NaN\n > n = base.fibonacciIndex( 1 )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.fibpoly":"\nbase.fibpoly( n, x )\n Evaluates a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Fibonacci polynomial.\n\n Returns\n -------\n out: number\n Evaluated Fibonacci polynomial.\n\n Examples\n --------\n // 2^4 + 3*2^2 + 1\n > var v = base.fibpoly( 5, 2.0 )\n 29.0\n\n\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n See Also\n --------\n base.evalpoly, base.lucaspoly\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n See Also\n --------\n base.evalpoly, base.lucaspoly","base.firstCodePoint":"\nbase.firstCodePoint( str, n )\n Returns the first `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstCodePoint( 'beep', 1 )\n 'b'\n > out = base.firstCodePoint( 'Boop', 1 )\n 'B'\n > out = base.firstCodePoint( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodeUnit, base.firstGraphemeCluster, firstChar\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str, n )\n Returns the first `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstCodeUnit( 'beep', 1 )\n 'b'\n > out = base.firstCodeUnit( 'Boop', 1 )\n 'B'\n > out = base.firstCodeUnit( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodePoint, base.firstGraphemeCluster, firstChar\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str, n )\n Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstGraphemeCluster( 'beep', 1 )\n 'b'\n > out = base.firstGraphemeCluster( 'Boop', 1 )\n 'B'\n > out = base.firstGraphemeCluster( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodeUnit, base.firstCodePoint, firstChar\n","base.flipsign":"\nbase.flipsign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `2047`, a significand greater than `0`, and a sign bit equal to either `1`\n or `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`; otherwise, behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsign( -3.0, 10.0 )\n -3.0\n > z = base.flipsign( -3.0, -1.0 )\n 3.0\n > z = base.flipsign( 1.0, -0.0 )\n -1.0\n > z = base.flipsign( -3.0, -0.0 )\n 3.0\n > z = base.flipsign( -0.0, 1.0 )\n -0.0\n > z = base.flipsign( 0.0, -1.0 )\n -0.0\n\n See Also\n --------\n base.copysign\n","base.flipsignf":"\nbase.flipsignf( x, y )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `255`, a significand greater than `0`, and a sign bit equal to either `1` or\n `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`; otherwise, behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Single-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsignf( -3.0, 10.0 )\n -3.0\n > z = base.flipsignf( -3.0, -1.0 )\n 3.0\n > z = base.flipsignf( 1.0, -0.0 )\n -1.0\n > z = base.flipsignf( -3.0, -0.0 )\n 3.0\n > z = base.flipsignf( -0.0, 1.0 )\n -0.0\n > z = base.flipsignf( 0.0, -1.0 )\n -0.0\n\n See Also\n --------\n base.copysignf, base.flipsign\n","base.float32ToInt32":"\nbase.float32ToInt32( x )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\n 0\n > y = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\n -3\n > y = base.float32ToInt32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToInt32( FLOAT32_PINF )\n 0\n > y = base.float32ToInt32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToUint32","base.float32ToUint32":"\nbase.float32ToUint32( x )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\n 0\n > y = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\n 4294967293\n > y = base.float32ToUint32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToUint32( FLOAT32_PINF )\n 0\n > y = base.float32ToUint32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToInt32","base.float64ToFloat32":"\nbase.float64ToFloat32( x )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: float\n Nearest single-precision floating-point number.\n\n Examples\n --------\n > var y = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n","base.float64ToInt32":"\nbase.float64ToInt32( x )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToInt32( 4294967295.0 )\n -1\n > y = base.float64ToInt32( 3.14 )\n 3\n > y = base.float64ToInt32( -3.14 )\n -3\n > y = base.float64ToInt32( NaN )\n 0\n > y = base.float64ToInt32( PINF )\n 0\n > y = base.float64ToInt32( NINF )\n 0\n\n See Also\n --------\n base.float64ToUint32","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness).\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n Returns\n -------\n out: Uint8Array\n Byte array.\n\n Examples\n --------\n > var y = base.float64ToInt64Bytes( 4294967297.0 )\n \n\n\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Uint8Array( 16 );\n > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n \n\n See Also\n --------\n base.float64ToInt32","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Uint8Array( 16 );\n > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n \n\n See Also\n --------\n base.float64ToInt32","base.float64ToUint32":"\nbase.float64ToUint32( x )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToUint32( 4294967297.0 )\n 1\n > y = base.float64ToUint32( 3.14 )\n 3\n > y = base.float64ToUint32( -3.14 )\n 4294967293\n > y = base.float64ToUint32( NaN )\n 0\n > y = base.float64ToUint32( PINF )\n 0\n > y = base.float64ToUint32( NINF )\n 0\n\n See Also\n --------\n base.float64ToInt32","base.floor":"\nbase.floor( x )\n Rounds a double-precision floating-point number toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor( 3.14 )\n 3.0\n > y = base.floor( -4.2 )\n -5.0\n > y = base.floor( -4.6 )\n -5.0\n > y = base.floor( 9.5 )\n 9.0\n > y = base.floor( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.round\n","base.floor2":"\nbase.floor2( x )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor2( 3.14 )\n 2.0\n > y = base.floor2( -4.2 )\n -8.0\n > y = base.floor2( -4.6 )\n -8.0\n > y = base.floor2( 9.5 )\n 8.0\n > y = base.floor2( 13.0 )\n 8.0\n > y = base.floor2( -13.0 )\n -16.0\n > y = base.floor2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor, base.floor10, base.round2\n","base.floor10":"\nbase.floor10( x )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor10( 3.14 )\n 1.0\n > y = base.floor10( -4.2 )\n -10.0\n > y = base.floor10( -4.6 )\n -10.0\n > y = base.floor10( 9.5 )\n 1.0\n > y = base.floor10( 13.0 )\n 10.0\n > y = base.floor10( -13.0 )\n -100.0\n > y = base.floor10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor, base.floor2, base.round10\n","base.floorb":"\nbase.floorb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.floorb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward negative infinity:\n > y = base.floorb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floor, base.floorn, base.roundb\n","base.floorf":"\nbase.floorf( x )\n Rounds a single-precision floating-point number toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorf( 3.14 )\n 3.0\n > y = base.floorf( -4.2 )\n -5.0\n > y = base.floorf( -4.6 )\n -5.0\n > y = base.floorf( 9.5 )\n 9.0\n > y = base.floorf( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceilf, base.floor\n","base.floorn":"\nbase.floorn( x, n )\n Rounds a double-precision floating-point number to the nearest multiple of\n `10^n` toward negative infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round toward negative infinity behavior:\n > y = base.floorn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.floorn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floor, base.floorb, base.roundn\n","base.floorsd":"\nbase.floorsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorsd( 3.14159, 5 )\n 3.1415\n > y = base.floorsd( 3.14159, 1 )\n 3.0\n > y = base.floorsd( 12368.0, 2 )\n 12000.0\n > y = base.floorsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floor, base.roundsd, base.truncsd\n","base.forEachChar":"\nbase.forEachChar( str, clbk[, thisArg] )\n Invokes a function for each UTF-16 code unit in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character\n - index: character index\n - str: input string\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each UTF-16 code unit in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachChar( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachCodePoint, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str, clbk[, thisArg] )\n Invokes a function for each Unicode code point in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: code point\n - index: starting code point index\n - str: input string\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each Unicode code point in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachCodePoint( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachGraphemeCluster, forEachChar\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str, clbk[, thisArg] )\n Invokes a function for each grapheme cluster (i.e., user-perceived\n character) in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: grapheme cluster\n - index: starting grapheme cluster index\n - str: input string\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each grapheme cluster in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachGraphemeCluster( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachCodePoint, forEachChar\n","base.fresnel":"\nbase.fresnel( x )\n Computes the Fresnel integrals S(x) and C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: Array\n S(x) and C(x).\n\n Examples\n --------\n > var y = base.fresnel( 0.0 )\n [ ~0.0, ~0.0 ]\n > y = base.fresnel( 1.0 )\n [ ~0.438, ~0.780 ]\n > y = base.fresnel( PINF )\n [ ~0.5, ~0.5 ]\n > y = base.fresnel( NINF )\n [ ~-0.5, ~-0.5 ]\n > y = base.fresnel( NaN )\n [ NaN, NaN ]\n\n\nbase.fresnel.assign( x, out, stride, offset )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n S(x) and C(x).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.fresnelc, base.fresnels","base.fresnel.assign":"\nbase.fresnel.assign( x, out, stride, offset )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n S(x) and C(x).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.fresnelc, base.fresnels","base.fresnelc":"\nbase.fresnelc( x )\n Computes the Fresnel integral C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n C(x).\n\n Examples\n --------\n > var y = base.fresnelc( 0.0 )\n ~0.0\n > y = base.fresnelc( 1.0 )\n ~0.780\n > y = base.fresnelc( PINF )\n ~0.5\n > y = base.fresnelc( NINF )\n ~-0.5\n > y = base.fresnelc( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnels\n","base.fresnels":"\nbase.fresnels( x )\n Computes the Fresnel integral S(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n S(x).\n\n Examples\n --------\n > var y = base.fresnels( 0.0 )\n ~0.0\n > y = base.fresnels( 1.0 )\n ~0.438\n > y = base.fresnels( PINF )\n ~0.5\n > y = base.fresnels( NINF )\n ~-0.5\n > y = base.fresnels( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnelc\n","base.frexp":"\nbase.frexp( x )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = base.frexp( 4.0 )\n [ 0.5, 3 ]\n > out = base.frexp( 0.0 )\n [ 0.0, 0 ]\n > out = base.frexp( -0.0 )\n [ -0.0, 0 ]\n > out = base.frexp( NaN )\n [ NaN, 0 ]\n > out = base.frexp( PINF )\n [ Infinity, 0 ]\n > out = base.frexp( NINF )\n [ -Infinity, 0 ]\n\n\nbase.frexp.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.frexp.assign( 4.0, out, 1, 0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.ldexp\n","base.frexp.assign":"\nbase.frexp.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.frexp.assign( 4.0, out, 1, 0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.ldexp","base.fromBinaryString":"\nbase.fromBinaryString( bstr )\n Creates a double-precision floating-point number from a literal bit\n representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var bstr;\n > bstr = '0100000000010000000000000000000000000000000000000000000000000000';\n > var val = base.fromBinaryString( bstr )\n 4.0\n > bstr = '0100000000001001001000011111101101010100010001000010110100011000';\n > val = base.fromBinaryString( bstr )\n 3.141592653589793\n > bstr = '1111111111100001110011001111001110000101111010111100100010100000';\n > val = base.fromBinaryString( bstr )\n -1.0e308\n\n // The function handles subnormals:\n > bstr = '1000000000000000000000000000000000000000000000000001100011010011';\n > val = base.fromBinaryString( bstr )\n -3.14e-320\n > bstr = '0000000000000000000000000000000000000000000000000000000000000001';\n > val = base.fromBinaryString( bstr )\n 5.0e-324\n\n // The function handles special values:\n > bstr = '0000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n 0.0\n > bstr = '1000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -0.0\n > bstr = '0111111111111000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n NaN\n > bstr = '0111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n Infinity\n > bstr = '1111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -Infinity\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var bstr = '01000000100000000000000000000000';\n > var val = base.fromBinaryStringf( bstr )\n 4.0\n > bstr = '01000000010010010000111111011011';\n > val = base.fromBinaryStringf( bstr )\n ~3.14\n > bstr = '11111111011011000011101000110011';\n > val = base.fromBinaryStringf( bstr )\n ~-3.14e+38\n\n // The function handles subnormals:\n > bstr = '10000000000000000000000000010110';\n > val = base.fromBinaryStringf( bstr )\n ~-3.08e-44\n > bstr = '00000000000000000000000000000001';\n > val = base.fromBinaryStringf( bstr )\n ~1.40e-45\n\n // The function handles special values:\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n 0.0\n > bstr = '10000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -0.0\n > bstr = '01111111110000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n NaN\n > bstr = '01111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n Infinity\n > bstr = '11111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -Infinity\n\n See Also\n --------\n base.toBinaryStringf, base.fromBinaryString\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr )\n Creates an unsigned 8-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 8-bit integer.\n\n Examples\n --------\n > var bstr = '01010101';\n > var val = base.fromBinaryStringUint8( bstr )\n 85\n > bstr = '00000000';\n > val = base.fromBinaryStringUint8( bstr )\n 0\n > bstr = '00000010';\n > val = base.fromBinaryStringUint8( bstr )\n 2\n > bstr = '11111111';\n > val = base.fromBinaryStringUint8( bstr )\n 255\n\n See Also\n --------\n base.fromBinaryStringUint16, base.fromBinaryStringUint32, base.toBinaryStringUint8\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr )\n Creates an unsigned 16-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 16-bit integer.\n\n Examples\n --------\n > var bstr = '0101010101010101';\n > var val = base.fromBinaryStringUint16( bstr )\n 21845\n > bstr = '0000000000000000';\n > val = base.fromBinaryStringUint16( bstr )\n 0\n > bstr = '0000000000000010';\n > val = base.fromBinaryStringUint16( bstr )\n 2\n > bstr = '1111111111111111';\n > val = base.fromBinaryStringUint16( bstr )\n 65535\n\n See Also\n --------\n base.toBinaryStringUint16, base.fromBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr )\n Creates an unsigned 32-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var bstr = '01010101010101010101010101010101';\n > var val = base.fromBinaryStringUint32( bstr )\n 1431655765\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringUint32( bstr )\n 0\n > bstr = '00000000000000000000000000000010';\n > val = base.fromBinaryStringUint32( bstr )\n 2\n > bstr = '11111111111111111111111111111111';\n > val = base.fromBinaryStringUint32( bstr )\n 4294967295\n\n See Also\n --------\n base.fromBinaryStringUint16, base.toBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes, stride, offset )\n Converts a signed 64-bit integer byte array to a double-precision floating-\n point number.\n\n The function assumes host byte order (endianness).\n\n Parameters\n ----------\n bytes: Array|TypedArray|Object\n Byte array.\n\n stride: integer\n Index stride.\n\n offset: integer\n Index offset.\n\n Returns\n -------\n out: number\n Number.\n\n Examples\n --------\n > var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\n > var y = base.fromInt64Bytes( bytes, 1, 0 )\n -1.0\n\n See Also\n --------\n base.float64ToInt64Bytes","base.fromWordf":"\nbase.fromWordf( word )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n\n Parameters\n ----------\n word: integer\n Unsigned integer.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var word = 1068180177; // => 0 01111111 01010110010001011010001\n > var f32 = base.fromWordf( word ) // when printed, promoted to float64\n 1.3370000123977661\n\n See Also\n --------\n base.fromWords\n","base.fromWords":"\nbase.fromWords( high, low )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n Parameters\n ----------\n high: integer\n Higher order word (unsigned 32-bit integer).\n\n low: integer\n Lower order word (unsigned 32-bit integer).\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var v = base.fromWords( 1774486211, 2479577218 )\n 3.14e201\n > v = base.fromWords( 3221823995, 1413754136 )\n -3.141592653589793\n > v = base.fromWords( 0, 0 )\n 0.0\n > v = base.fromWords( 2147483648, 0 )\n -0.0\n > v = base.fromWords( 2146959360, 0 )\n NaN\n > v = base.fromWords( 2146435072, 0 )\n Infinity\n > v = base.fromWords( 4293918720, 0 )\n -Infinity\n\n See Also\n --------\n base.fromWordf\n","base.gamma":"\nbase.gamma( x )\n Evaluates the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma( 4.0 )\n 6.0\n > y = base.gamma( -1.5 )\n ~2.363\n > y = base.gamma( -0.5 )\n ~-3.545\n > y = base.gamma( 0.5 )\n ~1.772\n > y = base.gamma( 0.0 )\n Infinity\n > y = base.gamma( -0.0 )\n -Infinity\n > y = base.gamma( NaN )\n NaN\n\n See Also\n --------\n base.gamma1pm1, base.gammainc, base.gammaincinv, base.gammaln\n","base.gamma1pm1":"\nbase.gamma1pm1( x )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma1pm1( 0.2 )\n ~-0.082\n > y = base.gamma1pm1( -6.7 )\n ~-0.991\n > y = base.gamma1pm1( 0.0 )\n 0.0\n > y = base.gamma1pm1( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv, base.gammaln\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z, delta )\n Computes the ratio of two gamma functions.\n\n The ratio is defined as: Γ(z) / Γ(z+Δ).\n\n Parameters\n ----------\n z: number\n First gamma parameter.\n\n delta: number\n Difference.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaDeltaRatio( 2.0, 3.0 )\n ~0.042\n > y = base.gammaDeltaRatio( 4.0, 0.5 )\n ~0.516\n > y = base.gammaDeltaRatio( 100.0, 0.0 )\n 1.0\n > y = base.gammaDeltaRatio( NaN, 3.0 )\n NaN\n > y = base.gammaDeltaRatio( 5.0, NaN )\n NaN\n > y = base.gammaDeltaRatio( NaN, NaN )\n NaN\n\n See Also\n --------\n base.gamma\n","base.gammainc":"\nbase.gammainc( x, s[, regularized[, upper]] )\n Computes the regularized incomplete gamma function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete gamma functions, respectively.\n\n If provided `x < 0` or `s <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n s: number\n Second function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete gamma function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete gamma function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammainc( 6.0, 2.0 )\n ~0.9826\n > y = base.gammainc( 1.0, 2.0, true, true )\n ~0.7358\n > y = base.gammainc( 7.0, 5.0 )\n ~0.8270\n > y = base.gammainc( 7.0, 5.0, false )\n ~19.8482\n > y = base.gammainc( NaN, 2.0 )\n NaN\n > y = base.gammainc( 6.0, NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammaincinv, base.gammaln\n","base.gammaincinv":"\nbase.gammaincinv( p, a[, upper] )\n Computes the inverse of the lower incomplete gamma function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second argument is the scale factor `a`.\n\n By default, the function inverts the lower regularized incomplete gamma\n function, `P(x,a)`. To invert the upper function `Q(x,a)`, set the `upper`\n argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Scale parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete gamma function; i.e., compute `xr` such that `Q(a,xr) = p`.\n Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaincinv( 0.5, 2.0 )\n ~1.678\n > y = base.gammaincinv( 0.1, 10.0 )\n ~6.221\n > y = base.gammaincinv( 0.75, 3.0 )\n ~3.92\n > y = base.gammaincinv( 0.75, 3.0, true )\n ~1.727\n > y = base.gammaincinv( 0.75, NaN )\n NaN\n > y = base.gammaincinv( NaN, 3.0 )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammainc, base.gammaln\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x )\n Calculates the Lanczos sum for the approximation of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSum( 4.0 )\n ~950.366\n > y = base.gammaLanczosSum( -1.5 )\n ~1373366.245\n > y = base.gammaLanczosSum( -0.5 )\n ~-699841.735\n > y = base.gammaLanczosSum( 0.5 )\n ~96074.186\n > y = base.gammaLanczosSum( 0.0 )\n Infinity\n > y = base.gammaLanczosSum( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSumExpGScaled\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Scaled Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSumExpGScaled( 4.0 )\n ~0.018\n > y = base.gammaLanczosSumExpGScaled( -1.5 )\n ~25.337\n > y = base.gammaLanczosSumExpGScaled( -0.5 )\n ~-12.911\n > y = base.gammaLanczosSumExpGScaled( 0.5 )\n ~1.772\n > y = base.gammaLanczosSumExpGScaled( 0.0 )\n Infinity\n > y = base.gammaLanczosSumExpGScaled( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSum\n","base.gammaln":"\nbase.gammaln( x )\n Evaluates the natural logarithm of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the gamma function.\n\n Examples\n --------\n > var y = base.gammaln( 1.0 )\n 0.0\n > y = base.gammaln( 2.0 )\n 0.0\n > y = base.gammaln( 4.0 )\n ~1.792\n > y = base.gammaln( -0.5 )\n ~1.266\n > y = base.gammaln( 0.5 )\n ~0.572\n > y = base.gammaln( 0.0 )\n Infinity\n > y = base.gammaln( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv\n","base.gcd":"\nbase.gcd( a, b )\n Computes the greatest common divisor (gcd).\n\n If both `a` and `b` are `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Greatest common divisor.\n\n Examples\n --------\n > var v = base.gcd( 48, 18 )\n 6\n\n See Also\n --------\n base.lcm\n","base.getHighWord":"\nbase.getHighWord( x )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Higher order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getHighWord( 3.14e201 )\n 1774486211\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n","base.getLowWord":"\nbase.getLowWord( x )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Lower order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getLowWord( 3.14e201 )\n 2479577218\n\n See Also\n --------\n base.getHighWord, base.setHighWord\n","base.hacovercos":"\nbase.hacovercos( x )\n Computes the half-value coversed cosine.\n\n The half-value coversed cosine is defined as `(1 + sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed cosine.\n\n Examples\n --------\n > var y = base.hacovercos( 3.14 )\n ~0.5008\n > y = base.hacovercos( -4.2 )\n ~0.9358\n > y = base.hacovercos( -4.6 )\n ~0.9968\n > y = base.hacovercos( 9.5 )\n ~0.4624\n > y = base.hacovercos( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacoversin, base.havercos\n","base.hacoversin":"\nbase.hacoversin( x )\n Computes the half-value coversed sine.\n\n The half-value coversed sine is defined as `(1 - sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed sine.\n\n Examples\n --------\n > var y = base.hacoversin( 3.14 )\n ~0.4992\n > y = base.hacoversin( -4.2 )\n ~0.0642\n > y = base.hacoversin( -4.6 )\n ~0.0032\n > y = base.hacoversin( 9.5 )\n ~0.538\n > y = base.hacoversin( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacovercos, base.haversin\n","base.havercos":"\nbase.havercos( x )\n Computes the half-value versed cosine.\n\n The half-value versed cosine is defined as `(1 + cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed cosine.\n\n Examples\n --------\n > var y = base.havercos( 3.14 )\n ~0.0\n > y = base.havercos( -4.2 )\n ~0.2549\n > y = base.havercos( -4.6 )\n ~0.4439\n > y = base.havercos( 9.5 )\n ~0.0014\n > y = base.havercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.haversin, base.vercos\n","base.haversin":"\nbase.haversin( x )\n Computes the half-value versed sine.\n\n The half-value versed sine is defined as `(1 - cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed sine.\n\n Examples\n --------\n > var y = base.haversin( 3.14 )\n ~1.0\n > y = base.haversin( -4.2 )\n ~0.7451\n > y = base.haversin( -4.6 )\n ~0.5561\n > y = base.haversin( 9.5 )\n ~0.9986\n > y = base.haversin( -0.0 )\n 0.0\n\n See Also\n --------\n base.havercos, base.versin\n","base.heaviside":"\nbase.heaviside( x[, continuity] )\n Evaluates the Heaviside function.\n\n The `continuity` parameter may be one of the following:\n\n - 'half-maximum': if `x == 0`, the function returns `0.5`.\n - 'left-continuous': if `x == 0`, the function returns `0`.\n - 'right-continuous': if `x == 0`, the function returns `1`.\n\n By default, if `x == 0`, the function returns `NaN` (i.e., the function is\n discontinuous).\n\n Parameters\n ----------\n x: number\n Input value.\n\n continuity: string (optional)\n Specifies how to handle `x == 0`. By default, if `x == 0`, the function\n returns `NaN`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.heaviside( 3.14 )\n 1.0\n > y = base.heaviside( -3.14 )\n 0.0\n > y = base.heaviside( 0.0 )\n NaN\n > y = base.heaviside( 0.0, 'half-maximum' )\n 0.5\n > y = base.heaviside( 0.0, 'left-continuous' )\n 0.0\n > y = base.heaviside( 0.0, 'right-continuous' )\n 1.0\n\n See Also\n --------\n base.ramp\n","base.hermitepoly":"\nbase.hermitepoly( n, x )\n Evaluates a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.hermitepoly( 1, 0.5 )\n 1.0\n > y = base.hermitepoly( -1, 0.5 )\n NaN\n > y = base.hermitepoly( 0, 0.5 )\n 1.0\n > y = base.hermitepoly( 2, 0.5 )\n -1.0\n\n\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n See Also\n --------\n base.evalpoly, base.normhermitepoly\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n See Also\n --------\n base.evalpoly, base.normhermitepoly","base.hypot":"\nbase.hypot( x, y )\n Computes the hypotenuse avoiding overflow and underflow.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypot( -5.0, 12.0 )\n 13.0\n > h = base.hypot( NaN, 12.0 )\n NaN\n > h = base.hypot( -0.0, -0.0 )\n 0.0\n\n","base.hypotf":"\nbase.hypotf( x, y )\n Computes the hypotenuse avoiding overflow and underflow (single-precision).\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypotf( -5.0, 12.0 )\n 13.0\n > h = base.hypotf( NaN, 12.0 )\n NaN\n > h = base.hypotf( -0.0, -0.0 )\n 0.0\n\n See Also\n --------\n base.hypot\n","base.identity":"\nbase.identity( x )\n Evaluates the identity function for a double-precision floating-point number\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Input value.\n\n Examples\n --------\n > var y = base.identity( -1.0 )\n -1.0\n > y = base.identity( 2.0 )\n 2.0\n > y = base.identity( 0.0 )\n 0.0\n > y = base.identity( -0.0 )\n -0.0\n > y = base.identity( NaN )\n NaN\n\n","base.identityf":"\nbase.identityf( x )\n Evaluates the identity function for a single-precision floating-point number\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Input value.\n\n Examples\n --------\n > var y = base.identityf( -1.0 )\n -1.0\n > y = base.identityf( 2.0 )\n 2.0\n > y = base.identityf( 0.0 )\n 0.0\n > y = base.identityf( -0.0 )\n -0.0\n > y = base.identityf( NaN )\n NaN\n\n See Also\n --------\n base.identityf\n","base.imul":"\nbase.imul( a, b )\n Performs C-like multiplication of two signed 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.imul( -10|0, 4|0 )\n -40\n\n See Also\n --------\n base.imuldw\n","base.imuldw":"\nbase.imuldw( a, b )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: Array\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.imuldw( 1, 10 )\n [ 0, 10 ]\n\n\nbase.imuldw.assign( a, b, out, stride, offset )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imul","base.imuldw.assign":"\nbase.imuldw.assign( a, b, out, stride, offset )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imul","base.int32ToUint32":"\nbase.int32ToUint32( x )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\n 4294967264\n > y = base.int32ToUint32( base.float64ToInt32( 3 ) )\n 3\n\n See Also\n --------\n base.uint32ToInt32\n","base.inv":"\nbase.inv( x )\n Computes the multiplicative inverse of a double-precision floating-point\n number `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.inv( -1.0 )\n -1.0\n > y = base.inv( 2.0 )\n 0.5\n > y = base.inv( 0.0 )\n Infinity\n > y = base.inv( -0.0 )\n -Infinity\n > y = base.inv( NaN )\n NaN\n\n See Also\n --------\n base.pow\n","base.invf":"\nbase.invf( x )\n Computes the multiplicative inverse of a single-precision floating-point\n number `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.invf( -1.0 )\n -1.0\n > y = base.invf( 2.0 )\n 0.5\n > y = base.invf( 0.0 )\n Infinity\n > y = base.invf( -0.0 )\n -Infinity\n > y = base.invf( NaN )\n NaN\n\n See Also\n --------\n base.inv\n","base.isComposite":"\nbase.isComposite( x )\n Tests if a number is composite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a composite number.\n\n Examples\n --------\n > var bool = base.isComposite( 10.0 )\n true\n > bool = base.isComposite( 11.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isPrime\n","base.isCoprime":"\nbase.isCoprime( a, b )\n Tests if two numbers are coprime.\n\n Parameters\n ----------\n a: number\n First value.\n\n b: number\n Second value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the values are coprime.\n\n Examples\n --------\n > var bool = base.isCoprime( 14.0, 15.0 )\n true\n > bool = base.isCoprime( 14.0, 21.0 )\n false\n\n See Also\n --------\n base.isComposite, base.isPrime, base.gcd\n","base.isEven":"\nbase.isEven( x )\n Tests if a finite numeric value is an even number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEven( 5.0 )\n false\n > bool = base.isEven( -2.0 )\n true\n > bool = base.isEven( 0.0 )\n true\n > bool = base.isEven( NaN )\n false\n\n See Also\n --------\n base.isOdd\n","base.isEvenInt32":"\nbase.isEvenInt32( x )\n Tests if a 32-bit integer is even.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEvenInt32( 5 )\n false\n > bool = base.isEvenInt32( -2 )\n true\n > bool = base.isEvenInt32( 0 )\n true\n\n See Also\n --------\n base.isEven, base.isOddInt32\n","base.isFinite":"\nbase.isFinite( x )\n Tests if a double-precision floating-point numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinite( 5.0 )\n true\n > bool = base.isFinite( -2.0e64 )\n true\n > bool = base.isFinite( PINF )\n false\n > bool = base.isFinite( NINF )\n false\n\n See Also\n --------\n base.isInfinite\n","base.isFinitef":"\nbase.isFinitef( x )\n Tests if a single-precision floating-point numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinitef( 5.0 )\n true\n > bool = base.isFinitef( -1.0e38 )\n true\n > bool = base.isFinitef( FLOAT32_PINF )\n false\n > bool = base.isFinitef( FLOAT32_NINF )\n false\n\n See Also\n --------\n base.isInfinitef\n","base.isInfinite":"\nbase.isInfinite( x )\n Tests if a double-precision floating-point numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinite( PINF )\n true\n > bool = base.isInfinite( NINF )\n true\n > bool = base.isInfinite( 5.0 )\n false\n > bool = base.isInfinite( NaN )\n false\n\n See Also\n --------\n base.isFinite\n","base.isInfinitef":"\nbase.isInfinitef( x )\n Tests if a single-precision floating-point numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinitef( FLOAT32_PINF )\n true\n > bool = base.isInfinitef( FLOAT32_NINF )\n true\n > bool = base.isInfinitef( 5.0 )\n false\n > bool = base.isInfinitef( NaN )\n false\n\n See Also\n --------\n base.isFinitef\n","base.isInteger":"\nbase.isInteger( x )\n Tests if a finite double-precision floating-point number is an integer.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an integer.\n\n Examples\n --------\n > var bool = base.isInteger( 1.0 )\n true\n > bool = base.isInteger( 3.14 )\n false\n\n","base.isnan":"\nbase.isnan( x )\n Tests if a double-precision floating-point numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnan( NaN )\n true\n > bool = base.isnan( 7.0 )\n false\n\n See Also\n --------\n base.isnanf\n","base.isnanf":"\nbase.isnanf( x )\n Tests if a single-precision floating-point numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnanf( NaN )\n true\n > bool = base.isnanf( 7.0 )\n false\n\n See Also\n --------\n base.isnan\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a negative integer.\n\n Examples\n --------\n > var bool = base.isNegativeInteger( -1.0 )\n true\n > bool = base.isNegativeInteger( 0.0 )\n false\n > bool = base.isNegativeInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNonNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNegativeZero":"\nbase.isNegativeZero( x )\n Tests if a double-precision floating-point numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZero( -0.0 )\n true\n > bool = base.isNegativeZero( 0.0 )\n false\n\n See Also\n --------\n base.isPositiveZero\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x )\n Tests if a single-precision floating-point numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZerof( -0.0 )\n true\n > bool = base.isNegativeZerof( 0.0 )\n false\n\n See Also\n --------\n base.isNegativeZero, base.isPositiveZerof\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonnegative integer.\n\n Examples\n --------\n > var bool = base.isNonNegativeInteger( 1.0 )\n true\n > bool = base.isNonNegativeInteger( 0.0 )\n true\n > bool = base.isNonNegativeInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonpositive integer.\n\n Examples\n --------\n > var bool = base.isNonPositiveInteger( -1.0 )\n true\n > bool = base.isNonPositiveInteger( 0.0 )\n true\n > bool = base.isNonPositiveInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isPositiveInteger\n","base.isOdd":"\nbase.isOdd( x )\n Tests if a finite numeric value is an odd number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOdd( 5.0 )\n true\n > bool = base.isOdd( -2.0 )\n false\n > bool = base.isOdd( 0.0 )\n false\n > bool = base.isOdd( NaN )\n false\n\n See Also\n --------\n base.isEven\n","base.isOddInt32":"\nbase.isOddInt32( x )\n Tests if a 32-bit integer is odd.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOddInt32( 5 )\n true\n > bool = base.isOddInt32( -2 )\n false\n > bool = base.isOddInt32( 0 )\n false\n\n See Also\n --------\n base.isEvenInt32, base.isOdd\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a positive integer.\n\n Examples\n --------\n > var bool = base.isPositiveInteger( 1.0 )\n true\n > bool = base.isPositiveInteger( 0.0 )\n false\n > bool = base.isPositiveInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isNonPositiveInteger\n","base.isPositiveZero":"\nbase.isPositiveZero( x )\n Tests if a double-precision floating-point numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZero( 0.0 )\n true\n > bool = base.isPositiveZero( -0.0 )\n false\n\n See Also\n --------\n base.isNegativeZero\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x )\n Tests if a single-precision floating-point numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZerof( 0.0 )\n true\n > bool = base.isPositiveZerof( -0.0 )\n false\n\n See Also\n --------\n base.isNegativeZerof, base.isPositiveZero\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x )\n Tests whether an unsigned integer is a power of 2.\n\n Parameters\n ----------\n x: integer\n Unsigned integer.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a power of 2.\n\n Examples\n --------\n > var bool = base.isPow2Uint32( 2 )\n true\n > bool = base.isPow2Uint32( 5 )\n false\n\n","base.isPrime":"\nbase.isPrime( x )\n Tests if a number is prime.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a prime number.\n\n Examples\n --------\n > var bool = base.isPrime( 11.0 )\n true\n > bool = base.isPrime( 3.14 )\n false\n\n See Also\n --------\n base.isComposite, base.isInteger\n","base.isProbability":"\nbase.isProbability( x )\n Tests if a double-precision floating-point number value is a probability.\n\n A probability is defined as a number on the closed interval [0,1].\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a probability.\n\n Examples\n --------\n > var bool = base.isProbability( 0.5 )\n true\n > bool = base.isProbability( 3.14 )\n false\n > bool = base.isProbability( NaN )\n false\n\n","base.isSafeInteger":"\nbase.isSafeInteger( x )\n Tests if a finite double-precision floating-point number is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a safe integer.\n\n Examples\n --------\n > var bool = base.isSafeInteger( 1.0 )\n true\n > bool = base.isSafeInteger( 2.0e200 )\n false\n > bool = base.isSafeInteger( 3.14 )\n false\n\n","base.kernelBetainc":"\nbase.kernelBetainc( x, a, b, regularized, upper )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\n [ ~1.277, ~0.926 ]\n > out = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n [ 0.36, 1.6 ]\n\n\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.betainc\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.betainc","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a, b, p, q )\n Computes the inverse of the lower incomplete beta function.\n\n Probabilities `p` and `q` must satisfy `p = 1 - q`.\n\n Parameters\n ----------\n a: number\n First function parameter (a positive number).\n\n b: number\n Second function parameter (a positive number).\n\n p: number\n Probability.\n\n q: number\n Probability equal to `1-p`.\n\n Returns\n -------\n out: Array\n Two-element array holding function value `y` and `1-y`.\n\n Examples\n --------\n > var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\n [ ~0.327, ~0.673 ]\n > y = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\n [ ~0.446, ~0.554 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\n [ ~0.082, ~0.918 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n [ ~0.235, ~0.765 ]\n\n See Also\n --------\n base.betaincinv\n","base.kernelCos":"\nbase.kernelCos( x, y )\n Computes the cosine of a double-precision floating-point number on the\n interval [-π/4, π/4].\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Cosine.\n\n Examples\n --------\n > var out = base.kernelCos( 0.0, 0.0 )\n ~1.0\n > out = base.kernelCos( PI/6.0, 0.0 )\n ~0.866\n > out = base.kernelCos( 0.785, -1.144e-17 )\n ~0.707\n > out = base.kernelCos( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.kernelSin, base.kernelTan\n","base.kernelSin":"\nbase.kernelSin( x, y )\n Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Sine.\n\n Examples\n --------\n > var y = base.kernelSin( 0.0, 0.0 )\n ~0.0\n > y = base.kernelSin( PI/6.0, 0.0 )\n ~0.5\n > y = base.kernelSin( 0.619, 9.279e-18 )\n ~0.58\n\n > y = base.kernelSin( NaN, 0.0 )\n NaN\n > y = base.kernelSin( 2.0, NaN )\n NaN\n > y = base.kernelSin( NaN, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelTan, base.sin\n","base.kernelTan":"\nbase.kernelTan( x, y, k )\n Computes the tangent of a double-precision floating-point number on the\n interval [-π/4, π/4].\n\n For increased accuracy, the number for which the tangent should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The numbers `x` and `y` must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either `x` or `y` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n k: integer\n If `k=1`, the function returns `tan(x+y)`. If `k=-1`, the function\n returns the negative inverse `-1/tan(x+y)`.\n\n Returns\n -------\n out: number\n Tangent.\n\n Examples\n --------\n > var out = base.kernelTan( PI/4.0, 0.0, 1 )\n ~1.0\n > out = base.kernelTan( PI/4.0, 0.0, -1 )\n ~-1.0\n > out = base.kernelTan( PI/6.0, 0.0, 1 )\n ~0.577\n > out = base.kernelTan( 0.664, 5.288e-17, 1 )\n ~0.783\n\n > out = base.kernelTan( NaN, 0.0, 1 )\n NaN\n > out = base.kernelTan( 3.0, NaN, 1 )\n NaN\n > out = base.kernelTan( 3.0, 0.0, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelSin, base.tan\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i, j )\n Evaluates the Kronecker delta.\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDelta( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDelta( 3.14, 3.14 )\n 1.0\n\n See Also\n --------\n base.diracDelta\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i, j )\n Evaluates the Kronecker delta (single-precision).\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDeltaf( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDeltaf( 3.14, 3.14 )\n 1.0\n\n See Also\n --------\n base.kroneckerDelta\n","base.labs":"\nbase.labs( x )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Absolute value.\n\n Examples\n --------\n > var v = base.labs( -1|0 )\n 1\n > v = base.labs( 2|0 )\n 2\n > v = base.labs( 0|0 )\n 0\n\n See Also\n --------\n base.abs\n","base.lcm":"\nbase.lcm( a, b )\n Computes the least common multiple (lcm).\n\n If either `a` or `b` is `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Least common multiple.\n\n Examples\n --------\n > var v = base.lcm( 21, 6 )\n 42\n\n See Also\n --------\n base.gcd\n","base.ldexp":"\nbase.ldexp( frac, exp )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n\n If `frac` equals positive or negative `zero`, `NaN`, or positive or negative\n infinity, the function returns a value equal to `frac`.\n\n Parameters\n ----------\n frac: number\n Fraction.\n\n exp: number\n Exponent.\n\n Returns\n -------\n out: number\n Double-precision floating-point number equal to `frac * 2^exp`.\n\n Examples\n --------\n > var x = base.ldexp( 0.5, 3 )\n 4.0\n > x = base.ldexp( 4.0, -2 )\n 1.0\n > x = base.ldexp( 0.0, 20 )\n 0.0\n > x = base.ldexp( -0.0, 39 )\n -0.0\n > x = base.ldexp( NaN, -101 )\n NaN\n > x = base.ldexp( PINF, 11 )\n Infinity\n > x = base.ldexp( NINF, -118 )\n -Infinity\n\n See Also\n --------\n base.frexp\n","base.ln":"\nbase.ln( x )\n Evaluates the natural logarithm of a double-precision floating-point number.\n\n For negative numbers, the natural logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ln( 4.0 )\n ~1.386\n > y = base.ln( 0.0 )\n -Infinity\n > y = base.ln( PINF )\n Infinity\n > y = base.ln( NaN )\n NaN\n > y = base.ln( -4.0 )\n NaN\n\n See Also\n --------\n base.exp, base.log10, base.log1p, base.log2\n","base.log":"\nbase.log( x, b )\n Computes the base `b` logarithm of `x`.\n\n For negative `b` or `x`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n b: number\n Base.\n\n Returns\n -------\n y: number\n Logarithm (base `b`).\n\n Examples\n --------\n > var y = base.log( 100.0, 10.0 )\n 2.0\n > y = base.log( 16.0, 2.0 )\n 4.0\n > y = base.log( 5.0, 1.0 )\n Infinity\n > y = base.log( NaN, 2.0 )\n NaN\n > y = base.log( 1.0, NaN )\n NaN\n > y = base.log( -4.0, 2.0 )\n NaN\n > y = base.log( 4.0, -2.0 )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log10, base.log1p, base.log2\n","base.log1mexp":"\nbase.log1mexp( x )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1mexp( -10.0 )\n ~-0.00005\n > y = base.log1mexp( 0.0 )\n -Infinity\n > y = base.log1mexp( 5.0 )\n ~-0.00676\n > y = base.log1mexp( 10.0 )\n ~-0.00005\n > y = base.log1mexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1p, base.log1pexp","base.log1p":"\nbase.log1p( x )\n Evaluates the natural logarithm of `1+x`.\n\n For `x < -1`, the function returns `NaN`, as the natural logarithm is not\n defined for negative numbers.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1p( 4.0 )\n ~1.609\n > y = base.log1p( -1.0 )\n -Infinity\n > y = base.log1p( 0.0 )\n 0.0\n > y = base.log1p( -0.0 )\n -0.0\n > y = base.log1p( -2.0 )\n NaN\n > y = base.log1p( NaN )\n NaN\n\n See Also\n --------\n base.ln, base.log\n","base.log1pexp":"\nbase.log1pexp( x )\n Evaluates the natural logarithm of `1+exp(x)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1pexp( -10.0 )\n ~0.000045\n > y = base.log1pexp( 0.0 )\n ~0.693147\n > y = base.log1pexp( 5.0 )\n ~5.006715\n > y = base.log1pexp( 34.0 )\n 34.0\n > y = base.log1pexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1mexp, base.log1p","base.log1pmx":"\nbase.log1pmx( x )\n Evaluates `ln(1+x) - x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > base.log1pmx( 1.1 )\n ~-0.358\n > base.log1pmx( 0.99 )\n ~-0.302\n > base.log1pmx( -0.99 )\n ~-3.615\n > base.log1pmx( -1.1 )\n NaN\n > base.log1pmx( NaN )\n NaN\n\n See Also\n --------\n base.ln, base.log1p","base.log2":"\nbase.log2( x )\n Evaluates the binary logarithm (base two).\n\n For negative numbers, the binary logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log2( 4.0 )\n 2.0\n > y = base.log2( 8.0 )\n 3.0\n > y = base.log2( 0.0 )\n -Infinity\n > y = base.log2( PINF )\n Infinity\n > y = base.log2( NaN )\n NaN\n > y = base.log2( -4.0 )\n NaN\n\n See Also\n --------\n base.exp2, base.ln, base.log\n","base.log10":"\nbase.log10( x )\n Evaluates the common logarithm (base 10).\n\n For negative numbers, the common logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log10( 100.0 )\n 2.0\n > y = base.log10( 8.0 )\n ~0.903\n > y = base.log10( 0.0 )\n -Infinity\n > y = base.log10( PINF )\n Infinity\n > y = base.log10( NaN )\n NaN\n > y = base.log10( -4.0 )\n NaN\n\n See Also\n --------\n base.exp10, base.ln, base.log\n","base.logaddexp":"\nbase.logaddexp( x, y )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.logaddexp( 90.0, 90.0 )\n ~90.6931\n > v = base.logaddexp( -20.0, 90.0 )\n 90.0\n > v = base.logaddexp( 0.0, -100.0 )\n ~3.7201e-44\n > v = base.logaddexp( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln\n","base.logit":"\nbase.logit( p )\n Evaluates the logit function.\n\n Let `p` be the probability of some event. The logit function is defined as\n the logarithm of the odds `p / (1-p)`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.logit( 0.2 )\n ~-1.386\n > y = base.logit( 0.9 )\n ~2.197\n > y = base.logit( -4.0 )\n NaN\n > y = base.logit( 1.5 )\n NaN\n > y = base.logit( NaN )\n NaN\n\n","base.lucas":"\nbase.lucas( n )\n Computes the nth Lucas number.\n\n Lucas numbers follow the recurrence relation\n\n L_n = L_{n-1} + L_{n-2}\n\n with seed values L_0 = 2 and L_1 = 1.\n\n If `n` is greater than `76`, the function returns `NaN`, as larger Lucas\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Lucas number.\n\n Examples\n --------\n > var y = base.lucas( 0 )\n 2\n > y = base.lucas( 1 )\n 1\n > y = base.lucas( 2 )\n 3\n > y = base.lucas( 3 )\n 4\n > y = base.lucas( 4 )\n 7\n > y = base.lucas( 77 )\n NaN\n > y = base.lucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n","base.lucaspoly":"\nbase.lucaspoly( n, x )\n Evaluates a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Lucas polynomial.\n\n Returns\n -------\n out: number\n Evaluated Lucas polynomial.\n\n Examples\n --------\n // 2^5 + 5*2^3 + 5*2\n > var v = base.lucaspoly( 5, 2.0 )\n 82.0\n\n\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n See Also\n --------\n base.evalpoly, base.fibpoly\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n See Also\n --------\n base.evalpoly, base.fibpoly","base.max":"\nbase.max( x, y )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.max( 3.14, 4.2 )\n 4.2\n > v = base.max( 3.14, NaN )\n NaN\n > v = base.max( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.maxn, base.min\n","base.maxabs":"\nbase.maxabs( x, y )\n Returns the maximum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n > var v = base.maxabs( 3.14, -4.2 )\n 4.2\n > v = base.maxabs( 3.14, NaN )\n NaN\n > v = base.maxabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.max, base.minabs\n","base.maxn":"\nbase.maxn( [x[, y[, ...args]]] )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns negative infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.maxn( 3.14, 4.2 )\n 4.2\n > v = base.maxn( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.maxn( 3.14, NaN )\n NaN\n > v = base.maxn( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.max, base.minn\n","base.min":"\nbase.min( x, y )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.min( 3.14, 4.2 )\n 3.14\n > v = base.min( 3.14, NaN )\n NaN\n > v = base.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max, base.minabs, base.minn\n","base.minabs":"\nbase.minabs( x, y )\n Returns the minimum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest upper bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n > var v = base.minabs( 3.14, -4.2 )\n 3.14\n > v = base.minabs( 3.14, NaN )\n NaN\n > v = base.minabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.min\n","base.minmax":"\nbase.minmax( x, y )\n Returns the minimum and maximum values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: Array\n Minimum and maximum values.\n\n Examples\n --------\n > var v = base.minmax( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmax( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmax( +0.0, -0.0 )\n [ -0.0, +0.0 ]\n\n\nbase.minmax.assign( x, y, out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.max, base.min, base.minmaxabs","base.minmax.assign":"\nbase.minmax.assign( x, y, out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.max, base.min, base.minmaxabs","base.minmaxabs":"\nbase.minmaxabs( x, y )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: Array\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var v = base.minmaxabs( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxabs( -5.9, 3.14)\n [ 3.14, 5.9 ]\n > v = base.minmaxabs( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxabs( +0.0, -0.0 )\n [ 0.0, 0.0 ]\n\n\nbase.minmaxabs.assign( x, y, out, stride, offset )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabs, base.minabs, base.minmax\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x, y, out, stride, offset )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabs, base.minabs, base.minmax","base.minn":"\nbase.minn( [x[, y[, ...args]]] )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.minn( 3.14, 4.2 )\n 3.14\n > v = base.minn( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.minn( 3.14, NaN )\n NaN\n > v = base.minn( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.maxn, base.min\n","base.modf":"\nbase.modf( x )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n Integral and fractional parts.\n\n Examples\n --------\n > var parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( +0.0 )\n [ +0.0, +0.0 ]\n > parts = base.modf( -0.0 )\n [ -0.0, -0.0 ]\n > parts = base.modf( PINF )\n [ Infinity, +0.0 ]\n > parts = base.modf( NINF )\n [ -Infinity, -0.0 ]\n > parts = base.modf( NaN )\n [ NaN, NaN ]\n\n\nbase.modf.assign( x, out, stride, offset )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var parts = base.modf.assign( 3.14, out, 1, 0 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true\n","base.modf.assign":"\nbase.modf.assign( x, out, stride, offset )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var parts = base.modf.assign( 3.14, out, 1, 0 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true","base.mul":"\nbase.mul( x, y )\n Multiplies two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.mul( -1.0, 5.0 )\n -5.0\n > v = base.mul( 2.0, 5.0 )\n 10.0\n > v = base.mul( 0.0, 5.0 )\n 0.0\n > v = base.mul( -0.0, 0.0 )\n -0.0\n > v = base.mul( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.div, base.sub\n","base.mulf":"\nbase.mulf( x, y )\n Multiplies two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.mulf( -1.0, 5.0 )\n -5.0\n > v = base.mulf( 2.0, 5.0 )\n 10.0\n > v = base.mulf( 0.0, 5.0 )\n 0.0\n > v = base.mulf( -0.0, 0.0 )\n -0.0\n > v = base.mulf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.divf, base.mul, base.subf\n","base.ndarray":"\nbase.ndarray( dtype, buffer, shape, strides, offset, order )\n Returns an ndarray.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n Returns\n -------\n ndarray: ndarray\n ndarray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.ndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nbase.ndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nbase.ndarray.prototype.order: string\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nbase.ndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nbase.ndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nbase.ndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nbase.ndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nbase.ndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays, fcn )\n Applies a unary callback to elements in an input ndarray and assigns results\n to elements in an output ndarray.\n\n Each provided \"ndarray\" should be an `object` with the following properties:\n\n - dtype: data type.\n - data: data buffer.\n - shape: dimensions.\n - strides: stride lengths.\n - offset: index offset.\n - order: specifies whether an ndarray is row-major (C-style) or column-major\n (Fortran-style).\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one input ndarray and one output ndarray.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n // Define ndarray data and meta data...\n > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dtype = 'float64';\n > var shape = [ 2, 2 ];\n > var sx = [ 2, 1 ];\n > var sy = [ 2, 1 ];\n > var ox = 0;\n > var oy = 0;\n > var order = 'row-major';\n\n // Using ndarrays...\n > var x = ndarray( dtype, xbuf, shape, sx, ox, order );\n > var y = ndarray( dtype, ybuf, shape, sy, oy, order );\n > base.ndarrayUnary( [ x, y ], base.abs );\n > y.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using minimal ndarray-like objects...\n > x = {\n ... 'dtype': dtype,\n ... 'data': xbuf,\n ... 'shape': shape,\n ... 'strides': sx,\n ... 'offset': ox,\n ... 'order': order\n ... };\n > y = {\n ... 'dtype': dtype,\n ... 'data': ybuf,\n ... 'shape': shape,\n ... 'strides': sy,\n ... 'offset': oy,\n ... 'order': order\n ... };\n > base.ndarrayUnary( [ x, y ], base.abs );\n > y.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n ndarrayDispatch\n","base.ndzeros":"\nbase.ndzeros( dtype, shape, order )\n Returns a zero-filled ndarray having a specified shape and data type.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n shape: ArrayLikeObject\n Array shape.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n \n > var sh = arr.shape\n [ 2, 2 ]\n > var dt = arr.dtype\n 'float64'\n\n See Also\n --------\n base.ndarray, base.ndzerosLike\n","base.ndzerosLike":"\nbase.ndzerosLike( x )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n\n Along with data type, shape, and order, the function infers the \"class\" of\n the returned ndarray from the provided ndarray. For example, if provided a\n \"base\" ndarray, the function returns a base ndarray. If provided a non-base\n ndarray, the function returns a non-base ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var dt = x.dtype\n 'float64'\n > var y = base.ndzerosLike( x )\n \n > sh = y.shape\n [ 2, 2 ]\n > dt = y.dtype\n 'float64'\n\n See Also\n --------\n base.ndarray, base.ndzeros\n","base.negafibonacci":"\nbase.negafibonacci( n )\n Computes the nth negaFibonacci number.\n\n The negaFibonacci numbers follow the recurrence relation\n\n F_{n-2} = F_{n} - F_{n-1}\n\n with seed values F_0 = 0 and F_{-1} = 1.\n\n If `|n|` is greater than `78`, the function returns `NaN` as larger\n negaFibonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaFibonacci number.\n\n Examples\n --------\n > var y = base.negafibonacci( 0 )\n 0\n > y = base.negafibonacci( -1 )\n 1\n > y = base.negafibonacci( -2 )\n -1\n > y = base.negafibonacci( -3 )\n 2\n > y = base.negafibonacci( -4 )\n -3\n > y = base.negafibonacci( -79 )\n NaN\n > y = base.negafibonacci( -80 )\n NaN\n > y = base.negafibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n","base.negalucas":"\nbase.negalucas( n )\n Computes the nth negaLucas number.\n\n The negaLucas numbers follow the recurrence relation\n\n L_{n-2} = L_{n} - L_{n-1}\n\n with seed values L_0 = 2 and L_{-1} = -1.\n\n If `|n|` is greater than `76`, the function returns `NaN` as larger\n negaLucas numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaLucas number.\n\n Examples\n --------\n > var y = base.negalucas( 0 )\n 2\n > y = base.negalucas( -1 )\n -1\n > y = base.negalucas( -2 )\n 3\n > y = base.negalucas( -3 )\n -4\n > y = base.negalucas( -4 )\n 7\n > y = base.negalucas( -77 )\n NaN\n > y = base.negalucas( -78 )\n NaN\n > y = base.negalucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.lucas, base.negafibonacci\n","base.nonfibonacci":"\nbase.nonfibonacci( n )\n Computes the nth non-Fibonacci number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Non-Fibonacci number.\n\n Examples\n --------\n > var v = base.nonfibonacci( 1 )\n 4\n > v = base.nonfibonacci( 2 )\n 6\n > v = base.nonfibonacci( 3 )\n 7\n > v = base.nonfibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.normalize":"\nbase.normalize( x )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalize( 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > var y = out[ 0 ];\n > var exponent = out[ 1 ];\n > var bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\n true\n\n // Special cases:\n > out = base.normalize( 0.0 )\n [ 0.0, 0 ];\n > out = base.normalize( PINF )\n [ Infinity, 0 ]\n > out = base.normalize( NINF )\n [ -Infinity, 0 ]\n > out = base.normalize( NaN )\n [ NaN, 0 ]\n\n\nbase.normalize.assign( x, out, stride, offset )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 )\n > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n [ 1.4141234400356668e-303, -52 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.normalizef\n","base.normalize.assign":"\nbase.normalize.assign( x, out, stride, offset )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 )\n > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n [ 1.4141234400356668e-303, -52 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.normalizef","base.normalizef":"\nbase.normalizef( x )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: Array\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23 ]\n > var y = out[ 0 ];\n > var exp = out[ 1 ];\n > var bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\n true\n\n // Special cases:\n > out = base.normalizef( FLOAT32_PINF )\n [ Infinity, 0 ]\n > out = base.normalizef( FLOAT32_NINF )\n [ -Infinity, 0 ]\n > out = base.normalizef( NaN )\n [ NaN, 0 ]\n\n\nbase.normalizef.assign( x, out, stride, offset )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n assigns results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > out = new Float32Array( 2 );\n > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalize","base.normalizef.assign":"\nbase.normalizef.assign( x, out, stride, offset )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n assigns results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > out = new Float32Array( 2 );\n > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalize","base.normhermitepoly":"\nbase.normhermitepoly( n, x )\n Evaluates a normalized Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.normhermitepoly( 1, 0.5 )\n 0.5\n > y = base.normhermitepoly( -1, 0.5 )\n NaN\n > y = base.normhermitepoly( 0, 0.5 )\n 1.0\n > y = base.normhermitepoly( 2, 0.5 )\n -0.75\n\n\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.normhermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -0.75\n\n See Also\n --------\n base.evalpoly, base.hermitepoly\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.normhermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -0.75\n\n See Also\n --------\n base.evalpoly, base.hermitepoly","base.pdiff":"\nbase.pdiff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdiff( 5.9, 3.14 )\n 2.76\n > v = base.pdiff( 3.14, 4.2 )\n 0.0\n > v = base.pdiff( 3.14, NaN )\n NaN\n > v = base.pdiff( -0.0, +0.0 )\n +0.0\n\n","base.pdifff":"\nbase.pdifff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdifff( 5.9, 3.15 )\n 2.75\n > v = base.pdifff( 3.14, 4.2 )\n 0.0\n > v = base.pdifff( 3.14, NaN )\n NaN\n > v = base.pdifff( -0.0, +0.0 )\n +0.0\n\n See Also\n --------\n base.pdiff\n","base.polygamma":"\nbase.polygamma( n, x )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n\n If `n` is not a nonnegative integer, the function returns `NaN`.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN` as either parameter, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Derivative order.\n\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.polygamma( 3, 1.2 )\n ~3.245\n > v = base.polygamma( 5, 1.2 )\n ~41.39\n > v = base.polygamma( 3, -4.9 )\n ~60014.239\n > v = base.polygamma( -1, 5.3 )\n NaN\n > v = base.polygamma( 2, -1.0 )\n Infinity\n\n See Also\n --------\n base.trigamma, base.digamma, base.gamma\n","base.pow":"\nbase.pow( b, x )\n Evaluates the exponential function `bˣ`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.pow( 2.0, 3.0 )\n 8.0\n > y = base.pow( 4.0, 0.5 )\n 2.0\n > y = base.pow( 100.0, 0.0 )\n 1.0\n > y = base.pow( PI, 5.0 )\n ~306.0197\n > y = base.pow( PI, -0.2 )\n ~0.7954\n > y = base.pow( NaN, 3.0 )\n NaN\n > y = base.pow( 5.0, NaN )\n NaN\n > y = base.pow( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.powm1\n","base.powm1":"\nbase.powm1( b, x )\n Evaluates `bˣ - 1`.\n\n When `b` is close to `1` and/or `x` is small, this function is more accurate\n than naively computing `bˣ` and subtracting `1`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.powm1( 2.0, 3.0 )\n 7.0\n > y = base.powm1( 4.0, 0.5 )\n 1.0\n > y = base.powm1( 0.0, 100.0 )\n -1.0\n > y = base.powm1( 100.0, 0.0 )\n 0.0\n > y = base.powm1( 0.0, 0.0 )\n 0.0\n > y = base.powm1( PI, 5.0 )\n ~305.0197\n > y = base.powm1( NaN, 3.0 )\n NaN\n > y = base.powm1( 5.0, NaN )\n NaN\n\n See Also\n --------\n base.pow\n","base.rad2deg":"\nbase.rad2deg( x )\n Converts an angle from radians to degrees.\n\n Parameters\n ----------\n x: number\n Angle in radians.\n\n Returns\n -------\n d: number\n Angle in degrees.\n\n Examples\n --------\n > var d = base.rad2deg( PI/2.0 )\n 90.0\n > d = base.rad2deg( -PI/4.0 )\n -45.0\n > d = base.rad2deg( NaN )\n NaN\n\n // Due to finite precision, canonical values may not be returned:\n > d = base.rad2deg( PI/6.0 )\n 29.999999999999996\n\n See Also\n --------\n base.deg2rad\n","base.ramp":"\nbase.ramp( x )\n Evaluates the ramp function.\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ramp( 3.14 )\n 3.14\n > y = base.ramp( -3.14 )\n 0.0\n\n See Also\n --------\n base.heaviside\n","base.rampf":"\nbase.rampf( x )\n Evaluates the ramp function (single-precision).\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.rampf( 3.14 )\n 3.14\n > y = base.rampf( -3.14 )\n 0.0\n\n See Also\n --------\n base.ramp\n","base.random.arcsine":"\nbase.random.arcsine( a, b )\n Returns a pseudorandom number drawn from an arcsine distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 5.0 )\n \n\n\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n \n\n\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'\n\n\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;\n\n\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;\n\n\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;\n\n\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;\n\n\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;\n\n\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, base.random.beta\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n ","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;","base.random.arcsine.state":"\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n ","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, base.random.beta","base.random.bernoulli":"\nbase.random.bernoulli( p )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.8 );\n\n\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'\n\n\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;\n\n\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;\n\n\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;\n\n\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;\n\n\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;\n\n\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, base.random.binomial\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n ","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, base.random.binomial","base.random.beta":"\nbase.random.beta( α, β )\n Returns a pseudorandom number drawn from a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 );\n\n\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'\n\n\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;\n\n\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;\n\n\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;\n\n\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;\n\n\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;\n\n\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.beta, random.iterators.beta, random.streams.beta\n","base.random.beta.factory":"\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.beta.NAME":"\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;","base.random.beta.seed":"\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;","base.random.beta.state":"\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n ","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.beta, random.iterators.beta, random.streams.beta","base.random.betaprime":"\nbase.random.betaprime( α, β )\n Returns a pseudorandom number drawn from a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 );\n\n\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'\n\n\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;\n\n\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;\n\n\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;\n\n\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;\n\n\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;\n\n\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.betaprime, random.iterators.betaprime, random.streams.betaprime\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;","base.random.betaprime.state":"\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n ","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.betaprime, random.iterators.betaprime, random.streams.betaprime","base.random.binomial":"\nbase.random.binomial( n, p )\n Returns a pseudorandom number drawn from a binomial distribution.\n\n If `n` is not a positive integer or `p` is not a probability, the function\n returns `NaN`.\n\n If `n` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 );\n\n\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'\n\n\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;\n\n\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;\n\n\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;\n\n\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;\n\n\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;\n\n\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.binomial, random.iterators.binomial, random.streams.binomial\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;","base.random.binomial.seed":"\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;","base.random.binomial.state":"\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n ","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.binomial, random.iterators.binomial, random.streams.binomial","base.random.boxMuller":"\nbase.random.boxMuller()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.boxMuller();\n\n\nbase.random.boxMuller.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.boxMuller.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.boxMuller.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.boxMuller.NAME\n 'box-muller'\n\n\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.boxMuller.PRNG;\n\n\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.boxMuller.seed;\n\n\nbase.random.boxMuller.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.boxMuller.seedLength;\n\n\nbase.random.boxMuller.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Get a copy of the current state:\n > var state = base.random.boxMuller.state\n \n\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Set the state:\n > base.random.boxMuller.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n\nbase.random.boxMuller.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.boxMuller.stateLength;\n\n\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.boxMuller.byteLength;\n\n\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.boxMuller.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.boxMuller, random.streams.boxMuller\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.boxMuller.factory();\n > r = rand();\n > r = rand();","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.boxMuller.NAME\n 'box-muller'","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.boxMuller.PRNG;","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.boxMuller.seed;","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.boxMuller.seedLength;","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Get a copy of the current state:\n > var state = base.random.boxMuller.state\n \n\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Set the state:\n > base.random.boxMuller.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n ","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.boxMuller.stateLength;","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.boxMuller.byteLength;","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.boxMuller.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.boxMuller, random.streams.boxMuller","base.random.cauchy":"\nbase.random.cauchy( x0, Ɣ )\n Returns a pseudorandom number drawn from a Cauchy distribution.\n\n If `x0` or `Ɣ` is `NaN` or `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 );\n\n\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n `Ɣ` be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n Ɣ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cauchy.factory();\n > var r = rand( 0.0, 1.5 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `x0` and `Ɣ`:\n > rand = base.random.cauchy.factory( 0.0, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cauchy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cauchy.NAME\n 'cauchy'\n\n\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cauchy.PRNG;\n\n\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cauchy.seed;\n\n\nbase.random.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cauchy.seedLength;\n\n\nbase.random.cauchy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cauchy.state\n \n\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cauchy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n\nbase.random.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cauchy.stateLength;\n\n\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cauchy.byteLength;\n\n\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cauchy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cauchy, random.iterators.cauchy, random.streams.cauchy\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n `Ɣ` be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n Ɣ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cauchy.factory();\n > var r = rand( 0.0, 1.5 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `x0` and `Ɣ`:\n > rand = base.random.cauchy.factory( 0.0, 1.5 );\n > r = rand();\n > r = rand();","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cauchy.NAME\n 'cauchy'","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cauchy.PRNG;","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cauchy.seed;","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cauchy.seedLength;","base.random.cauchy.state":"\nbase.random.cauchy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cauchy.state\n \n\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cauchy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n ","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cauchy.stateLength;","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cauchy.byteLength;","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cauchy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cauchy, random.iterators.cauchy, random.streams.cauchy","base.random.chi":"\nbase.random.chi( k )\n Returns a pseudorandom number drawn from a chi distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chi( 2 );\n\n\nbase.random.chi.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chi.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chi.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chi.NAME\n 'chi'\n\n\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chi.PRNG;\n\n\nbase.random.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chi.seed;\n\n\nbase.random.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chi.seedLength;\n\n\nbase.random.chi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chi.state\n \n\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Set the state:\n > base.random.chi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n\nbase.random.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chi.stateLength;\n\n\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chi.byteLength;\n\n\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chi, random.iterators.chi, random.streams.chi\n","base.random.chi.factory":"\nbase.random.chi.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chi.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chi.factory( 3 );\n > r = rand();\n > r = rand();","base.random.chi.NAME":"\nbase.random.chi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chi.NAME\n 'chi'","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chi.PRNG;","base.random.chi.seed":"\nbase.random.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chi.seed;","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chi.seedLength;","base.random.chi.state":"\nbase.random.chi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chi.state\n \n\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Set the state:\n > base.random.chi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n ","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chi.stateLength;","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chi.byteLength;","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chi, random.iterators.chi, random.streams.chi","base.random.chisquare":"\nbase.random.chisquare( k )\n Returns a pseudorandom number drawn from a chi-square distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 );\n\n\nbase.random.chisquare.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chisquare.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chisquare.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chisquare.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chisquare.NAME\n 'chisquare'\n\n\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chisquare.PRNG;\n\n\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chisquare.seed;\n\n\nbase.random.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chisquare.seedLength;\n\n\nbase.random.chisquare.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chisquare.state\n \n\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Set the state:\n > base.random.chisquare.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n\nbase.random.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chisquare.stateLength;\n\n\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chisquare.byteLength;\n\n\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chisquare.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chisquare, random.iterators.chisquare, random.streams.chisquare\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chisquare.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chisquare.factory( 3 );\n > r = rand();\n > r = rand();","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chisquare.NAME\n 'chisquare'","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chisquare.PRNG;","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chisquare.seed;","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chisquare.seedLength;","base.random.chisquare.state":"\nbase.random.chisquare.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chisquare.state\n \n\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Set the state:\n > base.random.chisquare.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n ","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chisquare.stateLength;","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chisquare.byteLength;","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chisquare.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chisquare, random.iterators.chisquare, random.streams.chisquare","base.random.cosine":"\nbase.random.cosine( μ, s )\n Returns a pseudorandom number drawn from a raised cosine distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 );\n\n\nbase.random.cosine.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cosine.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.cosine.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cosine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cosine.NAME\n 'cosine'\n\n\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cosine.PRNG;\n\n\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cosine.seed;\n\n\nbase.random.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cosine.seedLength;\n\n\nbase.random.cosine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cosine.state\n \n\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cosine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n\nbase.random.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cosine.stateLength;\n\n\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cosine.byteLength;\n\n\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cosine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cosine, random.iterators.cosine, random.streams.cosine\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cosine.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.cosine.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cosine.NAME\n 'cosine'","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cosine.PRNG;","base.random.cosine.seed":"\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cosine.seed;","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cosine.seedLength;","base.random.cosine.state":"\nbase.random.cosine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cosine.state\n \n\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cosine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n ","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cosine.stateLength;","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cosine.byteLength;","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cosine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cosine, random.iterators.cosine, random.streams.cosine","base.random.discreteUniform":"\nbase.random.discreteUniform( a, b )\n Returns a pseudorandom number drawn from a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 );\n\n\nbase.random.discreteUniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.discreteUniform.factory();\n > var r = rand( 0, 10 );\n > r = rand( -20, 20 );\n\n // Provide `a` and `b`:\n > rand = base.random.discreteUniform.factory( 0, 10 );\n > r = rand();\n > r = rand();\n\n\nbase.random.discreteUniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.discreteUniform.NAME\n 'discrete-uniform'\n\n\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.discreteUniform.PRNG;\n\n\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.discreteUniform.seed;\n\n\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.discreteUniform.seedLength;\n\n\nbase.random.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Get a copy of the current state:\n > var state = base.random.discreteUniform.state\n \n\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Set the state:\n > base.random.discreteUniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n\nbase.random.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.discreteUniform.stateLength;\n\n\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.discreteUniform.byteLength;\n\n\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.discreteUniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.discreteUniform.factory();\n > var r = rand( 0, 10 );\n > r = rand( -20, 20 );\n\n // Provide `a` and `b`:\n > rand = base.random.discreteUniform.factory( 0, 10 );\n > r = rand();\n > r = rand();","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.discreteUniform.NAME\n 'discrete-uniform'","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.discreteUniform.PRNG;","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.discreteUniform.seed;","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.discreteUniform.seedLength;","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Get a copy of the current state:\n > var state = base.random.discreteUniform.state\n \n\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Set the state:\n > base.random.discreteUniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n ","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.discreteUniform.stateLength;","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.discreteUniform.byteLength;","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.discreteUniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform","base.random.erlang":"\nbase.random.erlang( k, λ )\n Returns a pseudorandom number drawn from an Erlang distribution.\n\n If `k` is not a positive integer or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 );\n\n\nbase.random.erlang.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: integer (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.erlang.factory();\n > var r = rand( 2, 1.0 );\n > r = rand( 4, 3.14 );\n\n // Provide `k` and `λ`:\n > rand = base.random.erlang.factory( 2, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.erlang.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.erlang.NAME\n 'erlang'\n\n\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.erlang.PRNG;\n\n\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.erlang.seed;\n\n\nbase.random.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.erlang.seedLength;\n\n\nbase.random.erlang.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.erlang.state\n \n\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Set the state:\n > base.random.erlang.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n\nbase.random.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.erlang.stateLength;\n\n\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.erlang.byteLength;\n\n\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.erlang.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.erlang, random.iterators.erlang, random.streams.erlang\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: integer (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.erlang.factory();\n > var r = rand( 2, 1.0 );\n > r = rand( 4, 3.14 );\n\n // Provide `k` and `λ`:\n > rand = base.random.erlang.factory( 2, 1.5 );\n > r = rand();\n > r = rand();","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.erlang.NAME\n 'erlang'","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.erlang.PRNG;","base.random.erlang.seed":"\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.erlang.seed;","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.erlang.seedLength;","base.random.erlang.state":"\nbase.random.erlang.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.erlang.state\n \n\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Set the state:\n > base.random.erlang.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n ","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.erlang.stateLength;","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.erlang.byteLength;","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.erlang.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.erlang, random.iterators.erlang, random.streams.erlang","base.random.exponential":"\nbase.random.exponential( λ )\n Returns a pseudorandom number drawn from an exponential distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 );\n\n\nbase.random.exponential.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.exponential.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.exponential.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.exponential.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.exponential.NAME\n 'exponential'\n\n\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.exponential.PRNG;\n\n\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.exponential.seed;\n\n\nbase.random.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.exponential.seedLength;\n\n\nbase.random.exponential.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Get a copy of the current state:\n > var state = base.random.exponential.state\n \n\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Set the state:\n > base.random.exponential.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n\nbase.random.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.exponential.stateLength;\n\n\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.exponential.byteLength;\n\n\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.exponential.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.exponential, random.iterators.exponential, random.streams.exponential\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.exponential.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.exponential.factory( 10.0 );\n > r = rand();\n > r = rand();","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.exponential.NAME\n 'exponential'","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.exponential.PRNG;","base.random.exponential.seed":"\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.exponential.seed;","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.exponential.seedLength;","base.random.exponential.state":"\nbase.random.exponential.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Get a copy of the current state:\n > var state = base.random.exponential.state\n \n\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Set the state:\n > base.random.exponential.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n ","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.exponential.stateLength;","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.exponential.byteLength;","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.exponential.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.exponential, random.iterators.exponential, random.streams.exponential","base.random.f":"\nbase.random.f( d1, d2 )\n Returns a pseudorandom number drawn from an F distribution.\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.f( 2.0, 5.0 );\n\n\nbase.random.f.factory( [d1, d2, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n\n If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n `d2` be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.f.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.0, 3.14 );\n\n // Provide `d1` and `d2`:\n > rand = base.random.f.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.f.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.f.NAME\n 'f'\n\n\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.f.PRNG;\n\n\nbase.random.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.f.seed;\n\n\nbase.random.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.f.seedLength;\n\n\nbase.random.f.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.f.state\n \n\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.f.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n\nbase.random.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.f.stateLength;\n\n\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.f.byteLength;\n\n\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.f.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.f, random.iterators.f, random.streams.f\n","base.random.f.factory":"\nbase.random.f.factory( [d1, d2, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n\n If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n `d2` be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.f.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.0, 3.14 );\n\n // Provide `d1` and `d2`:\n > rand = base.random.f.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.f.NAME":"\nbase.random.f.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.f.NAME\n 'f'","base.random.f.PRNG":"\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.f.PRNG;","base.random.f.seed":"\nbase.random.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.f.seed;","base.random.f.seedLength":"\nbase.random.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.f.seedLength;","base.random.f.state":"\nbase.random.f.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.f.state\n \n\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.f.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n ","base.random.f.stateLength":"\nbase.random.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.f.stateLength;","base.random.f.byteLength":"\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.f.byteLength;","base.random.f.toJSON":"\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.f.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.f, random.iterators.f, random.streams.f","base.random.frechet":"\nbase.random.frechet( α, s, m )\n Returns a pseudorandom number drawn from a Fréchet distribution.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n If either `α`, `s`, or `m` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.frechet( 2.0, 5.0, 3.33 );\n\n\nbase.random.frechet.factory( [α, s, m, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n and `m` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.frechet.factory();\n > var r = rand( 1.0, 1.0, 0.5 );\n > r = rand( 2.0, 2.0, 1.0 );\n\n // Provide `α`, `s`, and `m`:\n > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.frechet.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.frechet.NAME\n 'frechet'\n\n\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.frechet.PRNG;\n\n\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.frechet.seed;\n\n\nbase.random.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.frechet.seedLength;\n\n\nbase.random.frechet.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.frechet.state\n \n\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.frechet.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n\nbase.random.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.frechet.stateLength;\n\n\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.frechet.byteLength;\n\n\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.frechet.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.frechet, random.iterators.frechet, random.streams.frechet\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α, s, m, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n and `m` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.frechet.factory();\n > var r = rand( 1.0, 1.0, 0.5 );\n > r = rand( 2.0, 2.0, 1.0 );\n\n // Provide `α`, `s`, and `m`:\n > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.frechet.NAME\n 'frechet'","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.frechet.PRNG;","base.random.frechet.seed":"\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.frechet.seed;","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.frechet.seedLength;","base.random.frechet.state":"\nbase.random.frechet.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.frechet.state\n \n\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.frechet.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n ","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.frechet.stateLength;","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.frechet.byteLength;","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.frechet.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.frechet, random.iterators.frechet, random.streams.frechet","base.random.gamma":"\nbase.random.gamma( α, β )\n Returns a pseudorandom number drawn from a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 );\n\n\nbase.random.gamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.gamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gamma.NAME\n 'gamma'\n\n\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gamma.PRNG;\n\n\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gamma.seed;\n\n\nbase.random.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gamma.seedLength;\n\n\nbase.random.gamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gamma.state\n \n\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n\nbase.random.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gamma.stateLength;\n\n\nbase.random.gamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.gamma.byteLength;\n\n\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gamma, random.iterators.gamma, random.streams.gamma\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.gamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gamma.NAME\n 'gamma'","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gamma.PRNG;","base.random.gamma.seed":"\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gamma.seed;","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gamma.seedLength;","base.random.gamma.state":"\nbase.random.gamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gamma.state\n \n\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n ","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gamma.stateLength;","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.gamma.byteLength;","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gamma, random.iterators.gamma, random.streams.gamma","base.random.geometric":"\nbase.random.geometric( p )\n Returns a pseudorandom number drawn from a geometric distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.geometric( 0.8 );\n\n\nbase.random.geometric.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.geometric.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.geometric.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.geometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.geometric.NAME\n 'geometric'\n\n\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.geometric.PRNG;\n\n\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.geometric.seed;\n\n\nbase.random.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.geometric.seedLength;\n\n\nbase.random.geometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.geometric.state\n \n\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Set the state:\n > base.random.geometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n\nbase.random.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.geometric.stateLength;\n\n\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.geometric.byteLength;\n\n\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.geometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.geometric, random.iterators.geometric, random.streams.geometric\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.geometric.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.geometric.factory( 0.3 );\n > r = rand();\n > r = rand();","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.geometric.NAME\n 'geometric'","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.geometric.PRNG;","base.random.geometric.seed":"\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.geometric.seed;","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.geometric.seedLength;","base.random.geometric.state":"\nbase.random.geometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.geometric.state\n \n\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Set the state:\n > base.random.geometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n ","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.geometric.stateLength;","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.geometric.byteLength;","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.geometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.geometric, random.iterators.geometric, random.streams.geometric","base.random.gumbel":"\nbase.random.gumbel( μ, β )\n Returns a pseudorandom number drawn from a Gumbel distribution.\n\n If `μ` or `β` is `NaN` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 );\n\n\nbase.random.gumbel.factory( [μ, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided `μ` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gumbel.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `β`:\n > rand = base.random.gumbel.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gumbel.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gumbel.NAME\n 'gumbel'\n\n\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gumbel.PRNG;\n\n\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gumbel.seed;\n\n\nbase.random.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gumbel.seedLength;\n\n\nbase.random.gumbel.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gumbel.state\n \n\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gumbel.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n\nbase.random.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gumbel.stateLength;\n\n\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.gumbel.byteLength;\n\n\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gumbel.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gumbel, random.iterators.gumbel, random.streams.gumbel\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided `μ` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gumbel.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `β`:\n > rand = base.random.gumbel.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gumbel.NAME\n 'gumbel'","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gumbel.PRNG;","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gumbel.seed;","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gumbel.seedLength;","base.random.gumbel.state":"\nbase.random.gumbel.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gumbel.state\n \n\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gumbel.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n ","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gumbel.stateLength;","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.gumbel.byteLength;","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gumbel.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gumbel, random.iterators.gumbel, random.streams.gumbel","base.random.hypergeometric":"\nbase.random.hypergeometric( N, K, n )\n Returns a pseudorandom number drawn from a hypergeometric distribution.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n returns `NaN`.\n\n If `n > N` or `K > N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 7 );\n\n\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n and `n` be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.hypergeometric.factory();\n > var r = rand( 20, 10, 15 );\n > r = rand( 20, 10, 7 );\n\n // Provide `N`, `K`, and `n`:\n > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n > r = rand();\n > r = rand();\n\n\nbase.random.hypergeometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.hypergeometric.NAME\n 'hypergeometric'\n\n\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.hypergeometric.PRNG;\n\n\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.hypergeometric.seed;\n\n\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.hypergeometric.seedLength;\n\n\nbase.random.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Get a copy of the current state:\n > var state = base.random.hypergeometric.state\n \n\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Set the state:\n > base.random.hypergeometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n\nbase.random.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.hypergeometric.stateLength;\n\n\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.hypergeometric.byteLength;\n\n\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.hypergeometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n and `n` be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.hypergeometric.factory();\n > var r = rand( 20, 10, 15 );\n > r = rand( 20, 10, 7 );\n\n // Provide `N`, `K`, and `n`:\n > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n > r = rand();\n > r = rand();","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.hypergeometric.NAME\n 'hypergeometric'","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.hypergeometric.PRNG;","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.hypergeometric.seed;","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.hypergeometric.seedLength;","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Get a copy of the current state:\n > var state = base.random.hypergeometric.state\n \n\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Set the state:\n > base.random.hypergeometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n ","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.hypergeometric.stateLength;","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.hypergeometric.byteLength;","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.hypergeometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat();\n\n\nbase.random.improvedZiggurat.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.improvedZiggurat.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.improvedZiggurat.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.improvedZiggurat.NAME\n 'improved-ziggurat'\n\n\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.improvedZiggurat.PRNG;\n\n\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.improvedZiggurat.seed;\n\n\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.seedLength;\n\n\nbase.random.improvedZiggurat.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Get a copy of the current state:\n > var state = base.random.improvedZiggurat.state\n \n\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Set the state:\n > base.random.improvedZiggurat.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.stateLength;\n\n\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.improvedZiggurat.byteLength;\n\n\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.improvedZiggurat.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.improvedZiggurat, random.streams.improvedZiggurat\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.improvedZiggurat.factory();\n > r = rand();\n > r = rand();","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.improvedZiggurat.NAME\n 'improved-ziggurat'","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.improvedZiggurat.PRNG;","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.improvedZiggurat.seed;","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.seedLength;","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Get a copy of the current state:\n > var state = base.random.improvedZiggurat.state\n \n\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Set the state:\n > base.random.improvedZiggurat.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n ","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.stateLength;","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.improvedZiggurat.byteLength;","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.improvedZiggurat.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.improvedZiggurat, random.streams.improvedZiggurat","base.random.invgamma":"\nbase.random.invgamma( α, β )\n Returns a pseudorandom number drawn from an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 );\n\n\nbase.random.invgamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.invgamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.invgamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.invgamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.invgamma.NAME\n 'invgamma'\n\n\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.invgamma.PRNG;\n\n\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.invgamma.seed;\n\n\nbase.random.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.invgamma.seedLength;\n\n\nbase.random.invgamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.invgamma.state\n \n\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.invgamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n\nbase.random.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.invgamma.stateLength;\n\n\nbase.random.invgamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.invgamma.byteLength;\n\n\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.invgamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.invgamma, random.iterators.invgamma, random.streams.invgamma\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.invgamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.invgamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.invgamma.NAME\n 'invgamma'","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.invgamma.PRNG;","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.invgamma.seed;","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.invgamma.seedLength;","base.random.invgamma.state":"\nbase.random.invgamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.invgamma.state\n \n\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.invgamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n ","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.invgamma.stateLength;","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.invgamma.byteLength;","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.invgamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.invgamma, random.iterators.invgamma, random.streams.invgamma","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a, b )\n Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n distribution.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 2.0, 5.0 );\n\n\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.kumaraswamy.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `a` and `b`:\n > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.kumaraswamy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.kumaraswamy.NAME\n 'kumaraswamy'\n\n\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.kumaraswamy.PRNG;\n\n\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.kumaraswamy.seed;\n\n\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.seedLength;\n\n\nbase.random.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.kumaraswamy.state\n \n\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.kumaraswamy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.stateLength;\n\n\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.kumaraswamy.byteLength;\n\n\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.kumaraswamy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.kumaraswamy.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `a` and `b`:\n > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.kumaraswamy.NAME\n 'kumaraswamy'","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.kumaraswamy.PRNG;","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.kumaraswamy.seed;","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.seedLength;","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.kumaraswamy.state\n \n\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.kumaraswamy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n ","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.stateLength;","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.kumaraswamy.byteLength;","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.kumaraswamy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy","base.random.laplace":"\nbase.random.laplace( μ, b )\n Returns a pseudorandom number drawn from a Laplace distribution.\n\n If `μ` or `b` is `NaN` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 );\n\n\nbase.random.laplace.factory( [μ, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n\n If provided `μ` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.laplace.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.laplace.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.laplace.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.laplace.NAME\n 'laplace'\n\n\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.laplace.PRNG;\n\n\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.laplace.seed;\n\n\nbase.random.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.laplace.seedLength;\n\n\nbase.random.laplace.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.laplace.state\n \n\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.laplace.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n\nbase.random.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.laplace.stateLength;\n\n\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.laplace.byteLength;\n\n\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.laplace.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.laplace, random.iterators.laplace, random.streams.laplace\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n\n If provided `μ` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.laplace.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.laplace.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.laplace.NAME\n 'laplace'","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.laplace.PRNG;","base.random.laplace.seed":"\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.laplace.seed;","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.laplace.seedLength;","base.random.laplace.state":"\nbase.random.laplace.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.laplace.state\n \n\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.laplace.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n ","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.laplace.stateLength;","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.laplace.byteLength;","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.laplace.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.laplace, random.iterators.laplace, random.streams.laplace","base.random.levy":"\nbase.random.levy( μ, c )\n Returns a pseudorandom number drawn from a Lévy distribution.\n\n If `μ` or `c` is `NaN` or `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 );\n\n\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'\n\n\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;\n\n\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;\n\n\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;\n\n\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;\n\n\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;\n\n\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.levy, random.iterators.levy, random.streams.levy\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.levy.NAME":"\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;","base.random.levy.seed":"\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;","base.random.levy.state":"\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n ","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.levy, random.iterators.levy, random.streams.levy","base.random.logistic":"\nbase.random.logistic( μ, s )\n Returns a pseudorandom number drawn from a logistic distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 );\n\n\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'\n\n\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;\n\n\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;\n\n\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;\n\n\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;\n\n\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;\n\n\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.logistic, random.iterators.logistic, random.streams.logistic\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;","base.random.logistic.seed":"\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;","base.random.logistic.state":"\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n ","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.logistic, random.iterators.logistic, random.streams.logistic","base.random.lognormal":"\nbase.random.lognormal( μ, σ )\n Returns a pseudorandom number drawn from a lognormal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 );\n\n\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'\n\n\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;\n\n\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;\n\n\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;\n\n\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;\n\n\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;\n\n\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.lognormal, random.iterators.lognormal, random.streams.lognormal\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;","base.random.lognormal.state":"\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n ","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.lognormal, random.iterators.lognormal, random.streams.lognormal","base.random.minstd":"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd();\n\n\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();\n\n\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838\n\n\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'\n\n\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1\n\n\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646\n\n\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;\n\n\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;\n\n\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;\n\n\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;\n\n\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();","base.random.minstd.factory":"\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646","base.random.minstd.seed":"\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;","base.random.minstd.state":"\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n ","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle();\n\n\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();\n\n\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654\n\n\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'\n\n\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1\n\n\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646\n\n\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;\n\n\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;\n\n\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;\n\n\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;\n\n\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n ","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi","base.random.mt19937":"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937();\n\n\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();\n\n\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775\n\n\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'\n\n\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 0\n\n\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295\n\n\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;\n\n\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;\n\n\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;\n\n\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;\n\n\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 0","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;","base.random.mt19937.state":"\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n ","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r, p )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n\n If `p` is not in the interval `(0,1)`, the function returns `NaN`.\n\n If `r` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.8 );\n\n\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'\n\n\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;\n\n\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;\n\n\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;\n\n\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;\n\n\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;\n\n\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n ","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial","base.random.normal":"\nbase.random.normal( μ, σ )\n Returns a pseudorandom number drawn from a normal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 );\n\n\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'\n\n\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;\n\n\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;\n\n\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;\n\n\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;\n\n\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;\n\n\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.normal, random.iterators.normal, random.streams.normal\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.normal.NAME":"\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;","base.random.normal.seed":"\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;","base.random.normal.state":"\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n ","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.normal, random.iterators.normal, random.streams.normal","base.random.pareto1":"\nbase.random.pareto1( α, β )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 );\n\n\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'\n\n\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;\n\n\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;\n\n\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;\n\n\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;\n\n\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;\n\n\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.pareto1, random.iterators.pareto1, random.streams.pareto1\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;","base.random.pareto1.state":"\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n ","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.pareto1, random.iterators.pareto1, random.streams.pareto1","base.random.poisson":"\nbase.random.poisson( λ )\n Returns a pseudorandom number drawn from a Poisson distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.poisson( 7.9 );\n\n\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'\n\n\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;\n\n\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;\n\n\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;\n\n\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;\n\n\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;\n\n\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.poisson, random.iterators.poisson, random.streams.poisson\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;","base.random.poisson.seed":"\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;","base.random.poisson.state":"\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n ","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.poisson, random.iterators.poisson, random.streams.poisson","base.random.randi":"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randi();\n\n\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();\n\n\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'\n\n\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;\n\n\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;\n\n\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;\n\n\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;\n\n\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;\n\n\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;\n\n\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;\n\n\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937\n","base.random.randi.factory":"\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();","base.random.randi.NAME":"\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;","base.random.randi.MIN":"\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;","base.random.randi.MAX":"\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;","base.random.randi.seed":"\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;","base.random.randi.state":"\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n ","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937","base.random.randn":"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randn();\n\n\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'\n\n\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;\n\n\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;\n\n\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;\n\n\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;\n\n\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;\n\n\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu\n","base.random.randn.factory":"\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();","base.random.randn.NAME":"\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;","base.random.randn.seed":"\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;","base.random.randn.state":"\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n ","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu","base.random.randu":"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number on the interval `[0,1)`.\n\n Examples\n --------\n > var r = base.random.randu();\n\n\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'\n\n\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;\n\n\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;\n\n\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;\n\n\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;\n\n\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;\n\n\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;\n\n\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;\n\n\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn\n","base.random.randu.factory":"\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();","base.random.randu.NAME":"\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;","base.random.randu.MIN":"\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;","base.random.randu.MAX":"\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;","base.random.randu.seed":"\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;","base.random.randu.state":"\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n ","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn","base.random.rayleigh":"\nbase.random.rayleigh( σ )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n\n If `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.rayleigh( 2.5 );\n\n\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'\n\n\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;\n\n\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;\n\n\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;\n\n\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;\n\n\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;\n\n\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n ","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh","base.random.t":"\nbase.random.t( v )\n Returns a pseudorandom number drawn from a Student's t distribution.\n\n If `v <= 0` or `v` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.t( 2.0 );\n\n\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'\n\n\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;\n\n\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;\n\n\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;\n\n\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;\n\n\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;\n\n\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.t, random.iterators.t, random.streams.t\n","base.random.t.factory":"\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();","base.random.t.NAME":"\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'","base.random.t.PRNG":"\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;","base.random.t.seed":"\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;","base.random.t.seedLength":"\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;","base.random.t.state":"\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n ","base.random.t.stateLength":"\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;","base.random.t.byteLength":"\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;","base.random.t.toJSON":"\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.t, random.iterators.t, random.streams.t","base.random.triangular":"\nbase.random.triangular( a, b, c )\n Returns a pseudorandom number drawn from a triangular distribution.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.triangular( 2.0, 5.0, 3.33 );\n\n\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'\n\n\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;\n\n\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;\n\n\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;\n\n\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;\n\n\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;\n\n\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.triangular, random.iterators.triangular, random.streams.triangular\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;","base.random.triangular.seed":"\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;","base.random.triangular.state":"\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n ","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.triangular, random.iterators.triangular, random.streams.triangular","base.random.uniform":"\nbase.random.uniform( a, b )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support (inclusive).\n\n b: number\n Maximum support (exclusive).\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 );\n\n\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'\n\n\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;\n\n\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;\n\n\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;\n\n\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;\n\n\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;\n\n\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.uniform, random.iterators.uniform, random.streams.uniform, base.random.discreteUniform, base.random.randu\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;","base.random.uniform.seed":"\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;","base.random.uniform.state":"\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n ","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.uniform, random.iterators.uniform, random.streams.uniform, base.random.discreteUniform, base.random.randu","base.random.weibull":"\nbase.random.weibull( k, λ )\n Returns a pseudorandom number drawn from a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If either `λ` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 );\n\n\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'\n\n\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;\n\n\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;\n\n\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;\n\n\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;\n\n\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;\n\n\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.weibull, random.iterators.weibull, random.streams.weibull\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;","base.random.weibull.seed":"\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;","base.random.weibull.state":"\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n ","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.weibull, random.iterators.weibull, random.streams.weibull","base.reldiff":"\nbase.reldiff( x, y[, scale] )\n Computes the relative difference of two real numbers.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference.\n\n Examples\n --------\n > var d = base.reldiff( 2.0, 5.0 )\n 0.6\n > d = base.reldiff( -1.0, 3.14 )\n ~1.318\n > d = base.reldiff( -2.0, 5.0, 'max-abs' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'max' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'min-abs' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'min' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'mean-abs' )\n 2.0\n > d = base.reldiff( -2.0, 5.0, 'mean' )\n ~4.667\n > d = base.reldiff( -2.0, 5.0, 'x' )\n 3.5\n > d = base.reldiff( 5.0, -2.0, 'x' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'y' )\n 1.4\n > d = base.reldiff( 5.0, -2.0, 'y' )\n 3.5\n\n // Custom scale function:\n > function scale( x, y ) {\n ... var s;\n ...\n ... x = base.abs( x );\n ... y = base.abs( y );\n ...\n ... // Maximum absolute value:\n ... s = (x < y ) ? y : x;\n ...\n ... // Scale in units of epsilon:\n ... return s * EPS;\n ... };\n > d = base.reldiff( 12.15, 12.149999999999999, scale )\n ~0.658\n\n See Also\n --------\n base.absdiff, base.epsdiff\n","base.rempio2":"\nbase.rempio2( x, y )\n Computes `x - nπ/2 = r`.\n\n The function returns `n` and stores the remainder `r` as the two numbers\n `y[0]` and `y[1]`, such that `y[0] + y[1] = r`.\n\n For input values larger than `2^20 * π/2` in magnitude, the function only\n returns the last three binary digits of `n` and not the full result.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: Array|TypedArray|Object\n Remainder elements.\n\n Returns\n -------\n n: integer\n Factor of `π/2`.\n\n Examples\n --------\n > var y = [ 0.0, 0.0 ];\n > var n = base.rempio2( 128.0, y )\n 81\n > var y1 = y[ 0 ]\n ~0.765\n > var y2 = y[ 1 ]\n ~3.618e-17\n\n\n","base.risingFactorial":"\nbase.risingFactorial( x, n )\n Computes the rising factorial of `x` and `n`.\n\n If provided a non-integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.risingFactorial( 0.9, 5 )\n ~94.766\n > v = base.risingFactorial( -9.0, 3 )\n -504.0\n > v = base.risingFactorial( 0.0, 2 )\n 0.0\n > v = base.risingFactorial( 3.0, -2 )\n 0.5\n\n See Also\n --------\n base.fallingFactorial\n","base.rotl32":"\nbase.rotl32( x, shift )\n Performs a bitwise rotation to the left.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 2147483649;\n > var bStr = base.toBinaryStringUint32( x )\n '10000000000000000000000000000001'\n > var y = base.rotl32( x, 10 )\n 1536\n > bstr = base.toBinaryStringUint32( y )\n '00000000000000000000011000000000'\n\n See Also\n --------\n base.rotr32\n","base.rotr32":"\nbase.rotr32( x, shift )\n Performs a bitwise rotation to the right.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 1;\n > var bStr = base.toBinaryStringUint32( x )\n '00000000000000000000000000000001'\n > var y = base.rotr32( x, 10 )\n 4194304\n > bstr = base.toBinaryStringUint32( y )\n '00000000010000000000000000000000'\n\n See Also\n --------\n base.rotl32\n","base.round":"\nbase.round( x )\n Rounds a numeric value to the nearest integer.\n\n Ties are rounded toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round( 3.14 )\n 3.0\n > y = base.round( -4.2 )\n -4.0\n > y = base.round( -4.6 )\n -5.0\n > y = base.round( 9.5 )\n 10.0\n > y = base.round( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.roundn, base.trunc\n","base.round2":"\nbase.round2( x )\n Rounds a numeric value to the nearest power of two on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round2( 3.14 )\n 4.0\n > y = base.round2( -4.2 )\n -4.0\n > y = base.round2( -4.6 )\n -4.0\n > y = base.round2( 9.5 )\n 8.0\n > y = base.round2( 13.0 )\n 16.0\n > y = base.round2( -13.0 )\n -16.0\n > y = base.round2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round, base.round10\n","base.round10":"\nbase.round10( x )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round10( 3.14 )\n 1.0\n > y = base.round10( -4.2 )\n -1.0\n > y = base.round10( -4.6 )\n -1.0\n > y = base.round10( 9.5 )\n 10.0\n > y = base.round10( 13.0 )\n 10.0\n > y = base.round10( -13.0 )\n -10.0\n > y = base.round10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round, base.round2\n","base.roundb":"\nbase.roundb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundb( 3.14159, -2, 10 )\n 3.14\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.roundb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two:\n > y = base.roundb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.round, base.roundn\n","base.roundn":"\nbase.roundn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundn( 3.14159, -2 )\n 3.14\n\n // If `n = 0`, standard round behavior:\n > y = base.roundn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.roundn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.round, base.roundb\n","base.roundsd":"\nbase.roundsd( x, n[, b] )\n Rounds a numeric value to the nearest number with `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.roundsd( 3.14159, 3 )\n 3.14\n > y = base.roundsd( 3.14159, 1 )\n 3.0\n > y = base.roundsd( 12368.0, 2 )\n 12000.0\n > y = base.roundsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.round, base.truncsd\n","base.rsqrt":"\nbase.rsqrt( x )\n Computes the reciprocal square root of a double-precision floating-point\n number.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrt( 4.0 )\n 0.5\n > y = base.rsqrt( 100.0 )\n 0.1\n > y = base.rsqrt( 0.0 )\n Infinity\n > y = base.rsqrt( Infinity )\n 0.0\n > y = base.rsqrt( -4.0 )\n NaN\n > y = base.rsqrt( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n","base.rsqrtf":"\nbase.rsqrtf( x )\n Computes the reciprocal square root of a single-precision floating-point\n number.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrtf( 4.0 )\n 0.5\n > y = base.rsqrtf( 0.0 )\n Infinity\n > y = base.rsqrtf( Infinity )\n 0.0\n > y = base.rsqrtf( -4.0 )\n NaN\n > y = base.rsqrtf( NaN )\n NaN\n\n See Also\n --------\n base.rsqrt, base.sqrtf\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value, dtype, order )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n\n If `value` is a number and `dtype` is a complex number data type, the\n function returns a zero-dimensional ndarray containing a complex number\n whose real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n dtype: string\n Data type.\n\n order: string\n Memory layout (either 'row-major' or 'column-major').\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\n \n > var sh = x.shape\n []\n > var dt = x.dtype\n 'float64'\n > var v = x.get()\n 1.0\n\n See Also\n --------\n array, base.ndarray, ndarray\n","base.setHighWord":"\nbase.setHighWord( x, high )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n high: integer\n Unsigned 32-bit integer to replace the higher order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same lower order word as `x`.\n\n Examples\n --------\n // Set the higher order bits of `+infinity` to return `1`:\n > var high = 1072693248 >>> 0;\n > var y = base.setHighWord( PINF, high )\n 1.0\n\n See Also\n --------\n base.getHighWord, base.setLowWord\n","base.setLowWord":"\nbase.setLowWord( x, low )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n\n Setting the lower order bits of `NaN` or positive or negative infinity will\n return `NaN`, as `NaN` is defined as a double whose exponent bit sequence is\n all ones and whose fraction can be any bit sequence except all zeros.\n Positive and negative infinity are defined as doubles with an exponent bit\n sequence equal to all ones and a fraction equal to all zeros. Hence,\n changing the less significant bits of positive and negative infinity\n converts each value to `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n low: integer\n Unsigned 32-bit integer to replace the lower order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same higher order word as `x`.\n\n Examples\n --------\n > var low = 5 >>> 0;\n > var x = 3.14e201;\n > var y = base.setLowWord( x, low )\n 3.139998651394392e+201\n\n // Special cases:\n > var low = 12345678;\n > var y = base.setLowWord( PINF, low )\n NaN\n > y = base.setLowWord( NINF, low )\n NaN\n > y = base.setLowWord( NaN, low )\n NaN\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n","base.sici":"\nbase.sici( x )\n Computes the sine and cosine integrals.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n Sine and cosine integrals.\n\n Examples\n --------\n > var y = base.sici( 3.0 )\n [ ~1.849, ~0.12 ]\n > y = base.sici( 0.0 )\n [ 0.0, -Infinity ]\n > y = base.sici( -9.0 )\n [ ~-1.665, ~0.055 ]\n > y = base.sici( NaN )\n [ NaN, NaN ]\n\n\nbase.sici.assign( x, out, stride, offset )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.sici.assign( 3.0, out, 1, 0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true\n","base.sici.assign":"\nbase.sici.assign( x, out, stride, offset )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.sici.assign( 3.0, out, 1, 0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true","base.signbit":"\nbase.signbit( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbit( 4.0 )\n false\n > bool = base.signbit( -9.14e-34 )\n true\n > bool = base.signbit( 0.0 )\n false\n > bool = base.signbit( -0.0 )\n true\n\n See Also\n --------\n base.signbitf\n","base.signbitf":"\nbase.signbitf( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\n false\n > bool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\n true\n > bool = base.signbitf( 0.0 )\n false\n > bool = base.signbitf( -0.0 )\n true\n\n See Also\n --------\n base.signbit\n","base.significandf":"\nbase.significandf( x )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Significand.\n\n Examples\n --------\n > var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\n 4293751\n > s = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\n 5288021\n > s = base.significandf( base.float64ToFloat32( -3.14 ) )\n 4781507\n > s = base.significandf( 0.0 )\n 0\n > s = base.significandf( NaN )\n 4194304\n\n","base.signum":"\nbase.signum( x )\n Evaluates the signum function for a double-precision floating-point number.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signum( -5.0 )\n -1.0\n > sign = base.signum( 5.0 )\n 1.0\n > sign = base.signum( -0.0 )\n -0.0\n > sign = base.signum( 0.0 )\n 0.0\n > sign = base.signum( NaN )\n NaN\n\n","base.signumf":"\nbase.signumf( x )\n Evaluates the signum function for a single-precision floating-point number.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signumf( -5.0 )\n -1.0\n > sign = base.signumf( 5.0 )\n 1.0\n > sign = base.signumf( -0.0 )\n -0.0\n > sign = base.signumf( 0.0 )\n 0.0\n > sign = base.signumf( NaN )\n NaN\n\n See Also\n --------\n base.signum\n","base.sin":"\nbase.sin( x )\n Computes the sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Sine.\n\n Examples\n --------\n > var y = base.sin( 0.0 )\n ~0.0\n > y = base.sin( PI/2.0 )\n ~1.0\n > y = base.sin( -PI/6.0 )\n ~-0.5\n > y = base.sin( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinpi, base.tan\n","base.sinc":"\nbase.sinc( x )\n Computes the normalized cardinal sine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cardinal sine.\n\n Examples\n --------\n > var y = base.sinc( 0.5 )\n ~0.637\n > y = base.sinc( -1.2 )\n ~-0.156\n > y = base.sinc( 0.0 )\n 1.0\n > y = base.sinc( NaN )\n NaN\n\n See Also\n --------\n base.sin\n","base.sincos":"\nbase.sincos( x )\n Simultaneously computes the sine and cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: Array\n Sine and cosine.\n\n Examples\n --------\n > var y = base.sincos( 0.0 )\n [ ~0.0, ~1.0 ]\n > y = base.sincos( PI/2.0 )\n [ ~1.0, ~0.0 ]\n > y = base.sincos( -PI/6.0 )\n [ ~-0.5, ~0.866 ]\n > y = base.sincos( NaN )\n [ NaN, NaN ]\n\n\nbase.sincos( x, out, stride, offset )\n Simultaneously computes the sine and cosine of a number and assigns\n results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Sine and cosine.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincos.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cos, base.sin, base.sincospi","base.sincospi":"\nbase.sincospi( x )\n Simultaneously computes the sine and cosine of a number times π.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: Array\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var y = base.sincospi( 0.0 )\n [ 0.0, 1.0 ]\n > y = base.sincospi( 0.5 )\n [ 1.0, 0.0 ]\n > y = base.sincospi( 0.1 )\n [ ~0.309, ~0.951 ]\n > y = base.sincospi( NaN )\n [ NaN, NaN ]\n\n\nbase.sincospi.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cospi, base.sincos, base.sinpi","base.sincospi.assign":"\nbase.sincospi.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cospi, base.sincos, base.sinpi","base.sinh":"\nbase.sinh( x )\n Computes the hyperbolic sine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic sine.\n\n Examples\n --------\n > var y = base.sinh( 0.0 )\n 0.0\n > y = base.sinh( 2.0 )\n ~3.627\n > y = base.sinh( -2.0 )\n ~-3.627\n > y = base.sinh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sin, base.tanh\n","base.sinpi":"\nbase.sinpi( x )\n Computes the value of `sin(πx)`.\n\n The function computes `sin(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.sinpi( 0.0 )\n 0.0\n > y = base.sinpi( 0.5 )\n 1.0\n > y = base.sinpi( 0.9 )\n ~0.309\n > y = base.sinpi( NaN )\n NaN\n\n See Also\n --------\n base.sin\n","base.spence":"\nbase.spence( x )\n Evaluates Spence’s function, which is also known as the dilogarithm.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.spence( 3.0 )\n ~-1.437\n > y = base.spence( 0.0 )\n ~1.645\n > y = base.spence( -9.0 )\n NaN\n > y = base.spence( NaN )\n NaN\n\n","base.sqrt":"\nbase.sqrt( x )\n Computes the principal square root of a double-precision floating-point\n number.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrt( 4.0 )\n 2.0\n > y = base.sqrt( 9.0 )\n 3.0\n > y = base.sqrt( 0.0 )\n 0.0\n > y = base.sqrt( -4.0 )\n NaN\n > y = base.sqrt( NaN )\n NaN\n\n See Also\n --------\n base.cbrt, base.rsqrt\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x )\n Computes the principal square root of `1+x` minus one.\n\n This function is more accurate than the obvious approach for small `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Square root of `1+x` minus one.\n\n Examples\n --------\n > var y = base.sqrt1pm1( 3.0 )\n 1.0\n > y = base.sqrt1pm1( 0.5 )\n ~0.225\n > y = base.sqrt1pm1( 0.02 )\n ~0.01\n > y = base.sqrt1pm1( -0.5 )\n ~-0.293\n > y = base.sqrt1pm1( -1.1 )\n NaN\n > y = base.sqrt1pm1( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n","base.sqrtf":"\nbase.sqrtf( x )\n Computes the principal square root of a single-precision floating-point\n number.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrtf( 4.0 )\n 2.0\n > y = base.sqrtf( 9.0 )\n 3.0\n > y = base.sqrtf( 0.0 )\n 0.0\n > y = base.sqrtf( -4.0 )\n NaN\n > y = base.sqrtf( NaN )\n NaN\n\n See Also\n --------\n base.cbrtf, base.rsqrtf, base.sqrt\n","base.sqrtpi":"\nbase.sqrtpi( x )\n Computes the principal square root of the product of π and a positive\n double-precision floating-point number.\n\n For `x < 0`, the square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root of the product of π and the input value.\n\n Examples\n --------\n > var y = base.sqrtpi( 4.0 )\n ~3.5449\n > y = base.sqrtpi( 10.0 )\n ~5.60499\n > y = base.sqrtpi( 0.0 )\n 0.0\n > y = base.sqrtpi( -4.0 )\n NaN\n > y = base.sqrtpi( NaN )\n NaN\n\n See Also\n --------\n base.sqrt","base.strided.binary":"\nbase.strided.binary( arrays, shape, strides, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary( [ x, y, z ], shape, strides, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1, dtypes2, dtypes3[, options] )\n Generates a list of binary interface signatures from strided array data\n types.\n\n The function returns a strided array having a stride length of `3` (i.e.,\n every `3` elements define a binary interface signature).\n\n For each signature (i.e., set of three consecutive non-overlapping strided\n array elements), the first two elements are the input data types and the\n third element is the return data type.\n\n All signatures follow type promotion rules.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the first input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the second input argument.\n\n dtypes3: ArrayLike\n List of supported data types for the output value.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing binary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n [...]\n\n See Also\n --------\n base.strided.binarySignatureCallbacks\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table, signatures )\n Assigns callbacks to binary interfaces according to type promotion rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing binary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\n > var t = {\n ... 'default': base.add,\n ... 'complex64': base.caddf,\n ... 'complex128': base.cadd\n ... };\n > var out = base.strided.binarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.binaryDtypeSignatures\n","base.strided.ccopy":"\nbase.strided.ccopy( N, x, strideX, y, strideY )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy( x.length, x, 1, y, 1 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imag( z )\n 2.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy( 2, x, -2, y, 1 );\n > z = y.get( 0 );\n > re = realf( z )\n 5.0\n > im = imag( z )\n 6.0\n\n // Using typed array views:\n > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.ccopy( 2, x1, -2, y1, 1 );\n > z = y0.get( 2 );\n > re = realf( z )\n 7.0\n > im = imag( z )\n 8.0\n\n\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imag( z )\n 2.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > z = y.get( y.length-1 );\n > re = realf( z )\n 3.0\n > im = imag( z )\n 4.0\n\n See Also\n --------\n base.strided.cswap\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imag( z )\n 2.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > z = y.get( y.length-1 );\n > re = realf( z )\n 3.0\n > im = imag( z )\n 4.0\n\n See Also\n --------\n base.strided.cswap","base.strided.cmap":"\nbase.strided.cmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap( x.length, x, 1, y, 1, base.cidentityf );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Using `N` and stride parameters:\n > y = new Complex64Array( x.length );\n > base.strided.cmap( 2, x, 2, y, -1, base.cidentityf );\n > v = y.get( 0 )\n \n > re = real( v )\n 5.0\n > im = imag( v )\n 6.0\n\n // Using view offsets:\n > var x0 = new Complex64Array( xbuf );\n > var y0 = new Complex64Array( x0.length );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf );\n > v = y1.get( 0 )\n \n > re = real( v )\n 7.0\n > im = imag( v )\n 8.0\n\n\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Advanced indexing:\n > x = new Complex64Array( xbuf );\n > y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\n > v = y.get( y.length-1 )\n \n > re = real( v )\n 3.0\n > im = imag( v )\n 4.0\n\n See Also\n --------\n base.strided.zmap, base.strided.unary\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Advanced indexing:\n > x = new Complex64Array( xbuf );\n > y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\n > v = y.get( y.length-1 )\n \n > re = real( v )\n 3.0\n > im = imag( v )\n 4.0\n\n See Also\n --------\n base.strided.zmap, base.strided.unary","base.strided.cswap":"\nbase.strided.cswap( N, x, strideX, y, strideY )\n Interchanges two complex single-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped with\n values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap( x.length, x, 1, y, 1 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 2.0\n > z = x.get( 0 );\n > re = realf( z )\n 6.0\n > im = imagf( z )\n 7.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap( 2, x, -2, y, 1 );\n > z = y.get( 0 );\n > re = realf( z )\n 5.0\n > im = imagf( z )\n 6.0\n > z = x.get( 0 );\n > re = realf( z )\n 0.0\n > im = imagf( z )\n 0.0\n\n // Using typed array views:\n > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.cswap( 2, x1, -2, y1, 1 );\n > z = y0.get( 2 );\n > re = realf( z )\n 7.0\n > im = imagf( z )\n 8.0\n > z = x0.get( 1 );\n > re = realf( z )\n 0.0\n > im = imagf( z )\n 0.0\n\n\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two complex single-precision floating-point vectors using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 2.0\n > z = x.get( 0 );\n > re = realf( z )\n 6.0\n > im = imagf( z )\n 7.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > z = y.get( y.length-1 );\n > re = realf( z )\n 3.0\n > im = imagf( z )\n 4.0\n > z = x.get( 1 );\n > re = realf( z )\n 0.0\n > im = imagf( z )\n 0.0\n\n See Also\n --------\n base.strided.ccopy\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two complex single-precision floating-point vectors using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 2.0\n > z = x.get( 0 );\n > re = realf( z )\n 6.0\n > im = imagf( z )\n 7.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > z = y.get( y.length-1 );\n > re = realf( z )\n 3.0\n > im = imagf( z )\n 4.0\n > z = x.get( 1 );\n > re = realf( z )\n 0.0\n > im = imagf( z )\n 0.0\n\n See Also\n --------\n base.strided.ccopy","base.strided.cumax":"\nbase.strided.cumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumax( N, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.cumax( N, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumax\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumax","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumaxabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.cumaxabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs","base.strided.cumin":"\nbase.strided.cumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumin( N, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.cumin( N, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumin\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumin","base.strided.cuminabs":"\nbase.strided.cuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cuminabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.cuminabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs","base.strided.dabs":"\nbase.strided.dabs( N, x, strideX, y, strideY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs( N, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dabs( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs","base.strided.dabs2":"\nbase.strided.dabs2( N, x, strideX, y, strideY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2( x.length, x, 1, y, 1 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2( N, x, 2, y, -1 )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dabs2( N, x1, -2, y1, 1 )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs2\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs2","base.strided.dapx":"\nbase.strided.dapx( N, alpha, x, stride )\n Adds a constant to each element in a double-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > var alpha = 5.0;\n > base.strided.dapx( x.length, alpha, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.dapx( N, alpha, x, stride )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > alpha = 5.0;\n > stride = 2;\n > base.strided.dapx( N, alpha, x1, stride )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\nbase.strided.dapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > var alpha = 5.0;\n > base.strided.dapx.ndarray( x.length, alpha, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.dapx.ndarray( N, alpha, x, stride, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gapx, base.strided.sapx\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > var alpha = 5.0;\n > base.strided.dapx.ndarray( x.length, alpha, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.dapx.ndarray( N, alpha, x, stride, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gapx, base.strided.sapx","base.strided.dapxsum":"\nbase.strided.dapxsum( N, alpha, x, stride )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dapxsum( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dapxsum( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.dapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N, alpha, x, stride )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dapxsumkbn( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dapxsumkbn( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N, alpha, x, stride )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dapxsumkbn2( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dapxsumkbn2( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N, alpha, x, stride )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dapxsumors( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dapxsumors( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.dapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N, alpha, x, stride )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dapxsumpw( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dapxsumpw( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.dapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw","base.strided.dasum":"\nbase.strided.dasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum( x.length, x, 1 )\n 15.0\n\n // Sum every other value:\n > s = base.strided.dasum( 3, x, 2 )\n 9.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.dasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum","base.strided.dasumpw":"\nbase.strided.dasumpw( N, x, stride )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dasumpw( N, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dasumpw( N, x1, stride )\n 5.0\n\nbase.strided.dasumpw.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dasumpw.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dasumpw.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw","base.strided.daxpy":"\nbase.strided.daxpy( N, alpha, x, strideX, y, strideY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.strided.daxpy( 3, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.dasum, base.strided.gaxpy, base.strided.saxpy\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.dasum, base.strided.gaxpy, base.strided.saxpy","base.strided.dcbrt":"\nbase.strided.dcbrt( N, x, strideX, y, strideY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt( x.length, x, 1, y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt( N, x, 2, y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcbrt( N, x1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, base.strided.scbrt\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, base.strided.scbrt","base.strided.dceil":"\nbase.strided.dceil( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil( x.length, x, 1, y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil( N, x, 2, y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dceil( N, x1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil","base.strided.dcopy":"\nbase.strided.dcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.scopy\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.scopy","base.strided.dcumax":"\nbase.strided.dcumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumax( N, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcumax( N, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumax\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumax","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumaxabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcumaxabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs","base.strided.dcumin":"\nbase.strided.dcumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumin( N, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcumin( N, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumin\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumin","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcuminabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcuminabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs","base.strided.dcusum":"\nbase.strided.dcusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements.\n\n The `N` and `stride` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumkbn( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcusumkbn( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumkbn2( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcusumkbn2( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2","base.strided.dcusumors":"\nbase.strided.dcusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumors( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcusumors( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumpw( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcusumpw( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N, x, strideX, y, strideY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad( x.length, x, 1, y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad( N, x, 2, y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ddeg2rad( N, x1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n strided.deg2rad, base.strided.sdeg2rad\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n strided.deg2rad, base.strided.sdeg2rad","base.strided.ddot":"\nbase.strided.ddot( N, x, strideX, y, strideY )\n Computes the dot product of two double-precision floating-point vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.ddot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot","base.strided.dfill":"\nbase.strided.dfill( N, alpha, x, stride )\n Fills a double-precision floating-point strided array with a specified\n scalar value.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill( 3, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dfill( 3, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.dfill.ndarray( N, alpha, x, stride, offset )\n Fills a double-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill, base.strided.sfill\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N, alpha, x, stride, offset )\n Fills a double-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill, base.strided.sfill","base.strided.dfloor":"\nbase.strided.dfloor( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor( x.length, x, 1, y, 1 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor( N, x, 2, y, -1 )\n [ 3.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dfloor( N, x1, -2, y1, 1 )\n [ 4.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor","base.strided.dinv":"\nbase.strided.dinv( N, x, strideX, y, strideY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv( x.length, x, 1, y, 1 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv( N, x, 2, y, -1 )\n [ 0.5, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dinv( N, x1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n strided.inv, base.strided.sinv\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n strided.inv, base.strided.sinv","base.strided.dmap":"\nbase.strided.dmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap( x.length, x, 1, y, 1, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap( 2, x, 2, y, -1, base.identity )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmap( 2, x1, -2, y1, 1, base.identity )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.smap, base.strided.unary\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.smap, base.strided.unary","base.strided.dmap2":"\nbase.strided.dmap2( N, x, sx, y, sy, z, sz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays and assigns results to a double-precision floating-point strided\n output array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\n [ 3.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\n [ 7.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.smap2, base.strided.binary\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.smap2, base.strided.binary","base.strided.dmax":"\nbase.strided.dmax( N, x, stride )\n Computes the maximum value of a double-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmax( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmax( N, x1, stride )\n 2.0\n\nbase.strided.dmax.ndarray( N, x, stride, offset )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N, x, stride, offset )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N, x, stride )\n Computes the maximum absolute value of a double-precision floating-point\n strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmaxabs( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmaxabs( N, x1, stride )\n 2.0\n\nbase.strided.dmaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs","base.strided.dmaxabssorted":"\nbase.strided.dmaxabssorted( N, x, stride )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmaxabssorted( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmaxabssorted( N, x1, stride )\n 3.0\n\nbase.strided.dmaxabssorted.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmaxabssorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted\n","base.strided.dmaxabssorted.ndarray":"\nbase.strided.dmaxabssorted.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmaxabssorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted","base.strided.dmaxsorted":"\nbase.strided.dmaxsorted( N, x, stride )\n Computes the maximum value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmaxsorted( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmaxsorted( N, x1, stride )\n 3.0\n\nbase.strided.dmaxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmaxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted\n","base.strided.dmaxsorted.ndarray":"\nbase.strided.dmaxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmaxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted","base.strided.dmean":"\nbase.strided.dmean( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.smean\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.smean","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeankbn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeankbn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn, base.strided.smeankbn\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn, base.strided.smeankbn","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeankbn2( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeankbn2( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2","base.strided.dmeanli":"\nbase.strided.dmeanli( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanli( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanli( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanli.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanli.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanli.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanlipw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanlipw( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanlipw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw\n","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw","base.strided.dmeanors":"\nbase.strided.dmeanors( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanpw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanpw( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N, c, x, strideX, out, strideOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and standard deviation equal to\n `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanstdev( N, 1, x, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev( N, 1, x1, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N, c, x, strideX, out, strideOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and standard deviation equal to\n `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanstdevpn( N, 1, x, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( N, 1, x1, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N, c, x, strideX, out, strideOut )\n Computes the mean and variance of a double-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanvar( N, 1, x, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar( N, 1, x1, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dvariance\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dvariance","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N, c, x, strideX, out, strideOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanvarpn( N, 1, x, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( N, 1, x1, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N, x, stride )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmediansorted( N, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dmediansorted( N, x1, 2 )\n 2.0\n\nbase.strided.dmediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted","base.strided.dmidrange":"\nbase.strided.dmidrange( N, x, stride )\n Computes the mid-range of a double-precision floating-point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmidrange( N, x, stride )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmidrange( N, x1, stride )\n 0.0\n\nbase.strided.dmidrange.ndarray( N, x, stride, offset )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmidrange.ndarray( N, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N, x, stride, offset )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmidrange.ndarray( N, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange","base.strided.dmin":"\nbase.strided.dmin( N, x, stride )\n Computes the minimum value of a double-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmin( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmin( N, x1, stride )\n -2.0\n\nbase.strided.dmin.ndarray( N, x, stride, offset )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N, x, stride, offset )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin","base.strided.dminabs":"\nbase.strided.dminabs( N, x, stride )\n Computes the minimum absolute value of a double-precision floating-point\n strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dminabs( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dminabs( N, x1, stride )\n 1.0\n\nbase.strided.dminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs","base.strided.dminsorted":"\nbase.strided.dminsorted( N, x, stride )\n Computes the minimum value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dminsorted( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dminsorted( N, x1, stride )\n -2.0\n\nbase.strided.dminsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dminsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dminsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted","base.strided.dmskabs":"\nbase.strided.dmskabs( N, x, sx, m, sm, y, sy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\n [ 5.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N, x, sx, m, sm, y, sy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N, x, sx, m, sm, y, sy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt","base.strided.dmskceil":"\nbase.strided.dmskceil( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N, x, sx, m, sm, y, sy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.dmskdeg2rad, base.strided.smskdeg2rad\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.dmskdeg2rad, base.strided.smskdeg2rad","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor","base.strided.dmskinv":"\nbase.strided.dmskinv( N, x, sx, m, sm, y, sy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\n [ 0.0, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.smskinv\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.smskinv","base.strided.dmskmap":"\nbase.strided.dmskmap( N, x, sx, m, sm, y, sy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n [ 0.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\n [ 0.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\n [ 0.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2","base.strided.dmskmax":"\nbase.strided.dmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dmskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax","base.strided.dmskmin":"\nbase.strided.dmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dmskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin","base.strided.dmskramp":"\nbase.strided.dmskramp( N, x, sx, m, sm, y, sy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.smskramp\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.smskramp","base.strided.dmskrange":"\nbase.strided.dmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dmskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N, x, sx, m, sm, y, sy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N, x, sx, m, sm, y, sy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc","base.strided.dnanasum":"\nbase.strided.dnanasum( N, x, stride )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum( x.length, x, 1 )\n 5.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanasum( N, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanasum( N, x1, stride )\n 5.0\n\nbase.strided.dnanasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanasum.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dasumpw\n","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanasum.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dasumpw","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N, x, stride )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors( x.length, x, 1 )\n 5.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanasumors( N, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanasumors( N, x1, stride )\n 5.0\n\nbase.strided.dnanasumors.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanasumors.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dnanasum\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanasumors.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dnanasum","base.strided.dnanmax":"\nbase.strided.dnanmax( N, x, stride )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmax( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmax( N, x1, stride )\n 2.0\n\nbase.strided.dnanmax.ndarray( N, x, stride, offset )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N, x, stride, offset )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N, x, stride )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmaxabs( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmaxabs( N, x1, stride )\n 2.0\n\nbase.strided.dnanmaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs","base.strided.dnanmean":"\nbase.strided.dnanmean( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.snanmean\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.snanmean","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmeanpw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmeanpw( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dnanmean\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dnanmean","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, using Welford's algorithm and ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd","base.strided.dnanmin":"\nbase.strided.dnanmin( N, x, stride )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmin( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmin( N, x1, stride )\n -2.0\n\nbase.strided.dnanmin.ndarray( N, x, stride, offset )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N, x, stride, offset )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N, x, stride )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanminabs( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanminabs( N, x1, stride )\n 1.0\n\nbase.strided.dnanminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dnanmskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dnanmskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dnanmskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange","base.strided.dnannsum":"\nbase.strided.dnannsum( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` .`stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnannsum( N, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnansum, base.strided.dsum\n","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnansum, base.strided.dsum","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnannsumkbn( N, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnannsumkbn2( N, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnannsumors( N, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnannsumpw( N, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw","base.strided.dnanrange":"\nbase.strided.dnanrange( N, x, stride )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanrange( N, x, stride )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanrange( N, x1, stride )\n 4.0\n\nbase.strided.dnanrange.ndarray( N, x, stride, offset )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanrange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N, x, stride, offset )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanrange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc","base.strided.dnansum":"\nbase.strided.dnansum( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansum.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnansumkbn( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnansumkbn( N, x1, stride )\n -1.0\n\nbase.strided.dnansumkbn.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnansumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnansumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnansumkbn2( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnansumkbn2( N, x1, stride )\n -1.0\n\nbase.strided.dnansumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnansumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnansumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2","base.strided.dnansumors":"\nbase.strided.dnansumors( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnansumors( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnansumors( N, x1, stride )\n -1.0\n\nbase.strided.dnansumors.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnansumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnansumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnansumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnansumpw( N, x1, stride )\n -1.0\n\nbase.strided.dnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvariancech( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvariancech( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvariancetk( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvariancetk( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvariancewd( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvariancewd( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvarianceyc( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvarianceyc( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc","base.strided.dnrm2":"\nbase.strided.dnrm2( N, x, stride )\n Computes the L2-norm of a double-precision floating-point vector.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` or `stride <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dnrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.gnrm2, base.strided.snrm2\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.gnrm2, base.strided.snrm2","base.strided.dramp":"\nbase.strided.dramp( N, x, strideX, y, strideY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp( x.length, x, 1, y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp( N, x, 2, y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dramp( N, x1, -2, y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n strided.ramp, base.strided.sramp\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n strided.ramp, base.strided.sramp","base.strided.drange":"\nbase.strided.drange( N, x, stride )\n Computes the range of a double-precision floating-point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange( x.length, x, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.drange( N, x, stride )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.drange( N, x1, stride )\n 4.0\n\nbase.strided.drange.ndarray( N, x, stride, offset )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N, x, stride, offset )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange","base.strided.drev":"\nbase.strided.drev( N, x, stride )\n Reverses a double-precision floating-point strided array in-place.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.drev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.drev.ndarray( N, x, stride, offset )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.drev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.grev, base.strided.srev\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N, x, stride, offset )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.drev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.grev, base.strided.srev","base.strided.drsqrt":"\nbase.strided.drsqrt( N, x, strideX, y, strideY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt( x.length, x, 1, y, 1 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt( N, x, 2, y, -1 )\n [ ~0.333, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.drsqrt( N, x1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsapxsum( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsapxsum( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.dsapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsapxsumpw( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsapxsumpw( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw","base.strided.dscal":"\nbase.strided.dscal( N, alpha, x, stride )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `stride <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal( x.length, 5.0, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy","base.strided.dsdot":"\nbase.strided.dsdot( N, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation and result.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > dot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, base.strided.sdsdot\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, base.strided.sdsdot","base.strided.dsem":"\nbase.strided.dsem( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsem( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsem( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsem.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsem.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dstdev\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsem.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dstdev","base.strided.dsemch":"\nbase.strided.dsemch( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsemch( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsemch( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsemch.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevch\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevch","base.strided.dsempn":"\nbase.strided.dsempn( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsempn( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsempn( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsempn.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevpn\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevpn","base.strided.dsemtk":"\nbase.strided.dsemtk( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsemtk( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsemtk( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsemtk.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevtk\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevtk","base.strided.dsemwd":"\nbase.strided.dsemwd( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsemwd( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsemwd( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsemwd.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevwd\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevwd","base.strided.dsemyc":"\nbase.strided.dsemyc( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsemyc( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsemyc( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsemyc.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevyc\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevyc","base.strided.dsmean":"\nbase.strided.dsmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and returning an extended precision\n result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsmeanpw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsmeanpw( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using ordinary recursive summation with\n extended accumulation, and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using a two-pass error correction algorithm\n with extended accumulation, and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnanmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnanmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsnanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using Welford's algorithm with extended\n accumulation, and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnanmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnanmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsnanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N, x, strideX, out, strideOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnannsumors( N, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors","base.strided.dsnansum":"\nbase.strided.dsnansum( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnansum( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnansum( N, x1, stride )\n -1.0\n\nbase.strided.dsnansum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnansum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnansum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnansumors( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnansumors( N, x1, stride )\n -1.0\n\nbase.strided.dsnansumors.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnansumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnansumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation,\n and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnansumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnansumpw( N, x1, stride )\n -1.0\n\nbase.strided.dsnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2ins( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsort2ins( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh","base.strided.dsorthp":"\nbase.strided.dsorthp( N, order, x, stride )\n Sorts a double-precision floating-point strided array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsorthp( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsorthp( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsorthp.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp","base.strided.dsortins":"\nbase.strided.dsortins( N, order, x, stride )\n Sorts a double-precision floating-point strided array using insertion sort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortins( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsortins( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsortins.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins","base.strided.dsortsh":"\nbase.strided.dsortsh( N, order, x, stride )\n Sorts a double-precision floating-point strided array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsortsh( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh","base.strided.dsqrt":"\nbase.strided.dsqrt( N, x, strideX, y, strideY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt( x.length, x, 1, y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt( N, x, 2, y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsqrt( N, x1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt","base.strided.dssum":"\nbase.strided.dssum( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dssum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dssum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dssum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssum.ndarray(3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssum.ndarray(3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean","base.strided.dssumors":"\nbase.strided.dssumors( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and returning\n an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dssumors( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dssumors( N, x1, stride )\n -1.0\n\nbase.strided.dssumors.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dssumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dssumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors","base.strided.dssumpw":"\nbase.strided.dssumpw( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dssumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dssumpw( N, x1, stride )\n -1.0\n\nbase.strided.dssumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dssumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dssumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw","base.strided.dstdev":"\nbase.strided.dstdev( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev","base.strided.dstdevch":"\nbase.strided.dstdevch( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc","base.strided.dsum":"\nbase.strided.dsum( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsum( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsum( N, x1, stride )\n -1.0\n\nbase.strided.dsum.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsumkbn( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsumkbn( N, x1, stride )\n -1.0\n\nbase.strided.dsumkbn.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsumkbn2( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsumkbn2( N, x1, stride )\n -1.0\n\nbase.strided.dsumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2","base.strided.dsumors":"\nbase.strided.dsumors( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsumors( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsumors( N, x1, stride )\n -1.0\n\nbase.strided.dsumors.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors","base.strided.dsumpw":"\nbase.strided.dsumpw( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsumpw( N, x1, stride )\n -1.0\n\nbase.strided.dsumpw.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw","base.strided.dsvariance":"\nbase.strided.dsvariance( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsvariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsvariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dsvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.variance, base.strided.svariance\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.variance, base.strided.svariance","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsvariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsvariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dsvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn","base.strided.dswap":"\nbase.strided.dswap( N, x, strideX, y, strideY )\n Interchanges two double-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped\n with values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap","base.strided.dtrunc":"\nbase.strided.dtrunc( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc( N, x, 2, y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dtrunc( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc","base.strided.dvariance":"\nbase.strided.dvariance( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance","base.strided.dvariancech":"\nbase.strided.dvariancech( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariancech( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariancech( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariancetk( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariancetk( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariancewd( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariancewd( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvarianceyc( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvarianceyc( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc","base.strided.dvarm":"\nbase.strided.dvarm( N, mean, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm( x.length, 1.0/3.0, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarm( N, 1.0/3.0, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dvarm( N, 1.0/3.0, 1, x1, 2 )\n ~4.3333\n\nbase.strided.dvarm.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N, mean, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn( x.length, 1.0/3.0, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmpn( N, 1.0/3.0, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dvarmpn( N, 1.0/3.0, 1, x1, 2 )\n ~4.3333\n\nbase.strided.dvarmpn.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N, mean, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk( x.length, 1.0/3.0, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmtk( N, 1.0/3.0, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dvarmtk( N, 1.0/3.0, 1, x1, 2 )\n ~4.3333\n\nbase.strided.dvarmtk.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm","base.strided.gapx":"\nbase.strided.gapx( N, alpha, x, stride )\n Adds a constant to each element in a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var alpha = 5.0;\n > base.strided.gapx( x.length, alpha, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.gapx( N, alpha, x, stride )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > alpha = 5.0;\n > stride = 2;\n > base.strided.gapx( N, alpha, x1, stride )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\nbase.strided.gapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var alpha = 5.0;\n > base.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.sapx\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var alpha = 5.0;\n > base.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.sapx","base.strided.gapxsum":"\nbase.strided.gapxsum( N, alpha, x, stride )\n Adds a constant to each strided array element and computes the sum.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gapxsum( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gapxsum( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.gapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N, alpha, x, stride )\n Adds a constant to each strided array element and computes the sum using an\n improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gapxsumkbn( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gapxsumkbn( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using an\n improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using an\n improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N, alpha, x, stride )\n Adds a constant to each strided array element and computes the sum using a\n second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gapxsumkbn2( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gapxsumkbn2( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using a\n second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using a\n second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N, alpha, x, stride )\n Adds a constant to each strided array element and computes the sum using\n ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gapxsumors( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gapxsumors( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.gapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N, alpha, x, stride )\n Adds a constant to each strided array element and computes the sum using\n pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gapxsumpw( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gapxsumpw( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.gapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw","base.strided.gasum":"\nbase.strided.gasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > s = base.strided.gasum( 3, x, 2 )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.gasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.sasum\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.sasum","base.strided.gasumpw":"\nbase.strided.gasumpw( N, x, stride )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gasumpw( N, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gasumpw( N, x1, stride )\n 5.0\n\nbase.strided.gasumpw.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.gasumpw.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.gasumpw.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw","base.strided.gaxpy":"\nbase.strided.gaxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.saxpy\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.saxpy","base.strided.gcopy":"\nbase.strided.gcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.scopy\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.scopy","base.strided.gcusum":"\nbase.strided.gcusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusum( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gcusum( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gcusumkbn( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn2( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gcusumkbn2( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2","base.strided.gcusumors":"\nbase.strided.gcusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumors( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gcusumors( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using pairwise\n summation.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumpw( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gcusumpw( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw","base.strided.gdot":"\nbase.strided.gdot( N, x, strideX, y, strideY )\n Computes the dot product of two vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.gdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, gdot\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, gdot","base.strided.gfill":"\nbase.strided.gfill( N, alpha, x, stride )\n Fills a strided array with a specified scalar value.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Constant.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfill( N, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gfill( N, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfill.ndarray( N, alpha, x, stride, offset )\n Fills a strided array with a specified scalar value using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Constant.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.sfill\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N, alpha, x, stride, offset )\n Fills a strided array with a specified scalar value using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Constant.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.sfill","base.strided.gfillBy":"\nbase.strided.gfillBy( N, x, stride, clbk[, thisArg] )\n Fills a strided array according to a provided callback function.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element\n - aidx: array index\n - sidx: strided index (offset + aidx*stride)\n - array: the input array\n\n The callback return value is used as the fill value for the current array\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy( x.length, x, 1, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfillBy( N, x, 2, fill )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gfillBy( N, x1, 2, fill )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfillBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N, x, strideX, out, strideOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnannsumkbn( N, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumkbn\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumkbn","base.strided.gnansum":"\nbase.strided.gnansum( N, x, stride )\n Computes the sum of strided array elements, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gnansum( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gnansum( N, x1, stride )\n -1.0\n\nbase.strided.gnansum.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N, x, stride )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gnansumkbn( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gnansumkbn( N, x1, stride )\n -1.0\n\nbase.strided.gnansumkbn.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N, x, stride )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gnansumkbn2( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gnansumkbn2( N, x1, stride )\n -1.0\n\nbase.strided.gnansumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2","base.strided.gnansumors":"\nbase.strided.gnansumors( N, x, stride )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gnansumors( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gnansumors( N, x1, stride )\n -1.0\n\nbase.strided.gnansumors.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N, x, stride )\n Computes the sum of strided array elements, ignoring `NaN` values and\n pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gnansumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gnansumpw( N, x1, stride )\n -1.0\n\nbase.strided.gnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw","base.strided.gnrm2":"\nbase.strided.gnrm2( N, x, stride )\n Computes the L2-norm of a vector.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` or `stride <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gnrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a vector using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.snrm2\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a vector using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.snrm2","base.strided.grev":"\nbase.strided.grev( N, x, stride )\n Reverses a strided array in-place.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.grev( N, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.grev( N, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.grev.ndarray( N, x, stride, offset )\n Reverses a strided array in-place using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.grev.ndarray( N, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.srev\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N, x, stride, offset )\n Reverses a strided array in-place using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.grev.ndarray( N, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.srev","base.strided.gscal":"\nbase.strided.gscal( N, alpha, x, stride )\n Multiplies a vector `x` by a constant `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `stride <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var alpha = 5.0;\n > base.strided.gscal( x.length, alpha, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.gscal.ndarray( N, alpha, x, stride, offset )\n Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.dscal, base.strided.gaxpy, base.strided.sscal\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N, alpha, x, stride, offset )\n Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.dscal, base.strided.gaxpy, base.strided.sscal","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2hp( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsort2hp( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2ins( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsort2ins( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2sh( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsort2sh( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.gsorthp":"\nbase.strided.gsorthp( N, order, x, stride )\n Sorts a strided array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsorthp( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsorthp( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsorthp.ndarray( N, order, x, stride, offset )\n Sorts a strided array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N, order, x, stride, offset )\n Sorts a strided array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.gsortins":"\nbase.strided.gsortins( N, order, x, stride )\n Sorts a strided array using insertion sort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortins( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsortins( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsortins.ndarray( N, order, x, stride, offset )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N, order, x, stride, offset )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins","base.strided.gsortsh":"\nbase.strided.gsortsh( N, order, x, stride )\n Sorts a strided array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortsh( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsortsh( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsortsh.ndarray( N, order, x, stride, offset )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N, order, x, stride, offset )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.gsum":"\nbase.strided.gsum( N, x, stride )\n Computes the sum of strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gsum( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gsum( N, x1, stride )\n -1.0\n\nbase.strided.gsum.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N, x, stride )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gsumkbn( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gsumkbn( N, x1, stride )\n -1.0\n\nbase.strided.gsumkbn.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N, x, stride )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gsumkbn2( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gsumkbn2( N, x1, stride )\n -1.0\n\nbase.strided.gsumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2","base.strided.gsumors":"\nbase.strided.gsumors( N, x, stride )\n Computes the sum of strided array elements using ordinary recursive\n summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gsumors( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gsumors( N, x1, stride )\n -1.0\n\nbase.strided.gsumors.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors","base.strided.gsumpw":"\nbase.strided.gsumpw( N, x, stride )\n Computes the sum of strided array elements using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gsumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gsumpw( N, x1, stride )\n -1.0\n\nbase.strided.gsumpw.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw","base.strided.gswap":"\nbase.strided.gswap( N, x, strideX, y, strideY )\n Interchanges vectors `x` and `y`.\n\n The `N` and stride parameters determine how values from `x` are swapped with\n values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap","base.strided.mapBy":"\nbase.strided.mapBy( N, x, sx, y, sy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element\n - idx: iteration index\n - indices: strided indices (offset + idx*stride)\n - arrays: input and output arrays\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy2, base.strided.unary\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy2, base.strided.unary","base.strided.mapBy2":"\nbase.strided.mapBy2( N, x, sx, y, sy, z, sz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements\n - idx: iteration index\n - indices: strided array indices (offset + idx*stride)\n - arrays: input and output arrays\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\n [ 8.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\n [ -4.0, 0.0 ]\n > z0\n [ 0.0, 0.0, -4.0, 0.0 ]\n\n\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 1.0, 1.0, 2.0, 2.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n [ 0.0, -4.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.binary\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 1.0, 1.0, 2.0, 2.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n [ 0.0, -4.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.binary","base.strided.max":"\nbase.strided.max( N, x, stride )\n Computes the maximum value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.max( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.max( N, x1, stride )\n 2.0\n\nbase.strided.max.ndarray( N, x, stride, offset )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.max.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N, x, stride, offset )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.max.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax","base.strided.maxabs":"\nbase.strided.maxabs( N, x, stride )\n Computes the maximum absolute value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.maxabs( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.maxabs( N, x1, stride )\n 2.0\n\nbase.strided.maxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs","base.strided.maxBy":"\nbase.strided.maxBy( N, x, stride, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element\n - aidx: array index\n - sidx: strided index (offset + aidx*stride)\n - array: the input array\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy( x.length, x, 1, accessor )\n 8.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxBy( N, x, 2, accessor )\n 8.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.maxBy( N, x1, 2, accessor )\n -4.0\n\nbase.strided.maxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax","base.strided.maxsorted":"\nbase.strided.maxsorted( N, x, stride )\n Computes the maximum value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.maxsorted( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.maxsorted( N, x1, stride )\n 3.0\n\nbase.strided.maxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted","base.strided.mean":"\nbase.strided.mean( N, x, stride )\n Computes the arithmetic mean of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.mean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.mean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.mean( N, x1, stride )\n ~-0.3333\n\nbase.strided.mean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.mean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.smean\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.mean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.smean","base.strided.meankbn":"\nbase.strided.meankbn( N, x, stride )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meankbn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meankbn( N, x1, stride )\n ~-0.3333\n\nbase.strided.meankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn","base.strided.meankbn2":"\nbase.strided.meankbn2( N, x, stride )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meankbn2( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meankbn2( N, x1, stride )\n ~-0.3333\n\nbase.strided.meankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2","base.strided.meanors":"\nbase.strided.meanors( N, x, stride )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.meanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors","base.strided.meanpn":"\nbase.strided.meanpn( N, x, stride )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.meanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn","base.strided.meanpw":"\nbase.strided.meanpw( N, x, stride )\n Computes the arithmetic mean of a strided array using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meanpw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meanpw( N, x1, stride )\n ~-0.3333\n\nbase.strided.meanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw","base.strided.meanwd":"\nbase.strided.meanwd( N, x, stride )\n Computes the arithmetic mean of a strided array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.meanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd","base.strided.mediansorted":"\nbase.strided.mediansorted( N, x, stride )\n Computes the median value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mediansorted( N, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.mediansorted( N, x1, 2 )\n 2.0\n\nbase.strided.mediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted","base.strided.min":"\nbase.strided.min( N, x, stride )\n Computes the minimum value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min( x.length, x, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.min( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.min( N, x1, stride )\n -2.0\n\nbase.strided.min.ndarray( N, x, stride, offset )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.min.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N, x, stride, offset )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.min.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin","base.strided.minabs":"\nbase.strided.minabs( N, x, stride )\n Computes the minimum absolute value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.minabs( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.minabs( N, x1, stride )\n 1.0\n\nbase.strided.minabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs","base.strided.minBy":"\nbase.strided.minBy( N, x, stride, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element\n - aidx: array index\n - sidx: strided index (offset + aidx*stride)\n - array: the input array\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy( x.length, x, 1, accessor )\n -10.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minBy( N, x, 2, accessor )\n -4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.minBy( N, x1, 2, accessor )\n -12.0\n\nbase.strided.minBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minBy.ndarray( N, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minBy.ndarray( N, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin","base.strided.minsorted":"\nbase.strided.minsorted( N, x, stride )\n Computes the minimum value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.minsorted( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.minsorted( N, x1, stride )\n -2.0\n\nbase.strided.minsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted","base.strided.mskmax":"\nbase.strided.mskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a strided array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.mskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax","base.strided.mskmin":"\nbase.strided.mskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a strided array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, -4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.mskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin","base.strided.mskrange":"\nbase.strided.mskrange( N, x, strideX, mask, strideMask )\n Computes the range of a strided array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.mskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange","base.strided.mskunary":"\nbase.strided.mskunary( arrays, shape, strides, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array and assigns results to elements in a\n strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > base.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.smskmap, base.strided.unary\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.smskmap, base.strided.unary","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1, dtypes2[, options] )\n Generates a list of masked unary interface signatures from strided array\n data types.\n\n The function returns a strided array having a stride length of three (i.e.,\n every three elements define a masked unary interface signature).\n\n For each signature (i.e., set of three consecutive non-overlapping strided\n array elements), the first element is the input data type, the second\n element is the mask data type, and the last element is the return data type.\n\n All signatures follow type promotion rules.\n\n The mask array data type is always `uint8`.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the output argument.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing masked unary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.mskunaryDtypeSignatures( dt, dt )\n [...]\n\n See Also\n --------\n base.strided.mskunarySignatureCallbacks\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table, signatures )\n Assigns callbacks to masked unary interfaces according to type promotion\n rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing masked unary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\n > var t = {\n ... 'default': base.identity,\n ... 'complex64': base.cidentityf,\n ... 'complex128': base.cidentity\n ... };\n > var out = base.strided.mskunarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.mskunaryDtypeSignatures\n","base.strided.nanmax":"\nbase.strided.nanmax( N, x, stride )\n Computes the maximum value of a strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmax( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmax( N, x1, stride )\n 2.0\n\nbase.strided.nanmax.ndarray( N, x, stride, offset )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N, x, stride, offset )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N, x, stride )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmaxabs( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmaxabs( N, x1, stride )\n 2.0\n\nbase.strided.nanmaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N, x, stride, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function,\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element\n - aidx: array index\n - sidx: strided index (offset + aidx*stride)\n - array: the input array\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy( x.length, x, 1, accessor )\n 8.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmaxBy( N, x, 2, accessor )\n 8.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanmaxBy( N, x1, 2, accessor )\n -4.0\n\nbase.strided.nanmaxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax","base.strided.nanmean":"\nbase.strided.nanmean( N, x, stride )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.nanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.snanmean\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.snanmean","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N, x, stride )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.nanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N, x, stride )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.nanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N, x, stride )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.nanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd","base.strided.nanmin":"\nbase.strided.nanmin( N, x, stride )\n Computes the minimum value of a strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmin( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmin( N, x1, stride )\n -2.0\n\nbase.strided.nanmin.ndarray( N, x, stride, offset )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N, x, stride, offset )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin","base.strided.nanminabs":"\nbase.strided.nanminabs( N, x, stride )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanminabs( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanminabs( N, x1, stride )\n 1.0\n\nbase.strided.nanminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs","base.strided.nanminBy":"\nbase.strided.nanminBy( N, x, stride, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function,\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element\n - aidx: array index\n - sidx: strided index (offset + aidx*stride)\n - array: the input array\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy( x.length, x, 1, accessor )\n -10.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanminBy( N, x, 2, accessor )\n -4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanminBy( N, x1, 2, accessor )\n -12.0\n\nbase.strided.nanminBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a strided array according to a mask and\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanmskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a strided array according to a mask and\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanmskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a strided array according to a mask and ignoring `NaN`\n values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanmskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange","base.strided.nanrange":"\nbase.strided.nanrange( N, x, stride )\n Computes the range of a strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanrange( N, x, stride )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanrange( N, x1, stride )\n 4.0\n\nbase.strided.nanrange.ndarray( N, x, stride, offset )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanrange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N, x, stride, offset )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanrange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N, x, stride, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element\n - aidx: array index\n - sidx: strided index (offset + aidx*stride)\n - array: the input array\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy( x.length, x, 1, accessor )\n 18.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanrangeBy( N, x, 2, accessor )\n 14.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanrangeBy( N, x1, 2, accessor )\n 8.0\n\nbase.strided.nanrangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange","base.strided.nanstdev":"\nbase.strided.nanstdev( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdev( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdev( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevch( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdevch( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevpn( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdevpn( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevtk( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdevtk( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevwd( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdevwd( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevyc( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdevyc( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc","base.strided.nanvariance":"\nbase.strided.nanvariance( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvariancech( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvariancech( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvariancetk( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvariancetk( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvariancewd( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvariancewd( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvarianceyc( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvarianceyc( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc","base.strided.nullary":"\nbase.strided.nullary( arrays, shape, strides, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n output array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary( [ x ], shape, strides, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting index (i.e., index offset) for\n the strided output array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1 ];\n > var offsets = [ 0 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting index (i.e., index offset) for\n the strided output array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1 ];\n > var offsets = [ 0 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.quaternary":"\nbase.strided.quaternary( arrays, shape, strides, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.quinary":"\nbase.strided.quinary( arrays, shape, strides, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary","base.strided.range":"\nbase.strided.range( N, x, stride )\n Computes the range of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range( x.length, x, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.range( N, x, stride )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.range( N, x1, stride )\n 4.0\n\nbase.strided.range.ndarray( N, x, stride, offset )\n Computes the range of a strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.range.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange\n","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N, x, stride, offset )\n Computes the range of a strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.range.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange","base.strided.rangeBy":"\nbase.strided.rangeBy( N, x, stride, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element\n - aidx: array index\n - sidx: strided index (offset + aidx*stride)\n - array: the input array\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy( x.length, x, 1, accessor )\n 18.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.rangeBy( N, x, 2, accessor )\n 12.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.rangeBy( N, x1, 2, accessor )\n 8.0\n\nbase.strided.rangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange","base.strided.sabs":"\nbase.strided.sabs( N, x, strideX, y, strideY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs( N, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sabs( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs, base.strided.sabs2\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs, base.strided.sabs2","base.strided.sabs2":"\nbase.strided.sabs2( N, x, strideX, y, strideY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2( x.length, x, 1, y, 1 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2( N, x, 2, y, -1 )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sabs2( N, x1, -2, y1, 1 )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs2, base.strided.sabs\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs2, base.strided.sabs","base.strided.sapx":"\nbase.strided.sapx( N, alpha, x, stride )\n Adds a constant to each element in a single-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > var alpha = 5.0;\n > base.strided.sapx( x.length, alpha, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.sapx( N, alpha, x, stride )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > alpha = 5.0;\n > stride = 2;\n > base.strided.sapx( N, alpha, x1, stride )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\nbase.strided.sapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > var alpha = 5.0;\n > base.strided.sapx.ndarray( x.length, alpha, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.sapx.ndarray( N, alpha, x, stride, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > var alpha = 5.0;\n > base.strided.sapx.ndarray( x.length, alpha, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.sapx.ndarray( N, alpha, x, stride, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx","base.strided.sapxsum":"\nbase.strided.sapxsum( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sapxsum( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sapxsum( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.sapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sapxsumkbn( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sapxsumkbn( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sapxsumkbn2( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sapxsumkbn2( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sapxsumors( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sapxsumors( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.sapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sapxsumpw( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sapxsumpw( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.sapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw","base.strided.sasum":"\nbase.strided.sasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and stride parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum( x.length, x, 1 )\n 15.0\n\n // Sum every other value:\n > s = base.strided.sasum( 3, x, 2 )\n 9.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.sasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.gasum\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.gasum","base.strided.sasumpw":"\nbase.strided.sasumpw( N, x, stride )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sasumpw( N, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sasumpw( N, x1, stride )\n 5.0\n\nbase.strided.sasumpw.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sasumpw.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sasumpw.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw","base.strided.saxpy":"\nbase.strided.saxpy( N, alpha, x, strideX, y, strideY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.strided.saxpy( 3, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gaxpy\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gaxpy","base.strided.scbrt":"\nbase.strided.scbrt( N, x, strideX, y, strideY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt( x.length, x, 1, y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt( N, x, 2, y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scbrt( N, x1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, strided.cbrt, base.strided.ssqrt\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, strided.cbrt, base.strided.ssqrt","base.strided.sceil":"\nbase.strided.sceil( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil( x.length, x, 1, y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil( N, x, 2, y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sceil( N, x1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc","base.strided.scopy":"\nbase.strided.scopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gcopy, base.strided.sswap\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gcopy, base.strided.sswap","base.strided.scumax":"\nbase.strided.scumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumax( N, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scumax( N, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumax, base.strided.scumin\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumax, base.strided.scumin","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumaxabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scumaxabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs","base.strided.scumin":"\nbase.strided.scumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumin( N, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scumin( N, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumin, base.strided.scumax\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumin, base.strided.scumax","base.strided.scuminabs":"\nbase.strided.scuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scuminabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scuminabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin","base.strided.scusum":"\nbase.strided.scusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusum( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scusum( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumkbn( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scusumkbn( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumkbn2( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scusumkbn2( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn","base.strided.scusumors":"\nbase.strided.scusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumors( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scusumors( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum","base.strided.scusumpw":"\nbase.strided.scusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumpw( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scusumpw( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N, x, strideX, y, strideY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad( x.length, x, 1, y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad( N, x, 2, y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sdeg2rad( N, x1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, strided.deg2rad\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, strided.deg2rad","base.strided.sdot":"\nbase.strided.sdot( N, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.sdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsapxsum( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsapxsum( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.sdsapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsapxsumpw( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsapxsumpw( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw\n","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsdot":"\nbase.strided.sdsdot( N, scalar, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns the provided scalar constant.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdot\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdot","base.strided.sdsmean":"\nbase.strided.sdsmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmean, base.strided.sdsnanmeanors\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmean, base.strided.sdsnanmeanors","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsnanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsnanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsnanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsnanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmeanors, base.strided.sdsnanmean\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmeanors, base.strided.sdsnanmean","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsnansum( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsnansum( N, x1, stride )\n -1.0\n\nbase.strided.sdsnansum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnansum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnansum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsnansumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsnansumpw( N, x1, stride )\n -1.0\n\nbase.strided.sdsnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw","base.strided.sdssum":"\nbase.strided.sdssum( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdssum( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdssum( N, x1, stride )\n -1.0\n\nbase.strided.sdssum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdssum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdssum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdssumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdssumpw( N, x1, stride )\n -1.0\n\nbase.strided.sdssumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdssumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdssumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw","base.strided.sfill":"\nbase.strided.sfill( N, alpha, x, stride )\n Fills a single-precision floating-point strided array with a specified\n scalar value.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfill( N, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sfill( N, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\nbase.strided.sfill.ndarray( N, alpha, x, stride, offset )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfill.ndarray( N, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.gfill\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N, alpha, x, stride, offset )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfill.ndarray( N, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.gfill","base.strided.sfloor":"\nbase.strided.sfloor( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor( x.length, x, 1, y, 1 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor( N, x, 2, y, -1 )\n [ 3.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sfloor( N, x1, -2, y1, 1 )\n [ 4.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc","base.strided.sinv":"\nbase.strided.sinv( N, x, strideX, y, strideY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv( x.length, x, 1, y, 1 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv( N, x, 2, y, -1 )\n [ 0.5, ~-0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sinv( N, x1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, strided.inv\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, strided.inv","base.strided.smap":"\nbase.strided.smap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap( x.length, x, 1, y, 1, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap( 2, x, 2, y, -1, base.identityf )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smap( 2, x1, -2, y1, 1, base.identityf )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.unary\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.unary","base.strided.smap2":"\nbase.strided.smap2( N, x, sx, y, sy, z, sz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\n [ 3.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\n [ 7.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.binary\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.binary","base.strided.smax":"\nbase.strided.smax( N, x, stride )\n Computes the maximum value of a single-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smax( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smax( N, x1, stride )\n 2.0\n\nbase.strided.smax.ndarray( N, x, stride, offset )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N, x, stride, offset )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax","base.strided.smaxabs":"\nbase.strided.smaxabs( N, x, stride )\n Computes the maximum absolute value of a single-precision floating-point\n strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smaxabs( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smaxabs( N, x1, stride )\n 2.0\n\nbase.strided.smaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N, x, stride )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smaxabssorted( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smaxabssorted( N, x1, stride )\n 3.0\n\nbase.strided.smaxabssorted.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smaxabssorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smaxabssorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N, x, stride )\n Computes the maximum value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smaxsorted( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smaxsorted( N, x1, stride )\n 3.0\n\nbase.strided.smaxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smaxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smaxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted","base.strided.smean":"\nbase.strided.smean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smean( N, x1, stride )\n ~-0.3333\n\nbase.strided.smean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean","base.strided.smeankbn":"\nbase.strided.smeankbn( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeankbn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeankbn( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.meankbn, base.strided.smean\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.meankbn, base.strided.smean","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeankbn2( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeankbn2( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean","base.strided.smeanli":"\nbase.strided.smeanli( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanli( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanli( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanli.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanli.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanli.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanlipw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanlipw( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanlipw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanlipw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanlipw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli","base.strided.smeanors":"\nbase.strided.smeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors","base.strided.smeanpn":"\nbase.strided.smeanpn( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn","base.strided.smeanpw":"\nbase.strided.smeanpw( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanpw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanpw( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.meanpw, base.strided.smean\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.meanpw, base.strided.smean","base.strided.smeanwd":"\nbase.strided.smeanwd( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd","base.strided.smediansorted":"\nbase.strided.smediansorted( N, x, stride )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smediansorted( N, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.smediansorted( N, x1, 2 )\n 2.0\n\nbase.strided.smediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean","base.strided.smidrange":"\nbase.strided.smidrange( N, x, stride )\n Computes the mid-range of a single-precision floating-point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smidrange( N, x, stride )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smidrange( N, x1, stride )\n 0.0\n\nbase.strided.smidrange.ndarray( N, x, stride, offset )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smidrange.ndarray( N, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N, x, stride, offset )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smidrange.ndarray( N, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange","base.strided.smin":"\nbase.strided.smin( N, x, stride )\n Computes the minimum value of a single-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin( x.length, x, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smin( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smin( N, x1, stride )\n -2.0\n\nbase.strided.smin.ndarray( N, x, stride, offset )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N, x, stride, offset )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin","base.strided.sminabs":"\nbase.strided.sminabs( N, x, stride )\n Computes the minimum absolute value of a single-precision floating-point\n strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sminabs( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sminabs( N, x1, stride )\n 1.0\n\nbase.strided.sminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs","base.strided.sminsorted":"\nbase.strided.sminsorted( N, x, stride )\n Computes the minimum value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sminsorted( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sminsorted( N, x1, stride )\n -2.0\n\nbase.strided.sminsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sminsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sminsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin","base.strided.smskabs":"\nbase.strided.smskabs( N, x, sx, m, sm, y, sy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\n [ 5.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2","base.strided.smskabs2":"\nbase.strided.smskabs2( N, x, sx, m, sm, y, sy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N, x, sx, m, sm, y, sy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt","base.strided.smskceil":"\nbase.strided.smskceil( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N, x, sx, m, sm, y, sy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.dmskdeg2rad, base.strided.sdeg2rad\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.dmskdeg2rad, base.strided.sdeg2rad","base.strided.smskfloor":"\nbase.strided.smskfloor( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc","base.strided.smskinv":"\nbase.strided.smskinv( N, x, sx, m, sm, y, sy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv( 2, x, 2, m, 2, y, -1 )\n [ 0.0, ~-0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.dmskinv\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.dmskinv","base.strided.smskmap":"\nbase.strided.smskmap( N, x, sx, m, sm, y, sy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n [ 0.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2","base.strided.smskmap2":"\nbase.strided.smskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\n [ 0.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\n [ 0.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap","base.strided.smskmax":"\nbase.strided.smskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.smskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax","base.strided.smskmin":"\nbase.strided.smskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.smskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin","base.strided.smskramp":"\nbase.strided.smskramp( N, x, sx, m, sm, y, sy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskramp, base.strided.sramp\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskramp, base.strided.sramp","base.strided.smskrange":"\nbase.strided.smskrange( N, x, strideX, mask, strideMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.smskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N, x, sx, m, sm, y, sy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N, x, sx, m, sm, y, sy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc","base.strided.snanmax":"\nbase.strided.snanmax( N, x, stride )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmax( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmax( N, x1, stride )\n 2.0\n\nbase.strided.snanmax.ndarray( N, x, stride, offset )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N, x, stride, offset )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N, x, stride )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmaxabs( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmaxabs( N, x1, stride )\n 2.0\n\nbase.strided.snanmaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs","base.strided.snanmean":"\nbase.strided.snanmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.snanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.smean, base.strided.nanmean\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.smean, base.strided.nanmean","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.snanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.snanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.snanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean\n","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean","base.strided.snanmin":"\nbase.strided.snanmin( N, x, stride )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmin( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmin( N, x1, stride )\n -2.0\n\nbase.strided.snanmin.ndarray( N, x, stride, offset )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N, x, stride, offset )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax","base.strided.snanminabs":"\nbase.strided.snanminabs( N, x, stride )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanminabs( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanminabs( N, x1, stride )\n 1.0\n\nbase.strided.snanminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanmskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanmskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanmskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin","base.strided.snanrange":"\nbase.strided.snanrange( N, x, stride )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanrange( N, x, stride )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanrange( N, x1, stride )\n 4.0\n\nbase.strided.snanrange.ndarray( N, x, stride, offset )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanrange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N, x, stride, offset )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanrange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange","base.strided.snanstdev":"\nbase.strided.snanstdev( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc","base.strided.snansum":"\nbase.strided.snansum( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snansum( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snansum( N, x1, stride )\n -1.0\n\nbase.strided.snansum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snansum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snansum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snansumkbn( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snansumkbn( N, x1, stride )\n -1.0\n\nbase.strided.snansumkbn.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snansumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snansumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snansumkbn2( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snansumkbn2( N, x1, stride )\n -1.0\n\nbase.strided.snansumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snansumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snansumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2","base.strided.snansumors":"\nbase.strided.snansumors( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snansumors( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snansumors( N, x1, stride )\n -1.0\n\nbase.strided.snansumors.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snansumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snansumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors","base.strided.snansumpw":"\nbase.strided.snansumpw( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snansumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snansumpw( N, x1, stride )\n -1.0\n\nbase.strided.snansumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw","base.strided.snanvariance":"\nbase.strided.snanvariance( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariance( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancech( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancepn( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancetk( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancewd( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvarianceyc( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc","base.strided.snrm2":"\nbase.strided.snrm2( N, x, stride )\n Computes the L2-norm of a single-precision floating-point vector.\n\n The `N` and `stride` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` or `stride <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.snrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.gnrm2\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.gnrm2","base.strided.sramp":"\nbase.strided.sramp( N, x, strideX, y, strideY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp( N, x, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sramp( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dramp, strided.ramp\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dramp, strided.ramp","base.strided.srange":"\nbase.strided.srange( N, x, stride )\n Computes the range of a single-precision floating-point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange( x.length, x, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.srange( N, x, stride )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.srange( N, x1, stride )\n 4.0\n\nbase.strided.srange.ndarray( N, x, stride, offset )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.srange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N, x, stride, offset )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.srange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range","base.strided.srev":"\nbase.strided.srev( N, x, stride )\n Reverses a single-precision floating-point strided array in-place.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.srev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.srev.ndarray( N, x, stride, offset )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.srev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.grev\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N, x, stride, offset )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.srev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.grev","base.strided.srsqrt":"\nbase.strided.srsqrt( N, x, strideX, y, strideY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt( x.length, x, 1, y, 1 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt( N, x, 2, y, -1 )\n [ ~0.333, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.srsqrt( N, x1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt","base.strided.sscal":"\nbase.strided.sscal( N, alpha, x, stride )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `stride <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal( x.length, 5.0, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssort2hp( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ssort2hp( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssort2ins( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ssort2ins( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssort2sh( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ssort2sh( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.ssorthp":"\nbase.strided.ssorthp( N, order, x, stride )\n Sorts a single-precision floating-point strided array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssorthp( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ssorthp( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.ssorthp.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssorthp.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssorthp.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.ssortins":"\nbase.strided.ssortins( N, order, x, stride )\n Sorts a single-precision floating-point strided array using insertion sort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssortins( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ssortins( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssortins.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssortins.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins","base.strided.ssortsh":"\nbase.strided.ssortsh( N, order, x, stride )\n Sorts a single-precision floating-point strided array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssortsh( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ssortsh( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.ssqrt":"\nbase.strided.ssqrt( N, x, strideX, y, strideY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt( x.length, x, 1, y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt( N, x, 2, y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ssqrt( N, x1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt","base.strided.sstdev":"\nbase.strided.sstdev( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance","base.strided.sstdevch":"\nbase.strided.sstdevch( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc","base.strided.ssum":"\nbase.strided.ssum( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.ssum( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.ssum( N, x1, stride )\n -1.0\n\nbase.strided.ssum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumkbn.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.ssumkbn2( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.ssumkbn2( N, x1, stride )\n -1.0\n\nbase.strided.ssumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumors":"\nbase.strided.ssumors( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumors.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw","base.strided.ssumpw":"\nbase.strided.ssumpw( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors","base.strided.sswap":"\nbase.strided.sswap( N, x, strideX, y, strideY )\n Interchanges two single-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped\n with values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.sswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap","base.strided.stdev":"\nbase.strided.stdev( N, correction, x, stride )\n Computes the standard deviation of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance","base.strided.stdevch":"\nbase.strided.stdevch( N, correction, x, stride )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech","base.strided.stdevpn":"\nbase.strided.stdevpn( N, correction, x, stride )\n Computes the standard deviation of a strided array using a two-pass\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn","base.strided.stdevtk":"\nbase.strided.stdevtk( N, correction, x, stride )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk","base.strided.stdevwd":"\nbase.strided.stdevwd( N, correction, x, stride )\n Computes the standard deviation of a strided array using Welford's\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd","base.strided.stdevyc":"\nbase.strided.stdevyc( N, correction, x, stride )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc","base.strided.strunc":"\nbase.strided.strunc( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc( N, x, 2, y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.strunc( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc","base.strided.svariance":"\nbase.strided.svariance( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance","base.strided.svariancech":"\nbase.strided.svariancech( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariancech( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariancech( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech","base.strided.svariancepn":"\nbase.strided.svariancepn( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn","base.strided.svariancetk":"\nbase.strided.svariancetk( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariancetk( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariancetk( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk","base.strided.svariancewd":"\nbase.strided.svariancewd( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariancewd( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariancewd( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svarianceyc( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svarianceyc( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc\n","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc","base.strided.ternary":"\nbase.strided.ternary( arrays, shape, strides, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary( [ x, y, z, w ], shape, strides, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary","base.strided.unary":"\nbase.strided.unary( arrays, shape, strides, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > base.strided.unary( [ x, y ], shape, strides, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var offsets = [ 0, 0 ];\n > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.unary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var offsets = [ 0, 0 ];\n > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.unary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays, shape, strides, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n\n The shape and stride parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element\n - idx: iteration index\n - indices: strided indices (offset + idx*stride)\n - arrays: input and output arrays\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using shape and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n > y\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > sh = [ 2 ];\n > st = [ -2, 1 ];\n > base.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\n > y1\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > var o = [ 0, 0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > o = [ 1, y.length-1 ];\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.unary\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > var o = [ 0, 0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > o = [ 1, y.length-1 ];\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.unary","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1, dtypes2[, options] )\n Generates a list of unary interface signatures from strided array data\n types.\n\n The function returns a strided array having a stride length of two (i.e.,\n every two elements define a unary interface signature).\n\n For each signature (i.e., set of two consecutive non-overlapping strided\n array elements), the first element is the input data type and the second\n element is the return data type.\n\n All signatures follow type promotion rules.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the output argument.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing unary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.unaryDtypeSignatures( dt, dt )\n [...]\n\n See Also\n --------\n base.strided.unarySignatureCallbacks\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table, signatures )\n Assigns callbacks to unary interfaces according to type promotion rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing unary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.unaryDtypeSignatures( dt, dt );\n > var t = {\n ... 'default': base.identity,\n ... 'complex64': base.cidentityf,\n ... 'complex128': base.cidentity\n ... };\n > var out = base.strided.unarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.unaryDtypeSignatures\n","base.strided.variance":"\nbase.strided.variance( N, correction, x, stride )\n Computes the variance of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.variance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.variance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.variance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance","base.strided.variancech":"\nbase.strided.variancech( N, correction, x, stride )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.variancech( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.variancech( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.variancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance","base.strided.variancepn":"\nbase.strided.variancepn( N, correction, x, stride )\n Computes the variance of a strided array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.variancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.variancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.variancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance","base.strided.variancetk":"\nbase.strided.variancetk( N, correction, x, stride )\n Computes the variance of a strided array using a one-pass textbook\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.variancetk( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.variancetk( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.variancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance","base.strided.variancewd":"\nbase.strided.variancewd( N, correction, x, stride )\n Computes the variance of a strided array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.variancewd( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.variancewd( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.variancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance","base.strided.varianceyc":"\nbase.strided.varianceyc( N, correction, x, stride )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.varianceyc( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.varianceyc( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.varianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance","base.strided.zmap":"\nbase.strided.zmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap( x.length, x, 1, y, 1, base.cidentity );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Using `N` and stride parameters:\n > y = new Complex128Array( x.length );\n > base.strided.zmap( 2, x, 2, y, -1, base.cidentity );\n > v = y.get( 0 )\n \n > re = real( v )\n 5.0\n > im = imag( v )\n 6.0\n\n // Using view offsets:\n > var x0 = new Complex128Array( xbuf );\n > var y0 = new Complex128Array( x0.length );\n > var x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.zmap( 2, x1, -2, y1, 1, base.cidentity );\n > v = y1.get( 0 )\n \n > re = real( v )\n 7.0\n > im = imag( v )\n 8.0\n\n\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Advanced indexing:\n > x = new Complex128Array( xbuf );\n > y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\n > v = y.get( y.length-1 )\n \n > re = real( v )\n 3.0\n > im = imag( v )\n 4.0\n\n See Also\n --------\n base.strided.cmap, base.strided.unary\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Advanced indexing:\n > x = new Complex128Array( xbuf );\n > y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\n > v = y.get( y.length-1 )\n \n > re = real( v )\n 3.0\n > im = imag( v )\n 4.0\n\n See Also\n --------\n base.strided.cmap, base.strided.unary","base.sub":"\nbase.sub( x, y )\n Subtracts two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.sub( -1.0, 5.0 )\n -6.0\n > v = base.sub( 2.0, 5.0 )\n -3.0\n > v = base.sub( 0.0, 5.0 )\n -5.0\n > v = base.sub( -0.0, 0.0 )\n -0.0\n > v = base.sub( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.div, base.mul\n","base.subf":"\nbase.subf( x, y )\n Subtracts two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.subf( -1.0, 5.0 )\n -6.0\n > v = base.subf( 2.0, 5.0 )\n -3.0\n > v = base.subf( 0.0, 5.0 )\n -5.0\n > v = base.subf( -0.0, 0.0 )\n -0.0\n > v = base.subf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.divf, base.mulf, base.sub\n","base.sumSeries":"\nbase.sumSeries( generator[, options] )\n Sum the elements of the series given by the supplied function.\n\n Parameters\n ----------\n generator: Function\n Series function.\n\n options: Object (optional)\n Options.\n\n options.maxTerms: integer (optional)\n Maximum number of terms to be added. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n the current term times the tolerance. Default: `2.22e-16`.\n\n options.initialValue: number (optional)\n Initial value of the resulting sum. Default: `0`.\n\n Returns\n -------\n out: number\n Sum of series terms.\n\n Examples\n --------\n // Using an ES6 generator function:\n > function* geometricSeriesGenerator( x ) {\n ... var exponent = 0;\n ... while ( true ) {\n ... yield Math.pow( x, exponent );\n ... exponent += 1;\n ... }\n ... };\n > var gen = geometricSeriesGenerator( 0.9 );\n > var out = base.sumSeries( gen )\n 10\n\n // Using a closure:\n > function geometricSeriesClosure( x ) {\n ... var exponent = -1;\n ... return function() {\n ... exponent += 1;\n ... return Math.pow( x, exponent );\n ... };\n ... };\n > gen = geometricSeriesClosure( 0.9 );\n > out = base.sumSeries( gen )\n 10\n\n // Setting an initial value for the sum:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\n 3\n // Changing the maximum number of terms to be summed:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\n ~1.998 // Infinite sum is 2\n\n // Adjusting the used tolerance:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n ~1.998\n\n","base.tan":"\nbase.tan( x )\n Computes the tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Tangent.\n\n Examples\n --------\n > var y = base.tan( 0.0 )\n ~0.0\n > y = base.tan( -PI/4.0 )\n ~-1.0\n > y = base.tan( PI/4.0 )\n ~1.0\n > y = base.tan( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sin\n","base.tanh":"\nbase.tanh( x )\n Computes the hyperbolic tangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic tangent.\n\n Examples\n --------\n > var y = base.tanh( 0.0 )\n 0.0\n > var y = base.tanh( -0.0 )\n -0.0\n > y = base.tanh( 2.0 )\n ~0.964\n > y = base.tanh( -2.0 )\n ~-0.964\n > y = base.tanh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sinh, base.tan\n","base.toBinaryString":"\nbase.toBinaryString( x )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bstr: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryString( 4.0 )\n '0100000000010000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PI )\n '0100000000001001001000011111101101010100010001000010110100011000'\n > str = base.toBinaryString( -1.0e308 )\n '1111111111100001110011001111001110000101111010111100100010100000'\n > str = base.toBinaryString( -3.14e-320 )\n '1000000000000000000000000000000000000000000000000001100011010011'\n > str = base.toBinaryString( 5.0e-324 )\n '0000000000000000000000000000000000000000000000000000000000000001'\n > str = base.toBinaryString( 0.0 )\n '0000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( -0.0 )\n '1000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NaN )\n '0111111111111000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PINF )\n '0111111111110000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NINF )\n '1111111111110000000000000000000000000000000000000000000000000000'\n\n See Also\n --------\n base.fromBinaryString, base.toBinaryStringf\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\n '01000000100000000000000000000000'\n > str = base.toBinaryStringf( base.float64ToFloat32( PI ) )\n '01000000010010010000111111011011'\n > str = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\n '11111110100101100111011010011001'\n > str = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\n '10000000001000100011000100001011'\n > str = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringf( 0.0 )\n '00000000000000000000000000000000'\n > str = base.toBinaryStringf( -0.0 )\n '10000000000000000000000000000000'\n > str = base.toBinaryStringf( NaN )\n '01111111110000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_PINF )\n '01111111100000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_NINF )\n '11111111100000000000000000000000'\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 8-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 8-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned 8-bit\n integers. Accordingly, care should be taken to ensure that only nonnegative\n integer values less than `256` (`2^8`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint8Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint8( a[ 0 ] )\n '00000001'\n > str = base.toBinaryStringUint8( a[ 1 ] )\n '00000100'\n > str = base.toBinaryStringUint8( a[ 2 ] )\n '00001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 16-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 16-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 16-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `65536` (`2^16`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint16Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint16( a[ 0 ] )\n '0000000000000001'\n > str = base.toBinaryStringUint16( a[ 1 ] )\n '0000000000000100'\n > str = base.toBinaryStringUint16( a[ 2 ] )\n '0000000000001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 32-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 32-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 32-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `4,294,967,296` (`2^32`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint32Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint32( a[ 0 ] )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringUint32( a[ 1 ] )\n '00000000000000000000000000000100'\n > str = base.toBinaryStringUint32( a[ 2 ] )\n '00000000000000000000000000001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toWordf":"\nbase.toWordf( x )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var f32 = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n > var w = base.toWordf( f32 )\n 1068180177\n\n See Also\n --------\n base.fromWordf, base.toWords\n","base.toWords":"\nbase.toWords( x )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array\n Higher and lower order words.\n\n Examples\n --------\n > var w = base.toWords( 3.14e201 )\n [ 1774486211, 2479577218 ]\n\n\nbase.toWords.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var out = new Uint32Array( 2 );\n > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n\n See Also\n --------\n base.fromWords, base.toWordf","base.toWords.assign":"\nbase.toWords.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var out = new Uint32Array( 2 );\n > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n\n See Also\n --------\n base.fromWords, base.toWordf","base.transpose":"\nbase.transpose( x )\n Transposes a matrix (or a stack of matrices).\n\n The returned ndarray is a *view* of the input ndarray. Accordingly, writing\n to the original ndarray will mutate the returned ndarray and vice versa.\n While powerful, this can lead to subtle bugs. In general, one should handle\n the returned ndarray as read-only.\n\n If provided an ndarray with fewer than two dimensions, the function raises\n an exception.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n \n > var sh = x.shape\n [ 2, 3 ]\n > var y = base.transpose( x )\n \n > sh = y.shape\n [ 3, 2 ]\n > var bool = ( x.data === y.data )\n true\n > bool = ( x.get( 0, 1 ) === y.get( 1, 0 ) )\n true\n\n See Also\n --------\n ndarray\n","base.tribonacci":"\nbase.tribonacci( n )\n Computes the nth Tribonacci number.\n\n Tribonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2} + F_{n-3}\n\n with seed values F_0 = 0, F_1 = 0, and F_2 = 1.\n\n If `n` is greater than `63`, the function returns `NaN`, as larger\n Tribonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Tribonacci number.\n\n Examples\n --------\n > var y = base.tribonacci( 0 )\n 0\n > y = base.tribonacci( 1 )\n 0\n > y = base.tribonacci( 2 )\n 1\n > y = base.tribonacci( 3 )\n 1\n > y = base.tribonacci( 4 )\n 2\n > y = base.tribonacci( 64 )\n NaN\n > y = base.tribonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.trigamma":"\nbase.trigamma( x )\n Evaluates the trigamma function.\n\n If `x` is `0` or a negative `integer`, the `function` returns `NaN`.\n\n If provided `NaN`, the `function` returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.trigamma( -2.5 )\n ~9.539\n > y = base.trigamma( 1.0 )\n ~1.645\n > y = base.trigamma( 10.0 )\n ~0.105\n > y = base.trigamma( NaN )\n NaN\n > y = base.trigamma( -1.0 )\n NaN\n\n See Also\n --------\n base.digamma, base.gamma\n","base.trunc":"\nbase.trunc( x )\n Rounds a double-precision floating-point number toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc( 3.14 )\n 3.0\n > y = base.trunc( -4.2 )\n -4.0\n > y = base.trunc( -4.6 )\n -4.0\n > y = base.trunc( 9.5 )\n 9.0\n > y = base.trunc( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.round\n","base.trunc2":"\nbase.trunc2( x )\n Rounds a numeric value to the nearest power of two toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc2( 3.14 )\n 2.0\n > y = base.trunc2( -4.2 )\n -4.0\n > y = base.trunc2( -4.6 )\n -4.0\n > y = base.trunc2( 9.5 )\n 8.0\n > y = base.trunc2( 13.0 )\n 8.0\n > y = base.trunc2( -13.0 )\n -8.0\n > y = base.trunc2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round2, base.trunc, base.trunc10\n","base.trunc10":"\nbase.trunc10( x )\n Rounds a numeric value to the nearest power of ten toward zero.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc10( 3.14 )\n 1.0\n > y = base.trunc10( -4.2 )\n -1.0\n > y = base.trunc10( -4.6 )\n -1.0\n > y = base.trunc10( 9.5 )\n 1.0\n > y = base.trunc10( 13.0 )\n 10.0\n > y = base.trunc10( -13.0 )\n -10.0\n > y = base.trunc10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round10, base.trunc, base.trunc2\n","base.truncb":"\nbase.truncb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.truncb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward zero:\n > y = base.truncb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.roundb, base.trunc, base.truncn\n","base.truncf":"\nbase.truncf( x )\n Rounds a single-precision floating-point number toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncf( 3.14 )\n 3.0\n > y = base.truncf( -4.2 )\n -4.0\n > y = base.truncf( -4.6 )\n -4.0\n > y = base.truncf( 9.5 )\n 9.0\n > y = base.truncf( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceilf, base.floorf, base.trunc\n","base.truncn":"\nbase.truncn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round behavior:\n > y = base.truncn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.truncn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.roundn, base.trunc, base.truncb\n","base.truncsd":"\nbase.truncsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncsd( 3.14159, 5 )\n 3.1415\n > y = base.truncsd( 3.14159, 1 )\n 3.0\n > y = base.truncsd( 12368.0, 2 )\n 12000.0\n > y = base.truncsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.roundsd, base.trunc\n","base.umul":"\nbase.umul( a, b )\n Performs C-like multiplication of two unsigned 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.umul( 10>>>0, 4>>>0 )\n 40\n\n See Also\n --------\n base.imul\n","base.umuldw":"\nbase.umuldw( a, b )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: Array\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.umuldw( 1, 10 )\n [ 0, 10 ]\n\n\nbase.umuldw.assign( a, b, out, stride, offset )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imuldw, base.umul\n","base.umuldw.assign":"\nbase.umuldw.assign( a, b, out, stride, offset )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imuldw, base.umul","base.uint32ToInt32":"\nbase.uint32ToInt32( x )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\n -1\n > y = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n 3\n\n","base.vercos":"\nbase.vercos( x )\n Computes the versed cosine.\n\n The versed cosine is defined as `1 + cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed cosine.\n\n Examples\n --------\n > var y = base.vercos( 3.14 )\n ~0.0\n > y = base.vercos( -4.2 )\n ~0.5097\n > y = base.vercos( -4.6 )\n ~0.8878\n > y = base.vercos( 9.5 )\n ~0.0028\n > y = base.vercos( -0.0 )\n 2.0\n\n See Also\n --------\n base.cos, base.versin\n","base.versin":"\nbase.versin( x )\n Computes the versed sine.\n\n The versed sine is defined as `1 - cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed sine.\n\n Examples\n --------\n > var y = base.versin( 3.14 )\n ~2.0\n > y = base.versin( -4.2 )\n ~1.490\n > y = base.versin( -4.6 )\n ~1.112\n > y = base.versin( 9.5 )\n ~1.997\n > y = base.versin( -0.0 )\n 0.0\n\n See Also\n --------\n base.cos, base.sin, base.vercos\n","base.wrap":"\nbase.wrap( v, min, max )\n Wraps a value on the half-open interval `[min,max)`.\n\n The function does not distinguish between positive and negative zero. Where\n appropriate, the function returns positive zero.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to wrap.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Wrapped value.\n\n Examples\n --------\n > var y = base.wrap( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.wrap( -3.14, 0.0, 5.0 )\n ~1.86\n > y = base.wrap( 3.14, 0.0, 3.0 )\n ~0.14\n > y = base.wrap( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.wrap( 0.0, -3.14, -0.0 )\n -3.14\n > y = base.wrap( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clamp\n","base.xlog1py":"\nbase.xlog1py( x, y )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlog1py( 3.0, 2.0 )\n ~3.296\n > out = base.xlog1py( 1.5, 5.9 )\n ~2.897\n > out = base.xlog1py( 0.9, 1.0 )\n ~0.624\n > out = base.xlog1py( 1.0, 0.0 )\n 0.0\n > out = base.xlog1py( 0.0, -2.0 )\n 0.0\n > out = base.xlog1py( 1.5, NaN )\n NaN\n > out = base.xlog1py( 0.0, NaN )\n NaN\n > out = base.xlog1py( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.log1p, base.xlogy\n","base.xlogy":"\nbase.xlogy( x, y )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlogy( 3.0, 2.0 )\n ~2.079\n > out = base.xlogy( 1.5, 5.9 )\n ~2.662\n > out = base.xlogy( 0.9, 1.0 )\n 0.0\n > out = base.xlogy( 0.0, -2.0 )\n 0.0\n > out = base.xlogy( 1.5, NaN )\n NaN\n > out = base.xlogy( 0.0, NaN )\n NaN\n > out = base.xlogy( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.ln, base.xlog1py\n","base.zeta":"\nbase.zeta( s )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.zeta( 1.1 )\n ~10.584\n > y = base.zeta( -4.0 )\n 0.0\n > y = base.zeta( 70.0 )\n 1.0\n > y = base.zeta( 0.5 )\n ~-1.46\n > y = base.zeta( NaN )\n NaN\n\n // Evaluate at a pole:\n > y = base.zeta( 1.0 )\n NaN\n\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and and other characteristics.\n\n Each array element has the following eleven fields:\n\n - education: number of years of education.\n - south: indicator variable for southern region (1 if a person lives in the\n South; 0 if a person does not live in the South).\n - gender: gender of the person.\n - experience: number of years of work experience.\n - union: indicator variable for union membership (1 if union member; 0 if\n not a union member).\n - wage: wage (in dollars per hour).\n - age: age (in years).\n - race: ethnicity/race (white, hispanic, and other).\n - occupation: occupational category (management, sales, clerical, service,\n professional, and other).\n - sector: sector (other, manufacturing, or construction).\n - married: marital status (0 if unmarried; 1 if married).\n\n Based on residual plots, wages were log-transformed to stabilize the\n variance.\n\n Returns\n -------\n out: Array\n CPS data.\n\n Examples\n --------\n > var data = BERNDT_CPS_WAGES_1985()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Berndt, Ernst R. 1991. _The Practice of Econometrics_. Addison Wesley\n Longman Publishing Co.\n\n","bifurcate":"\nbifurcate( collection, [options,] filter )\n Splits values into two groups.\n\n If an element in `filter` is truthy, then the corresponding element in the\n input collection belongs to the first group; otherwise, the collection\n element belongs to the second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n filter: Array|TypedArray|Object\n A collection indicating which group an element in the input collection\n belongs to. If an element in `filter` is truthy, the corresponding\n element in `collection` belongs to the first group; otherwise, the\n collection element belongs to the second group. If provided an object,\n the object must be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var f = [ true, true, false, true ];\n > var out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n > f = [ 1, 1, 0, 1 ];\n > out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > f = [ true, true, false, true ];\n > var opts = { 'returns': 'indices' };\n > out = bifurcate( collection, opts, f )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = bifurcate( collection, opts, f )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo'] ] ]\n\n See Also\n --------\n bifurcateBy, bifurcateOwn, group\n","bifurcateBy":"\nbifurcateBy( collection, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If a predicate function returns a truthy value, a collection value is\n placed in the first group; otherwise, a collection value is placed in the\n second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = bifurcateBy( collection, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, groupBy\n","bifurcateByAsync":"\nbifurcateByAsync( collection, [options,] predicate, done )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an predicate function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If a predicate function calls the `next` callback with a truthy group value,\n a collection value is placed in the first group; otherwise, a collection\n value is placed in the second group.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n [ [ 1000, 3000 ], [ 2500 ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ 2, 0 ], [ 1 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ [ 2, 1000 ], [ 0, 3000 ] ], [ [ 1, 2500 ] ] ]\n\n // Limit number of concurrent invocations:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n // Process sequentially:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n See Also\n --------\n bifurcateBy, groupByAsync\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n See Also\n --------\n bifurcateBy, groupByAsync","bifurcateIn":"\nbifurcateIn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object with no prototype, the function returns an empty\n array.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var out = bifurcateIn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateOwn, groupIn\n","bifurcateOwn":"\nbifurcateOwn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object, the function returns an empty array.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = bifurcateOwn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateIn, groupOwn\n","BigInt":"\nBigInt( value )\n Returns a BigInt.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support BigInts.\n\n Parameters\n ----------\n value: integer|string\n Value of the BigInt.\n\n Returns\n -------\n out: BigInt\n BigInt.\n\n Examples\n --------\n > var v = ( BigInt ) ? BigInt( '1' ) : null\n\n\nTODO: document properties/methods\n\n","binomialTest":"\nbinomialTest( x[, n][, options] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: (number|Array)\n Number of successes or two-element array with successes and failures.\n\n n: Array (optional)\n Total number of observations.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.p: number (optional)\n Hypothesized probability under the null hypothesis. Default: `0.5`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Sample proportion.\n\n out.ci: Array\n 1-alpha confidence interval for the success probability.\n\n out.nullValue: number\n Assumed success probability under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var out = binomialTest( 682, 925 )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( [ 682, 925 - 682 ] )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( 21, 40, {\n ... 'p': 0.4,\n ... 'alternative': 'greater'\n ... })\n {\n 'pValue': ~0.074,\n 'statistic': 0.525\n // ...\n }\n\n","Boolean":"\nBoolean( value )\n Returns a boolean.\n\n When invoked without `new`,\n\n - if provided `false`, `null`, `undefined`, `-0`, `0`, `NaN`, or an empty\n string, the function returns `false`.\n - if provided any other value, including an empty object, an empty array,\n the string `'false'`, or a `Boolean` object (including a `Boolean` object\n whose value is `false`), the function returns `true`.\n\n When invoked with `new`, the constructor returns a `Boolean` object, which\n is an object wrapper for a primitive boolean value. The value of the\n returned `Boolean` object follows the same conversion semantics as when the\n constructor is invoked without `new`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: boolean|Boolean\n Boolean primitive or object.\n\n Examples\n --------\n > var b = new Boolean( null )\n \n > b = Boolean( null )\n false\n > b = Boolean( [] )\n true\n\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n\n Returns\n -------\n out: string\n String representation.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.toString()\n 'true'\n\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n\n Returns\n -------\n out: boolean\n Boolean primitive.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.valueOf()\n true\n\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n\n Returns\n -------\n out: string\n String representation.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.toString()\n 'true'","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n\n Returns\n -------\n out: boolean\n Boolean primitive.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.valueOf()\n true","broadcastArray":"\nbroadcastArray( x, shape )\n Broadcasts an ndarray to a specified shape.\n\n The returned array is a read-only view on the input array data buffer. The\n view is typically *not* contiguous. As more than one element of a returned\n view may refer to the same memory location, writing to the input array may\n affect multiple elements. If you need to write to the input array, copy the\n input array before broadcasting.\n\n The function throws an error if a provided ndarray is incompatible with a\n provided shape.\n\n The function always returns a new ndarray instance even if the input ndarray\n shape and the desired shape are the same.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n shape: ArrayLikeObject\n Desired shape.\n\n Returns\n -------\n out: ndarray\n Broadcasted array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = broadcastArray( x, [ 3, 2, 2 ] )\n \n > sh = y.shape\n [ 3, 2, 2 ]\n > var v = y.get( 0, 0, 0 )\n 1\n > v = y.get( 0, 0, 1 )\n 2\n > v = y.get( 0, 1, 0 )\n 3\n > v = y.get( 0, 1, 1 )\n 4\n > v = y.get( 1, 0, 0 )\n 1\n > v = y.get( 1, 1, 0 )\n 3\n > v = y.get( 2, 0, 0 )\n 1\n > v = y.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, broadcastArrays, ndarray, maybeBroadcastArray\n","broadcastArrays":"\nbroadcastArrays( ...arrays )\n Broadcasts ndarrays to a common shape.\n\n The function supports two (mutually exclusive) means of providing ndarray\n arguments:\n\n 1. Providing a single array containing ndarray arguments.\n 2. Providing ndarray arguments as separate arguments.\n\n The returned arrays are read-only views on their respective underlying\n array data buffers. The views are typically **not** contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to a view may affect multiple elements. If you need to write to an\n input array, copy the array before broadcasting.\n\n The function throws an error if provided broadcast-incompatible ndarrays.\n\n The function always returns new ndarray instances even if an input ndarray\n and the broadcasted shape are the same.\n\n Parameters\n ----------\n arrays: ...ndarray|ArrayLikeObject\n Array arguments.\n\n Returns\n -------\n out: Array\n Broadcasted arrays.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = ndzeros( [ 3, 2, 2 ] )\n \n > var out = broadcastArrays( [ x, y ] )\n [ , ]\n\n // Retrieve the broadcasted \"x\" array:\n > var bx = out[ 0 ]\n \n > sh = bx.shape\n [ 3, 2, 2 ]\n\n // Retrieve broadcasted elements...\n > var v = bx.get( 0, 0, 0 )\n 1\n > v = bx.get( 0, 0, 1 )\n 2\n > v = bx.get( 0, 1, 0 )\n 3\n > v = bx.get( 0, 1, 1 )\n 4\n > v = bx.get( 1, 0, 0 )\n 1\n > v = bx.get( 1, 1, 0 )\n 3\n > v = bx.get( 2, 0, 0 )\n 1\n > v = bx.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, broadcastArray, ndarray, maybeBroadcastArrays\n","Buffer":"\nBuffer\n Buffer constructor.\n\n\nBuffer( size )\n Allocates a buffer having a specified number of bytes.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 4 )\n \n\n\nBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = new Buffer( [ 1, 2, 3, 4 ] );\n > var b2 = new Buffer( b1 )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( array )\n Allocates a buffer using an array of octets.\n\n Parameters\n ----------\n array: Array\n Array of octets.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 'beep boop' )\n \n\n\nTODO: add methods and properties\n\n\n See Also\n --------\n ArrayBuffer\n","buffer2json":"\nbuffer2json( buffer )\n Returns a JSON representation of a buffer.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n out.type: string\n Value type. The assigned value is always \"Buffer\".\n\n out.data: Array\n Buffer data.\n\n Examples\n --------\n > var buf = new allocUnsafe( 2 );\n > buf[ 0 ] = 1;\n > buf[ 1 ] = 2;\n > var json = buffer2json( buf )\n { 'type': 'Buffer', 'data': [ 1, 2 ] }\n\n See Also\n --------\n typedarray2json, reviveBuffer\n","BYTE_ORDER":"\nBYTE_ORDER\n Platform byte order.\n\n Possible values:\n\n - 'little-endian'\n - 'big-endian'\n - 'mixed-endian'\n - 'unknown'\n\n Examples\n --------\n > BYTE_ORDER\n \n\n See Also\n --------\n IS_BIG_ENDIAN, IS_LITTLE_ENDIAN\n","camelcase":"\ncamelcase( str )\n Converts a string to camel case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Camel-cased string.\n\n Examples\n --------\n > var out = camelcase( 'Hello World!' )\n 'helloWorld'\n > out = camelcase( 'beep boop' )\n 'beepBoop'\n\n See Also\n --------\n constantcase, kebabcase, pascalcase, snakecase","capitalize":"\ncapitalize( str )\n Capitalizes the first character in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Capitalized string.\n\n Examples\n --------\n > var out = capitalize( 'beep' )\n 'Beep'\n > out = capitalize( 'Boop' )\n 'Boop'\n\n See Also\n --------\n uncapitalize, uppercase\n","capitalizeKeys":"\ncapitalizeKeys( obj )\n Converts the first letter of each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'aa': 1, 'bb': 2 };\n > var out = capitalizeKeys( obj )\n { 'Aa': 1, 'Bb': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n","CATALAN":"\nCATALAN\n Catalan's constant.\n\n Examples\n --------\n > CATALAN\n 0.915965594177219\n\n","CBRT_EPS":"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n\n Examples\n --------\n > CBRT_EPS\n 0.0000060554544523933395\n\n See Also\n --------\n EPS, SQRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n Returns US birth data from 1969 to 1988, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_BIRTHS_1969_1988()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1994_2003, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n Returns US birth data from 1994 to 2003, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_BIRTHS_1994_2003()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1969_1988, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n the Center for Disease Control and Prevention's National Center for Health\n Statistics.\n\n All birth data by race before 1980 are based on race of the child. Starting\n in 1980, birth data by race are based on race of the mother. Birth data are\n used to calculate infant mortality rate.\n\n Returns\n -------\n out: Array\n Infant mortality data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n { 'black': [...], 'white': [...] }\n\n","chdir":"\nchdir( path )\n Changes the current working directory.\n\n If unable to set the current working directory (e.g., due to a non-existent\n path), the function returns an error; otherwise, the function returns\n `null`.\n\n Parameters\n ----------\n path: string\n Desired working directory.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = chdir( '/path/to/current/working/directory' )\n\n See Also\n --------\n cwd\n","chi2gof":"\nchi2gof( x, y[, ...args][, options] )\n Performs a chi-square goodness-of-fit test.\n\n A chi-square goodness-of-fit test is computed for the null hypothesis that\n the values of `x` come from the discrete probability distribution specified\n by `y`.\n\n The second argument can either be expected frequencies, population\n probabilities summing to one, or a discrete probability distribution name to\n test against.\n\n When providing a discrete probability distribution name, distribution\n parameters *must* be supplied as additional arguments.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n By default, the p-value is computed using a chi-square distribution with\n `k-1` degrees of freedom, where `k` is the length of `x`.\n\n If provided distribution arguments are estimated (e.g., via maximum\n likelihood estimation), the degrees of freedom should be corrected. Set the\n `ddof` option to use `k-1-n` degrees of freedom, where `n` is the degrees of\n freedom adjustment.\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five.\n\n Instead of relying on chi-square approximation to calculate the p-value, one\n can use Monte Carlo simulation. When the `simulate` option is `true`, the\n simulation is performed by re-sampling from the discrete probability\n distribution specified by `y`.\n\n Parameters\n ----------\n x: ndarray|Array|TypedArray\n Observation frequencies.\n\n y: ndarray|Array|TypedArray|string\n Expected frequencies, population probabilities, or a discrete\n probability distribution name.\n\n args: ...number (optional)\n Distribution parameters. Distribution parameters will be passed to a\n probability mass function (PMF) as arguments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.ddof: number (optional)\n Delta degrees of freedom adjustment. Default: 0.\n\n options.simulate: boolean (optional)\n Boolean indicating whether to calculate p-values by Monte Carlo\n simulation. The simulation is performed by re-sampling from the discrete\n distribution specified by `y`. Default: false.\n\n options.iterations: number (optional)\n Number of Monte Carlo iterations. Default: 500.\n\n Returns\n -------\n out: Object\n Test results object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number|null\n Degrees of freedom.\n\n out.method: string\n Test name.\n\n out.toString: Function\n Serializes results as formatted output.\n\n out.toJSON: Function\n Serializes results as JSON.\n\n Examples\n --------\n // Provide expected probabilities...\n > var x = [ 89, 37, 30, 28, 2 ];\n > var p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > var out = chi2gof( x, p );\n > var o = out.toJSON()\n { 'pValue': ~0.0406, 'statistic': ~9.9901, ... }\n > out.toString()\n\n // Set significance level...\n > var opts = { 'alpha': 0.01 };\n > out = chi2gof( x, p, opts );\n > out.toString()\n\n // Calculate the test p-value via Monte Carlo simulation...\n > x = [ 89, 37, 30, 28, 2 ];\n > p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > opts = { 'simulate': true, 'iterations': 1000 };\n > out = chi2gof( x, p, opts );\n > out.toString()\n\n // Verify that data comes from Poisson distribution...\n > var lambda = 3.0;\n > var rpois = base.random.poisson.factory( lambda );\n > var len = 400;\n > x = [];\n > for ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n // Generate a frequency table...\n > var freqs = new Int32Array( len );\n > for ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\n > out = chi2gof( freqs, 'poisson', lambda );\n > out.toString()\n\n","chi2test":"\nchi2test( x[, options] )\n Performs a chi-square independence test.\n\n For a two-way contingency table, the function computes a chi-square\n independence test for the null hypothesis that the joint distribution of the\n cell counts is the product of the row and column marginals (i.e. that the\n row and column variables are independent).\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five. The Yates' continuity correction is enabled\n by default for 2x2 tables to account for this, although it tends to\n over-correct.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n Parameters\n ----------\n x: ndarray|Array>\n Two-way table of observed frequencies.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.correct: boolean (optional)\n Boolean indicating whether to use Yates' continuity correction when\n provided a 2x2 contingency table. Default: true.\n\n Returns\n -------\n out: Object\n Test results object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number\n Degrees of freedom.\n\n out.expected: ndarray\n Expected frequencies.\n\n out.method: string\n Test name.\n\n out.toString: Function\n Serializes results as formatted output.\n\n out.toJSON: Function\n Serializes results as JSON.\n\n Examples\n --------\n > var x = [ [ 20, 30 ], [ 30, 20 ] ];\n > var out = chi2test( x );\n > var o = out.toJSON()\n { 'rejected': false, 'pValue': ~0.072, 'statistic': 3.24, ... }\n > out.toString()\n\n // Set significance level...\n > var opts = { 'alpha': 0.1 };\n > out = chi2test( x, opts );\n > o = out.toJSON()\n { 'rejected': true, 'pValue': ~0.072, 'statistic': 3.24, ... }\n > out.toString()\n\n // Disable Yates' continuity correction (primarily used with small counts):\n > opts = { 'correct': false };\n > out = chi2test( x, opts );\n > out.toString()\n\n","circarray2iterator":"\ncircarray2iterator( src[, options][, mapFcn[, thisArg]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, an iterator iterates over elements\n from right-to-left. Default: 1.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = circarray2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n array2iterator, stridedarray2iterator\n","circularArrayStream":"\ncircularArrayStream( src[, options] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );\n\n\ncircularArrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream, stridedArrayStream\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream, stridedArrayStream","CircularBuffer":"\nCircularBuffer( buffer )\n Circular buffer constructor.\n\n Parameters\n ----------\n buffer: integer|ArrayLike\n Buffer size or an array-like object to use as the underlying buffer.\n\n Returns\n -------\n buf: Object\n Circular buffer data structure.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.length\n 3\n > b.count\n 3\n > b.push( 'boop' )\n 'foo'\n\n\nCircularBuffer.prototype.clear()\n Clears a buffer.\n\n Returns\n -------\n out: Object\n Circular buffer instance.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.count\n 3\n > b.clear();\n > b.count\n 0\n\n\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n\n Returns\n -------\n out: integer\n Number of elements currently in the buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.count\n 0\n > b.push( 'foo' );\n > b.count\n 1\n > b.push( 'bar' );\n > b.count\n 2\n\n\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a circular buffer is full.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.full\n false\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.full\n true\n\n\nCircularBuffer.prototype.iterator( [niters] )\n Returns an iterator for iterating over a circular buffer.\n\n A returned iterator does not iterate over partially full buffers.\n\n Parameters\n ----------\n niters: integer (optional)\n Number of iterations. Default: infinity.\n\n Returns\n -------\n out: Iterator\n Iterator.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var it = b.iterator( b.length );\n > var v = it.next().value\n 'bar'\n > v = it.next().value\n 'beep'\n > v = it.next().value\n 'boop'\n > var bool = it.next().done\n true\n\n\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n\n Returns\n -------\n out: integer\n Buffer length.\n\n Examples\n --------\n > var b = CircularBuffer( [ 0, 0, 0 ] );\n > var len = b.length\n 3\n\n\nCircularBuffer.prototype.push( value )\n Adds a value to a circular buffer.\n\n Parameters\n ----------\n value: any\n Value to add.\n\n Returns\n -------\n out: any\n Removed element (or undefined).\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' )\n undefined\n > b.push( 'bar' )\n undefined\n > b.push( 'beep' )\n undefined\n > b.push( 'boop' )\n 'foo'\n\n\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n\n Returns\n -------\n out: Array\n Circular buffer values.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var vals = b.toArray()\n [ 'bar', 'beep', 'boop' ]\n\n\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n\n Returns\n -------\n out: Object\n Serialized circular buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var o = b.toJSON()\n {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n See Also\n --------\n FIFO, Stack\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n Clears a buffer.\n\n Returns\n -------\n out: Object\n Circular buffer instance.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.count\n 3\n > b.clear();\n > b.count\n 0","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n\n Returns\n -------\n out: integer\n Number of elements currently in the buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.count\n 0\n > b.push( 'foo' );\n > b.count\n 1\n > b.push( 'bar' );\n > b.count\n 2","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a circular buffer is full.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.full\n false\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.full\n true","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters] )\n Returns an iterator for iterating over a circular buffer.\n\n A returned iterator does not iterate over partially full buffers.\n\n Parameters\n ----------\n niters: integer (optional)\n Number of iterations. Default: infinity.\n\n Returns\n -------\n out: Iterator\n Iterator.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var it = b.iterator( b.length );\n > var v = it.next().value\n 'bar'\n > v = it.next().value\n 'beep'\n > v = it.next().value\n 'boop'\n > var bool = it.next().done\n true","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n\n Returns\n -------\n out: integer\n Buffer length.\n\n Examples\n --------\n > var b = CircularBuffer( [ 0, 0, 0 ] );\n > var len = b.length\n 3","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value )\n Adds a value to a circular buffer.\n\n Parameters\n ----------\n value: any\n Value to add.\n\n Returns\n -------\n out: any\n Removed element (or undefined).\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' )\n undefined\n > b.push( 'bar' )\n undefined\n > b.push( 'beep' )\n undefined\n > b.push( 'boop' )\n 'foo'","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n\n Returns\n -------\n out: Array\n Circular buffer values.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var vals = b.toArray()\n [ 'bar', 'beep', 'boop' ]","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n\n Returns\n -------\n out: Object\n Serialized circular buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var o = b.toJSON()\n {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n See Also\n --------\n FIFO, Stack","close":"\nclose( fd, clbk )\n Asynchronously closes a file descriptor, so that the file descriptor no\n longer refers to any file and may be reused.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n clbk: Function\n Callback to invoke upon closing a file descriptor.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close( fd, done ); };\n\n\nclose.sync( fd )\n Synchronously closes a file descriptor.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n Returns\n -------\n out: Error|void\n If an error occurs, an error object; otherwise, undefined.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n exists, open, readFile\n","close.sync":"\nclose.sync( fd )\n Synchronously closes a file descriptor.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n Returns\n -------\n out: Error|void\n If an error occurs, an error object; otherwise, undefined.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n exists, open, readFile","CMUDICT":"\nCMUDICT( [options] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n\n Data includes the following:\n\n - dict: the main pronouncing dictionary\n - phones: manners of articulation for each sound\n - symbols: complete list of ARPABET symbols used by the dictionary\n - vp: verbal pronunciations of punctuation marks\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n CMUdict dataset.\n\n Examples\n --------\n > var data = CMUDICT();\n > var dict = data.dict\n {...}\n > var phones = data.phones\n {...}\n > var symbols = data.symbols\n [...]\n > var vp = data.vp\n {...}\n\n","codePointAt":"\ncodePointAt( str, idx[, backward] )\n Returns a Unicode code point from a string at a specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n idx: integer\n Position. If less than `0`, the string position is determined relative\n to the end of the input string.\n\n backward: boolean (optional)\n Backward iteration for low surrogates. Default: false.\n\n Returns\n -------\n out: integer\n Unicode code point.\n\n Examples\n --------\n > var out = codePointAt( 'last man standing', 4 )\n 32\n > out = codePointAt( 'presidential election', 8, true )\n 116\n > out = codePointAt( 'अनुच्छेद', 2 )\n 2369\n > out = codePointAt( '🌷', 1, true )\n 127799\n\n See Also\n --------\n fromCodePoint","commonKeys":"\ncommonKeys( obj1, obj2[, ...obj] )\n Returns the common own property names of two or more objects.\n\n Parameters\n ----------\n obj1: any\n First object.\n\n obj2: any\n Second object.\n\n obj: ...any (optional)\n Additional objects.\n\n Returns\n -------\n out: Array\n Common keys of objects.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > var keys = commonKeys( obj1, obj2 )\n [ 'a', 'b' ]\n\n See Also\n --------\n commonKeysIn, objectKeys","commonKeysIn":"\ncommonKeysIn( obj1, obj2[, ...obj] )\n Returns the common own and inherited property names of two or more objects.\n\n Parameters\n ----------\n obj1: any\n First object.\n\n obj2: any\n Second object.\n\n obj: ...any (optional)\n Additional objects.\n\n Returns\n -------\n out: Array\n Common keys.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > var keys = commonKeysIn( obj1, obj2 )\n [ 'a', 'b' ]\n\n See Also\n --------\n commonKeys, keysIn","complex":"\ncomplex( real, imag[, dtype] )\n Creates a complex number.\n\n The function supports the following data types:\n\n - float64\n - float32\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n z: Complex\n Complex number.\n\n Examples\n --------\n > var z = complex( 5.0, 3.0, 'float64' )\n \n > z = complex( 5.0, 3.0, 'float32' )\n \n\n See Also\n --------\n Complex128, Complex64\n","Complex64":"\nComplex64( real, imag )\n 64-bit complex number constructor.\n\n Both the real and imaginary components are stored as single-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex64\n 64-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n z.BYTES_PER_ELEMENT\n Size (in bytes) of each component. Value: 4.\n\n z.byteLength\n Length (in bytes) of a complex number. Value: 8.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n See Also\n --------\n complex, Complex128\n","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n Canonical single-precision complex floating-point NaN.\n\n Examples\n --------\n > COMPLEX64_NAN\n \n\n See Also\n --------\n COMPLEX128_NAN\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n\n Examples\n --------\n > COMPLEX64_NUM_BYTES\n 8\n\n See Also\n --------\n COMPLEX128_NUM_BYTES, FLOAT32_NUM_BYTES\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n Single-precision complex floating-point zero.\n\n Examples\n --------\n > COMPLEX64_ZERO\n \n\n See Also\n --------\n COMPLEX128_ZERO\n","Complex128":"\nComplex128( real, imag )\n 128-bit complex number constructor.\n\n Both the real and imaginary components are stored as double-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex128\n 128-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n z.BYTES_PER_ELEMENT\n Size (in bytes) of each component. Value: 8.\n\n z.byteLength\n Length (in bytes) of a complex number. Value: 16.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n See Also\n --------\n complex, Complex64\n","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n Canonical double-precision complex floating-point NaN.\n\n Examples\n --------\n > COMPLEX128_NAN\n \n\n See Also\n --------\n COMPLEX64_NAN\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n\n Examples\n --------\n > COMPLEX128_NUM_BYTES\n 16\n\n See Also\n --------\n COMPLEX64_NUM_BYTES, FLOAT64_NUM_BYTES\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n Double-precision complex floating-point zero.\n\n Examples\n --------\n > COMPLEX128_ZERO\n \n\n See Also\n --------\n COMPLEX64_ZERO\n","complexarray":"\ncomplexarray( [dtype] )\n Creates a complex typed array.\n\n The function supports the following data types:\n\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n\n The default typed array data type is `complex128`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr = complexarray()\n \n > arr = complexarray( 'complex64' )\n \n\n\ncomplexarray( length[, dtype] )\n Returns a complex number typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr = complexarray( 5 )\n \n > arr = complexarray( 5, 'complex64' )\n \n\n\ncomplexarray( complexarray[, dtype] )\n Creates a complex number typed array from another complex number typed\n array.\n\n Parameters\n ----------\n complexarray: ComplexArray\n Complex number typed array from which to generate another complex number\n typed array.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\n > var arr2 = complexarray( arr1, 'complex64' )\n \n\n\ncomplexarray( obj[, dtype] )\n Creates a complex number typed array from an array-like object or iterable.\n\n If an array-like object contains interleaved real and imaginary components,\n the array-like object must have a length which is a multiple of two.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\n > var arr2 = complexarray( arr1, 'complex64' )\n \n\n\ncomplexarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a complex number typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first array element.\n Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 64 );\n > var arr = complexarray( buf, 0, 8, 'complex64' )\n \n\n See Also\n --------\n typedarray, realarray\n","complexarrayCtors":"\ncomplexarrayCtors( dtype )\n Returns a complex typed array constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Complex typed array constructor.\n\n Examples\n --------\n > var ctor = complexarrayCtors( 'complex64' )\n \n > ctor = complexarrayCtors( 'float32' )\n null\n\n See Also\n --------\n arrayCtors, typedarrayCtors, realarrayCtors\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n Returns a list of complex typed array data types.\n\n Returns\n -------\n out: Array\n List of complex typed array data types.\n\n Examples\n --------\n > var out = complexarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, typedarrayDataTypes, realarrayDataTypes, ndarrayDataTypes\n","complexCtors":"\ncomplexCtors( dtype )\n Returns a complex number constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = complexCtors( 'complex128' )\n \n > ctor = complexCtors( 'complex' )\n null\n\n See Also\n --------\n complexarrayCtors\n","complexDataType":"\ncomplexDataType( value )\n Returns the data type of a complex number object.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var v = new Complex128( 1.0, 2.0 );\n > var dt = complexDataType( v )\n 'complex128'\n > dt = complexDataType( 'beep' )\n null\n\n See Also\n --------\n arrayDataType\n","complexDataTypes":"\ncomplexDataTypes()\n Returns a list of complex number data types.\n\n The output array contains the following data types:\n\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n\n Returns\n -------\n out: Array\n List of complex number data types.\n\n Examples\n --------\n > var out = complexDataTypes()\n \n\n See Also\n --------\n complexarrayDataTypes\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1, dtype2] )\n Returns the complex number data type with the smallest size and closest\n \"kind\" to which data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n Data type.\n\n dtype2: string (optional)\n Data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = complexPromotionRules( 'complex128', 'complex64' )\n 'complex128'\n\n See Also\n --------\n arrayPromotionRules, ndarrayPromotionRules\n","compose":"\ncompose( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as an argument\n to the next function. The result of the leftmost function is the result\n of the whole.\n\n Notes:\n\n - Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n - The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x ) {\n ... return 2 * x;\n ... }\n > function b( x ) {\n ... return x + 3;\n ... }\n > function c( x ) {\n ... return x / 5;\n ... }\n > var f = compose( c, b, a );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n composeAsync\n","composeAsync":"\ncomposeAsync( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as the first argument\n of the next function. The result of the leftmost function is the result\n of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a composed function calls the `next` callback with a truthy `error`\n argument, the composite function suspends execution and immediately calls\n the `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = composeAsync( c, b, a );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n compose\n","configdir":"\nconfigdir( [p] )\n Returns a directory for user-specific configuration files.\n\n On Windows platforms, the function first checks for a `LOCALAPPDATA`\n environment variable before checking for an `APPDATA` environment variable.\n This means that machine specific user configuration files have precedence\n over roaming user configuration files.\n\n On non-Windows platforms, if the function is unable to locate the current\n user's `home` directory, the function returns `null`. Similarly, on Windows\n platforms, if the function is unable to locate an application data\n directory, the function also returns `null`.\n\n Parameters\n ----------\n p: string (optional)\n Path to append to a base directory.\n\n Returns\n -------\n out: string|null\n Directory.\n\n Examples\n --------\n > var dir = configdir()\n e.g., '/Users//Library/Preferences'\n > dir = configdir( 'appname/config' )\n e.g., '/Users//Library/Preferences/appname/config'\n\n See Also\n --------\n homedir, tmpdir\n","conj":"\nconj( z )\n Returns the complex conjugate of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex conjugate.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conj( z );\n > v.toString()\n '5 - 3i'\n\n See Also\n --------\n imag, real, reim\n","conjf":"\nconjf( z )\n Returns the complex conjugate of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Complex conjugate.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conjf( z );\n > v.toString()\n '5 - 3i'\n\n See Also\n --------\n conj, imagf, realf, reimf\n","constantcase":"\nconstantcase( str )\n Converts a string to constant case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Constant-cased string.\n\n Examples\n --------\n > var out = constantcase( 'Hello World!' )\n 'HELLO_WORLD'\n > out = constantcase( 'I am a tiny little teapot' )\n 'I_AM_A_TINY_LITTLE_TEAPOT'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","constantFunction":"\nconstantFunction( val )\n Creates a function which always returns the same value.\n\n Notes:\n\n - When provided an object reference, the returned `function` always returns\n the same reference.\n\n Parameters\n ----------\n val: any\n Value to always return.\n\n Returns\n -------\n out: Function\n Constant function.\n\n Examples\n --------\n > var fcn = constantFunction( 3.14 );\n > var v = fcn()\n 3.14\n > v = fcn()\n 3.14\n > v = fcn()\n 3.14\n\n See Also\n --------\n argumentFunction, identity\n","constantStream":"\nconstantStream( value[, options] )\n Returns a readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream( 'beep', opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );\n\n\nconstantStream.objectMode( value[, options] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream\n","constantStream.factory":"\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );","constantStream.objectMode":"\nconstantStream.objectMode( value[, options] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream","constructorName":"\nconstructorName( val )\n Determines the name of a value's constructor.\n\n Parameters\n ----------\n val: any\n Input value.\n\n Returns\n -------\n out: string\n Name of a value's constructor.\n\n Examples\n --------\n > var v = constructorName( 'a' )\n 'String'\n > v = constructorName( {} )\n 'Object'\n > v = constructorName( true )\n 'Boolean'\n\n See Also\n --------\n functionName\n","contains":"\ncontains( val, searchValue[, position] )\n Tests if an array-like value contains a search value.\n\n When `val` is a string, the function checks whether the characters of the\n search string are found in the input string. The search is case-sensitive.\n\n When `val` is an array-like object, the function checks whether the input\n array contains an element strictly equal to the specified search value.\n\n For strings, this function is modeled after `String.prototype.includes`,\n part of the ECMAScript 6 specification. This function is different from a\n call to `String.prototype.includes.call` insofar as type-checking is\n performed for all arguments.\n\n The function does not distinguish between positive and negative zero.\n\n If `position < 0`, the search is performed for the entire input array or\n string.\n\n\n Parameters\n ----------\n val: ArrayLike\n Input value.\n\n searchValue: any\n Value to search for.\n\n position: integer (optional)\n Position at which to start searching for `searchValue`. Default: `0`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input value contains another value.\n\n Examples\n --------\n > var bool = contains( 'Hello World', 'World' )\n true\n > bool = contains( 'Hello World', 'world' )\n false\n > bool = contains( [ 1, 2, 3, 4 ], 2 )\n true\n > bool = contains( [ NaN, 2, 3, 4 ], NaN )\n true\n\n // Supply a position:\n > bool = contains( 'Hello World', 'Hello', 6 )\n false\n > bool = contains( [ true, NaN, false ], true, 1 )\n false\n\n","convertArray":"\nconvertArray( arr, dtype )\n Converts an input array to an array of a different data type.\n\n The function supports the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Array to convert.\n\n dtype: string\n Output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var arr = [ 1.0, 2.0, 3.0, 4.0 ];\n > var out = convertArray( arr, 'float32' )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArraySame\n","convertArraySame":"\nconvertArraySame( x, y )\n Converts an input array to the same data type as a second input array.\n\n The function supports input arrays having the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Array to convert.\n\n y: Array|TypedArray\n Array having desired output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = new Float32Array( 0 );\n > var out = convertArraySame( x, y )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArray\n","convertPath":"\nconvertPath( from, to )\n Converts between POSIX and Windows paths.\n\n Parameters\n ----------\n from: string\n Input path.\n\n to: string\n Output path convention: 'win32', 'mixed', or 'posix'.\n\n Returns\n -------\n out: string\n Converted path.\n\n Examples\n --------\n > var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\n 'c:\\\\foo\\\\bar\\\\beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'mixed' )\n 'c:/foo/bar/beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\n 'C:\\\\\\\\foo\\\\bar\\\\beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\n 'C:/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n\n","copy":"\ncopy( value[, level] )\n Copy or deep clone a value to an arbitrary depth.\n\n The implementation can handle circular references.\n\n If a `Number`, `String`, or `Boolean` object is encountered, the value is\n cloned as a primitive. This behavior is intentional.\n\n For objects, the implementation only copies enumerable keys and their\n associated property descriptors.\n\n The implementation only checks whether basic `Objects`, `Arrays`, and class\n instances are extensible, sealed, and/or frozen.\n\n Functions are not cloned; their reference is copied.\n\n The implementation supports custom error types which are `Error` instances\n (e.g., ES2015 subclasses).\n\n Support for copying class instances is inherently fragile. Any instances\n with privileged access to variables (e.g., within closures) cannot be\n cloned. This stated, basic copying of class instances is supported. Provided\n an environment which supports ES5, the implementation is greedy and performs\n a deep clone of any arbitrary class instance and its properties. The\n implementation assumes that the concept of `level` applies only to the class\n instance reference, but not to its internal state.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n level: integer (optional)\n Copy depth. Default: Infinity.\n\n Returns\n -------\n out: any\n Value copy.\n\n Examples\n --------\n > var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > var out = copy( value )\n [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ]\n > var bool = ( value[ 0 ].c === out[ 0 ].c )\n false\n\n // Set the `level` option to limit the copy depth:\n > value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > out = copy( value, 1 );\n > bool = ( value[ 0 ] === out[ 0 ] )\n true\n > bool = ( value[ 0 ].c === out[ 0 ].c )\n true\n\n\n See Also\n --------\n merge\n","copyBuffer":"\ncopyBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = array2buffer( [ 1, 2, 3, 4 ] );\n > var b2 = copyBuffer( b1 )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n allocUnsafe, Buffer\n","countBy":"\ncountBy( collection, [options,] indicator )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: collection value\n - index: collection index\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = countBy( collection, indicator )\n { 'b': 3, 'other': 1 }\n\n See Also\n --------\n group, groupBy\n","countByAsync":"\ncountByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"even\": 2, \"odd\": 1 }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { \"even\": 2, \"odd\": 2 }\n\n See Also\n --------\n countBy, groupByAsync, tabulateByAsync\n","countByAsync.factory":"\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { \"even\": 2, \"odd\": 2 }\n\n See Also\n --------\n countBy, groupByAsync, tabulateByAsync","currentYear":"\ncurrentYear()\n Returns the current year.\n\n Returns\n -------\n out: integer\n Current year.\n\n Examples\n --------\n > var y = currentYear()\n \n\n","curry":"\ncurry( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curry( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curry( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curry( obj.greet, obj );\n > var str = f( 'Hello' )( 'there' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curryRight, uncurry, uncurryRight\n","curryRight":"\ncurryRight( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n This function applies arguments starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curryRight( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curryRight( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curryRight( obj.greet, obj );\n > var str = f( 'there' )( 'Hello' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curry, uncurry, uncurryRight\n","cwd":"\ncwd()\n Returns the current working directory.\n\n Returns\n -------\n path: string\n Current working directory of the process.\n\n Examples\n --------\n > var dir = cwd()\n '/path/to/current/working/directory'\n\n See Also\n --------\n chdir\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n Returns a list of familiar English words.\n\n Returns\n -------\n out: Array\n List of familiar English words.\n\n Examples\n --------\n > var list = DALE_CHALL_NEW()\n [ 'a', 'able', 'aboard', 'about', 'above', ... ]\n\n References\n ----------\n - Chall, Jeanne Sternlicht, and Edgar Dale. 1995. *Readability revisited:\n the new Dale-Chall readability formula*. Brookline Books.\n .\n\n","datasets":"\ndatasets( name[, options] )\n Returns a dataset.\n\n The function forwards provided options to the dataset interface specified\n by `name`.\n\n Parameters\n ----------\n name: string\n Dataset name.\n\n options: Object (optional)\n Function options.\n\n Returns\n -------\n out: any\n Dataset.\n\n Examples\n --------\n > var out = datasets( 'MONTH_NAMES_EN' )\n [ 'January', 'February', ... ]\n > var opts = { 'data': 'cities' };\n > out = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n [ {...}, {...}, ... ]\n\n","DataView":"\nDataView( buffer[, byteOffset[, byteLength]] )\n Returns a data view representing a provided array buffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer|SharedArrayBuffer\n Array buffer.\n\n byteOffset: integer (optional)\n Offset (in bytes) to the first byte in the array buffer for the new view\n to reference. Default: 0.\n\n byteLength: integer (optional)\n Number of elements in the byte array. If not provided, the view's length\n will equal the buffer's length.\n\n Returns\n -------\n out: DataView\n A data view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n > var dv = new DataView( buf )\n \n\n\nDataView.prototype.buffer\n Read-only property which returns the underyling array buffer.\n\n Examples\n --------\n > var buf1 = new ArrayBuffer( 5 );\n > var dv = new DataView( buf1 );\n > var buf2 = dv.buffer\n \n > var b = ( buf1 === buf2 )\n true\n\n\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf );\n > dv.byteLength\n 5\n\n\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf, 2 );\n > dv.byteLength\n 3\n > dv.byteOffset\n 2\n\n\nTODO: document properties/methods\n\n\n See Also\n --------\n ArrayBuffer, typedarray\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n Read-only property which returns the underyling array buffer.\n\n Examples\n --------\n > var buf1 = new ArrayBuffer( 5 );\n > var dv = new DataView( buf1 );\n > var buf2 = dv.buffer\n \n > var b = ( buf1 === buf2 )\n true","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf );\n > dv.byteLength\n 5","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf, 2 );\n > dv.byteLength\n 3\n > dv.byteOffset\n 2","datespace":"\ndatespace( start, stop[, length][ , options] )\n Generates an array of linearly spaced dates.\n\n Parameters\n ----------\n start: number\n Start time as either a `Date` object, Unix timestamp, JavaScript\n timestamp, or date string.\n\n stop: number\n Stop time as either a `Date` object, Unix timestamp, JavaScript\n timestamp, or date string.\n\n length: integer (optional)\n Length of output array. Default: `100`.\n\n options: Object (optional)\n Options.\n\n options.round: string (optional)\n Specifies how sub-millisecond times should be rounded:\n [ 'floor', 'ceil', 'round' ]. Default: 'floor'.\n\n Returns\n -------\n arr: Array\n Array of dates.\n\n Examples\n --------\n > var stop = '2014-12-02T07:00:54.973Z';\n > var start = new Date( stop ) - 60000;\n > var arr = datespace( start, stop, 6 )\n [...]\n\n // Equivalent of Math.ceil():\n > var opts = { 'round': 'ceil' };\n > arr = datespace( 1417503655000, 1417503655001, 3, opts )\n [...]\n\n See Also\n --------\n linspace, logspace\n","dayOfQuarter":"\ndayOfQuarter( [month[, day, year]] )\n Returns the day of the quarter.\n\n By default, the function returns the day of the quarter for the current date\n (according to local time). To determine the day of the quarter for a\n particular day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the quarter.\n\n Examples\n --------\n > var day = dayOfQuarter()\n \n > day = dayOfQuarter( new Date() )\n \n > day = dayOfQuarter( 12, 31, 2017 )\n 92\n\n // Other ways to supply month:\n > day = dayOfQuarter( 'dec', 31, 2017 )\n 92\n > day = dayOfQuarter( 'december', 31, 2017 )\n 92\n\n See Also\n --------\n dayOfYear\n","dayOfYear":"\ndayOfYear( [month[, day, year]] )\n Returns the day of the year.\n\n By default, the function returns the day of the year for the current date\n (according to local time). To determine the day of the year for a particular\n day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the year.\n\n Examples\n --------\n > var day = dayOfYear()\n \n > day = dayOfYear( new Date() )\n \n > day = dayOfYear( 12, 31, 2016 )\n 366\n\n // Other ways to supply month:\n > day = dayOfYear( 'dec', 31, 2016 )\n 366\n > day = dayOfYear( 'december', 31, 2016 )\n 366\n\n See Also\n --------\n dayOfQuarter\n","daysInMonth":"\ndaysInMonth( [month[, year]] )\n Returns the number of days in a month.\n\n By default, the function returns the number of days in the current month\n of the current year (according to local time). To determine the number of\n days for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Days in a month.\n\n Examples\n --------\n > var num = daysInMonth()\n \n > num = daysInMonth( 2 )\n \n > num = daysInMonth( 2, 2016 )\n 29\n > num = daysInMonth( 2, 2017 )\n 28\n\n // Other ways to supply month:\n > num = daysInMonth( 'feb', 2016 )\n 29\n > num = daysInMonth( 'february', 2016 )\n 29\n\n See Also\n --------\n daysInYear\n","daysInYear":"\ndaysInYear( [value] )\n Returns the number of days in a year according to the Gregorian calendar.\n\n By default, the function returns the number of days in the current year\n (according to local time). To determine the number of days for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of days in a year.\n\n Examples\n --------\n > var num = daysInYear()\n \n > num = daysInYear( 2016 )\n 366\n > num = daysInYear( 2017 )\n 365\n\n See Also\n --------\n daysInMonth\n","ddot":"\nddot( x, y )\n Computes the dot product of two double-precision floating-point vectors.\n\n If provided empty vectors, the function returns `0.0`.\n\n Parameters\n ----------\n x: ndarray\n First input array whose underlying data type is 'float64'.\n\n y: ndarray\n Second input array whose underlying data type is 'float64'.\n\n Returns\n -------\n dot: number\n The dot product.\n\n Examples\n --------\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > ddot( x, y )\n -5.0\n\n See Also\n --------\n base.strided.ddot, gdot, sdot\n","debugSinkStream":"\ndebugSinkStream( [options,] [clbk] )\n Returns a writable stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > var s = debugSinkStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );\n\n\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream, inspectSinkStream\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream, inspectSinkStream","debugStream":"\ndebugStream( [options,] [clbk] )\n Returns a transform stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = debugStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );\n\n\ndebugStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n","debugStream.factory":"\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );","debugStream.objectMode":"\ndebugStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream","decorateAfter":"\ndecorateAfter( fcn, arity, after[, thisArg] )\n Decorates a provided function such that the function's return value is\n provided as an argument to another function.\n\n Decorators are intended to be transparent, meaning that, when interfacing\n with an API, the decorated API should have the same signature (i.e., number\n of parameters) as the decorated function.\n\n Thus, a typical value for `arity` is `fcn.length`. This function does not\n require equality, however, and the `arity` argument is allowed to diverge\n from that of the decorated function. Specifying a differing `arity` does\n *not* affect function evaluation behavior, as the returned function passes\n all provided arguments to the decorated function.\n\n If the `after` function returns `undefined`, the returned decorator returns\n the return value of the decorated function `fcn`; otherwise, the returned\n decorator returns the return value of `after`.\n\n The returned decorator supports an `arity` less than or equal to `10` (i.e.,\n the maximum arity of the returned function is `10`). For an arity greater\n than `10`, the returned function has an arity equal to `0`. While this\n violates strict notions of a decorator, for all practical purposes, this is\n unlikely to be an issue, as the vast majority of functions have fewer than\n `10` parameters and the need for explicitly checking function length is\n relatively uncommon.\n\n Common use cases for decorating a function with additional actions *after*\n invocation include logging, capturing invocation statistics, and validating\n return values.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5\n\n\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n\n Code generation may be problematic in browser contexts enforcing a strict\n content security policy] (CSP). If running in or targeting an environment\n with a CSP, avoid using code generation.\n\n For non-native functions, the function supports returning a decorator whose\n API exactly matches the API of the decorated function, including function\n length and parameter names.\n\n For native functions, due to how native functions serialize to strings, the\n function generates placeholder parameter names, which are unlikely to match\n the canonical parameter names. Using placeholder parameter names ensures\n that the length of the decorator (i.e., number of parameters) matches the\n decorated function and, except in scenarios involving function source code\n inspection, will not affect runtime behavior.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter.factory( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5\n\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n\n Code generation may be problematic in browser contexts enforcing a strict\n content security policy] (CSP). If running in or targeting an environment\n with a CSP, avoid using code generation.\n\n For non-native functions, the function supports returning a decorator whose\n API exactly matches the API of the decorated function, including function\n length and parameter names.\n\n For native functions, due to how native functions serialize to strings, the\n function generates placeholder parameter names, which are unlikely to match\n the canonical parameter names. Using placeholder parameter names ensures\n that the length of the decorator (i.e., number of parameters) matches the\n decorated function and, except in scenarios involving function source code\n inspection, will not affect runtime behavior.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter.factory( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5","deepEqual":"\ndeepEqual( a, b )\n Tests for deep equality between two values.\n\n Parameters\n ----------\n a: any\n First comparison value.\n\n b: any\n Second comparison value.\n\n Returns\n -------\n out: boolean\n Boolean indicating if `a` is deep equal to `b`.\n\n Examples\n --------\n > var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\n true\n\n > bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\n false\n\n > bool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n false\n\n See Also\n --------\n isStrictEqual, isSameValue\n","deepGet":"\ndeepGet( obj, path[, options] )\n Returns a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: any\n Nested property value.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a.b.c' )\n 'd'\n\n // Specify a custom separator via the `sep` option:\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n 'd'\n\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n See Also\n --------\n deepPluck, deepSet\n","deepGet.factory":"\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n See Also\n --------\n deepPluck, deepSet","deepHasOwnProp":"\ndeepHasOwnProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path.\n\n The function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepHasOwnProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet","deepHasProp":"\ndeepHasProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var obj = { 'a': new Foo() };\n > var bool = deepHasProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > bool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasProp.factory":"\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet","deepPluck":"\ndeepPluck( arr, path[, options] )\n Extracts a nested property value from each element of an object array.\n\n If a key path does not exist, the function sets the plucked value as\n `undefined`.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. Default:\n true.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': { 'b': { 'c': 1 } } },\n ... { 'a': { 'b': { 'c': 2 } } }\n ... ];\n > var out = deepPluck( arr, 'a.b.c' )\n [ 1, 2 ]\n > arr = [\n ... { 'a': [ 0, 1, 2 ] },\n ... { 'a': [ 3, 4, 5 ] }\n ... ];\n > out = deepPluck( arr, [ 'a', 1 ] )\n [ 1, 4 ]\n\n See Also\n --------\n deepGet, deepSet\n","deepSet":"\ndeepSet( obj, path, value[, options] )\n Sets a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n value: any\n Value to set.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if the property was successfully set.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepSet( obj, 'a.b.c', 'beep' )\n true\n\n // Specify an alternative separator via the sep option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n // To create a key path which does not exist, set the create option to true:\n > bool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\n > obj\n { 'a': { 'b': { 'c': 'beep' }, 'e': { 'c': 'boop' } } }\n\n\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n See Also\n --------\n deepGet, deepPluck\n","deepSet.factory":"\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n See Also\n --------\n deepGet, deepPluck","defineMemoizedProperty":"\ndefineMemoizedProperty( obj, prop, descriptor )\n Defines a memoized object property.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() {\n ... return 'bar';\n ... };\n > defineMemoizedProperty( obj, 'foo', {\n ... 'configurable': false,\n ... 'enumerable': true,\n ... 'writable': false,\n ... 'value': foo\n ... });\n > obj.foo\n 'bar'\n\n See Also\n --------\n setMemoizedReadOnly, defineProperty\n","defineProperties":"\ndefineProperties( obj, properties )\n Defines (and/or modifies) object properties.\n\n The second argument is an object whose own enumerable property values are\n descriptors for the properties to be defined or modified.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n A property descriptor has the following optional properties:\n\n - configurable: boolean indicating if property descriptor can be changed and\n if the property can be deleted from the provided object. Default: false.\n\n - enumerable: boolean indicating if the property shows up when enumerating\n object properties. Default: false.\n\n - writable: boolean indicating if the value associated with the property can\n be changed with an assignment operator. Default: false.\n\n - value: property value.\n\n - get: function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used as\n the property value. Default: undefined.\n\n - set: function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called with\n one argument (the value being assigned to the property) and with the `this`\n context set to the object through which the property is assigned. Default: undefined.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the properties.\n\n properties: Object\n Object with property descriptors.\n\n Returns\n -------\n obj: Object\n Object on which properties were defined (and/or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperties( obj, {\n ... 'foo': {\n ... 'value': 'bar',\n ... 'writable': false,\n ... 'configurable': false,\n ... 'enumerable': true\n ... },\n ... 'baz': {\n ... 'value': 13\n ... }\n ... });\n > obj.foo\n 'bar'\n > obj.baz\n 13\n\n See Also\n --------\n defineProperty, setReadOnly\n","defineProperty":"\ndefineProperty( obj, prop, descriptor )\n Defines (or modifies) an object property.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: any (optional)\n Property value.\n\n descriptor.get: Function|void (optional)\n Function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used\n as the property value. Default: undefined.\n\n descriptor.set: Function|void (optional)\n Function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called\n with one argument (the value being assigned to the property) and with\n the `this` context set to the object through which the property is\n assigned. Default: undefined.\n\n Returns\n -------\n obj: Object\n Object on which the property was defined (or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperty( obj, 'foo', {\n ... 'value': 'bar',\n ... 'enumerable': true,\n ... 'writable': false\n ... });\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n defineProperties, setReadOnly\n","dirname":"\ndirname( path )\n Returns a directory name.\n\n Parameters\n ----------\n path: string\n Path.\n\n Returns\n -------\n out: string\n Directory name.\n\n Examples\n --------\n > var dir = dirname( './foo/bar/index.js' )\n './foo/bar'\n\n See Also\n --------\n extname\n","dotcase":"\ndotcase( str )\n Converts a string to dot case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Dot-cased string.\n\n Examples\n --------\n > var out = dotcase( 'Hello World!' )\n 'hello.world'\n > out = dotcase( 'beep boop' )\n 'beep.boop'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","DoublyLinkedList":"\nDoublyLinkedList()\n Doubly linked list constructor.\n\n Returns\n -------\n list: Object\n Doubly linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the first list node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node. For its third argument, the\n method accepts a location: 'before' or 'after'. Default: 'after'.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation. For its sole argument, the method accepts a\n direction: 'forward' or 'reverse'. Default: 'forward'.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = DoublyLinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n LinkedList, Stack\n","doUntil":"\ndoUntil( fcn, predicate[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doUntil( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntilAsync, doUntilEach, doWhile, until, whilst\n","doUntilAsync":"\ndoUntilAsync( fcn, predicate, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from one)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is falsy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doUntilAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, untilAsync, whileAsync\n","doUntilEach":"\ndoUntilEach( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doUntilEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, untilEach\n","doUntilEachRight":"\ndoUntilEachRight( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doUntilEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, untilEachRight\n","doWhile":"\ndoWhile( fcn, predicate[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doWhile( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, doWhileEach, until, whilst\n","doWhileAsync":"\ndoWhileAsync( fcn, predicate, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from one)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is truthy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doWhileAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhile, untilAsync, whileAsync\n","doWhileEach":"\ndoWhileEach( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doWhileEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, whileEach\n","doWhileEachRight":"\ndoWhileEachRight( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doWhileEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, whileEachRight\n","dswap":"\ndswap( x, y )\n Interchanges two double-precision floating-point vectors.\n\n Parameters\n ----------\n x: ndarray\n First input array whose underlying data type is 'float64'.\n\n y: ndarray\n Second input array whose underlying data type is 'float64'.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > dswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dswap, gswap, sswap\n","E":"\nE\n Euler's number.\n\n Examples\n --------\n > E\n 2.718281828459045\n\n","EMOJI":"\nEMOJI()\n Returns an emoji database.\n\n Returns\n -------\n out: Array\n Emoji database.\n\n Examples\n --------\n > var data = EMOJI()\n [ {...}, ... ]\n\n See Also\n --------\n EMOJI_CODE_PICTO, EMOJI_PICTO_CODE\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n Returns an object mapping emoji codes to pictographs.\n\n Returns\n -------\n out: Object\n An object mapping emoji codes to pictographs.\n\n Examples\n --------\n > var out = EMOJI_CODE_PICTO()\n\n See Also\n --------\n EMOJI, EMOJI_PICTO_CODE\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n Returns an object mapping emoji pictographs to codes.\n\n Returns\n -------\n out: Object\n An object mapping emoji pictographs to codes.\n\n Examples\n --------\n > var out = EMOJI_PICTO_CODE()\n\n See Also\n --------\n EMOJI, EMOJI_CODE_PICTO\n","emptyStream":"\nemptyStream( [options] )\n Returns an \"empty\" readable stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = emptyStream();\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );\n\n\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n constantStream\n","emptyStream.factory":"\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );","emptyStream.objectMode":"\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n constantStream","endsWith":"\nendsWith( str, search[, len] )\n Tests if a string ends with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n len: integer (optional)\n Substring length. Restricts the search to a substring within the input\n string beginning from the leftmost character. If provided a negative\n value, `len` indicates to ignore the last `len` characters, returning\n the same output as `str.length + len`. Default: `str.length`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string ends with the characters of another\n string.\n\n Examples\n --------\n > var bool = endsWith( 'beep', 'ep' )\n true\n > bool = endsWith( 'Beep', 'op' )\n false\n > bool = endsWith( 'Beep', 'ee', 3 )\n true\n > bool = endsWith( 'Beep', 'ee', -1 )\n true\n > bool = endsWith( 'beep', '' )\n true\n\n See Also\n --------\n startsWith\n","enumerableProperties":"\nenumerableProperties( value )\n Returns an array of an object's own enumerable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = enumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerablePropertiesIn, enumerablePropertySymbols, inheritedEnumerableProperties, objectKeys, nonEnumerableProperties, properties\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = enumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbolsIn, inheritedEnumerableProperties, keysIn, nonEnumerablePropertiesIn, propertiesIn\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value )\n Returns an array of an object's own enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedEnumerablePropertySymbols, objectKeys, nonEnumerablePropertySymbols, propertySymbols\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedEnumerablePropertySymbols, keysIn, nonEnumerablePropertySymbolsIn, propertySymbolsIn\n","ENV":"\nENV\n An object containing the user environment.\n\n Examples\n --------\n > var user = ENV.USER\n \n\n See Also\n --------\n ARGV\n","EPS":"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n\n Examples\n --------\n > EPS\n 2.220446049250313e-16\n\n See Also\n --------\n FLOAT32_EPS\n","error2json":"\nerror2json( error )\n Returns a JSON representation of an error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n The JSON object is guaranteed to have the following properties:\n\n - type: error type.\n - message: error message.\n\n The only standardized cross-platform property is `message`. Depending on the\n platform, the following properties *may* be present:\n\n - name: error name.\n - stack: stack trace.\n - code: error code (Node.js system errors).\n - errno: error code string (Node.js system errors).\n - syscall: string representing the failed system call (Node.js system\n errors).\n\n The function also serializes all enumerable properties.\n\n The implementation supports custom error types and sets the `type` field to\n the closest built-in error type.\n\n Parameters\n ----------\n error: Error\n Error to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var err = new Error( 'beep' );\n > var json = error2json( err )\n \n\n See Also\n --------\n reviveError\n","EULERGAMMA":"\nEULERGAMMA\n The Euler-Mascheroni constant.\n\n Examples\n --------\n > EULERGAMMA\n 0.5772156649015329\n\n","every":"\nevery( collection )\n Tests whether all elements in a collection are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 1, 1, 1, 1, 1 ];\n > var bool = every( arr )\n true\n\n See Also\n --------\n any, everyBy, forEach, none, some\n","everyBy":"\neveryBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyBy( arr, positive )\n true\n\n See Also\n --------\n anyBy, everyByRight, forEach, noneBy, someBy\n","everyByAsync":"\neveryByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync\n","everyByAsync.factory":"\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync","everyByRight":"\neveryByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyByRight( arr, positive )\n true\n\n See Also\n --------\n anyBy, every, everyBy, forEachRight, noneByRight, someByRight\n","everyByRightAsync":"\neveryByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync","evil":"\nevil( str )\n Alias for `eval` global.\n\n A reference to `eval` is treated differently by the compiler. For example,\n when evaluating code containing block-scoped declarations (e.g., `let`,\n `const`, `function`, `class`), the compiler may throw an `error` complaining\n that block-scoped declarations are not yet supported outside of\n `strict mode`. One possible workaround is to include `\"use strict\";` in the\n evaluated code.\n\n Parameters\n ----------\n str: string\n Code to evaluate.\n\n Returns\n -------\n out: any\n Returned value if applicable.\n\n Examples\n --------\n > var v = evil( '5*4*3*2*1' )\n 120\n\n","EXEC_PATH":"\nEXEC_PATH\n Absolute pathname of the executable which started the current Node.js\n process.\n\n Examples\n --------\n > EXEC_PATH\n \n\n","exists":"\nexists( path, clbk )\n Asynchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n clbk: Function\n Callback to invoke after testing for path existence. A callback may\n accept a single argument, a boolean indicating whether a path exists, or\n two arguments, an error argument and a boolean, matching the error-first\n callback convention used in most asynchronous Node.js APIs.\n\n Examples\n --------\n > function done( error, bool ) { console.log( bool ); };\n > exists( './beep/boop', done );\n\n\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n See Also\n --------\n readFile, readDir\n","exists.sync":"\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n See Also\n --------\n readFile, readDir","expandAcronyms":"\nexpandAcronyms( str )\n Expands acronyms in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded acronyms.\n\n Examples\n --------\n > var str = 'LOL, this is fun. I am ROFL.';\n > var out = expandAcronyms( str )\n 'laughing out loud, this is fun. I am rolling on the floor laughing.'\n\n > str = 'brb, I need to check my mail. thx!';\n > out = expandAcronyms( str )\n 'be right back, I need to check my mail. thanks!'\n\n See Also\n --------\n expandContractions\n","expandContractions":"\nexpandContractions( str )\n Expands all contractions to their formal equivalents.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded contractions.\n\n Examples\n --------\n > var str = 'I won\\'t be able to get y\\'all out of this one.';\n > var out = expandContractions( str )\n 'I will not be able to get you all out of this one.'\n\n > str = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\n > out = expandContractions( str )\n 'It ought not to be my fault, because, you know, I did not know'\n\n","extname":"\nextname( filename )\n Returns a filename extension.\n\n Parameters\n ----------\n filename: string\n Filename.\n\n Returns\n -------\n ext: string\n Filename extension.\n\n Examples\n --------\n > var ext = extname( 'index.js' )\n '.js'\n\n See Also\n --------\n dirname\n","FancyArray":"\nFancyArray( dtype, buffer, shape, strides, offset, order[, options] )\n Returns a FancyArray instance.\n\n A FancyArray is an ndarray which supports slicing via indexing expressions.\n\n A FancyArray is an ndarray instance and supports all ndarray options,\n attributes, and methods. A FancyArray can be consumed by any API which\n supports ndarray instances.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on ndarray views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use and\n scripting. For performance critical applications, prefer equivalent\n functional APIs supporting ndarray instances.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n ndarray: FancyArray\n FancyArray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nFancyArray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nFancyArray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nFancyArray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nFancyArray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nFancyArray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nFancyArray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nFancyArray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nFancyArray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","FancyArray.prototype.data":"\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","FancyArray.prototype.length":"\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","FancyArray.prototype.order":"\nFancyArray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray","fastmath.abs":"\nfastmath.abs( x )\n Computes an absolute value.\n\n This implementation is not IEEE 754 compliant. If provided `-0`, the\n function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Absolute value.\n\n Examples\n --------\n > var v = fastmath.abs( -1.0 )\n 1.0\n > v = fastmath.abs( 2.0 )\n 2.0\n > v = fastmath.abs( 0.0 )\n 0.0\n > v = fastmath.abs( -0.0 )\n -0.0\n > v = fastmath.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs\n","fastmath.acosh":"\nfastmath.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n The domain of `x` is restricted to `[1,+infinity)`. If `x < 1`, the function\n will return `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var v = fastmath.acosh( 1.0 )\n 0.0\n > v = fastmath.acosh( 2.0 )\n ~1.317\n > v = fastmath.acosh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.acosh( 1.0e308 )\n Infinity\n\n See Also\n --------\n base.acosh\n","fastmath.ampbm":"\nfastmath.ampbm( x, y )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n\n The algorithm computes only an approximation.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.ampbm( 5.0, 12.0 )\n ~13.514\n\n\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n See Also\n --------\n base.hypot\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n See Also\n --------\n base.hypot","fastmath.asinh":"\nfastmath.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var v = fastmath.asinh( 0.0 )\n 0.0\n > v = fastmath.asinh( 2.0 )\n ~1.444\n > v = fastmath.asinh( -2.0 )\n ~-1.444\n > v = fastmath.asinh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.asinh( 1.0e200 )\n Infinity\n\n // The function underflows for small `x`:\n > v = fastmath.asinh( 1.0e-50 )\n 0.0\n\n See Also\n --------\n base.asinh\n","fastmath.atanh":"\nfastmath.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n The domain of `x` is restricted to `[-1,1]`. If `|x| > 1`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var v = fastmath.atanh( 0.0 )\n 0.0\n > v = fastmath.atanh( 0.9 )\n ~1.472\n > v = fastmath.atanh( 1.0 )\n Infinity\n > v = fastmath.atanh( -1.0 )\n -Infinity\n > v = fastmath.atanh( NaN )\n NaN\n\n // The function underflows for small `x`:\n > v = fastmath.atanh( 1.0e-17 )\n 0.0\n\n See Also\n --------\n base.atanh\n","fastmath.hypot":"\nfastmath.hypot( x, y )\n Computes the hypotenuse.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.hypot( -5.0, 12.0 )\n 13.0\n\n // For a sufficiently large `x` and/or `y`, the function overflows:\n > h = fastmath.hypot( 1.0e154, 1.0e154 )\n Infinity\n\n // For sufficiently small `x` and/or `y`, the function underflows:\n > h = fastmath.hypot( 1e-200, 1.0e-200 )\n 0.0\n\n See Also\n --------\n base.hypot\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n\n This function provides a performance boost when requiring only approximate\n computations for integer arguments.\n\n For high-precision applications, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer binary logarithm (base two).\n\n Examples\n --------\n > var v = fastmath.log2Uint32( 4 >>> 0 )\n 2\n > v = fastmath.log2Uint32( 8 >>> 0 )\n 3\n > v = fastmath.log2Uint32( 9 >>> 0 )\n 3\n\n See Also\n --------\n base.log2\n","fastmath.max":"\nfastmath.max( x, y )\n Returns the maximum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = fastmath.max( 3.14, 4.2 )\n 4.2\n > v = fastmath.max( 3.14, NaN )\n NaN\n > v = fastmath.max( NaN, 3.14 )\n 3.14\n > v = fastmath.max( -0.0, +0.0 )\n +0.0\n > v = fastmath.max( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max\n","fastmath.min":"\nfastmath.min( x, y )\n Returns the minimum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = fastmath.min( 3.14, 4.2 )\n 3.14\n > v = fastmath.min( 3.14, NaN )\n NaN\n > v = fastmath.min( NaN, 3.14 )\n 3.14\n > v = fastmath.min( -0.0, +0.0 )\n +0.0\n > v = fastmath.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.min\n","fastmath.powint":"\nfastmath.powint( x, y )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n\n This function is not recommended for high-precision applications due to\n error accumulation.\n\n If provided a negative exponent, the function first computes the reciprocal\n of the base and then evaluates the exponential function. This can introduce\n significant error.\n\n Parameters\n ----------\n x: number\n Base.\n\n y: integer\n Signed 32-bit integer exponent.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = fastmath.powint( 2.0, 3 )\n 8.0\n > v = fastmath.powint( 3.14, 0 )\n 1.0\n > v = fastmath.powint( 2.0, -2 )\n 0.25\n > v = fastmath.powint( 0.0, 0 )\n 1.0\n > v = fastmath.powint( -3.14, 1 )\n -3.14\n > v = fastmath.powint( NaN, 0 )\n NaN\n\n See Also\n --------\n base.pow\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n\n Prefer hardware `sqrt` over a software implementation.\n\n When using a software `sqrt`, this function provides a performance boost\n when an application requires only approximate computations for integer\n arguments.\n\n For applications requiring high-precision, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer square root.\n\n Examples\n --------\n > var v = fastmath.sqrtUint32( 9 >>> 0 )\n 3\n > v = fastmath.sqrtUint32( 2 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 3 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 0 >>> 0 )\n 0\n\n See Also\n --------\n base.sqrt\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common female first names.\n\n Examples\n --------\n > var list = FEMALE_FIRST_NAMES_EN()\n [ 'Aaren', 'Aarika', 'Abagael', 'Abagail', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. \"Moby Word II.\" .\n\n See Also\n --------\n MALE_FIRST_NAMES_EN\n","FIFO":"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n\n Returns\n -------\n queue: Object\n First-in-first-out queue.\n\n queue.clear: Function\n Clears the queue.\n\n queue.first: Function\n Returns the \"oldest\" queue value (i.e., the value which is \"first-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.iterator: Function\n Returns an iterator for iterating over a queue. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from queue mutation during\n iteration, a returned iterator **always** iterates over a queue\n \"snapshot\", which is defined as the list of queue elements at the time\n of the method's invocation.\n\n queue.last: Function\n Returns the \"newest\" queue value (i.e., the value which is \"last-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.length: integer\n Queue length.\n\n queue.pop: Function\n Removes and returns the current \"first-out\" value from the queue. If the\n queue is empty, the returned value is `undefined`.\n\n queue.push: Function\n Adds a value to the queue.\n\n queue.toArray: Function\n Returns an array of queue values.\n\n queue.toJSON: Function\n Serializes a queue as JSON.\n\n Examples\n --------\n > var q = FIFO();\n > q.push( 'foo' ).push( 'bar' );\n > q.length\n 2\n > q.pop()\n 'foo'\n > q.length\n 1\n > q.pop()\n 'bar'\n > q.length\n 0\n\n See Also\n --------\n Stack\n","filledarray":"\nfilledarray( [dtype] )\n Creates a filled array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarray()\n \n > arr = filledarray( 'float32' )\n \n\n\nfilledarray( value, length[, dtype] )\n Returns a filled array having a specified length.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarray( 1.0, 5 )\n [ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n > arr = filledarray( 1, 5, 'int32' )\n [ 1, 1, 1, 1, 1 ]\n\n\nfilledarray( value, array[, dtype] )\n Creates a filled array from another array (or array-like object).\n\n Parameters\n ----------\n value: any\n Fill value.\n\n array: ArrayLikeObject\n Array from which to generate another array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\n [ 2.0, 2.0, 2.0 ]\n > var arr2 = filledarray( 1.0, arr1, 'float32' )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, iterable[, dtype] )\n Creates a filled array from an iterable.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n iterable: Iterable\n Iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = iterConstant( 3.0, {'iter': 3} );\n > var arr2 = filledarray( 1.0, arr1, 'float32' )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, buffer[, byteOffset[, length]][, dtype] )\n Returns a filled typed array view of an ArrayBuffer.\n\n The 'generic' array data type is *not* supported.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n [ 1.0, 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n filledarrayBy, typedarray\n","filledarrayBy":"\nfilledarrayBy( [dtype] )\n Creates a filled array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarrayBy()\n \n > arr = filledarrayBy( 'float32' )\n \n\n\nfilledarrayBy( length[, dtype], clbk[, thisArg] )\n Returns a filled array according to a provided callback function and having\n a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var arr = filledarrayBy( 5, clbk )\n [ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n > arr = filledarrayBy( 5, 'int32', clbk )\n [ 1, 1, 1, 1, 1 ]\n\n\nfilledarrayBy( array[, dtype], clbk[, thisArg] )\n Creates a filled array from another array (or array-like object) according\n to a provided callback function.\n\n Parameters\n ----------\n array: ArrayLikeObject\n Array from which to generate another array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\n [ 2.0, 2.0, 2.0 ]\n > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( iterable[, dtype], clbk[, thisArg] )\n Creates a filled array from an iterable according to a provided callback\n function.\n\n Parameters\n ----------\n iterable: Iterable\n Iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = iterConstant( 3.0, {'iter': 3} );\n > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( buffer[, byteOffset[, length]][, dtype], clbk[, thisArg] )\n Returns a filled typed array view of an ArrayBuffer according to a provided\n callback function.\n\n The 'generic' array data type is *not* supported.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n filledarray, typedarray\n","filterArguments":"\nfilterArguments( fcn, predicate[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n\n Only those arguments in which the predicate function returns a truthy value\n are applied to a provided function.\n\n The predicate function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > function predicate( v ) { return ( v !== 2 ); };\n > var bar = filterArguments( foo, predicate );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n maskArguments, rejectArguments, reorderArguments, reverseArguments\n","find":"\nfind( arr, [options,] clbk )\n Finds elements in an array-like object that satisfy a test condition.\n\n Parameters\n ----------\n arr: Array|TypedArray|string\n Object from which elements will be tested.\n\n options: Object (optional)\n Options.\n\n options.k: integer (optional)\n Limits the number of returned elements. The sign determines the\n direction in which to search. If set to a negative integer, the function\n searches from last element to first element. Default: arr.length.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'indices'.\n\n clbk: Function\n Function invoked for each array element. If the return value is truthy,\n the value is considered to have satisfied the test condition.\n\n Returns\n -------\n out: Array\n Array of indices, element values, or arrays of index-value pairs.\n\n Examples\n --------\n > var data = [ 30, 20, 50, 60, 10 ];\n > function condition( val ) { return val > 20; };\n > var vals = find( data, condition )\n [ 0, 2, 3 ]\n\n // Limit number of results:\n > data = [ 30, 20, 50, 60, 10 ];\n > var opts = { 'k': 2, 'returns': 'values' };\n > vals = find( data, opts, condition )\n [ 30, 50 ]\n\n // Return both indices and values as index-value pairs:\n > data = [ 30, 20, 50, 60, 10 ];\n > opts = { 'k': -2, 'returns': '*' };\n > vals = find( data, opts, condition )\n [ [ 3, 60 ], [ 2, 50 ] ]\n\n","firstChar":"\nfirstChar( str[, n][, options] )\n Returns the first character(s) of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to return. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = firstChar( 'beep' )\n 'b'\n > out = firstChar( 'Boop', 1 )\n 'B'\n > out = firstChar( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n removeFirst\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n Returns FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n\n Returns\n -------\n out: Array\n FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n\n Examples\n --------\n > var data = FIVETHIRTYEIGHT_FFQ()\n [ {...}, ... ]\n\n References\n ----------\n - Aschwanden, Christie. 2016. \"You Can't Trust What You Read About\n Nutrition.\" .\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n","flattenArray":"\nflattenArray( arr[, options] )\n Flattens an array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > var out = flattenArray( arr )\n [ 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Set the maximum depth:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2 } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > var bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n true\n\n // Deep copy:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2, 'copy': true } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n false\n\n\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: ArrayLike\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n See Also\n --------\n flattenObject\n","flattenArray.factory":"\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: ArrayLike\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n See Also\n --------\n flattenObject","flattenObject":"\nflattenObject( obj[, options] )\n Flattens an object.\n\n Parameters\n ----------\n obj: ObjectLike\n Object to flatten.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n out: ObjectLike\n Flattened object.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flattenObject( obj )\n { 'a.b.c': 'd' }\n\n // Set the `depth` option to flatten to a specified depth:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'depth': 1 } )\n { 'a.b': { 'c': 'd' } }\n > var bool = ( obj.a.b === out[ 'a.b' ] )\n true\n\n // Set the `delimiter` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'delimiter': '-|-' } )\n { 'a-|-b-|-c': 'd' }\n\n // Flatten arrays:\n > obj = { 'a': { 'b': [ 1, 2, 3 ] } };\n > out = flattenObject( obj, { 'flattenArrays': true } )\n { 'a.b.0': 1, 'a.b.1': 2, 'a.b.2': 3 }\n\n\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n See Also\n --------\n flattenArray\n","flattenObject.factory":"\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n See Also\n --------\n flattenArray","flignerTest":"\nflignerTest( ...x[, options] )\n Computes the Fligner-Killeen test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = flignerTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = flignerTest( arr, { 'groups': groups } )\n\n See Also\n --------\n bartlettTest\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n Platform float word order.\n\n Possible values:\n\n - 'little-endian'\n - 'big-endian'\n - 'unknown'\n\n Examples\n --------\n > FLOAT_WORD_ORDER\n \n\n See Also\n --------\n BYTE_ORDER\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_CBRT_EPS\n 0.09921256574801247\n\n See Also\n --------\n FLOAT16_EPS, FLOAT16_SQRT_EPS, FLOAT32_CBRT_EPS, CBRT_EPS\n","FLOAT16_EPS":"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_EPS\n 0.0009765625\n\n See Also\n --------\n FLOAT32_EPS, EPS\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT16_EXPONENT_BIAS\n 15\n\n See Also\n --------\n FLOAT32_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT16_MAX":"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_MAX\n 65504.0\n\n See Also\n --------\n FLOAT32_MAX, FLOAT64_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n\n The maximum safe half-precision floating-point integer is given by\n `2^11 - 1`.\n\n Examples\n --------\n > FLOAT16_MAX_SAFE_INTEGER\n 2047\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n\n The minimum safe half-precision floating-point integer is given by\n `-(2^11 - 1)`.\n\n Examples\n --------\n > FLOAT16_MIN_SAFE_INTEGER\n -2047\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT16_NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_PINF, FLOAT32_NINF, NINF\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_NUM_BYTES\n 2\n\n See Also\n --------\n FLOAT32_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT16_PINF":"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT16_PINF\n Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_PINF, PINF\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n\n The effective number of bits is `10` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT16_PRECISION\n 11\n\n See Also\n --------\n FLOAT32_PRECISION, FLOAT64_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_NORMAL\n 6.103515625e-5\n\n See Also\n --------\n FLOAT16_SMALLEST_SUBNORMAL, FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_SUBNORMAL\n 5.960464477539063e-8\n\n See Also\n --------\n FLOAT16_SMALLEST_NORMAL, FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_SQRT_EPS\n 0.03125\n\n See Also\n --------\n FLOAT16_EPS, FLOAT32_SQRT_EPS, SQRT_EPS\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_CBRT_EPS\n 0.004921566694974899\n\n See Also\n --------\n FLOAT32_EPS, FLOAT32_SQRT_EPS, CBRT_EPS\n","FLOAT32_EPS":"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_EPS\n 1.1920928955078125e-7\n\n See Also\n --------\n EPS\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT32_EXPONENT_BIAS\n 127\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT32_MAX":"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX\n 3.4028234663852886e+38\n\n See Also\n --------\n FLOAT16_MAX, FLOAT64_MAX\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n\n The maximum safe single-precision floating-point integer is given by\n `2^24 - 1`.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_INTEGER\n 16777215\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n\n The minimum safe single-precision floating-point integer is given by\n `-(2^24 - 1)`.\n\n Examples\n --------\n > FLOAT32_MIN_SAFE_INTEGER\n -16777215\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"\nFLOAT32_NAN\n Single-precision floating-point NaN.\n\n Examples\n --------\n > FLOAT32_NAN\n NaN\n\n See Also\n --------\n NAN\n","FLOAT32_NINF":"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT32_NINF\n -Infinity\n\n See Also\n --------\n FLOAT32_PINF, NINF\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_NUM_BYTES\n 4\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT32_PINF":"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT32_PINF\n Infinity\n\n See Also\n --------\n FLOAT32_NINF, PINF\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n\n The effective number of bits is `23` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT32_PRECISION\n 24\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT64_PRECISION\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_NORMAL\n 1.1754943508222875e-38\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_SUBNORMAL\n 1.401298464324817e-45\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_SQRT_EPS\n 0.0003452669770922512\n\n See Also\n --------\n FLOAT32_EPS, SQRT_EPS\n","Float32Array":"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array()\n \n\n\nFloat32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Float32Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'\n\n\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n \n\n\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20\n\n\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5\n\n\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float32Array.from":"\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]","Float32Array.of":"\nFloat32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4","Float32Array.name":"\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n ","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT64_EXPONENT_BIAS\n 1023\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT32_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_EXPONENT_MASK\n 2146435072\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n '01111111111100000000000000000000'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n 1048575\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n '00000000000011111111111111111111'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_EXPONENT_MASK\n","FLOAT64_MAX":"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX\n 1.7976931348623157e+308\n\n See Also\n --------\n FLOAT16_MAX, FLOAT32_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT\n 1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n -1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT\n 308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_LN\n 709.782712893384\n\n See Also\n --------\n FLOAT64_MIN_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_FIBONACCI\n 8944394323791464\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n\n The maximum safe double-precision floating-point integer is given by\n `2^53 - 1`.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_INTEGER\n 9007199254740991\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_LUCAS\n 7639424778862807\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI, FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_FIBONACCI\n 78\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_LUCAS\n 76\n\n See Also\n --------\n FLOAT64_MAX_SAFE_LUCAS, FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT\n -1022\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n -1074\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n -324\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MIN_LN\n -708.3964185322641\n\n See Also\n --------\n FLOAT64_MAX_LN\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n\n The minimum safe double-precision floating-point integer is given by\n `-(2^53 - 1)`.\n\n Examples\n --------\n > FLOAT64_MIN_SAFE_INTEGER\n -9007199254740991\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_NUM_BYTES\n 8\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT32_NUM_BYTES\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n\n The effective number of bits is `52` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT64_PRECISION\n 53\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT32_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_NORMAL\n 2.2250738585072014e-308\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_SUBNORMAL\n 4.940656458412465e-324\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","Float64Array":"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array()\n \n\n\nFloat64Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = new Float64Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'\n\n\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n \n\n\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40\n\n\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5\n\n\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float64Array.from":"\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]","Float64Array.of":"\nFloat64Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8","Float64Array.name":"\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n ","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","forEach":"\nforEach( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEach( arr, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n forEachAsync, forEachRight\n","forEachAsync":"\nforEachAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEach, forEachRightAsync\n","forEachAsync.factory":"\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEach, forEachRightAsync","forEachChar":"\nforEachChar( str, [options,] clbk[, thisArg] )\n Invokes a function for each character in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character\n - index: starting character index\n - str: input string\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters over which to iterate. The following modes are\n supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n clbk: Function\n The function to invoke for each character in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > forEachChar( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n forEach\n","forEachRight":"\nforEachRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEachRight( arr, logger )\n 3: 4\n 2: 3\n 1: 2\n 0: 1\n\n See Also\n --------\n forEach, forEachRightAsync\n","forEachRightAsync":"\nforEachRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEachAsync, forEachRight\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEachAsync, forEachRight","forIn":"\nforIn( obj, fcn[, thisArg] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n\n When invoked, the function is provided three arguments:\n\n - `value`: object property value\n - `key`: object property\n - `obj`: the input object\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > function Foo() { return this; };\n > Foo.prototype.beep = 'boop';\n > var obj = new Foo();\n > forIn( obj, logger )\n beep: boop\n\n See Also\n --------\n forEach, forOwn\n","forOwn":"\nforOwn( obj, fcn[, thisArg] )\n Invokes a function for each own enumerable property of an object.\n\n When invoked, the function is provided three arguments:\n\n - `value`: object property value\n - `key`: object property\n - `obj`: the input object\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n The function determines the list of own enumerable properties *before*\n invoking the provided function. Hence, any modifications made to the input\n object *after* calling this function (such as adding and removing\n properties) will *not* affect the list of visited properties.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > forOwn( obj, logger )\n a: 1\n b: 2\n c: 3\n d: 4\n\n See Also\n --------\n forEach, forIn\n","FOURTH_PI":"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n\n Examples\n --------\n > FOURTH_PI\n 7.85398163397448309616e-1\n\n See Also\n --------\n PI\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n\n Examples\n --------\n > FOURTH_ROOT_EPS\n 0.0001220703125\n\n See Also\n --------\n EPS\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n\n Each array element has the following fields:\n\n - date: collection date (month/day/year; e.g., 01/01/1980).\n - all_workers: wage rates for hourly and non-hourly workers.\n - hourly_workers: wage rates for hourly workers.\n - non_hourly_workers: wage rates for non-hourly workers.\n - less_than_high_school: wage rates for workers with less than a high school\n education.\n - high_school: wage rates for workers with a high school education.\n - some_college: wage rates for workers with some college education.\n - college: wage rates for workers with a college education.\n - construction: wage rates for workers in the construction industry.\n - finance: wage rates for workers in the finance industry.\n - manufacturing: wage rates for workers in the manufacturing industry.\n\n Returns\n -------\n out: Array\n Wage rates.\n\n Examples\n --------\n > var data = FRB_SF_WAGE_RIGIDITY()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Federal Reserve Bank of San Francisco. 2017. \"Wage Rigidity.\" .\n\n","fromCodePoint":"\nfromCodePoint( ...pt )\n Creates a string from a sequence of Unicode code points.\n\n In addition to multiple arguments, the function also supports providing an\n array-like object as a single argument containing a sequence of Unicode code\n points.\n\n Parameters\n ----------\n pt: ...integer\n Sequence of Unicode code points.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = fromCodePoint( 9731 )\n '☃'\n > out = fromCodePoint( [ 9731 ] )\n '☃'\n > out = fromCodePoint( 97, 98, 99 )\n 'abc'\n > out = fromCodePoint( [ 97, 98, 99 ] )\n 'abc'\n\n See Also\n --------\n codePointAt\n","Function":"\nFunction( [...argNames,] body )\n Returns a Function object.\n\n Argument names must be strings corresponding to valid JavaScript parameters\n (i.e., a plain identifier, or, in environments supporting such parameters, a\n rest parameter or destructured parameter, optionally with a default).\n\n Parameters\n ----------\n argNames: ...any (optional)\n Parameter names.\n\n body: string\n Function body.\n\n Returns\n -------\n fcn: Function\n Function object.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f( 1, 2 )\n 3\n\n\nFunction.prototype.apply( thisArg, args )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: Array\n Array of arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.apply( null, [ 1, 2 ] )\n 3\n\nFunction.prototype.call( thisArg, ...args )\n Calls a function with a given `this` value and arguments provided\n individually.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.call( null, 1, 2 )\n 3\n\nFunction.prototype.bind( thisArg, ...args )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n fcn: Function\n Bound function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > var g = f.bind( null, 1 );\n > g( 2 )\n 3\n\nFunction.prototype.toString()\n Returns a string representation of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.toString()\n 'function anonymous( x, y ) { return x + y; }'\n\nFunction.prototype.length\n The number of arguments expected by the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.length\n 2\n\nFunction.prototype.name\n The name of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name\n 'anonymous'\n\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name = 'add';\n > f.name\n 'add'\n\nFunction.prototype.prototype\n The prototype of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.prototype\n {}\n\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg, args )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: Array\n Array of arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.apply( null, [ 1, 2 ] )\n 3","Function.prototype.call":"\nFunction.prototype.call( thisArg, ...args )\n Calls a function with a given `this` value and arguments provided\n individually.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.call( null, 1, 2 )\n 3","Function.prototype.bind":"\nFunction.prototype.bind( thisArg, ...args )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n fcn: Function\n Bound function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > var g = f.bind( null, 1 );\n > g( 2 )\n 3","Function.prototype.toString":"\nFunction.prototype.toString()\n Returns a string representation of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.toString()\n 'function anonymous( x, y ) { return x + y; }'","Function.prototype.length":"\nFunction.prototype.length\n The number of arguments expected by the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.length\n 2","Function.prototype.name":"\nFunction.prototype.name\n The name of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name\n 'anonymous'\n\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name = 'add';\n > f.name\n 'add'","Function.prototype.prototype":"\nFunction.prototype.prototype\n The prototype of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.prototype\n {}","function2string":"\nfunction2string( fcn )\n Returns a string representing the source code of a provided function.\n\n If called on built-in functions, functions created by `Function#bind()`, or\n other non-JavaScript functions, the function returns a \"native\" function\n string similar to the following:\n\n \"function foo() { [native code] }\"\n\n For intrinsic object methods and functions, `foo` is the initial name of the\n function.\n\n If called on a function created by the `Function` constructor, the function\n returns the source code of a synthesized function declaration having the\n name \"anonymous\" and using the provided parameters and function body.\n\n Starting in ES2018, the ECMAScript specification requires that the returned\n string contain the exact same source code as it was declared, including any\n whitespace and/or comments. If the host is unable to access the source code,\n the specification requires that the returned string be the native function\n string.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n String representing the function's source code.\n\n Examples\n --------\n > function2string( base.erf )\n \n\n See Also\n --------\n Function\n","functionName":"\nfunctionName( fcn )\n Returns the name of a function.\n\n If provided an anonymous function, the function returns an empty `string` or\n the string `\"anonymous\"`.\n\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n Function name.\n\n Examples\n --------\n > var v = functionName( String )\n 'String'\n > v = functionName( function foo(){} )\n 'foo'\n > v = functionName( function(){} )\n '' || 'anonymous'\n\n See Also\n --------\n constructorName\n","functionSequence":"\nfunctionSequence( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as an argument to the next function. The result of the\n rightmost function is the result of the whole.\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x ) { return 2 * x; };\n > function b( x ) { return x + 3; };\n > function c( x ) { return x / 5; };\n > var f = functionSequence( a, b, c );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n compose, functionSequenceAsync\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as the first argument of the next function. The result of\n the rightmost function is the result of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the pipeline function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = functionSequenceAsync( a, b, c );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n composeAsync, functionSequence\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n\n Examples\n --------\n > GAMMA_LANCZOS_G\n 10.900511\n\n","gdot":"\ngdot( x, y )\n Computes the dot product of two vectors.\n\n In general, for best performance, especially for large vectors, provide\n 1-dimensional ndarrays whose underlying data type is either 'float64' or\n 'float32'.\n\n If provided empty vectors, the function returns `0.0`.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n First input array.\n\n y: ndarray|ArrayLikeObject\n Second input array.\n\n Returns\n -------\n dot: number\n The dot product.\n\n Examples\n --------\n // Using ndarrays...\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > gdot( x, y )\n -5.0\n\n // Using array-like objects...\n > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > gdot( x, y )\n -5.0\n\n See Also\n --------\n base.strided.gdot, ddot, sdot\n","getegid":"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n\n The function only returns an effective group identity on POSIX platforms.\n For all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric group identity.\n\n Examples\n --------\n > var gid = getegid()\n\n See Also\n --------\n geteuid, getgid, getuid\n","geteuid":"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n\n The function only returns an effective user identity on POSIX platforms. For\n all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric user identity.\n\n Examples\n --------\n > var uid = geteuid()\n\n See Also\n --------\n getegid, getgid, getuid\n","getgid":"\ngetgid()\n Returns the numeric group identity of the calling process.\n\n The function only returns a group identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric group identity.\n\n Examples\n --------\n > var gid = getgid()\n\n See Also\n --------\n getegid, geteuid, getuid\n","getGlobal":"\ngetGlobal( [codegen] )\n Returns the global object.\n\n Parameters\n ----------\n codegen: boolean (optional)\n Boolean indicating whether to use code generation to resolve the global\n object. Code generation is the *most* reliable means for resolving the\n global object; however, using code generation may violate content\n security policies (CSPs). Default: false.\n\n Returns\n -------\n global: Object\n Global object.\n\n Examples\n --------\n > var g = getGlobal()\n {...}\n\n","getPrototypeOf":"\ngetPrototypeOf( value )\n Returns the prototype of a provided object.\n\n In contrast to the native `Object.getPrototypeOf`, this function does not\n throw when provided `null` or `undefined`. Instead, similar to when provided\n any value with *no* inherited properties, the function returns `null`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object|null\n Prototype.\n\n Examples\n --------\n > var proto = getPrototypeOf( {} )\n {}\n\n See Also\n --------\n isPrototypeOf\n","getuid":"\ngetuid()\n Returns the numeric user identity of the calling process.\n\n The function only returns a user identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric user identity.\n\n Examples\n --------\n > var uid = getuid()\n\n See Also\n --------\n getegid, geteuid, getgid\n","GLAISHER":"\nGLAISHER\n Glaisher-Kinkelin constant.\n\n Examples\n --------\n > GLAISHER\n 1.2824271291006226\n\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over each grapheme cluster in a string.\n\n When invoked, an input function is provided three arguments:\n\n - value: grapheme cluster\n - index: iterated value index\n - src: source string\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke a string's `@@iterator` method, regardless of whether this method is\n defined. To convert a string to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: string\n String from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = graphemeClusters2iterator( '🌷🍕' );\n > var v = it.next().value\n '🌷'\n > v = it.next().value\n '🍕'\n > var bool = it.next().done\n true\n\n See Also\n --------\n array2iterator, graphemeClusters2iteratorRight\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over each grapheme\n cluster in a string.\n\n When invoked, an input function is provided three arguments:\n\n - value: grapheme cluster\n - index: iterated value index\n - src: source string\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke a string's `@@iterator` method, regardless of whether this method is\n defined. To convert a string to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: string\n String from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = graphemeClusters2iteratorRight( '🌷🍕' );\n > var v = it.next().value\n '🍕'\n > v = it.next().value\n '🌷'\n > var bool = it.next().done\n true\n\n See Also\n --------\n array2iteratorRight, graphemeClusters2iterator\n","group":"\ngroup( collection, [options,] groups )\n Groups values as arrays associated with distinct keys.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n groups: Array|TypedArray|Object\n A collection defining which group an element in the input collection\n belongs to. Each value in `groups` should resolve to a value which can\n be serialized as an object key. If provided an object, the object must\n be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var groups = [ 'b', 'b', 'f', 'b' ];\n > var out = group( collection, groups )\n { 'b': [ 'beep', 'boop', 'bar' ], 'f': [ 'foo' ] }\n > groups = [ 1, 1, 2, 1 ];\n > out = group( collection, groups )\n { '1': [ 'beep', 'boop', 'bar' ], '2': [ 'foo' ] }\n\n // Output group results as indices:\n > groups = [ 'b', 'b', 'f', 'b' ];\n > var opts = { 'returns': 'indices' };\n > out = group( collection, opts, groups )\n { 'b': [ 0, 1, 3 ], 'f': [ 2 ] }\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = group( collection, opts, groups )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'f': [ [2, 'foo'] ] }\n\n See Also\n --------\n bifurcate, countBy, groupBy\n","groupBy":"\ngroupBy( collection, [options,] indicator )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = groupBy( collection, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ 0, 1, 3 ], 'other': [ 2 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'other': [ [2, 'foo' ] ] }\n\n See Also\n --------\n bifurcateBy, countBy, group\n","groupByAsync":"\ngroupByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 1000, 3000 ], \"false\": [ 2500 ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 2, 0 ], \"false\": [ 1 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ [ 2, 1000 ], [ 0, 3000 ] ], \"false\": [ [ 1, 2500 ] ] }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n See Also\n --------\n bifurcateByAsync, countByAsync, groupBy\n","groupByAsync.factory":"\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n See Also\n --------\n bifurcateByAsync, countByAsync, groupBy","groupIn":"\ngroupIn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object with no prototype, the function returns an empty\n object.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > var out = groupIn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateIn, groupBy, groupOwn\n","groupOwn":"\ngroupOwn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object, the function returns an empty object.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = groupOwn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateOwn, group, groupBy\n","gswap":"\ngswap( x, y )\n Interchanges two vectors.\n\n In general, for best performance, especially for large vectors, provide\n 1-dimensional ndarrays whose underlying data type is either 'float64' or\n 'float32'.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n First input array.\n\n y: ndarray|ArrayLikeObject\n Second input array.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n // Using ndarrays...\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > gswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n // Using array-like objects...\n > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > gswap( x, y );\n > x\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gswap, dswap, sswap\n","HALF_LN2":"\nHALF_LN2\n One half times the natural logarithm of `2`.\n\n Examples\n --------\n > HALF_LN2\n 3.46573590279972654709e-01\n\n See Also\n --------\n LN2\n","HALF_PI":"\nHALF_PI\n One half times the mathematical constant `π`.\n\n Examples\n --------\n > HALF_PI\n 1.5707963267948966\n\n See Also\n --------\n PI\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 14 attributes:\n\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n - medv: median value of owner-occupied homes in $1000's\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n Additionally, as documented by Gilley and Pace (1996), the dataset contains\n eight miscoded median values.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES_CORRECTED, PACE_BOSTON_HOUSE_PRICES\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 15 attributes:\n\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n - medv: median value of owner-occupied homes in $1000's\n - cmedv: corrected median value of owner-occupied homes in $1000's\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, PACE_BOSTON_HOUSE_PRICES\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `ArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasArrayBufferSupport()\n \n\n See Also\n --------\n hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasSharedArrayBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `async`/`await` support.\n\n Examples\n --------\n > var bool = hasAsyncAwaitSupport()\n \n\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.asyncIterator`\n support.\n\n Examples\n --------\n > var bool = hasAsyncIteratorSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport, hasSymbolSupport\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n Tests for native `BigInt64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `BigInt64Array` support.\n\n Examples\n --------\n > var bool = hasBigInt64ArraySupport()\n \n\n See Also\n --------\n hasBigIntSupport, hasBigUint64ArraySupport\n","hasBigIntSupport":"\nhasBigIntSupport()\n Tests for native `BigInt` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `BigInt` support.\n\n Examples\n --------\n > var bool = hasBigIntSupport()\n \n\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n Tests for native `BigUint64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `BigUint64Array` support.\n\n Examples\n --------\n > var bool = hasBigUint64ArraySupport()\n \n\n See Also\n --------\n hasBigIntSupport, hasBigInt64ArraySupport\n","hasClassSupport":"\nhasClassSupport()\n Tests for native `class` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `class` support.\n\n Examples\n --------\n > var bool = hasClassSupport()\n \n\n","hasDataViewSupport":"\nhasDataViewSupport()\n Tests for native `DataView` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `DataView` support.\n\n Examples\n --------\n > var bool = hasDataViewSupport()\n \n\n See Also\n --------\n hasArrayBufferSupport\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperties`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertiesSupport()\n \n\n See Also\n --------\n hasDefinePropertySupport\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperty`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertySupport()\n \n\n See Also\n --------\n hasDefinePropertiesSupport\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float32Array` support.\n\n Examples\n --------\n > var bool = hasFloat32ArraySupport()\n \n\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float64Array` support.\n\n Examples\n --------\n > var bool = hasFloat64ArraySupport()\n \n\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n Tests for native function `name` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has function `name` support.\n\n Examples\n --------\n > var bool = hasFunctionNameSupport()\n \n\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n Tests whether an environment supports native generator functions.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment support generator functions.\n\n Examples\n --------\n > var bool = hasGeneratorSupport()\n \n\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n Tests for `globalThis` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `globalThis` support.\n\n Examples\n --------\n > var bool = hasGlobalThisSupport()\n \n\n See Also\n --------\n getGlobal\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int8Array` support.\n\n Examples\n --------\n > var bool = hasInt8ArraySupport()\n \n\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int16Array` support.\n\n Examples\n --------\n > var bool = hasInt16ArraySupport()\n \n\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int32Array` support.\n\n Examples\n --------\n > var bool = hasInt32ArraySupport()\n \n\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.iterator`\n support.\n\n Examples\n --------\n > var bool = hasIteratorSymbolSupport()\n \n\n See Also\n --------\n hasAsyncIteratorSymbolSupport, hasSymbolSupport\n","hasMapSupport":"\nhasMapSupport()\n Tests for native `Map` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Map` support.\n\n Examples\n --------\n > var bool = hasMapSupport()\n \n\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Buffer` support.\n\n Examples\n --------\n > var bool = hasNodeBufferSupport()\n \n\n","hasOwnProp":"\nhasOwnProp( value, property )\n Tests if an object has a specified property.\n\n In contrast to the native `Object.prototype.hasOwnProperty`, this function\n does not throw when provided `null` or `undefined`. Instead, the function\n returns `false`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasOwnProp( beep, 'boop' )\n true\n > bool = hasOwnProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp\n","hasProp":"\nhasProp( value, property )\n Tests if an object has a specified property, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasProp( beep, 'boop' )\n true\n > bool = hasProp( beep, 'toString' )\n true\n > bool = hasProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp\n","hasProxySupport":"\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Proxy` support.\n\n Examples\n --------\n > var bool = hasProxySupport()\n \n\n","hasSetSupport":"\nhasSetSupport()\n Tests for native `Set` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Set` support.\n\n Examples\n --------\n > var bool = hasSetSupport()\n \n\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `SharedArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasSharedArrayBufferSupport()\n \n\n See Also\n --------\n hasArrayBufferSupport, hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasSymbolSupport":"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol` support.\n\n Examples\n --------\n > var bool = hasSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n Tests for native `toStringTag` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `toStringTag` support.\n\n Examples\n --------\n > var bool = hasToStringTagSupport()\n \n\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8Array` support.\n\n Examples\n --------\n > var bool = hasUint8ArraySupport()\n \n\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8ClampedArray` support.\n\n Examples\n --------\n > var bool = hasUint8ClampedArraySupport()\n \n\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n Tests for native `Uint16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint16Array` support.\n\n Examples\n --------\n > var bool = hasUint16ArraySupport()\n \n\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n Tests for native `Uint32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint32Array` support.\n\n Examples\n --------\n > var bool = hasUint32ArraySupport()\n \n\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str, pos )\n Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n\n Parameters\n ----------\n str: string\n Input string.\n\n pos: integer\n Position.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether surrogate pair exists at specified position.\n\n Examples\n --------\n > var out = hasUTF16SurrogatePairAt( '🌷', 0 )\n true\n > out = hasUTF16SurrogatePairAt( '🌷', 1 )\n false\n\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakMap` support.\n\n Examples\n --------\n > var bool = hasWeakMapSupport()\n \n\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakSet` support.\n\n Examples\n --------\n > var bool = hasWeakSetSupport()\n \n\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native WebAssembly support.\n\n Examples\n --------\n > var bool = hasWebAssemblySupport()\n \n\n","headercase":"\nheadercase( str )\n Converts a string to HTTP header case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n HTTP header-cased string.\n\n Examples\n --------\n > var out = headercase( 'Hello World!' )\n 'Hello-World'\n > out = headercase( 'beep boop' )\n 'Beep-Boop'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n\n This dataset is a classic dataset commonly used in examples demonstrating\n outlier detection.\n\n Returns\n -------\n out: Array\n Observations.\n\n Examples\n --------\n > var d = HERNDON_VENUS_SEMIDIAMETERS()\n [ -0.30, -0.44, ..., 0.39, 0.10 ]\n\n References\n ----------\n - Chauvenet, William. 1868. _A Manual of Spherical and Practical Astronomy_.\n 5th ed. Vol. 5. London, England: Trübner & Co.\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n - Tietjen, Gary L., and Roger H. Moore. 1972. \"Some Grubbs-Type Statistics\n for the Detection of Several Outliers.\" _Technometrics_ 14 (3). Taylor &\n Francis: 583–97. doi:10.1080/00401706.1972.10488948.\n\n","homedir":"\nhomedir()\n Returns the current user's home directory.\n\n If unable to locate a home directory, the function returns `null`.\n\n Returns\n -------\n out: string|null\n Home directory.\n\n Examples\n --------\n > var home = homedir()\n e.g., '/Users/'\n\n See Also\n --------\n configdir, tmpdir\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n Number of hours in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var hrs = days * HOURS_IN_DAY\n 75.36\n\n See Also\n --------\n HOURS_IN_WEEK\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n Number of hours in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var hrs = wks * HOURS_IN_WEEK\n 527.52\n\n See Also\n --------\n HOURS_IN_DAY\n","hoursInMonth":"\nhoursInMonth( [month[, year]] )\n Returns the number of hours in a month.\n\n By default, the function returns the number of hours in the current month of\n the current year (according to local time). To determine the number of hours\n for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Hours in a month.\n\n Examples\n --------\n > var num = hoursInMonth()\n \n > num = hoursInMonth( 2 )\n \n > num = hoursInMonth( 2, 2016 )\n 696\n > num = hoursInMonth( 2, 2017 )\n 672\n\n // Other ways to supply month:\n > num = hoursInMonth( 'feb', 2016 )\n 696\n > num = hoursInMonth( 'february', 2016 )\n 696\n\n See Also\n --------\n hoursInYear\n","hoursInYear":"\nhoursInYear( [value] )\n Returns the number of hours in a year according to the Gregorian calendar.\n\n By default, the function returns the number of hours in the current year\n (according to local time). To determine the number of hours for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of hours in a year.\n\n Examples\n --------\n > var num = hoursInYear()\n \n > num = hoursInYear( 2016 )\n 8784\n > num = hoursInYear( 2017 )\n 8760\n\n See Also\n --------\n hoursInMonth\n","httpServer":"\nhttpServer( [options,] [requestListener] )\n Returns a function to create an HTTP server.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.port: integer (optional)\n Server port. Default: `0` (i.e., randomly assigned).\n\n options.maxport: integer (optional)\n Max server port when port hunting. Default: `maxport = port`.\n\n options.hostname: string (optional)\n Server hostname.\n\n options.address: string (optional)\n Server address. Default: `'127.0.0.1'`.\n\n requestListener: Function (optional)\n Request callback.\n\n Returns\n -------\n createServer: Function\n Function to create an HTTP server.\n\n Examples\n --------\n // Basic usage:\n > var createServer = httpServer()\n \n\n // Provide a request callback:\n > function onRequest( request, response ) {\n ... console.log( request.url );\n ... response.end( 'OK' );\n ... };\n > createServer = httpServer( onRequest )\n \n\n // Specify a specific port:\n > var opts = { 'port': 7331 };\n > createServer = httpServer( opts )\n \n\n\ncreateServer( done )\n Creates an HTTP server.\n\n Parameters\n ----------\n done: Function\n Callback to invoke after creating a server.\n\n Examples\n --------\n > function done( error, server ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Success!' );\n ... server.close();\n ... };\n > var createServer = httpServer();\n > createServer( done );\n\n","identity":"\nidentity( x )\n Identity function.\n\n Parameters\n ----------\n x: any\n Input value.\n\n Returns\n -------\n out: any\n Input value.\n\n Examples\n --------\n > var v = identity( 3.14 )\n 3.14\n\n See Also\n --------\n constantFunction\n","ifelse":"\nifelse( bool, x, y )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n Returns\n -------\n z: any\n Either `x` or `y`.\n\n Examples\n --------\n > var z = ifelse( true, 1.0, -1.0 )\n 1.0\n > z = ifelse( false, 1.0, -1.0 )\n -1.0\n\n See Also\n --------\n ifelseAsync, ifthen\n","ifelseAsync":"\nifelseAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n\n A predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate completion\n\n The callback function accepts two arguments:\n\n - error: error object\n - bool: condition used to determine whether to invoke `x` or `y`\n\n The `done` callback is invoked upon function completion and is provided at\n most two arguments:\n\n - error: error object\n - result: either `x` or `y`\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, true );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifelseAsync( predicate, 'beep', 'boop', done )\n 'beep'\n\n See Also\n --------\n ifthenAsync, ifelse\n","ifthen":"\nifthen( bool, x, y )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n Returns\n -------\n z: any\n Return value of either `x` or `y`.\n\n Examples\n --------\n > function x() { return 1.0; };\n > function y() { return -1.0; };\n > var z = ifthen( true, x, y )\n 1.0\n > z = ifthen( false, x, y )\n -1.0\n\n See Also\n --------\n ifthenAsync, ifelse\n","ifthenAsync":"\nifthenAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n\n The predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate function completion\n\n The predicate function callback accepts two arguments:\n\n - error: error object\n - bool: condition used to determine whether to invoke `x` or `y`\n\n Both `x` and `y` are provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the `done` callback is invoked with only an\n error argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, false );\n ... }\n ... };\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'beep' );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifthenAsync( predicate, x, y, done )\n 'boop'\n\n See Also\n --------\n ifelseAsync, ifthen\n","imag":"\nimag( z )\n Returns the imaginary component of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var im = imag( z )\n 3.0\n\n See Also\n --------\n real, reim\n","imagf":"\nimagf( z )\n Returns the imaginary component of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var im = imagf( z )\n 3.0\n\n See Also\n --------\n imag, realf, reimf\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ACANTHUS_MOLLIS()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Acanthus mollis*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ALLIUM_OREOPHILUM\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_AIRPLANE_FROM_ABOVE()\n \n\n References\n ----------\n - Azari, Fédèle. 1929. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium ostrowskianum*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ALLIUM_OREOPHILUM()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Allium ostrowskianum*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ACANTHUS_MOLLIS\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_BLACK_CANYON()\n \n\n References\n ----------\n - O'Sullivan, Timothy H. 1871. *Black Cañon, Colorado River, From Camp 8,\n Looking Above*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_DUST_BOWL_HOME()\n \n\n References\n ----------\n - Lange, Dorothea. 1940. *Abandoned Dust Bowl Home*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n \n\n References\n ----------\n - Braun, Adolphe. 1870. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_HOUSE_CAT()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_NUDE_MALE\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_NUDE_MALE()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_HOUSE_CAT\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_MARCH_PASTORAL()\n \n\n References\n ----------\n - Emerson, Peter Henry. 1888. *A March Pastoral*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_NAGASAKI_BOATS()\n \n\n References\n ----------\n - Beato, Felice. 1865. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","incrapcorr":"\nincrapcorr( [mx, my] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrapcorr();\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator()\n ~1.0\n\n See Also\n --------\n incrmapcorr, incrpcorr, incrpcorr2\n","incrBinaryClassification":"\nincrBinaryClassification( N[, options] )\n Returns an accumulator function which incrementally performs binary\n classification using stochastic gradient descent (SGD).\n\n If provided a feature vector and response value, the accumulator function\n updates a binary classification model and returns updated model\n coefficients.\n\n If not provided a feature vector and response value, the accumulator\n function returns the current model coefficients.\n\n Stochastic gradient descent is sensitive to the scaling of the features. One\n is advised to either scale each feature to `[0,1]` or `[-1,1]` or to\n transform the features into z-scores with zero mean and unit variance. One\n should keep in mind that the same scaling has to be applied to training data\n in order to obtain accurate predictions.\n\n In general, the more data provided to an accumulator, the more reliable the\n model predictions.\n\n Parameters\n ----------\n N: integer\n Number of features.\n\n options: Object (optional)\n Function options.\n\n options.intercept: boolean (optional)\n Boolean indicating whether to include an intercept. Default: true.\n\n options.lambda: number (optional)\n Regularization parameter. Default: 1.0e-4.\n\n options.learningRate: ArrayLike (optional)\n Learning rate function and associated (optional) parameters. The first\n array element specifies the learning rate function and must be one of\n the following:\n\n - ['constant', ...]: constant learning rate function. To set the\n learning rate, provide a second array element. By default, when the\n learn rate function is 'constant', the learning rate is set to 0.02.\n\n - ['basic']: basic learning rate function according to the formula\n `10/(10+t)` where `t` is the current iteration.\n\n - ['invscaling', ...]: inverse scaling learning rate function according\n to the formula `eta0/pow(t, power_t)` where `eta0` is the initial\n learning rate and `power_t` is the exponent controlling how quickly the\n learning rate decreases. To set the initial learning rate, provide a\n second array element. By default, the initial learning rate is 0.02. To\n set the exponent, provide a third array element. By default, the\n exponent is 0.5.\n\n - ['pegasos']: Pegasos learning rate function according to the formula\n `1/(lambda*t)` where `t` is the current iteration and `lambda` is the\n regularization parameter.\n\n Default: ['basic'].\n\n options.loss: string (optional)\n Loss function. Must be one of the following:\n\n - hinge: hinge loss function. Corresponds to a soft-margin linear\n Support Vector Machine (SVM), which can handle non-linearly separable\n data.\n\n - log: logistic loss function. Corresponds to Logistic Regression.\n\n - modifiedHuber: Huber loss function variant for classification.\n\n - perceptron: hinge loss function without a margin. Corresponds to the\n original Perceptron by Rosenblatt.\n\n - squaredHinge: squared hinge loss function SVM (L2-SVM).\n\n Default: 'log'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts response values for one ore more observation vectors. Provide a\n second argument to specify the prediction type. Must be one of the\n following: 'label', 'probability', or 'linear'. Default: 'label'.\n\n Note that the probability prediction type is only compatible with 'log'\n and 'modifiedHuber' loss functions.\n\n Examples\n --------\n // Create an accumulator:\n > var opts = {};\n > opts.intercept = true;\n > opts.lambda = 1.0e-5;\n > var acc = incrBinaryClassification( 3, opts );\n\n // Update the model:\n > var buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\n > var x = array( buf );\n > var coefs = acc( x, 1 )\n \n\n // Create a new observation vector:\n > buf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\n > x = array( buf );\n\n // Predict the response value:\n > var yhat = acc.predict( x )\n \n\n See Also\n --------\n incrSGDRegression\n","incrcount":"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n See Also\n --------\n incrmean, incrsum, incrsummary\n","incrcovariance":"\nincrcovariance( [mx, my] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n\n If provided values, the accumulator function returns an updated unbiased\n sample covariance. If not provided values, the accumulator function returns\n the current unbiased sample covariance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovariance();\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator()\n ~-7.49\n\n See Also\n --------\n incrmcovariance, incrpcorr, incrvariance\n","incrcovmat":"\nincrcovmat( out[, means] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n unbiased sample covariance matrix. If not provided a data vector, the\n accumulator function returns the current unbiased sample covariance matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the covariance matrix or a square 2-dimensional ndarray for\n storing the covariance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovariance, incrpcorrmat\n","incrcv":"\nincrcv( [mean] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcv();\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator()\n ~0.47\n\n See Also\n --------\n incrmean, incrmcv, incrstdev, incrvmr\n","increwmean":"\nincrewmean( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwmean( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -1.5\n > v = accumulator()\n -1.5\n\n See Also\n --------\n increwvariance, incrmean, incrmmean, incrwmean\n","increwstdev":"\nincrewstdev( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n\n If provided a value, the accumulator function returns an updated standard\n deviation. If not provided a value, the accumulator function returns the\n current standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwstdev( 0.5 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n 3.5\n > s = accumulator()\n 3.5\n\n See Also\n --------\n increwvariance, incrmstdev, incrstdev\n","increwvariance":"\nincrewvariance( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n\n If provided a value, the accumulator function returns an updated variance.\n If not provided a value, the accumulator function returns the current\n variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwvariance( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 0.0\n > v = accumulator( -5.0 )\n 12.25\n > v = accumulator()\n 12.25\n\n See Also\n --------\n increwmean, increwstdev, incrvariance, incrmvariance\n","incrgmean":"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n\n If provided a value, the accumulator function returns an updated geometric\n mean. If not provided a value, the accumulator function returns the current\n geometric mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n If provided a negative value, the accumulated value is `NaN` for all future\n invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrgmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator()\n ~3.16\n\n See Also\n --------\n incrhmean, incrmean, incrmgmean, incrsummary\n","incrgrubbs":"\nincrgrubbs( [options] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the test statistic is `NaN` for all future invocations.\n\n The accumulator must be provided *at least* three data points before\n performing Grubbs' test. Until at least three data points are provided, the\n accumulator returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n options.init: integer (optional)\n Number of data points the accumulator should use to compute initial\n statistics *before* testing for an outlier. Until the accumulator is\n provided the number of data points specified by this option, the\n accumulator returns `null`. Default: 100.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrgrubbs();\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrmgrubbs\n","incrhmean":"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n\n If provided a value, the accumulator function returns an updated harmonic\n mean. If not provided a value, the accumulator function returns the current\n harmonic mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrhmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator()\n ~2.86\n\n See Also\n --------\n incrgmean, incrmean, incrmhmean, incrsummary\n","incrkmeans":"\nincrkmeans( k[, ndims][, options] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n\n If not provided initial centroids, the accumulator caches data vectors for\n subsequent centroid initialization. Until an accumulator computes initial\n centroids, an accumulator returns `null`.\n\n Once an accumulator has initial centroids (either provided or computed), if\n provided a data vector, the accumulator function returns updated cluster\n results. If not provided a data vector, the accumulator function returns the\n current cluster results.\n\n Cluster results are comprised of the following:\n\n - centroids: a `k x ndims` matrix containing centroid locations. Each\n centroid is the component-wise mean of the data points assigned to a\n centroid's corresponding cluster.\n - stats: a `k x 4` matrix containing cluster statistics.\n\n Cluster statistics consists of the following columns:\n\n - 0: number of data points assigned to a cluster.\n - 1: total within-cluster sum of squared distances.\n - 2: arithmetic mean of squared distances.\n - 3: corrected sample standard deviation of squared distances.\n\n Because an accumulator incrementally partitions data, one should *not*\n expect cluster statistics to match similar statistics had provided data been\n analyzed via a batch algorithm. In an incremental context, data points which\n would not be considered part of a particular cluster when analyzed via a\n batch algorithm may contribute to that cluster's statistics when analyzed\n incrementally.\n\n In general, the more data provided to an accumulator, the more reliable the\n cluster statistics.\n\n Parameters\n ----------\n k: integer|ndarray\n Number of clusters or a `k x ndims` matrix containing initial centroids.\n\n ndims: integer (optional)\n Number of dimensions. This argument must accompany an integer-valued\n first argument.\n\n options: Object (optional)\n Function options.\n\n options.metric: string (optional)\n Distance metric. Must be one of the following: 'euclidean', 'cosine', or\n 'correlation'. Default: 'euclidean'.\n\n options.init: ArrayLike (optional)\n Centroid initialization method and associated (optional) parameters. The\n first array element specifies the initialization method and must be one\n of the following: 'kmeans++', 'sample', or 'forgy'. The second array\n element specifies the number of data points to use when calculating\n initial centroids. When performing kmeans++ initialization, the third\n array element specifies the number of trials to perform when randomly\n selecting candidate centroids. Typically, more trials is correlated with\n initial centroids which lead to better clustering; however, a greater\n number of trials increases computational overhead. Default: ['kmeans++',\n k, 2+⌊ln(k)⌋ ].\n\n options.normalize: boolean (optional)\n Boolean indicating whether to normalize incoming data. This option is\n only relevant for non-Euclidean distance metrics. If set to `true`, an\n accumulator partitioning data based on cosine distance normalizes\n provided data to unit Euclidean length. If set to `true`, an accumulator\n partitioning data based on correlation distance first centers provided\n data and then normalizes data dimensions to have zero mean and unit\n variance. If this option is set to `false` and the metric is either\n cosine or correlation distance, then incoming data *must* already be\n normalized. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy incoming data to prevent mutation\n during normalization. Default: true.\n\n options.seed: any (optional)\n PRNG seed. Setting this option is useful when wanting reproducible\n initial centroids.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts centroid assignment for each data point in a provided matrix.\n To specify an output vector, provide a 1-dimensional ndarray as the\n first argument. Each element in the returned vector corresponds to a\n predicted cluster index for a respective data point.\n\n Examples\n --------\n > var accumulator = incrkmeans( 5, 2 );\n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v );\n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v );\n\n","incrkurtosis":"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n\n If provided a value, the accumulator function returns an updated corrected\n sample excess kurtosis. If not provided a value, the accumulator function\n returns the current corrected sample excess kurtosis.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrkurtosis();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( 2.0 )\n null\n > v = accumulator( -4.0 )\n null\n > v = accumulator( -4.0 )\n -6.0\n\n See Also\n --------\n incrmean, incrskewness, incrstdev, incrsummary, incrvariance\n","incrmaape":"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n\n If provided input values, the accumulator function returns an updated mean\n arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current mean arctangent absolute percentage\n error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.3218\n > m = accumulator( 5.0, 2.0 )\n ~0.6523\n > m = accumulator()\n ~0.6523\n\n See Also\n --------\n incrmae, incrmape, incrmean, incrmmaape\n","incrmae":"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute error. If not provided input values, the accumulator function\n returns the current mean absolute error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmae();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmape, incrme, incrmean, incrmmae\n","incrmapcorr":"\nincrmapcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample absolute correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample absolute correlation coefficient. If not provided values, the\n accumulator function returns the current moving sample absolute correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmapcorr( 3 );\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator( 3.0, -1.0 )\n ~0.925\n > ar = accumulator( 5.0, -9.5 )\n ~0.863\n > ar = accumulator()\n ~0.863\n\n See Also\n --------\n incrapcorr, incrmpcorr, incrmpcorr2\n","incrmape":"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute percentage error. If not provided input values, the accumulator\n function returns the current mean absolute percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator()\n ~91.67\n\n See Also\n --------\n incrmaape, incrmae, incrmean, incrmmape\n","incrmax":"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n\n If provided a value, the accumulator function returns an updated maximum\n value. If not provided a value, the accumulator function returns the current\n maximum value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmax();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmidrange, incrmin, incrmmax, incrrange, incrsummary\n","incrmaxabs":"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n\n If provided a value, the accumulator function returns an updated maximum\n absolute value. If not provided a value, the accumulator function returns\n the current maximum absolute value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaxabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmax, incrminabs, incrmmaxabs\n","incrmcovariance":"\nincrmcovariance( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample covariance.\n\n If provided values, the accumulator function returns an updated moving\n unbiased sample covariance. If not provided values, the accumulator function\n returns the current moving unbiased sample covariance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcovariance( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator( 3.0, -1.0 )\n -8.35\n > v = accumulator( 5.0, -9.5 )\n -29.42\n > v = accumulator()\n -29.42\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrmvariance\n","incrmcv":"\nincrmcv( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n\n The `W` parameter defines the number of values over which to compute the\n moving coefficient of variation.\n\n If provided a value, the accumulator function returns an updated moving\n coefficient of variation. If not provided a value, the accumulator function\n returns the current moving coefficient of variation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcv( 3 );\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator( 3.0 )\n 0.5\n > cv = accumulator( 7.0 )\n ~0.83\n > cv = accumulator()\n ~0.83\n\n See Also\n --------\n incrcv, incrmmean, incrmstdev, incrmvmr\n","incrmda":"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n\n If provided input values, the accumulator function returns an updated mean\n directional accuracy. If not provided input values, the accumulator function\n returns the current mean directional accuracy.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmda();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 4.0 )\n 0.5\n > m = accumulator()\n 0.5\n\n See Also\n --------\n incrmape, incrmmda\n","incrme":"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n\n If provided input values, the accumulator function returns an updated mean\n error. If not provided input values, the accumulator function returns the\n current mean error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrme();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmae, incrmean, incrmme\n","incrmean":"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator()\n -1.5\n\n See Also\n --------\n incrmidrange, incrmmean, incrstdev, incrsum, incrsummary, incrvariance\n","incrmeanabs":"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator()\n 3.5\n\n See Also\n --------\n incrmean, incrmmeanabs, incrsumabs\n","incrmeanabs2":"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs2();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 4.0\n > mu = accumulator( -5.0 )\n 14.5\n > mu = accumulator()\n 14.5\n\n See Also\n --------\n incrmean, incrmeanabs, incrmmeanabs2, incrsumabs2\n","incrmeanstdev":"\nincrmeanstdev( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanstdev();\n > var ms = accumulator()\n null\n > ms = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > ms = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > ms = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > ms = accumulator( 5.0 )\n [ 1.25, ~4.35 ]\n > ms = accumulator()\n [ 1.25, ~4.35 ]\n\n See Also\n --------\n incrmean, incrmeanvar, incrmmeanstdev, incrstdev\n","incrmeanvar":"\nincrmeanvar( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanvar();\n > var mv = accumulator()\n null\n > mv = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > mv = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > mv = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > mv = accumulator( 5.0 )\n [ 1.25, ~18.92 ]\n > mv = accumulator()\n [ 1.25, ~18.92 ]\n\n See Also\n --------\n incrmean, incrmeanstdev, incrmmeanvar, incrvariance\n","incrmgmean":"\nincrmgmean( W )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving geometric mean.\n\n If provided a value, the accumulator function returns an updated moving\n geometric mean. If not provided a value, the accumulator function returns\n the current moving geometric mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmgmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator( 3.0 )\n ~3.11\n > v = accumulator( 5.0 )\n ~4.22\n > v = accumulator()\n ~4.22\n\n See Also\n --------\n incrgmean, incrmhmean, incrmmean\n","incrmgrubbs":"\nincrmgrubbs( W[, options] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n The `W` parameter defines the number of values over which to perform Grubbs'\n test. The minimum window size is 3.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n Until provided `W` values, the accumulator function returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrmgrubbs( 20 );\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrgrubbs\n","incrmhmean":"\nincrmhmean( W )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving harmonic mean.\n\n If provided a value, the accumulator function returns an updated moving\n harmonic mean. If not provided a value, the accumulator function returns the\n current moving harmonic mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmhmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator( 3.0 )\n ~2.90\n > v = accumulator( 5.0 )\n ~4.09\n > v = accumulator()\n ~4.09\n\n See Also\n --------\n incrhmean, incrmgmean, incrmmean\n","incrmidrange":"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If provided a value, the accumulator function returns an updated mid-range.\n If not provided a value, the accumulator function returns the current mid-\n range.\n\n If provided `NaN`, the mid-range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmidrange();\n > var v = accumulator()\n null\n > v = accumulator( 3.14 )\n 3.14\n > v = accumulator( -5.0 )\n ~-0.93\n > v = accumulator( 10.1 )\n 2.55\n > v = accumulator()\n 2.55\n\n See Also\n --------\n incrmean, incrmax, incrmin, incrrange, incrsummary\n","incrmin":"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n\n If provided a value, the accumulator function returns an updated minimum\n value. If not provided a value, the accumulator function returns the current\n minimum value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmin();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 10.1 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmax, incrmidrange, incrmmin, incrrange, incrsummary\n","incrminabs":"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n\n If provided a value, the accumulator function returns an updated minimum\n absolute value. If not provided a value, the accumulator function returns\n the current minimum absolute value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 3.14\n > m = accumulator()\n 3.14\n\n See Also\n --------\n incrmaxabs, incrmin, incrmminabs\n","incrminmax":"\nincrminmax( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmax();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmminmax, incrrange\n","incrminmaxabs":"\nincrminmaxabs( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmaxabs();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator()\n [ 2.0, 5.0 ]\n\n See Also\n --------\n incrmaxabs, incrminabs, incrminmax, incrmminmaxabs\n","incrmmaape":"\nincrmmaape( W )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean arctangent absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean arctangent absolute\n percentage error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.32\n > m = accumulator( 5.0, 2.0 )\n ~0.65\n > m = accumulator( 3.0, 2.0 )\n ~0.59\n > m = accumulator( 2.0, 5.0 )\n ~0.66\n > m = accumulator()\n ~0.66\n\n See Also\n --------\n incrmaape, incrmmape, incrmmpe, incrmmean\n","incrmmae":"\nincrmmae( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute error.\n\n If provided a value, the accumulator function returns an updated moving\n mean absolute error. If not provided a value, the accumulator function\n returns the current moving mean absolute error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmae( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n 3.0\n > m = accumulator( 5.0, -2.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmae, incrmme, incrmmean\n","incrmmape":"\nincrmmape( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean absolute percentage\n error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator( 3.0, 2.0 )\n ~77.78\n > m = accumulator( 2.0, 5.0 )\n ~86.67\n > m = accumulator()\n ~86.67\n\n See Also\n --------\n incrmape, incrmmaape, incrmmpe, incrmmean\n","incrmmax":"\nincrmmax( W )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum.\n\n If provided a value, the accumulator function returns an updated moving\n maximum. If not provided a value, the accumulator function returns the\n current moving maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmax( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 3.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmmidrange, incrmmin, incrmrange, incrmsummary\n","incrmmaxabs":"\nincrmmaxabs( W )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n maximum absolute value. If not provided a value, the accumulator function\n returns the current moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaxabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 3.0 )\n 5.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmaxabs, incrmmax, incrmminabs\n","incrmmda":"\nincrmmda( W )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean directional accuracy.\n\n If provided input values, the accumulator function returns an updated moving\n mean directional accuracy. If not provided input values, the accumulator\n function returns the current moving mean directional accuracy.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmda( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( 5.0, 2.0 )\n 0.5\n > m = accumulator( 3.0, 2.0 )\n ~0.33\n > m = accumulator( 4.0, 5.0 )\n ~0.33\n > m = accumulator()\n ~0.33\n\n See Also\n --------\n incrmda, incrmmape\n","incrmme":"\nincrmme( W )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean error.\n\n If provided a value, the accumulator function returns an updated moving\n mean error. If not provided a value, the accumulator function returns the\n current moving mean error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmme( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n ~2.33\n > m = accumulator( 5.0, -2.0 )\n ~-0.33\n > m = accumulator()\n ~-0.33\n\n See Also\n --------\n incrme, incrmmae, incrmmean\n","incrmmean":"\nincrmmean( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmean( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator( 3.0 )\n 0.0\n > mu = accumulator( 5.0 )\n 1.0\n > mu = accumulator()\n 1.0\n\n See Also\n --------\n incrmean, incrmsum, incrmstdev, incrmsummary, incrmvariance\n","incrmmeanabs":"\nincrmmeanabs( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator( 3.0 )\n ~3.33\n > mu = accumulator( 5.0 )\n ~4.33\n > mu = accumulator()\n ~4.33\n\n See Also\n --------\n incrmeanabs, incrmmean, incrmsumabs\n","incrmmeanabs2":"\nincrmmeanabs2( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs2( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 4.0\n > m = accumulator( -5.0 )\n 14.5\n > m = accumulator( 3.0 )\n ~12.67\n > m = accumulator( 5.0 )\n ~19.67\n > m = accumulator()\n ~19.67\n\n See Also\n --------\n incrmeanabs2, incrmmeanabs, incrmsumabs2\n","incrmmeanstdev":"\nincrmmeanstdev( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanstdev( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > v = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > v = accumulator( 5.0 )\n [ 1.0, ~5.29 ]\n > v = accumulator()\n [ 1.0, ~5.29 ]\n\n See Also\n --------\n incrmeanstdev, incrmmean, incrmmeanvar, incrmstdev\n","incrmmeanvar":"\nincrmmeanvar( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanvar( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > v = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > v = accumulator( 5.0 )\n [ 1.0, 28.0 ]\n > v = accumulator()\n [ 1.0, 28.0 ]\n\n See Also\n --------\n incrmeanvar, incrmmean, incrmmeanstdev, incrmvariance\n","incrmmidrange":"\nincrmmidrange( W )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of values over which to compute\n the moving mid-range.\n\n If provided a value, the accumulator function returns an updated moving mid-\n range. If not provided a value, the accumulator function returns the current\n moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmidrange( 3 );\n > var mr = accumulator()\n null\n > mr = accumulator( 2.0 )\n 2.0\n > mr = accumulator( -5.0 )\n -1.5\n > mr = accumulator( 3.0 )\n -1.0\n > mr = accumulator( 5.0 )\n 0.0\n > mr = accumulator()\n 0.0\n\n See Also\n --------\n incrmmean, incrmmax, incrmmin, incrmrange\n","incrmmin":"\nincrmmin( W )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum. If not provided a value, the accumulator function returns the\n current moving minimum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmin( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 3.0 )\n -5.0\n > m = accumulator( 5.0 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmin, incrmmax, incrmmidrange, incrmrange, incrmsummary\n","incrmminabs":"\nincrmminabs( W )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n minimum absolute value. If not provided a value, the accumulator function\n returns the current moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 2.0\n > m = accumulator( 5.0 )\n 3.0\n > m = accumulator()\n 3.0\n\n See Also\n --------\n incrminabs, incrmmaxabs, incrmmin\n","incrmminmax":"\nincrmminmax( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum and maximum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmax( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmmax, incrminmax, incrmmin, incrmrange\n","incrmminmaxabs":"\nincrmminmaxabs( [out,] W )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n\n The `W` parameter defines the number of values over which to compute moving\n minimum and maximum absolute values.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmaxabs( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 3.0, 5.0 ]\n > mm = accumulator()\n [ 3.0, 5.0 ]\n\n See Also\n --------\n incrminmaxabs, incrmmax, incrmmaxabs, incrmmin, incrmminabs, incrmminmax\n","incrmmpe":"\nincrmmpe( W )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean percentage error. If not provided input values, the accumulator\n function returns the current moving mean percentage error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmpe( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator( 3.0, 2.0 )\n ~-55.56\n > m = accumulator( 2.0, 5.0 )\n ~-46.67\n > m = accumulator()\n ~-46.67\n\n See Also\n --------\n incrmmape, incrmme, incrmpe\n","incrmmse":"\nincrmmse( W )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean squared error.\n\n If provided a value, the accumulator function returns an updated moving mean\n squared error. If not provided a value, the accumulator function returns the\n current moving mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmse( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator( 3.0, 2.0 )\n 17.0\n > m = accumulator( 5.0, -2.0 )\n 33.0\n > m = accumulator()\n 33.0\n\n See Also\n --------\n incrmrmse, incrmrss, incrmse\n","incrmpcorr":"\nincrmpcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation coefficient. If not provided values, the accumulator\n function returns the current moving sample correlation coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator( 3.0, -1.0 )\n ~-0.925\n > r = accumulator( 5.0, -9.5 )\n ~-0.863\n > r = accumulator()\n ~-0.863\n\n See Also\n --------\n incrmcovariance, incrmpcorrdist, incrpcorr\n","incrmpcorr2":"\nincrmpcorr2( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving squared sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n squared sample correlation coefficient. If not provided values, the\n accumulator function returns the current moving squared sample correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr2( 3 );\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator( 3.0, -1.0 )\n ~0.86\n > r2 = accumulator( 5.0, -9.5 )\n ~0.74\n > r2 = accumulator()\n ~0.74\n\n See Also\n --------\n incrmapcorr, incrmpcorr, incrpcorr2\n","incrmpcorrdist":"\nincrmpcorrdist( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n However, due to limitations inherent in representing numeric values using\n floating-point format (i.e., the inability to represent numeric values with\n infinite precision), the correlation distance between perfectly correlated\n random variables may *not* be `0` or `2`. In fact, the correlation distance\n is *not* guaranteed to be strictly on the interval [0,2]. Any computed\n distance should, however, be within floating-point roundoff error.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation distance.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation distance. If not provided values, the accumulator\n function returns the current moving sample correlation distance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorrdist( 3 );\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator( 3.0, -1.0 )\n ~1.925\n > d = accumulator( 5.0, -9.5 )\n ~1.863\n > d = accumulator()\n ~1.863\n\n See Also\n --------\n incrmpcorr, incrpcorrdist\n","incrmpe":"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n\n If provided input values, the accumulator function returns an updated mean\n percentage error. If not provided input values, the accumulator function\n returns the current mean percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpe();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator()\n ~-58.33\n\n See Also\n --------\n incrmape, incrme, incrmmpe\n","incrmprod":"\nincrmprod( W )\n Returns an accumulator function which incrementally computes a moving\n product.\n\n The `W` parameter defines the number of values over which to compute the\n moving product.\n\n If provided a value, the accumulator function returns an updated moving\n product. If not provided a value, the accumulator function returns the\n current moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n For accumulations over large windows or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmprod( 3 );\n > var p = accumulator()\n null\n > p = accumulator( 2.0 )\n 2.0\n > p = accumulator( -5.0 )\n -10.0\n > p = accumulator( 3.0 )\n -30.0\n > p = accumulator( 5.0 )\n -75.0\n > p = accumulator()\n -75.0\n\n See Also\n --------\n incrmsum, incrprod\n","incrmrange":"\nincrmrange( W )\n Returns an accumulator function which incrementally computes a moving range.\n\n The `W` parameter defines the number of values over which to compute the\n moving range.\n\n If provided a value, the accumulator function returns an updated moving\n range. If not provided a value, the accumulator function returns the current\n moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrange( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0 )\n 0.0\n > r = accumulator( -5.0 )\n 7.0\n > r = accumulator( 3.0 )\n 8.0\n > r = accumulator( 5.0 )\n 10.0\n > r = accumulator()\n 10.0\n\n See Also\n --------\n incrmmax, incrmmean, incrmmin, incrmsummary, incrrange\n","incrmrmse":"\nincrmrmse( W )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving root mean squared error.\n\n If provided a value, the accumulator function returns an updated moving root\n mean squared error. If not provided a value, the accumulator function\n returns the current moving root mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrmse( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator( 3.0, 2.0 )\n ~4.12\n > r = accumulator( 5.0, -2.0 )\n ~5.74\n > r = accumulator()\n ~5.74\n\n See Also\n --------\n incrmmse, incrmrss, incrrmse\n","incrmrss":"\nincrmrss( W )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n\n The `W` parameter defines the number of values over which to compute the\n moving residual sum of squares.\n\n If provided a value, the accumulator function returns an updated moving\n residual sum of squares. If not provided a value, the accumulator function\n returns the current moving residual sum of squares.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrss( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator( 3.0, 2.0 )\n 51.0\n > r = accumulator( 5.0, -2.0 )\n 99.0\n > r = accumulator()\n 99.0\n\n See Also\n --------\n incrrss, incrmmse, incrmrmse\n","incrmse":"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n\n If provided input values, the accumulator function returns an updated mean\n squared error. If not provided input values, the accumulator function\n returns the current mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmse();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator()\n 25.0\n\n See Also\n --------\n incrmmse, incrrmse, incrrss\n","incrmstdev":"\nincrmstdev( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving corrected sample standard deviation.\n\n If provided a value, the accumulator function returns an updated moving\n corrected sample standard deviation. If not provided a value, the\n accumulator function returns the current moving corrected sample standard\n deviation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmstdev( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator( 3.0 )\n ~4.36\n > s = accumulator( 5.0 )\n ~5.29\n > s = accumulator()\n ~5.29\n\n See Also\n --------\n incrmmean, incrmsummary, incrmvariance, incrstdev\n","incrmsum":"\nincrmsum( W )\n Returns an accumulator function which incrementally computes a moving sum.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsum( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator( 3.0 )\n 0.0\n > s = accumulator( 5.0 )\n 3.0\n > s = accumulator()\n 3.0\n\n See Also\n --------\n incrmmean, incrmsummary, incrsum\n","incrmsumabs":"\nincrmsumabs( W )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator( 3.0 )\n 10.0\n > s = accumulator( -5.0 )\n 13.0\n > s = accumulator()\n 13.0\n\n See Also\n --------\n incrmmeanabs, incrmsum, incrsum, incrsumabs\n","incrmsumabs2":"\nincrmsumabs2( W )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs2( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator( 3.0 )\n 38.0\n > s = accumulator( -5.0 )\n 59.0\n > s = accumulator()\n 59.0\n\n See Also\n --------\n incrmmeanabs2, incrmsumabs, incrsumabs, incrsumabs2\n","incrmsummary":"\nincrmsummary( W )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n\n The `W` parameter defines the number of values over which to compute the\n moving statistical summary.\n\n If provided a value, the accumulator function returns an updated moving\n statistical summary. If not provided a value, the accumulator function\n returns the current moving statistical summary.\n\n The returned summary is an object containing the following fields:\n\n - window: window size.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - range: range.\n - midrange: arithmetic mean of the minimum and maximum values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n summaries are calculated from smaller sample sizes. Until the window is\n full, each returned summary is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsummary( 3 );\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsum, incrmvariance, incrsummary\n","incrmsumprod":"\nincrmsumprod( W )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n\n The `W` parameter defines the number of (x,y) pairs over which to compute\n the moving sum of products.\n\n If provided input values, the accumulator function returns an updated moving\n sum. If not provided input values, the accumulator function returns the\n current moving sum.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumprod( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator( 3.0, -2.0 )\n -10.0\n > s = accumulator( 5.0, 3.0 )\n -1.0\n > s = accumulator()\n -1.0\n\n See Also\n --------\n incrmprod, incrmsum, incrsumprod\n","incrmvariance":"\nincrmvariance( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample variance.\n\n If provided a value, the accumulator function returns an updated moving\n unbiased sample variance. If not provided a value, the accumulator function\n returns the current moving unbiased sample variance.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvariance( 3 );\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator( 3.0 )\n 19.0\n > s2 = accumulator( 5.0 )\n 28.0\n > s2 = accumulator()\n 28.0\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsummary, incrvariance\n","incrmvmr":"\nincrmvmr( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n\n The `W` parameter defines the number of values over which to compute the\n moving variance-to-mean ratio.\n\n If provided a value, the accumulator function returns an updated moving\n variance-to-mean ratio. If not provided a value, the accumulator function\n returns the current moving variance-to-mean ratio.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvmr( 3 );\n > var F = accumulator()\n null\n > F = accumulator( 2.0 )\n 0.0\n > F = accumulator( 1.0 )\n ~0.33\n > F = accumulator( 3.0 )\n 0.5\n > F = accumulator( 7.0 )\n ~2.55\n > F = accumulator()\n ~2.55\n\n See Also\n --------\n incrmmean, incrmvariance, incrvmr\n","incrnancount":"\nincrnancount()\n Returns an accumulator function which incrementally updates a count,\n ignoring `NaN` values.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnancount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n See Also\n --------\n incrnansum\n","incrnansum":"\nincrnansum()\n Returns an accumulator function which incrementally computes a sum, ignoring\n `NaN` values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( NaN )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n See Also\n --------\n incrnansumabs, incrsum\n","incrnansumabs":"\nincrnansumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values, ignoring NaN values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( NaN )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n See Also\n --------\n incrnansum, incrnansumabs2, incrsumabs\n","incrnansumabs2":"\nincrnansumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values, ignoring NaN values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( NaN )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n See Also\n --------\n incrnansum, incrnansumabs, incrsumabs2\n","incrpcorr":"\nincrpcorr( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated sample\n correlation coefficient. If not provided values, the accumulator function\n returns the current sample correlation coefficient.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator()\n ~-1.0\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrsummary\n","incrpcorr2":"\nincrpcorr2( [mx, my] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr2();\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator()\n ~1.0\n\n See Also\n --------\n incrapcorr, incrmpcorr2, incrpcorr\n","incrpcorrdist":"\nincrpcorrdist( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n If provided values, the accumulator function returns an updated sample\n correlation distance. If not provided values, the accumulator function\n returns the current sample correlation distance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdist();\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator()\n ~2.0\n\n See Also\n --------\n incrcovariance, incrpcorr, incrsummary\n","incrpcorrdistmat":"\nincrpcorrdistmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation distance matrix. If not provided a data vector, the\n accumulator function returns the current sample correlation distance matrix.\n\n Due to limitations inherent in representing numeric values using floating-\n point format (i.e., the inability to represent numeric values with infinite\n precision), the correlation distance between perfectly correlated random\n variables may *not* be `0` or `2`. In fact, the correlation distance is\n *not* guaranteed to be strictly on the interval [0,2]. Any computed distance\n should, however, be within floating-point roundoff error.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation distance matrix or a square 2-dimensional\n ndarray for storing the correlation distance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdistmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrpcorrdist, incrpcorrmat\n","incrpcorrmat":"\nincrpcorrmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation matrix. If not provided a data vector, the accumulator\n function returns the current sample correlation matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation matrix or a square 2-dimensional ndarray for\n storing the correlation matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovmat, incrpcorr, incrpcorrdistmat\n","incrprod":"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n\n If provided a value, the accumulator function returns an updated product. If\n not provided a value, the accumulator function returns the current product.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrprod();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -10.0\n > v = accumulator()\n -10.0\n\n See Also\n --------\n incrmprod, incrsum, incrsummary\n","incrrange":"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n\n If provided a value, the accumulator function returns an updated range. If\n not provided a value, the accumulator function returns the current range.\n\n If provided `NaN`, the range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrange();\n > var v = accumulator()\n null\n > v = accumulator( -2.0 )\n 0.0\n > v = accumulator( 1.0 )\n 3.0\n > v = accumulator( 3.0 )\n 5.0\n > v = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmean, incrmin, incrmrange, incrsummary\n","incrrmse":"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n\n If provided input values, the accumulator function returns an updated root\n mean squared error. If not provided input values, the accumulator function\n returns the current root mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrmse();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator()\n 5.0\n\n See Also\n --------\n incrmrmse, incrmse, incrrss\n","incrrss":"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n\n If provided input values, the accumulator function returns an updated\n residual sum of squares. If not provided input values, the accumulator\n function returns the current residual sum of squares.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrss();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator()\n 50.0\n\n See Also\n --------\n incrmrss, incrmse, incrrmse\n","incrskewness":"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n\n If provided a value, the accumulator function returns an updated corrected\n sample skewness. If not provided a value, the accumulator function returns\n the current corrected sample skewness.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrskewness();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( -5.0 )\n null\n > v = accumulator( -10.0 )\n ~0.492\n > v = accumulator()\n ~0.492\n\n See Also\n --------\n incrkurtosis, incrmean, incrstdev, incrsummary, incrvariance\n","incrspace":"\nincrspace( start, stop[, increment] )\n Generates a linearly spaced numeric array using a provided increment.\n\n If an `increment` is not provided, the default `increment` is `1`.\n\n The output array is guaranteed to include the `start` value but does not\n include the `stop` value.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Array element bound.\n\n increment: number (optional)\n Increment. Default: `1`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = incrspace( 0, 11, 2 )\n [ 0, 2, 4, 6, 8, 10 ]\n\n See Also\n --------\n linspace, logspace\n","incrstdev":"\nincrstdev( [mean] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n\n If provided a value, the accumulator function returns an updated corrected\n sample standard deviation. If not provided a value, the accumulator function\n returns the current corrected sample standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrstdev();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator()\n ~4.95\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrsummary, incrvariance\n","incrsum":"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n See Also\n --------\n incrcount, incrmean, incrmsum, incrprod, incrsummary\n","incrsumabs":"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n See Also\n --------\n incrmeanabs, incrmsumabs, incrsum\n","incrsumabs2":"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n See Also\n --------\n incrmeanabs2, incrmsumabs2, incrsumabs\n","incrsummary":"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n\n If provided a value, the accumulator function returns an updated summary. If\n not provided a value, the accumulator function returns the current summary.\n\n The returned summary is an object containing the following fields:\n\n - count: count.\n - max: maximum value.\n - min: minimum value.\n - range: range.\n - midrange: mid-range.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - skewness: corrected sample skewness.\n - kurtosis: corrected sample excess kurtosis.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsummary();\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrcount, incrkurtosis, incrmax, incrmean, incrmidrange, incrmin, incrmsummary, incrrange, incrskewness, incrstdev, incrsum, incrvariance\n","incrsumprod":"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n\n If provided input values, the accumulator function returns an updated sum.\n If not provided input values, the accumulator function returns the current\n sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumprod();\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator()\n -4.0\n\n See Also\n --------\n incrmsumprod, incrprod, incrsum\n","incrvariance":"\nincrvariance( [mean] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n\n If provided a value, the accumulator function returns an updated unbiased\n sample variance. If not provided a value, the accumulator function returns\n the current unbiased sample variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvariance();\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator()\n 24.5\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrstdev, incrsummary\n","incrvmr":"\nincrvmr( [mean] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvmr();\n > var D = accumulator()\n null\n > D = accumulator( 2.0 )\n 0.0\n > D = accumulator( 1.0 )\n ~0.33\n > D = accumulator()\n ~0.33\n\n See Also\n --------\n incrmean, incrmvmr, incrvariance\n","incrwmean":"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n\n If provided arguments, the accumulator function returns an updated weighted\n mean. If not provided arguments, the accumulator function returns the\n current weighted mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n The accumulator function accepts two arguments:\n\n - x: value\n - w: weight\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrwmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0, 1.0 )\n 2.0\n > mu = accumulator( 2.0, 0.5 )\n 2.0\n > mu = accumulator( 3.0, 1.5 )\n 2.5\n > mu = accumulator()\n 2.5\n\n See Also\n --------\n increwmean, incrmean, incrmmean\n","ind2sub":"\nind2sub( shape, idx[, options] )\n Converts a linear index to an array of subscripts.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n Returns\n -------\n out: Array\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var s = ind2sub( d, 17 )\n [ 1, 2, 2 ]\n\n\nind2sub.assign( shape, idx[, options], out )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n out: Array|TypedArray|Object\n Output array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var out = [ 0, 0, 0 ];\n > var s = ind2sub.assign( d, 17, out )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n See Also\n --------\n array, ndarray, sub2ind\n","ind2sub.assign":"\nind2sub.assign( shape, idx[, options], out )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n out: Array|TypedArray|Object\n Output array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var out = [ 0, 0, 0 ];\n > var s = ind2sub.assign( d, 17, out )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n See Also\n --------\n array, ndarray, sub2ind","indexOf":"\nindexOf( arr, searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n Search is performed using *strict equality* comparison.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object.\n\n searchElement: any\n Element to find.\n\n fromIndex: integer (optional)\n Starting index (if negative, the start index is determined relative to\n last element).\n\n Returns\n -------\n out: integer\n Index or -1.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ 4, 3, 2, 1 ];\n > var idx = indexOf( arr, 3 )\n 1\n > arr = [ 4, 3, 2, 1 ];\n > idx = indexOf( arr, 5 )\n -1\n\n // Using a `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, 3 )\n 5\n\n // `fromIndex` which exceeds `array` length:\n > arr = [ 1, 2, 3, 4, 2, 5 ];\n > idx = indexOf( arr, 2, 10 )\n -1\n\n // Negative `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\n > idx = indexOf( arr, 2, -4 )\n 5\n > idx = indexOf( arr, 2, -1 )\n 7\n\n // Negative `fromIndex` exceeding input `array` length:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, -10 )\n 1\n\n // Array-like objects:\n > var str = 'bebop';\n > idx = indexOf( str, 'o' )\n 3\n\n","inherit":"\ninherit( ctor, superCtor )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n\n This function is not designed to work with ES2015/ES6 classes. For\n ES2015/ES6 classes, use `class` with `extends`.\n\n Parameters\n ----------\n ctor: Object|Function\n Constructor which will inherit.\n\n superCtor: Object|Function\n Super (parent) constructor.\n\n Returns\n -------\n out: Object|Function\n Child constructor.\n\n Examples\n --------\n // Create a parent constructor:\n > function Foo() { return this; };\n > Foo.prototype.beep = function beep() { return 'boop'; };\n\n // Create a child constructor:\n > function Bar() { Foo.call( this ); return this; };\n\n // Setup inheritance:\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var v = bar.beep()\n 'boop'\n\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value[, level] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited enumerable properties.\n\n Examples\n --------\n > var props = inheritedEnumerableProperties( {} )\n\n See Also\n --------\n enumerableProperties, enumerablePropertiesIn, inheritedEnumerablePropertySymbols, inheritedKeys, inheritedNonEnumerableProperties, inheritedProperties\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedEnumerablePropertySymbols( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbols, inheritedKeys, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedKeys":"\ninheritedKeys( value[, level] )\n Returns an array of an object's inherited enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable property names.\n\n Examples\n --------\n > var keys = inheritedKeys( {} )\n\n See Also\n --------\n objectKeys, keysIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value[, level] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited non-enumerable properties.\n\n Examples\n --------\n > var props = inheritedNonEnumerableProperties( {} )\n\n See Also\n --------\n inheritedEnumerableProperties, inheritedNonEnumerablePropertyNames, inheritedNonEnumerablePropertySymbols, inheritedKeys, nonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value[, level] )\n Returns an array of an object's inherited non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited non-enumerable property names.\n\n Examples\n --------\n > var keys = inheritedNonEnumerablePropertyNames( {} )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertySymbols, objectKeys, nonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedNonEnumerablePropertySymbols( [] )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertyNames, nonEnumerableProperties, nonEnumerablePropertyNames, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedProperties":"\ninheritedProperties( value[, level] )\n Returns an array of an object's inherited property names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited property names and symbols.\n\n Examples\n --------\n > var symbols = inheritedProperties( [] )\n\n See Also\n --------\n properties, propertiesIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value, property[, level] )\n Returns a property descriptor for an object's inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var desc = inheritedPropertyDescriptor( {}, 'toString' )\n {...}\n\n See Also\n --------\n propertyDescriptor, propertyDescriptorIn, inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value[, level] )\n Returns an object's inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object\n An object's inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = inheritedPropertyDescriptors( obj )\n { 'foo': {...}, ... }\n\n See Also\n --------\n propertyDescriptors, propertyDescriptorsIn, inheritedKeys, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyNames":"\ninheritedPropertyNames( value[, level] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable and non-enumerable property\n names.\n\n Examples\n --------\n > var keys = inheritedPropertyNames( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertySymbols, propertyNames, propertyNamesIn\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value[, level] )\n Returns an array of an object's inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited symbol properties.\n\n Examples\n --------\n > var symbols = inheritedPropertySymbols( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, propertySymbols, propertySymbolsIn\n","inheritedWritableProperties":"\ninheritedWritableProperties( value[, level] )\n Returns an array of an object's inherited writable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited writable properties.\n\n Examples\n --------\n > var props = inheritedWritableProperties( {} )\n\n See Also\n --------\n inheritedWritablePropertyNames, inheritedWritablePropertySymbols, writableProperties, writablePropertiesIn, properties\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value[, level] )\n Returns an array of an object's inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited writable property names.\n\n Examples\n --------\n > var keys = inheritedWritablePropertyNames( {} )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertyNames, writablePropertyNamesIn, properties\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value[, level] )\n Returns an array of an object's inherited writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited writable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedWritablePropertySymbols( [] )\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertySymbols, writablePropertySymbolsIn, properties\n","inmap":"\ninmap( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmap( arr, foo )\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEach, inmapRight, map\n","inmapAsync":"\ninmapAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: value used to update the collection\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 2000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 2000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n\n\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n See Also\n --------\n forEachAsync, inmapRightAsync, inmap\n","inmapAsync.factory":"\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n See Also\n --------\n forEachAsync, inmapRightAsync, inmap","inmapRight":"\ninmapRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmapRight( arr, foo )\n 2: 3.0\n 1: 2.0\n 0: 1.0\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEachRight, inmap, mapRight\n","inmapRightAsync":"\ninmapRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: value used to update the collection\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 6000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 6000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n\n\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n See Also\n --------\n forEachRightAsync, inmapAsync, inmapRight\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n See Also\n --------\n forEachRightAsync, inmapAsync, inmapRight","inspectSinkStream":"\ninspectSinkStream( [options,] clbk )\n Returns a writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream","inspectStream":"\ninspectStream( [options,] clbk )\n Returns a transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream\n","inspectStream.factory":"\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","inspectStream.objectMode":"\ninspectStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream","instanceOf":"\ninstanceOf( value, constructor )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n\n While the prototype of an `object` created using object literal notion is\n `undefined`, the function returns `true` when provided an `object` literal\n and the `Object` constructor. This maintains consistent behavior with the\n `instanceof` operator.\n\n Parameters\n ----------\n value: any\n Input value.\n\n constructor: Function\n Constructor.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an instance of a provided constructor.\n\n Examples\n --------\n > var bool = instanceOf( [], Array )\n true\n > bool = instanceOf( {}, Object )\n true\n > bool = instanceOf( null, Object )\n false\n\n See Also\n --------\n isPrototypeOf, constructorName, inherit, typeOf\n","INT8_MAX":"\nINT8_MAX\n Maximum signed 8-bit integer.\n\n The maximum signed 8-bit integer is given by `2^7 - 1`.\n\n Examples\n --------\n > INT8_MAX\n 127\n\n See Also\n --------\n INT8_MIN\n","INT8_MIN":"\nINT8_MIN\n Minimum signed 8-bit integer.\n\n The minimum signed 8-bit integer is given by `-(2^7)`.\n\n Examples\n --------\n > INT8_MIN\n -128\n\n See Also\n --------\n INT8_MAX\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n\n Examples\n --------\n > INT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT16_NUM_BYTES, INT32_NUM_BYTES, UINT8_NUM_BYTES\n","Int8Array":"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array()\n \n\n\nInt8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Int8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'\n\n\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n \n\n\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5\n\n\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5\n\n\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int8Array.from":"\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int8Array.of":"\nInt8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1","Int8Array.name":"\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n ","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Int8Array.prototype.length":"\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","INT16_MAX":"\nINT16_MAX\n Maximum signed 16-bit integer.\n\n The maximum signed 16-bit integer is given by `2^15 - 1`.\n\n Examples\n --------\n > INT16_MAX\n 32767\n\n See Also\n --------\n INT16_MIN\n","INT16_MIN":"\nINT16_MIN\n Minimum signed 16-bit integer.\n\n The minimum signed 16-bit integer is given by `-(2^15)`.\n\n Examples\n --------\n > INT16_MIN\n -32768\n\n See Also\n --------\n INT16_MAX\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n\n Examples\n --------\n > INT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT32_NUM_BYTES, INT8_NUM_BYTES, UINT16_NUM_BYTES\n","Int16Array":"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array()\n \n\n\nInt16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Int16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'\n\n\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n \n\n\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10\n\n\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5\n\n\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int16Array.from":"\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int16Array.of":"\nInt16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2","Int16Array.name":"\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n ","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2","Int16Array.prototype.length":"\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","INT32_MAX":"\nINT32_MAX\n Maximum signed 32-bit integer.\n\n The maximum signed 32-bit integer is given by `2^31 - 1`.\n\n Examples\n --------\n > INT32_MAX\n 2147483647\n\n See Also\n --------\n INT32_MIN\n","INT32_MIN":"\nINT32_MIN\n Minimum signed 32-bit integer.\n\n The minimum signed 32-bit integer is given by `-(2^31)`.\n\n Examples\n --------\n > INT32_MIN\n -2147483648\n\n See Also\n --------\n INT32_MAX\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n\n Examples\n --------\n > INT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT16_NUM_BYTES, INT8_NUM_BYTES, UINT32_NUM_BYTES\n","Int32Array":"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array()\n \n\n\nInt32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 5, 5, 5 ] );\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Int32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'\n\n\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n \n\n\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20\n\n\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5\n\n\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int32Array.from":"\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int32Array.of":"\nInt32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4","Int32Array.name":"\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n ","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Int32Array.prototype.length":"\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n\n Examples\n --------\n > IS_BIG_ENDIAN\n \n\n See Also\n --------\n IS_LITTLE_ENDIAN\n","IS_BROWSER":"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n\n Examples\n --------\n > IS_BROWSER\n \n\n","IS_DARWIN":"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n\n Examples\n --------\n > IS_DARWIN\n \n\n","IS_ELECTRON":"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n\n Examples\n --------\n > IS_ELECTRON\n \n\n See Also\n --------\n IS_ELECTRON_MAIN, IS_ELECTRON_RENDERER\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n\n Examples\n --------\n > IS_ELECTRON_MAIN\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_RENDERER\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n\n Examples\n --------\n > IS_ELECTRON_RENDERER\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_MAIN\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n\n Examples\n --------\n > IS_LITTLE_ENDIAN\n \n\n See Also\n --------\n IS_BIG_ENDIAN\n","IS_NODE":"\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n\n Examples\n --------\n > IS_NODE\n \n\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n\n Examples\n --------\n > IS_WEB_WORKER\n \n\n","IS_WINDOWS":"\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n\n Examples\n --------\n > IS_WINDOWS\n \n\n","isAbsolutePath":"\nisAbsolutePath( value )\n Tests if a value is an absolute path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an absolute path.\n\n Examples\n --------\n // Windows environment:\n > var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n\n // POSIX environment:\n > bool = isAbsolutePath( '/foo/bar/baz' )\n true\n\n\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false\n\n\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isRelativePath\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false","isAbsolutePath.win32":"\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isRelativePath","isAccessorArray":"\nisAccessorArray( value )\n Tests if a value is an array-like object supporting the accessor (get/set)\n protocol.\n\n An accessor array is defined as an array, typed array, or an array-like\n object (excluding strings and functions) having `get` and `set` methods for\n accessing array elements.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an accessor array.\n\n Examples\n --------\n > var bool = isAccessorArray( new Complex64Array( 10 ) )\n true\n > bool = isAccessorArray( [] )\n false\n > bool = isAccessorArray( { 'length': 0 } )\n false\n > bool = isAccessorArray( {} )\n false\n\n See Also\n --------\n isArrayLike, isArrayLikeObject, isCollection\n","isAccessorProperty":"\nisAccessorProperty( value, property )\n Tests if an object's own property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has an accessor\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorProperty( obj, 'boop' )\n false\n > bool = isAccessorProperty( obj, 'beep' )\n true\n\n See Also\n --------\n hasOwnProp, isAccessorPropertyIn, isDataProperty\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value, property )\n Tests if an object's own or inherited property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has an\n accessor descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorPropertyIn( obj, 'boop' )\n false\n > bool = isAccessorPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n hasProp, isAccessorProperty, isDataPropertyIn\n","isAlphagram":"\nisAlphagram( value )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n\n The function first checks that an input value is a string before validating\n that the value is an alphagram. For non-string values, the function returns\n `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an alphagram.\n\n Examples\n --------\n > var out = isAlphagram( 'beep' )\n true\n > out = isAlphagram( 'zba' )\n false\n > out = isAlphagram( '' )\n false\n\n See Also\n --------\n isAnagram\n","isAlphaNumeric":"\nisAlphaNumeric( str )\n Tests whether a string contains only alphanumeric characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only alphanumeric\n characters.\n\n Examples\n --------\n > var bool = isAlphaNumeric( 'abc0123456789' )\n true\n > bool = isAlphaNumeric( 'abcdef' )\n true\n > bool = isAlphaNumeric( '0xff' )\n true\n > bool = isAlphaNumeric( '' )\n false\n\n See Also\n --------\n isDigitString\n","isAnagram":"\nisAnagram( str, value )\n Tests if a value is an anagram.\n\n Parameters\n ----------\n str: string\n Comparison string.\n\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an anagram.\n\n Examples\n --------\n > var str1 = 'I am a weakish speller';\n > var str2 = 'William Shakespeare';\n > var bool = isAnagram( str1, str2 )\n true\n > bool = isAnagram( 'bat', 'tabba' )\n false\n\n See Also\n --------\n isAlphagram\n","isArguments":"\nisArguments( value )\n Tests if a value is an arguments object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an arguments object.\n\n Examples\n --------\n > function foo() { return arguments; };\n > var bool = isArguments( foo() )\n true\n > bool = isArguments( [] )\n false\n\n","isArray":"\nisArray( value )\n Tests if a value is an array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array.\n\n Examples\n --------\n > var bool = isArray( [] )\n true\n > bool = isArray( {} )\n false\n\n See Also\n --------\n isArrayLike\n","isArrayArray":"\nisArrayArray( value )\n Tests if a value is an array of arrays.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of arrays.\n\n Examples\n --------\n > var bool = isArrayArray( [ [], [] ] )\n true\n > bool = isArrayArray( [ {}, {} ] )\n false\n > bool = isArrayArray( [] )\n false\n\n","isArrayBuffer":"\nisArrayBuffer( value )\n Tests if a value is an ArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an ArrayBuffer.\n\n Examples\n --------\n > var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\n true\n > bool = isArrayBuffer( [] )\n false\n\n See Also\n --------\n isSharedArrayBuffer, isTypedArray\n","isArrayBufferView":"\nisArrayBufferView( value )\n Tests if a value is a `ArrayBuffer` view.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `ArrayBuffer` view.\n\n Examples\n --------\n > var bool = isArrayBufferView( new Int8Array() )\n true\n > bool = isArrayBufferView( [] )\n false\n\n See Also\n --------\n isDataView, isTypedArray\n","isArrayLength":"\nisArrayLength( value )\n Tests if a value is a valid array length.\n\n A valid length property for an Array instance is any integer value on the\n interval [0, 2^32-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a valid array length.\n\n Examples\n --------\n > var bool = isArrayLength( 5 )\n true\n > bool = isArrayLength( 2.0e200 )\n false\n > bool = isArrayLength( -3.14 )\n false\n > bool = isArrayLength( null )\n false\n\n See Also\n --------\n isArray\n","isArrayLike":"\nisArrayLike( value )\n Tests if a value is array-like.\n\n If provided a string, the function returns `true`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is array-like.\n\n Examples\n --------\n > var bool = isArrayLike( [] )\n true\n > bool = isArrayLike( { 'length': 10 } )\n true\n > bool = isArrayLike( 'beep' )\n true\n > bool = isArrayLike( null )\n false\n\n See Also\n --------\n isArray, isArrayLikeObject, isCollection\n","isArrayLikeObject":"\nisArrayLikeObject( value )\n Tests if a value is an array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object.\n\n Examples\n --------\n > var bool = isArrayLikeObject( [] )\n true\n > bool = isArrayLikeObject( { 'length': 10 } )\n true\n > bool = isArrayLikeObject( 'beep' )\n false\n\n See Also\n --------\n isArray, isArrayLike, isCollection\n","isASCII":"\nisASCII( str )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string has all ASCII characters.\n\n Examples\n --------\n > var str = 'beep boop';\n > var bool = isASCII( str )\n true\n > bool = isASCII( fromCodePoint( 130 ) )\n false\n\n See Also\n --------\n isString\n","isBetween":"\nisBetween( value, a, b[, left, right] )\n Tests if a value is between two values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is between two values.\n\n Examples\n --------\n > var bool = isBetween( 3.14, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.0, 4.0 )\n true\n > bool = isBetween( 4.0, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.14, 4.0 )\n false\n > bool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\n false\n > bool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetweenArray\n","isBetweenArray":"\nisBetweenArray( value, a, b[, left, right] )\n Tests if a value is an array-like object where every element is between two\n values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object where every\n element is between two values.\n\n Examples\n --------\n > var arr = [ 3.0, 3.14, 4.0 ];\n > var bool = isBetweenArray( arr, 3.0, 4.0 )\n true\n > bool = isBetweenArray( arr, 3.14, 4.0 )\n false\n > bool = isBetweenArray( arr, 3.0, 3.14 )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetween\n","isBigInt":"\nisBigInt( value )\n Tests if a value is a BigInt.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a BigInt.\n\n Examples\n --------\n > var bool = isBigInt( BigInt( '1' ) )\n true\n > bool = isBigInt( Object( BigInt( '1' ) ) )\n true\n > bool = isBigInt( {} )\n false\n > bool = isBigInt( null )\n false\n > bool = isBigInt( true )\n false\n\n","isBigInt64Array":"\nisBigInt64Array( value )\n Tests if a value is a BigInt64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a BigInt64Array.\n\n Examples\n --------\n > var bool = isBigInt64Array( new BigInt64Array( 10 ) )\n true\n > bool = isBigInt64Array( [] )\n false\n\n See Also\n --------\n isBigUint64Array\n","isBigUint64Array":"\nisBigUint64Array( value )\n Tests if a value is a BigUint64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a BigUint64Array.\n\n Examples\n --------\n > var bool = isBigUint64Array( new BigUint64Array( 10 ) )\n true\n > bool = isBigUint64Array( [] )\n false\n\n See Also\n --------\n isBigInt64Array\n","isBinaryString":"\nisBinaryString( value )\n Tests if a value is a binary string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a binary string.\n\n Examples\n --------\n > var bool = isBinaryString( '1000101' )\n true\n > bool = isBinaryString( 'beep' )\n false\n > bool = isBinaryString( '' )\n false\n\n See Also\n --------\n isString\n","isBlankString":"\nisBlankString( value )\n Tests if a value is a blank string (i.e., an empty string or a string\n consisting only of whitespace characters).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a blank string.\n\n Examples\n --------\n > var bool = isBlankString( ' ' )\n true\n > bool = isBlankString( 'beep' )\n false\n > bool = isBlankString( null )\n false\n\n See Also\n --------\n isString, isEmptyString\n","isBoolean":"\nisBoolean( value )\n Tests if a value is a boolean.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean.\n\n Examples\n --------\n > var bool = isBoolean( false )\n true\n > bool = isBoolean( new Boolean( false ) )\n true\n\n\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false\n\n\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true\n\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false","isBoolean.isObject":"\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true","isBooleanArray":"\nisBooleanArray( value )\n Tests if a value is an array-like object of booleans.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object of booleans.\n\n Examples\n --------\n > var bool = isBooleanArray( [ true, false, true ] )\n true\n > bool = isBooleanArray( [ true, 'abc', false ] )\n false\n\n\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false\n\n\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true\n\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false","isBooleanArray.objects":"\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true","isBoxedPrimitive":"\nisBoxedPrimitive( value )\n Tests if a value is a JavaScript boxed primitive.\n\n Boxed primitive objects can be created with one of the following:\n\n - new Boolean()\n - new Number()\n - new String()\n - Object( Symbol() ) (ES6/ES2015)\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a JavaScript boxed primitive.\n\n Examples\n --------\n > var bool = isBoxedPrimitive( new Boolean( false ) )\n true\n > bool = isBoxedPrimitive( true )\n false\n\n See Also\n --------\n isPrimitive\n","isBuffer":"\nisBuffer( value )\n Tests if a value is a Buffer instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Buffer instance.\n\n Examples\n --------\n > var bool = isBuffer( new Buffer( 'beep' ) )\n true\n > bool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\n true\n > bool = isBuffer( {} )\n false\n > bool = isBuffer( [] )\n false\n\n","isCapitalized":"\nisCapitalized( value )\n Tests if a value is a string having an uppercase first character.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string with an uppercase first\n character.\n\n Examples\n --------\n > var bool = isCapitalized( 'Hello' )\n true\n > bool = isCapitalized( 'world' )\n false\n\n See Also\n --------\n isString\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value )\n Tests if a value is a matrix which is symmetric about its center.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a centrosymmetric matrix.\n\n Examples\n --------\n > var buf = [ 2, 1, 1, 2 ];\n > var M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isCentrosymmetricMatrix( M )\n true\n > bool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isCentrosymmetricMatrix( 3.14 )\n false\n > bool = isCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isCircular":"\nisCircular( value )\n Tests if an object-like value contains a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an object-like value contains a circular\n reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircular( obj )\n true\n > bool = isCircular( {} )\n false\n > bool = isCircular( null )\n false\n\n See Also\n --------\n isCircularArray, isCircularPlainObject\n","isCircularArray":"\nisCircularArray( value )\n Tests if a value is an array containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing a\n circular reference.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > arr.push( arr );\n > var bool = isCircularArray( arr )\n true\n > bool = isCircularArray( [] )\n false\n > bool = isCircularArray( null )\n false\n\n See Also\n --------\n isCircular, isCircularPlainObject\n","isCircularPlainObject":"\nisCircularPlainObject( value )\n Tests if a value is a plain object containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object containing a\n circular reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircularPlainObject( obj )\n true\n > bool = isCircularPlainObject( {} )\n false\n > bool = isCircularPlainObject( null )\n false\n\n See Also\n --------\n isCircular, isCircularArray\n","isClass":"\nisClass( value )\n Tests if a value is a class.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a class.\n\n Examples\n --------\n > var bool = isClass( class Person {} )\n true\n > bool = isClass( function Person() {} )\n false\n > bool = isClass( {} )\n false\n > bool = isClass( null )\n false\n > bool = isClass( true )\n false\n","isCollection":"\nisCollection( value )\n Tests if a value is a collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a collection.\n\n Examples\n --------\n > var bool = isCollection( [] )\n true\n > bool = isCollection( { 'length': 0 } )\n true\n > bool = isCollection( {} )\n false\n\n See Also\n --------\n isArrayLike, isArrayLikeObject\n","isComplex":"\nisComplex( value )\n Tests if a value is a 64-bit or 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit or 128-bit complex\n number.\n\n Examples\n --------\n > var bool = isComplex( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex( 3.14 )\n false\n > bool = isComplex( {} )\n false\n\n See Also\n --------\n isComplex64, isComplex128\n","isComplex64":"\nisComplex64( value )\n Tests if a value is a 64-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit complex number.\n\n Examples\n --------\n > var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex64( new Complex128( 3.0, 1.0 ) )\n false\n > bool = isComplex64( 3.14 )\n false\n > bool = isComplex64( {} )\n false\n\n See Also\n --------\n isComplex, isComplex128\n","isComplex64Array":"\nisComplex64Array( value )\n Tests if a value is a Complex64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex64Array.\n\n Examples\n --------\n > var bool = isComplex64Array( new Complex64Array( 10 ) )\n true\n > bool = isComplex64Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128Array, isComplexTypedArray\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64MatrixLike( M )\n true\n > bool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64MatrixLike( 3.14 )\n false\n > bool = isComplex64MatrixLike( {} )\n false\n\n See Also\n --------\n isComplex128MatrixLike, isndarrayLike, isMatrixLike\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value )\n Tests if a value is an ndarray-like object containing single-precision\n complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64ndarrayLike( M )\n true\n > bool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64ndarrayLike( 3.14 )\n false\n > bool = isComplex64ndarrayLike( {} )\n false\n\n See Also\n --------\n isComplex128ndarrayLike, isndarrayLike\n","isComplex64VectorLike":"\nisComplex64VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64VectorLike( M )\n true\n > bool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64VectorLike( 3.14 )\n false\n > bool = isComplex64VectorLike( {} )\n false\n\n See Also\n --------\n isComplex128VectorLike, isndarrayLike, isVectorLike\n","isComplex128":"\nisComplex128( value )\n Tests if a value is a 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 128-bit complex number.\n\n Examples\n --------\n > var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex128( new Complex64( 2.0, 2.0 ) )\n false\n > bool = isComplex128( 3.14 )\n false\n > bool = isComplex128( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64\n","isComplex128Array":"\nisComplex128Array( value )\n Tests if a value is a Complex128Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex128Array.\n\n Examples\n --------\n > var bool = isComplex128Array( new Complex128Array( 10 ) )\n true\n > bool = isComplex128Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex128, isComplex64Array, isComplexTypedArray\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing double-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex128';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex128MatrixLike( M )\n true\n > bool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128MatrixLike( 3.14 )\n false\n > bool = isComplex128MatrixLike( {} )\n false\n\n See Also\n --------\n isComplex64MatrixLike, isndarrayLike, isMatrixLike\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value )\n Tests if a value is an ndarray-like object containing double-precision\n complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n double-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex128';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex128ndarrayLike( M )\n true\n > bool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128ndarrayLike( 3.14 )\n false\n > bool = isComplex128ndarrayLike( {} )\n false\n\n See Also\n --------\n isComplex64ndarrayLike, isndarrayLike\n","isComplex128VectorLike":"\nisComplex128VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing double-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex128';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex128VectorLike( M )\n true\n > bool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128VectorLike( 3.14 )\n false\n > bool = isComplex128VectorLike( {} )\n false\n\n See Also\n --------\n isComplex64VectorLike, isndarrayLike, isVectorLike\n","isComplexLike":"\nisComplexLike( value )\n Tests if a value is a complex number-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a complex number-like object.\n\n Examples\n --------\n > var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplexLike( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplexLike( 3.14 )\n false\n > bool = isComplexLike( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128\n","isComplexTypedArray":"\nisComplexTypedArray( value )\n Tests if a value is a complex typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a complex typed array.\n\n Examples\n --------\n > var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n true\n\n See Also\n --------\n isComplex, isComplex64Array, isComplex128Array\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value )\n Tests if a value is complex-typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is complex-typed-array-like.\n\n Examples\n --------\n > var bool = isComplexTypedArrayLike( new Complex128Array() )\n true\n > bool = isComplexTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4,\n ... 'get': function get() {},\n ... 'set': function set() {}\n ... })\n true\n\n See Also\n --------\n isComplexLike, isComplexTypedArray, isComplex64Array, isComplex128Array\n","isComposite":"\nisComposite( value )\n Tests if a value is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a composite number.\n\n Examples\n --------\n > var bool = isComposite( 4.0 )\n true\n > bool = isComposite( new Number( 4.0 ) )\n true\n > bool = isComposite( 3.14 )\n false\n > bool = isComposite( -4.0 )\n false\n > bool = isComposite( null )\n false\n\n\nisComposite.isPrimitive( value )\n Tests if a value is a number primitive which is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n composite number.\n\n Examples\n --------\n > var bool = isComposite.isPrimitive( 4.0 )\n true\n > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n false\n\n\nisComposite.isObject( value )\n Tests if a value is a number object having a value which is a composite\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a composite number.\n\n Examples\n --------\n > var bool = isComposite.isObject( 4.0 )\n false\n > bool = isComposite.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isPrime\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value )\n Tests if a value is a number primitive which is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n composite number.\n\n Examples\n --------\n > var bool = isComposite.isPrimitive( 4.0 )\n true\n > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n false","isComposite.isObject":"\nisComposite.isObject( value )\n Tests if a value is a number object having a value which is a composite\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a composite number.\n\n Examples\n --------\n > var bool = isComposite.isObject( 4.0 )\n false\n > bool = isComposite.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isPrime","isConfigurableProperty":"\nisConfigurableProperty( value, property )\n Tests if an object's own property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurableProperty( obj, 'boop' )\n true\n > bool = isConfigurableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isReadableProperty, isWritableProperty\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurablePropertyIn( obj, 'boop' )\n true\n > bool = isConfigurablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isCubeNumber":"\nisCubeNumber( value )\n Tests if a value is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber( 8.0 )\n true\n > bool = isCubeNumber( new Number( 8.0 ) )\n true\n > bool = isCubeNumber( 3.14 )\n false\n > bool = isCubeNumber( -5.0 )\n false\n > bool = isCubeNumber( null )\n false\n\n\nisCubeNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a cube\n number.\n\n Examples\n --------\n > var bool = isCubeNumber.isPrimitive( 8.0 )\n true\n > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n false\n\n\nisCubeNumber.isObject( value )\n Tests if a value is a number object having a value which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber.isObject( 8.0 )\n false\n > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a cube\n number.\n\n Examples\n --------\n > var bool = isCubeNumber.isPrimitive( 8.0 )\n true\n > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n false","isCubeNumber.isObject":"\nisCubeNumber.isObject( value )\n Tests if a value is a number object having a value which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber.isObject( 8.0 )\n false\n > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber","isDataProperty":"\nisDataProperty( value, property )\n Tests if an object's own property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has a data descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataProperty( obj, 'boop' )\n true\n > bool = isDataProperty( obj, 'beep' )\n false\n\n See Also\n --------\n hasOwnProp, isAccessorProperty, isDataPropertyIn\n","isDataPropertyIn":"\nisDataPropertyIn( value, property )\n Tests if an object's own or inherited property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has a data\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataPropertyIn( obj, 'boop' )\n true\n > bool = isDataPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n hasProp, isAccessorPropertyIn, isDataProperty\n","isDataView":"\nisDataView( value )\n Tests if a value is a DataView.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a DataView.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 10 );\n > var bool = isDataView( new DataView( buf ) )\n true\n > bool = isDataView( [] )\n false\n\n See Also\n --------\n isArrayBuffer, isTypedArray\n","isDateObject":"\nisDateObject( value )\n Tests if a value is a Date object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Date object.\n\n Examples\n --------\n > var bool = isDateObject( new Date() )\n true\n > bool = isDateObject( '2017-01-01' )\n false\n\n","isDateObjectArray":"\nisDateObjectArray( value )\n Tests if a value is an array-like object containing only Date objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if value is an array-like object containing only Date\n objects.\n\n Examples\n --------\n > var bool = isDateObjectArray( [ new Date(), new Date() ] )\n true\n > bool = isDateObjectArray( [ {}, {} ] )\n false\n > bool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\n false\n > bool = isDateObjectArray( [] )\n false\n\n See Also\n --------\n isDateObject\n","isDigitString":"\nisDigitString( str )\n Tests whether a string contains only numeric digits.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only numeric digits.\n\n Examples\n --------\n > var bool = isDigitString( '0123456789' )\n true\n > bool = isDigitString( 'abcdef' )\n false\n > bool = isDigitString( '0xff' )\n false\n > bool = isDigitString( '' )\n false\n\n See Also\n --------\n isHexString, isString\n","isEmailAddress":"\nisEmailAddress( value )\n Tests if a value is an email address.\n\n Validation is not rigorous. *9* RFCs relate to email addresses, and\n accounting for all of them is a fool's errand. The function performs the\n simplest validation; i.e., requiring at least one `@` symbol.\n\n For rigorous validation, send a confirmation email. If the email bounces,\n consider the email invalid.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an email address.\n\n Examples\n --------\n > var bool = isEmailAddress( 'beep@boop.com' )\n true\n > bool = isEmailAddress( 'beep' )\n false\n > bool = isEmailAddress( null )\n false\n\n","isEmptyArray":"\nisEmptyArray( value )\n Tests if a value is an empty array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty array.\n\n Examples\n --------\n > var bool = isEmptyArray( [] )\n true\n > bool = isEmptyArray( [ 1, 2, 3 ] )\n false\n > bool = isEmptyArray( {} )\n false\n\n See Also\n --------\n isArray, isEmptyArrayLikeObject, isEmptyCollection\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value )\n Tests if a value is an empty array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an empty array-like object.\n\n Examples\n --------\n > var bool = isEmptyArrayLikeObject( [] )\n true\n > bool = isEmptyArrayLikeObject( { 'length': 0 } )\n true\n > bool = isEmptyArrayLikeObject( '' )\n false\n\n See Also\n --------\n isArrayLikeObject, isEmptyArray, isEmptyCollection\n","isEmptyCollection":"\nisEmptyCollection( value )\n Tests if a value is an empty collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty collection.\n\n Examples\n --------\n > var bool = isEmptyCollection( [] )\n true\n > bool = isEmptyCollection( { 'length': 0 } )\n true\n > bool = isEmptyCollection( [ 1, 2, 3 ] )\n false\n > bool = isEmptyCollection( {} )\n false\n\n See Also\n --------\n isCollection, isEmptyArray, isEmptyArrayLikeObject\n","isEmptyObject":"\nisEmptyObject( value )\n Tests if a value is an empty object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty object.\n\n Examples\n --------\n > var bool = isEmptyObject( {} )\n true\n > bool = isEmptyObject( { 'beep': 'boop' } )\n false\n > bool = isEmptyObject( [] )\n false\n\n See Also\n --------\n isObject, isPlainObject\n","isEmptyString":"\nisEmptyString( value )\n Tests if a value is an empty string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty string.\n\n Examples\n --------\n > var bool = isEmptyString( '' )\n true\n > bool = isEmptyString( new String( '' ) )\n true\n > bool = isEmptyString( 'beep' )\n false\n > bool = isEmptyString( [] )\n false\n\n\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false\n\n\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n See Also\n --------\n isString\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false","isEmptyString.isObject":"\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n See Also\n --------\n isString","isEnumerableProperty":"\nisEnumerableProperty( value, property )\n Tests if an object's own property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is enumerable.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isEnumerableProperty( beep, 'boop' )\n true\n > bool = isEnumerableProperty( beep, 'hasOwnProperty' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isEnumerablePropertyIn( obj, 'boop' )\n true\n > bool = isEnumerablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isError":"\nisError( value )\n Tests if a value is an Error object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Error object.\n\n Examples\n --------\n > var bool = isError( new Error( 'beep' ) )\n true\n > bool = isError( {} )\n false\n\n","isEvalError":"\nisEvalError( value )\n Tests if a value is an EvalError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided an EvalError (or a descendant) object,\n false positives may occur due to the fact that the EvalError constructor\n inherits from Error and has no internal class of its own. Hence, EvalError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an EvalError object.\n\n Examples\n --------\n > var bool = isEvalError( new EvalError( 'beep' ) )\n true\n > bool = isEvalError( {} )\n false\n\n See Also\n --------\n isError\n","isEven":"\nisEven( value )\n Tests if a value is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether is an even number.\n\n Examples\n --------\n > var bool = isEven( 4.0 )\n true\n > bool = isEven( new Number( 4.0 ) )\n true\n > bool = isEven( 3.0 )\n false\n > bool = isEven( -3.14 )\n false\n > bool = isEven( null )\n false\n\n\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false\n\n\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n See Also\n --------\n isOdd\n","isEven.isPrimitive":"\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false","isEven.isObject":"\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n See Also\n --------\n isOdd","isFalsy":"\nisFalsy( value )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is falsy.\n\n Examples\n --------\n > var bool = isFalsy( false )\n true\n > bool = isFalsy( '' )\n true\n > bool = isFalsy( 0 )\n true\n > bool = isFalsy( null )\n true\n > bool = isFalsy( void 0 )\n true\n > bool = isFalsy( NaN )\n true\n > bool = isFalsy( {} )\n false\n > bool = isFalsy( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n","isFalsyArray":"\nisFalsyArray( value )\n Tests if a value is an array-like object containing only falsy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only falsy values.\n\n Examples\n --------\n > var bool = isFalsyArray( [ null, '' ] )\n true\n > bool = isFalsyArray( [ {}, [] ] )\n false\n > bool = isFalsyArray( [] )\n false\n\n See Also\n --------\n isFalsy, isTruthyArray\n","isFinite":"\nisFinite( value )\n Tests if a value is a finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a finite number.\n\n Examples\n --------\n > var bool = isFinite( 5.0 )\n true\n > bool = isFinite( new Number( 5.0 ) )\n true\n > bool = isFinite( 1.0/0.0 )\n false\n > bool = isFinite( null )\n false\n\n\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isFiniteArray, isInfinite\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false","isFinite.isObject":"\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isFiniteArray, isInfinite","isFiniteArray":"\nisFiniteArray( value )\n Tests if a value is an array-like object of finite numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of finite\n numbers.\n\n Examples\n --------\n > var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n false\n\n\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isFinite, isInfinite\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isFiniteArray.objects":"\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isFinite, isInfinite","isFloat32Array":"\nisFloat32Array( value )\n Tests if a value is a Float32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float32Array.\n\n Examples\n --------\n > var bool = isFloat32Array( new Float32Array( 10 ) )\n true\n > bool = isFloat32Array( [] )\n false\n\n See Also\n --------\n isFloat64Array\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32MatrixLike( M )\n true\n > bool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32MatrixLike( 3.14 )\n false\n > bool = isFloat32MatrixLike( {} )\n false\n\n See Also\n --------\n isFloat64MatrixLike, isndarrayLike, isMatrixLike\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value )\n Tests if a value is an ndarray-like object containing single-precision\n floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32ndarrayLike( M )\n true\n > bool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32ndarrayLike( 3.14 )\n false\n > bool = isFloat32ndarrayLike( {} )\n false\n\n See Also\n --------\n isFloat64ndarrayLike, isndarrayLike\n","isFloat32VectorLike":"\nisFloat32VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32VectorLike( M )\n true\n > bool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32VectorLike( 3.14 )\n false\n > bool = isFloat32VectorLike( {} )\n false\n\n See Also\n --------\n isFloat64VectorLike, isndarrayLike, isVectorLike\n","isFloat64Array":"\nisFloat64Array( value )\n Tests if a value is a Float64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float64Array.\n\n Examples\n --------\n > var bool = isFloat64Array( new Float64Array( 10 ) )\n true\n > bool = isFloat64Array( [] )\n false\n\n See Also\n --------\n isFloat32Array\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64MatrixLike( M )\n true\n > bool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64MatrixLike( 3.14 )\n false\n > bool = isFloat64MatrixLike( {} )\n false\n\n See Also\n --------\n isFloat32MatrixLike, isndarrayLike, isMatrixLike\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value )\n Tests if a value is an ndarray-like object containing double-precision\n floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64ndarrayLike( M )\n true\n > bool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64ndarrayLike( 3.14 )\n false\n > bool = isFloat64ndarrayLike( {} )\n false\n\n See Also\n --------\n isFloat32ndarrayLike, isndarrayLike\n","isFloat64VectorLike":"\nisFloat64VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64VectorLike( M )\n true\n > bool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64VectorLike( 3.14 )\n false\n > bool = isFloat64VectorLike( {} )\n false\n\n See Also\n --------\n isFloat32VectorLike, isndarrayLike, isVectorLike\n","isFunction":"\nisFunction( value )\n Tests if a value is a function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a function.\n\n Examples\n --------\n > function beep() {};\n > var bool = isFunction( beep )\n true\n > bool = isFunction( {} )\n false\n\n","isFunctionArray":"\nisFunctionArray( value )\n Tests if a value is an array-like object containing only functions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n functions.\n\n Examples\n --------\n > function beep() {};\n > function boop() {};\n > var bool = isFunctionArray( [ beep, boop ] )\n true\n > bool = isFunctionArray( [ {}, beep ] )\n false\n > bool = isFunctionArray( [] )\n false\n\n See Also\n --------\n isArray\n","isGeneratorObject":"\nisGeneratorObject( value )\n Tests if a value is a generator object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a generator object.\n\n Examples\n --------\n > function* generateID() {\n ... var idx = 0;\n ... while ( idx < idx+1 ) {\n ... yield idx;\n ... idx += 1;\n ... }\n ... };\n > var bool = isGeneratorObject( generateID() )\n true\n > bool = isGeneratorObject( generateID )\n false\n > bool = isGeneratorObject( {} )\n false\n > bool = isGeneratorObject( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObjectLike\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value )\n Tests if a value is generator object-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is generator object-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {},\n ... 'return': function noop() {},\n ... 'throw': function noop() {}\n ... };\n > var bool = isGeneratorObjectLike( obj )\n true\n > bool = isGeneratorObjectLike( {} )\n false\n > bool = isGeneratorObjectLike( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObject\n","isgzipBuffer":"\nisgzipBuffer( value )\n Tests if a value is a gzip buffer.\n\n A gzip buffer is defined as either a Node.js Buffer or Uint8Array which\n contains a 10-byte header, a body containing the compressed payload, and an\n 8-byte footer containing a CRC-32 checksum and the length of the original\n uncompressed data, modulo 2^32.\n\n This function only examines the 10-byte header to ensure the header includes\n the expected magic number and compression method. The function does not\n perform an integrity check.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a gzip buffer.\n\n Examples\n --------\n > var buf = new Uint8Array( 20 );\n > buf[ 0 ] = 31; // 0x1f => magic number\n > buf[ 1 ] = 139; // 0x8b\n > buf[ 2 ] = 8; // 0x08 => compression method\n > var bool = isgzipBuffer( buf )\n true\n > bool = isgzipBuffer( [] )\n false\n\n See Also\n --------\n isBuffer, isUint8Array\n","isHexString":"\nisHexString( str )\n Tests whether a string contains only hexadecimal digits.\n\n The function does not recognize `x` (as in the standard `0x` prefix).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only hexadecimal digits.\n\n Examples\n --------\n > var bool = isHexString( '0123456789abcdefABCDEF' )\n true\n > bool = isHexString( '0xffffff' )\n false\n > bool = isHexString( 'x' )\n false\n > bool = isHexString( '' )\n false\n\n See Also\n --------\n isString\n","isInfinite":"\nisInfinite( value )\n Tests if a value is an infinite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an infinite number.\n\n Examples\n --------\n > var bool = isInfinite( 1.0/0.0 )\n true\n > bool = isInfinite( new Number( -1.0/0.0 ) )\n true\n > bool = isInfinite( 5.0 )\n false\n > bool = isInfinite( '1.0/0.0' )\n false\n\n\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false\n\n\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n See Also\n --------\n isFinite\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false","isInfinite.isObject":"\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n See Also\n --------\n isFinite","isInheritedProperty":"\nisInheritedProperty( value, property )\n Tests if an object has an inherited property.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has an inherited property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isInheritedProperty( beep, 'boop' )\n false\n > bool = isInheritedProperty( beep, 'toString' )\n true\n > bool = isInheritedProperty( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp, hasProp\n","isInt8Array":"\nisInt8Array( value )\n Tests if a value is an Int8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int8Array.\n\n Examples\n --------\n > var bool = isInt8Array( new Int8Array( 10 ) )\n true\n > bool = isInt8Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt32Array\n","isInt16Array":"\nisInt16Array( value )\n Tests if a value is an Int16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int16Array.\n\n Examples\n --------\n > var bool = isInt16Array( new Int16Array( 10 ) )\n true\n > bool = isInt16Array( [] )\n false\n\n See Also\n --------\n isInt32Array, isInt8Array\n","isInt32Array":"\nisInt32Array( value )\n Tests if a value is an Int32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int32Array.\n\n Examples\n --------\n > var bool = isInt32Array( new Int32Array( 10 ) )\n true\n > bool = isInt32Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt8Array\n","isInteger":"\nisInteger( value )\n Tests if a value is an integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an integer.\n\n Examples\n --------\n > var bool = isInteger( 5.0 )\n true\n > bool = isInteger( new Number( 5.0 ) )\n true\n > bool = isInteger( -3.14 )\n false\n > bool = isInteger( null )\n false\n\n\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isNumber\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false","isInteger.isObject":"\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isNumber","isIntegerArray":"\nisIntegerArray( value )\n Tests if a value is an array-like object of integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of integer\n values.\n\n Examples\n --------\n > var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isIntegerArray( [ -3.0, '3.0' ] )\n false\n\n\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isIntegerArray.objects":"\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isIterableLike":"\nisIterableLike( value )\n Tests if a value is iterable-like.\n\n In order to be iterable, an object must implement the @@iterator method,\n which, when called, returns an iterator protocol-compliant object.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n In environments lacking Symbol.iterator support, this function always\n returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterable-like.\n\n Examples\n --------\n > var bool = isIterableLike( [ 1, 2, 3 ] )\n \n > bool = isIterableLike( {} )\n false\n > bool = isIterableLike( null )\n false\n\n See Also\n --------\n isIteratorLike\n","isIteratorLike":"\nisIteratorLike( value )\n Tests if a value is iterator-like.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterator-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {}\n ... };\n > var bool = isIteratorLike( obj )\n true\n > bool = isIteratorLike( {} )\n false\n > bool = isIteratorLike( null )\n false\n\n See Also\n --------\n isIterableLike\n","isJSON":"\nisJSON( value )\n Tests if a value is a parseable JSON string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a parseable JSON string.\n\n Examples\n --------\n > var bool = isJSON( '{\"a\":5}' )\n true\n > bool = isJSON( '{a\":5}' )\n false\n\n","isLeapYear":"\nisLeapYear( value )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n\n A leap year is defined as any year which is exactly divisible by 4, except\n for years which are exactly divisible by 100 and not by 400. In this\n definition, 100 corresponds to years marking a new century, and 400\n corresponds to the length of the *leap cycle*.\n\n If not provided any arguments, the function returns a boolean indicating\n if the current year (according to local time) is a leap year.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value corresponds to a leap year.\n\n Examples\n --------\n > var bool = isLeapYear( new Date() )\n \n > bool = isLeapYear( 1996 )\n true\n > bool = isLeapYear( 2001 )\n false\n\n","isLocalhost":"\nisLocalhost( value )\n Tests whether a value is a localhost hostname.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a localhost hostname.\n\n Examples\n --------\n > var bool = isLocalhost( 'localhost' )\n true\n > bool = isLocalhost( '127.0.0.1' )\n true\n > bool = isLocalhost( 'stdlib.io' )\n false\n","isLowercase":"\nisLowercase( value )\n Tests if a value is a lowercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a lowercase string.\n\n Examples\n --------\n > var bool = isLowercase( 'hello' )\n true\n > bool = isLowercase( 'World' )\n false\n\n See Also\n --------\n isString, isUppercase\n","isMatrixLike":"\nisMatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isMatrixLike( M )\n true\n > bool = isMatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isMatrixLike( 3.14 )\n false\n > bool = isMatrixLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isndarrayLike, isTypedArrayLike, isVectorLike\n","isMethod":"\nisMethod( value, property )\n Tests if an object has a specified method name.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n The function only searches own properties.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': function beep() { return 'beep'; } };\n > var bool = isMethod( beep, 'boop' )\n true\n > bool = isMethod( beep, 'toString' )\n false\n\n See Also\n --------\n hasOwnProp, isFunction, isMethodIn\n","isMethodIn":"\nisMethodIn( value, property )\n Tests if an object has a specified method name, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isMethodIn( beep, 'toString' )\n true\n > bool = isMethodIn( beep, 'boop' )\n false\n > bool = isMethodIn( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp, isFunction, isMethod\n","isMultiSlice":"\nisMultiSlice( value )\n Tests if a value is a MultiSlice object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a MultiSlice object.\n\n Examples\n --------\n > var bool = isMultiSlice( new MultiSlice() )\n true\n > bool = isMultiSlice( 3.14 )\n false\n > bool = isMultiSlice( {} )\n false\n\n See Also\n --------\n isSlice, MultiSlice\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value )\n Tests if a value is named typed tuple-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is named typed tuple-like.\n\n Examples\n --------\n > var Point = namedtypedtuple( [ 'x', 'y' ] );\n > var p = new Point();\n > var bool = isNamedTypedTupleLike( p )\n true\n > bool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isNamedTypedTupleLike( 3.14 )\n false\n > bool = isNamedTypedTupleLike( {} )\n false\n\n See Also\n --------\n namedtypedtuple\n","isnan":"\nisnan( value )\n Tests if a value is NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is NaN.\n\n Examples\n --------\n > var bool = isnan( NaN )\n true\n > bool = isnan( new Number( NaN ) )\n true\n > bool = isnan( 3.14 )\n false\n > bool = isnan( null )\n false\n\n\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false\n\n\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n See Also\n --------\n isNumber\n","isnan.isPrimitive":"\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false","isnan.isObject":"\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n See Also\n --------\n isNumber","isNaNArray":"\nisNaNArray( value )\n Tests if a value is an array-like object containing only NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n NaN values.\n\n Examples\n --------\n > var bool = isNaNArray( [ NaN, NaN, NaN ] )\n true\n > bool = isNaNArray( [ NaN, 2 ] )\n false\n\n\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true\n\n\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n See Also\n --------\n isnan\n","isNaNArray.primitives":"\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true","isNaNArray.objects":"\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n See Also\n --------\n isnan","isNativeFunction":"\nisNativeFunction( value )\n Tests if a value is a native function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a native function.\n\n Examples\n --------\n > var bool = isNativeFunction( Date )\n true\n > function beep() {};\n > bool = isNativeFunction( beep )\n false\n > bool = isNativeFunction( {} )\n false\n\n See Also\n --------\n isFunction\n","isndarrayLike":"\nisndarrayLike( value )\n Tests if a value is ndarray-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is ndarray-like.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isndarrayLike( M )\n true\n > bool = isndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isndarrayLike( 3.14 )\n false\n > bool = isndarrayLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isTypedArrayLike, isVectorLike\n","isNegativeInteger":"\nisNegativeInteger( value )\n Tests if a value is a negative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative integer.\n\n Examples\n --------\n > var bool = isNegativeInteger( -5.0 )\n true\n > bool = isNegativeInteger( new Number( -5.0 ) )\n true\n > bool = isNegativeInteger( 5.0 )\n false\n > bool = isNegativeInteger( -3.14 )\n false\n > bool = isNegativeInteger( null )\n false\n\n\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isNegativeIntegerArray":"\nisNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only negative integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative integers.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNegativeNumber":"\nisNegativeNumber( value )\n Tests if a value is a negative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative number.\n\n Examples\n --------\n > var bool = isNegativeNumber( -5.0 )\n true\n > bool = isNegativeNumber( new Number( -5.0 ) )\n true\n > bool = isNegativeNumber( -3.14 )\n true\n > bool = isNegativeNumber( 5.0 )\n false\n > bool = isNegativeNumber( null )\n false\n\n\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n See Also\n --------\n isNumber\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n See Also\n --------\n isNumber","isNegativeNumberArray":"\nisNegativeNumberArray( value )\n Tests if a value is an array-like object containing only negative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNegativeZero":"\nisNegativeZero( value )\n Tests if a value is negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero( -0.0 )\n true\n > bool = isNegativeZero( new Number( -0.0 ) )\n true\n > bool = isNegativeZero( -3.14 )\n false\n > bool = isNegativeZero( 0.0 )\n false\n > bool = isNegativeZero( null )\n false\n\n\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false\n\n\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n See Also\n --------\n isNumber, isPositiveZero\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false","isNegativeZero.isObject":"\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n See Also\n --------\n isNumber, isPositiveZero","isNodeBuiltin":"\nisNodeBuiltin( str )\n Tests whether a string matches a Node.js built-in module name.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string matches a Node.js built-in module\n name.\n\n Examples\n --------\n > var bool = isNodeBuiltin( 'cluster' )\n true\n > bool = isNodeBuiltin( 'crypto' )\n true\n > bool = isNodeBuiltin( 'fs-extra' )\n false\n > bool = isNodeBuiltin( '' )\n false\n\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value )\n Tests if a value is Node duplex stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node duplex stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Duplex;\n > s = new Stream();\n > var bool = isNodeDuplexStreamLike( s )\n true\n > bool = isNodeDuplexStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value )\n Tests if a value is Node readable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node readable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Readable;\n > s = new Stream();\n > var bool = isNodeReadableStreamLike( s )\n true\n > bool = isNodeReadableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeREPL":"\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if running in a Node.js REPL environment.\n\n Examples\n --------\n > var bool = isNodeREPL()\n \n\n","isNodeStreamLike":"\nisNodeStreamLike( value )\n Tests if a value is Node stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Stream;\n > s = new Stream();\n > var bool = isNodeStreamLike( s )\n true\n > bool = isNodeStreamLike( {} )\n false\n\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value )\n Tests if a value is Node transform stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node transform stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Transform;\n > s = new Stream();\n > var bool = isNodeTransformStreamLike( s )\n true\n > bool = isNodeTransformStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value )\n Tests if a value is Node writable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node writable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Writable;\n > s = new Stream();\n > var bool = isNodeWritableStreamLike( s )\n true\n > bool = isNodeWritableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value, property )\n Tests if an object's own property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurableProperty( obj, 'boop' )\n false\n > bool = isNonConfigurableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurablePropertyIn( obj, 'boop' )\n false\n > bool = isNonConfigurablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value, property )\n Tests if an object's own property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerableProperty( obj, 'boop' )\n false\n > bool = isNonEnumerableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadableProperty, isWritableProperty\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerablePropertyIn( obj, 'boop' )\n false\n > bool = isNonEnumerablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadablePropertyIn, isWritablePropertyIn\n","isNonNegativeFinite":"\nisNonNegativeFinite( value )\n Tests if a value is a nonnegative finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative finite number.\n\n Examples\n --------\n > var bool = isNonNegativeFinite( 5.0 )\n true\n > bool = isNonNegativeFinite( new Number( 5.0 ) )\n true\n > bool = isNonNegativeFinite( 3.14 )\n true\n > bool = isNonNegativeFinite( -5.0 )\n false\n > bool = isNonNegativeFinite( null )\n false\n > bool = isNonNegativeFinite( PINF )\n false\n\n\nisNonNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeFinite.isObject( value )\n Tests if a value is a number object having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a \n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isObject( 3.0 )\n false\n > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonNegativeNumber, isNumber\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value )\n Tests if a value is a number object having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a \n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isObject( 3.0 )\n false\n > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonNegativeNumber, isNumber","isNonNegativeInteger":"\nisNonNegativeInteger( value )\n Tests if a value is a nonnegative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative integer.\n\n Examples\n --------\n > var bool = isNonNegativeInteger( 5.0 )\n true\n > bool = isNonNegativeInteger( new Number( 5.0 ) )\n true\n > bool = isNonNegativeInteger( 3.14 )\n false\n > bool = isNonNegativeInteger( -5.0 )\n false\n > bool = isNonNegativeInteger( null )\n false\n\n\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNonNegativeNumber, isNumber\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNonNegativeNumber, isNumber","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative integers.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonNegativeNumber":"\nisNonNegativeNumber( value )\n Tests if a value is a nonnegative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative number.\n\n Examples\n --------\n > var bool = isNonNegativeNumber( 5.0 )\n true\n > bool = isNonNegativeNumber( new Number( 5.0 ) )\n true\n > bool = isNonNegativeNumber( 3.14 )\n true\n > bool = isNonNegativeNumber( -5.0 )\n false\n > bool = isNonNegativeNumber( null )\n false\n\n\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNonNegativeFinite, isNonNegativeInteger, isNumber\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNonNegativeFinite, isNonNegativeInteger, isNumber","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonPositiveInteger":"\nisNonPositiveInteger( value )\n Tests if a value is a nonpositive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive integer.\n\n Examples\n --------\n > var bool = isNonPositiveInteger( -5.0 )\n true\n > bool = isNonPositiveInteger( new Number( -5.0 ) )\n true\n > bool = isNonPositiveInteger( 5.0 )\n false\n > bool = isNonPositiveInteger( -3.14 )\n false\n > bool = isNonPositiveInteger( null )\n false\n\n\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive integers.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonPositiveNumber":"\nisNonPositiveNumber( value )\n Tests if a value is a nonpositive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive number.\n\n Examples\n --------\n > var bool = isNonPositiveNumber( -5.0 )\n true\n > bool = isNonPositiveNumber( new Number( -5.0 ) )\n true\n > bool = isNonPositiveNumber( -3.14 )\n true\n > bool = isNonPositiveNumber( 5.0 )\n false\n > bool = isNonPositiveNumber( null )\n false\n\n\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isNumber","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value )\n Tests if a value is a non-symmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a non-symmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 2, 3, 4 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isNonSymmetricMatrix( M )\n true\n > bool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isNonSymmetricMatrix( 3.14 )\n false\n > bool = isNonSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isNull":"\nisNull( value )\n Tests if a value is null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is null.\n\n Examples\n --------\n > var bool = isNull( null )\n true\n > bool = isNull( true )\n false\n\n See Also\n --------\n isUndefined, isUndefinedOrNull\n","isNullArray":"\nisNullArray( value )\n Tests if a value is an array-like object containing only null values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n null values.\n\n Examples\n --------\n > var bool = isNullArray( [ null, null, null ] )\n true\n > bool = isNullArray( [ NaN, 2, null ] )\n false\n\n See Also\n --------\n isArray, isNull\n","isNumber":"\nisNumber( value )\n Tests if a value is a number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number.\n\n Examples\n --------\n > var bool = isNumber( 3.14 )\n true\n > bool = isNumber( new Number( 3.14 ) )\n true\n > bool = isNumber( NaN )\n true\n > bool = isNumber( null )\n false\n\n\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false\n\n\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true\n\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false","isNumber.isObject":"\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true","isNumberArray":"\nisNumberArray( value )\n Tests if a value is an array-like object containing only numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n numbers.\n\n Examples\n --------\n > var bool = isNumberArray( [ 1, 2, 3 ] )\n true\n > bool = isNumberArray( [ '1', 2, 3 ] )\n false\n\n\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false\n\n\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isNumber, isNumericArray\n","isNumberArray.primitives":"\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false","isNumberArray.objects":"\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isNumber, isNumericArray","isNumericArray":"\nisNumericArray( value )\n Tests if a value is a numeric array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a numeric array.\n\n Examples\n --------\n > var bool = isNumericArray( new Int8Array( 10 ) )\n true\n > bool = isNumericArray( [ 1, 2, 3 ] )\n true\n > bool = isNumericArray( [ '1', '2', '3' ] )\n false\n\n See Also\n --------\n isArray, isNumberArray, isTypedArray\n\n","isObject":"\nisObject( value )\n Tests if a value is an object; e.g., `{}`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an object.\n\n Examples\n --------\n > var bool = isObject( {} )\n true\n > bool = isObject( true )\n false\n\n See Also\n --------\n isObjectLike, isPlainObject\n","isObjectArray":"\nisObjectArray( value )\n Tests if a value is an array-like object containing only objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n objects.\n\n Examples\n --------\n > var bool = isObjectArray( [ {}, new Number(3.0) ] )\n true\n > bool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isObject\n","isObjectLike":"\nisObjectLike( value )\n Tests if a value is object-like.\n\n Return values are the same as would be obtained using the built-in `typeof`\n operator except that `null` is not considered an object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is object-like.\n\n Examples\n --------\n > var bool = isObjectLike( {} )\n true\n > bool = isObjectLike( [] )\n true\n > bool = isObjectLike( null )\n false\n\n See Also\n --------\n isObject, isPlainObject\n","isOdd":"\nisOdd( value )\n Tests if a value is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an odd number.\n\n Examples\n --------\n > var bool = isOdd( 5.0 )\n true\n > bool = isOdd( new Number( 5.0 ) )\n true\n > bool = isOdd( 4.0 )\n false\n > bool = isOdd( new Number( 4.0 ) )\n false\n > bool = isOdd( -3.14 )\n false\n > bool = isOdd( null )\n false\n\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false\n\n\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n See Also\n --------\n isEven\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false","isOdd.isObject":"\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n See Also\n --------\n isEven","isoWeeksInYear":"\nisoWeeksInYear( [year] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n\n By default, the function returns the number of ISO weeks in the current year\n (according to local time). To determine the number of ISO weeks for a\n particular year, provide either a year or a `Date` object.\n\n Parameters\n ----------\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Number of ISO weeks in a year.\n\n Examples\n --------\n > var num = isoWeeksInYear()\n \n > num = isoWeeksInYear( 2015 )\n 53\n > num = isoWeeksInYear( 2017 )\n 52\n\n","isPersymmetricMatrix":"\nisPersymmetricMatrix( value )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a persymmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 2, 3, 1 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isPersymmetricMatrix( M )\n true\n > bool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isPersymmetricMatrix( 3.14 )\n false\n > bool = isPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isPlainObject":"\nisPlainObject( value )\n Tests if a value is a plain object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object.\n\n Examples\n --------\n > var bool = isPlainObject( {} )\n true\n > bool = isPlainObject( null )\n false\n\n See Also\n --------\n isObject\n","isPlainObjectArray":"\nisPlainObjectArray( value )\n Tests if a value is an array-like object containing only plain objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n plain objects.\n\n Examples\n --------\n > var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isPlainObjectArray( [ {}, new Number(3.0) ] )\n false\n > bool = isPlainObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPlainObject\n","isPositiveInteger":"\nisPositiveInteger( value )\n Tests if a value is a positive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive integer.\n\n Examples\n --------\n > var bool = isPositiveInteger( 5.0 )\n true\n > bool = isPositiveInteger( new Number( 5.0 ) )\n true\n > bool = isPositiveInteger( 3.14 )\n false\n > bool = isPositiveInteger( -5.0 )\n false\n > bool = isPositiveInteger( null )\n false\n\n\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isPositiveIntegerArray":"\nisPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only positive integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive integers.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isInteger, isPositiveInteger\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isInteger, isPositiveInteger","isPositiveNumber":"\nisPositiveNumber( value )\n Tests if a value is a positive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive number.\n\n Examples\n --------\n > var bool = isPositiveNumber( 5.0 )\n true\n > bool = isPositiveNumber( new Number( 5.0 ) )\n true\n > bool = isPositiveNumber( 3.14 )\n true\n > bool = isPositiveNumber( -5.0 )\n false\n > bool = isPositiveNumber( null )\n false\n\n\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber","isPositiveNumberArray":"\nisPositiveNumberArray( value )\n Tests if a value is an array-like object containing only positive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive numbers.\n\n Examples\n --------\n > var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isNumber, isPositiveNumber\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isNumber, isPositiveNumber","isPositiveZero":"\nisPositiveZero( value )\n Tests if a value is positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero( 0.0 )\n true\n > bool = isPositiveZero( new Number( 0.0 ) )\n true\n > bool = isPositiveZero( -3.14 )\n false\n > bool = isPositiveZero( -0.0 )\n false\n > bool = isPositiveZero( null )\n false\n\n\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false\n\n\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n See Also\n --------\n isNumber, isNegativeZero\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false","isPositiveZero.isObject":"\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n See Also\n --------\n isNumber, isNegativeZero","isPrime":"\nisPrime( value )\n Tests if a value is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a prime number.\n\n Examples\n --------\n > var bool = isPrime( 5.0 )\n true\n > bool = isPrime( new Number( 5.0 ) )\n true\n > bool = isPrime( 3.14 )\n false\n > bool = isPrime( -5.0 )\n false\n > bool = isPrime( null )\n false\n\n\nisPrime.isPrimitive( value )\n Tests if a value is a number primitive which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a prime\n number.\n\n Examples\n --------\n > var bool = isPrime.isPrimitive( 5.0 )\n true\n > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n false\n\n\nisPrime.isObject( value )\n Tests if a value is a number object having a value which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a prime number.\n\n Examples\n --------\n > var bool = isPrime.isObject( 5.0 )\n false\n > bool = isPrime.isObject( new Number( 5.0 ) )\n true\n\n\n See Also\n --------\n isComposite, isInteger, isNumber\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value )\n Tests if a value is a number primitive which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a prime\n number.\n\n Examples\n --------\n > var bool = isPrime.isPrimitive( 5.0 )\n true\n > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n false","isPrime.isObject":"\nisPrime.isObject( value )\n Tests if a value is a number object having a value which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a prime number.\n\n Examples\n --------\n > var bool = isPrime.isObject( 5.0 )\n false\n > bool = isPrime.isObject( new Number( 5.0 ) )\n true\n\n\n See Also\n --------\n isComposite, isInteger, isNumber","isPrimitive":"\nisPrimitive( value )\n Tests if a value is a JavaScript primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a JavaScript primitive.\n\n Examples\n --------\n > var bool = isPrimitive( true )\n true\n > bool = isPrimitive( {} )\n false\n\n See Also\n --------\n isBoxedPrimitive\n","isPrimitiveArray":"\nisPrimitiveArray( value )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n JavaScript primitives.\n\n Examples\n --------\n > var bool = isPrimitiveArray( [ '3', 2, null ] )\n true\n > bool = isPrimitiveArray( [ {}, 2, 1 ] )\n false\n > bool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPrimitive\n","isPRNGLike":"\nisPRNGLike( value )\n Tests if a value is PRNG-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is PRNG-like.\n\n Examples\n --------\n > var bool = isPRNGLike( base.random.randu )\n true\n > bool = isPRNGLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isPRNGLike( 3.14 )\n false\n > bool = isPRNGLike( {} )\n false\n\n","isProbability":"\nisProbability( value )\n Tests if a value is a probability.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a probability.\n\n Examples\n --------\n > var bool = isProbability( 0.5 )\n true\n > bool = isProbability( new Number( 0.5 ) )\n true\n > bool = isProbability( 3.14 )\n false\n > bool = isProbability( -5.0 )\n false\n > bool = isProbability( null )\n false\n\n\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false\n\n\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false","isProbability.isObject":"\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n See Also\n --------\n isNumber","isProbabilityArray":"\nisProbabilityArray( value )\n Tests if a value is an array-like object containing only probabilities.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\n true\n > bool = isProbabilityArray( [ 0.8, 1.2 ] )\n false\n > bool = isProbabilityArray( [ 0.8, '0.2' ] )\n false\n\n\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false\n\n\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n See Also\n --------\n isArray, isProbability\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false","isProbabilityArray.objects":"\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n See Also\n --------\n isArray, isProbability","isPropertyKey":"\nisPropertyKey( value )\n Tests whether a value is a property key.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether value is a property key.\n\n Examples\n --------\n > var out = isPropertyKey( 'foo' )\n true\n > out = isPropertyKey( 1 )\n true\n > out = isPropertyKey( true )\n false\n\n See Also\n --------\n isString, isSymbol, isNonNegativeInteger, hasOwnProp, hasProp","isPrototypeOf":"\nisPrototypeOf( value, proto )\n Tests if an object's prototype chain contains a provided prototype.\n\n The function returns `false` if provided a primitive value.\n\n This function is generally more robust than the `instanceof` operator (e.g.,\n where inheritance is performed without using constructors).\n\n Parameters\n ----------\n value: any\n Input value.\n\n proto: Object|Function\n Prototype.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a provided prototype exists in a prototype chain.\n\n Examples\n --------\n > function Foo() { return this; };\n > function Bar() { return this; };\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var bool = isPrototypeOf( bar, Foo.prototype )\n true\n\n See Also\n --------\n getPrototypeOf\n","isRangeError":"\nisRangeError( value )\n Tests if a value is a RangeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a RangeError (or a descendant) object,\n false positives may occur due to the fact that the RangeError constructor\n inherits from Error and has no internal class of its own. Hence, RangeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a RangeError object.\n\n Examples\n --------\n > var bool = isRangeError( new RangeError( 'beep' ) )\n true\n > bool = isRangeError( {} )\n false\n\n See Also\n --------\n isError\n","isReadableProperty":"\nisReadableProperty( value, property )\n Tests if an object's own property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadableProperty( obj, 'boop' )\n true\n > bool = isReadableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isReadablePropertyIn, isWritableProperty\n","isReadablePropertyIn":"\nisReadablePropertyIn( value, property )\n Tests if an object's own or inherited property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadablePropertyIn( obj, 'boop' )\n true\n > bool = isReadablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isReadableProperty, isWritablePropertyIn\n","isReadOnlyProperty":"\nisReadOnlyProperty( value, property )\n Tests if an object's own property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is read-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyProperty( obj, 'boop' )\n true\n > bool = isReadOnlyProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadableProperty, isWritableProperty\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is read-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyPropertyIn( obj, 'boop' )\n true\n > bool = isReadOnlyPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isReadWriteProperty":"\nisReadWriteProperty( value, property )\n Tests if an object's own property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWriteProperty( obj, 'boop' )\n true\n > bool = isReadWriteProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadableProperty, isWritableProperty\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value, property )\n Tests if an object's own or inherited property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable\n and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWritePropertyIn( obj, 'boop' )\n true\n > bool = isReadWritePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadablePropertyIn, isWritablePropertyIn\n","isReferenceError":"\nisReferenceError( value )\n Tests if a value is a ReferenceError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a ReferenceError (or a descendant)\n object, false positives may occur due to the fact that the ReferenceError\n constructor inherits from Error and has no internal class of its own.\n Hence, ReferenceError impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a ReferenceError object.\n\n Examples\n --------\n > var bool = isReferenceError( new ReferenceError( 'beep' ) )\n true\n > bool = isReferenceError( {} )\n false\n\n See Also\n --------\n isError\n","isRegExp":"\nisRegExp( value )\n Tests if a value is a regular expression.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression.\n\n Examples\n --------\n > var bool = isRegExp( /\\.+/ )\n true\n > bool = isRegExp( {} )\n false\n\n","isRegExpString":"\nisRegExpString( value )\n Tests if a value is a regular expression string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression string.\n\n Examples\n --------\n > var bool = isRegExpString( '/beep/' )\n true\n > bool = isRegExpString( 'beep' )\n false\n > bool = isRegExpString( '' )\n false\n > bool = isRegExpString( null )\n false\n\n See Also\n --------\n isRegExp\n","isRelativePath":"\nisRelativePath( value )\n Tests if a value is a relative path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a relative path.\n\n Examples\n --------\n // Windows environments:\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n\n // POSIX environments:\n > bool = isRelativePath( './foo/bar/baz' )\n true\n\n\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false\n\n\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isAbsolutePath\n","isRelativePath.posix":"\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false","isRelativePath.win32":"\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isAbsolutePath","isSafeInteger":"\nisSafeInteger( value )\n Tests if a value is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a safe integer.\n\n Examples\n --------\n > var bool = isSafeInteger( 5.0 )\n true\n > bool = isSafeInteger( new Number( 5.0 ) )\n true\n > bool = isSafeInteger( 2.0e200 )\n false\n > bool = isSafeInteger( -3.14 )\n false\n > bool = isSafeInteger( null )\n false\n\n\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isInteger, isNumber\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false","isSafeInteger.isObject":"\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isInteger, isNumber","isSafeIntegerArray":"\nisSafeIntegerArray( value )\n Tests if a value is an array-like object containing only safe integers.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing\n only safe integers.\n\n Examples\n --------\n > var arr = [ -3.0, new Number(0.0), 2.0 ];\n > var bool = isSafeIntegerArray( arr )\n true\n > arr = [ -3.0, '3.0' ];\n > bool = isSafeIntegerArray( arr )\n false\n\n\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false\n\n\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isSafeInteger\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isSafeInteger","isSameArray":"\nisSameArray( v1, v2 )\n Tests if two arguments are both generic arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0 ];\n > var y = [ 1.0, 2.0, 3.0 ];\n > var bool = isSameArray( x, y )\n true\n\n > x = [ NaN, NaN, NaN ];\n > y = [ NaN, NaN, NaN ];\n > bool = isSameArray( x, y )\n true\n\n See Also\n --------\n isArray, isSameValue\n","isSameComplex64":"\nisSameComplex64( v1, v2 )\n Tests if two arguments are both single-precision complex floating-point\n numbers and have the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex64( 1.0, 2.0 );\n > var y = new Complex64( 1.0, 2.0 );\n > var bool = isSameComplex64( x, y )\n true\n\n > x = new Complex64( NaN, NaN );\n > y = new Complex64( NaN, NaN );\n > bool = isSameComplex64( x, y )\n true\n\n See Also\n --------\n isComplex64, isSameComplex128, isSameValue\n","isSameComplex64Array":"\nisSameComplex64Array( v1, v2 )\n Tests if two arguments are both Complex64Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var bool = isSameComplex64Array( x, y )\n true\n\n > x = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n > y = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n > bool = isSameComplex64Array( x, y )\n true\n\n See Also\n --------\n isComplex64Array, isSameComplex128Array, isSameFloat32Array, isSameValue\n","isSameComplex128":"\nisSameComplex128( v1, v2 )\n Tests if two arguments are both double-precision complex floating-point\n numbers and have the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex128( 1.0, 2.0 );\n > var y = new Complex128( 1.0, 2.0 );\n > var bool = isSameComplex128( x, y )\n true\n\n > x = new Complex128( NaN, NaN );\n > y = new Complex128( NaN, NaN );\n > bool = isSameComplex128( x, y )\n true\n\n See Also\n --------\n isComplex128, isSameComplex64, isSameValue\n","isSameComplex128Array":"\nisSameComplex128Array( v1, v2 )\n Tests if two arguments are both Complex128Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var bool = isSameComplex128Array( x, y )\n true\n\n > x = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n > y = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n > bool = isSameComplex128Array( x, y )\n true\n\n See Also\n --------\n isComplex128Array, isSameComplex64Array, isSameFloat64Array, isSameValue\n","isSameFloat32Array":"\nisSameFloat32Array( v1, v2 )\n Tests if two arguments are both Float32Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > var bool = isSameFloat32Array( x, y )\n true\n\n > x = new Float32Array( [ NaN, NaN, NaN ] );\n > y = new Float32Array( [ NaN, NaN, NaN ] );\n > bool = isSameFloat32Array( x, y )\n true\n\n See Also\n --------\n isSameFloat64Array, isSameValue\n","isSameFloat64Array":"\nisSameFloat64Array( v1, v2 )\n Tests if two arguments are both Float64Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > var bool = isSameFloat64Array( x, y )\n true\n\n > x = new Float64Array( [ NaN, NaN, NaN ] );\n > y = new Float64Array( [ NaN, NaN, NaN ] );\n > bool = isSameFloat64Array( x, y )\n true\n\n See Also\n --------\n isSameFloat32Array, isSameValue\n","isSameNativeClass":"\nisSameNativeClass( a, b )\n Tests if two arguments have the same native class.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments have the same native class.\n\n Examples\n --------\n > var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\n true\n > bool = isSameNativeClass( 'beep', 'boop' )\n true\n > bool = isSameNativeClass( {}, [] )\n false\n\n See Also\n --------\n isSameType, isSameValue, isStrictEqual\n","isSameType":"\nisSameType( a, b )\n Tests if two arguments have the same type.\n\n The function uses the `typeof` operator to test for the same type.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments have the same type.\n\n Examples\n --------\n > var bool = isSameType( true, true )\n true\n > bool = isSameType( {}, [] )\n true\n > bool = isSameType( 3.12, -3.12 )\n true\n > bool = isSameType( 0.0, '0.0' )\n false\n\n See Also\n --------\n isSameNativeClass, isSameValue, isStrictEqual\n","isSameValue":"\nisSameValue( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValue( true, true )\n true\n > bool = isSameValue( {}, {} )\n false\n > bool = isSameValue( -0.0, -0.0 )\n true\n > bool = isSameValue( -0.0, 0.0 )\n false\n > bool = isSameValue( NaN, NaN )\n true\n\n See Also\n --------\n isSameValueZero, isStrictEqual\n","isSameValueZero":"\nisSameValueZero( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValueZero( true, true )\n true\n > bool = isSameValueZero( {}, {} )\n false\n > bool = isSameValueZero( -0.0, -0.0 )\n true\n > bool = isSameValueZero( -0.0, 0.0 )\n true\n > bool = isSameValueZero( NaN, NaN )\n true\n\n See Also\n --------\n isSameValue, isStrictEqual\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value )\n Tests if a value is a SharedArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SharedArrayBuffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffer...\n > var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\n true\n > bool = isSharedArrayBuffer( [] )\n false\n\n See Also\n --------\n isArrayBuffer, isTypedArray\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value )\n Tests if a value is a skew-centrosymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-centrosymmetric matrix.\n\n Examples\n --------\n > var buf = [ 2, 1, -1, -2 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewCentrosymmetricMatrix( M )\n true\n > bool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewCentrosymmetricMatrix( 3.14 )\n false\n > bool = isSkewCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isCentrosymmetricMatrix, isMatrixLike, isSkewSymmetricMatrix\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value )\n Tests if a value is a skew-persymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-persymmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 0, 0, -1 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewPersymmetricMatrix( M )\n true\n > bool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewPersymmetricMatrix( 3.14 )\n false\n > bool = isSkewPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isPersymmetricMatrix, isSkewSymmetricMatrix\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-symmetric matrix.\n\n Examples\n --------\n > var buf = [ 0, -1, 1, 0 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewSymmetricMatrix( M )\n true\n > bool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewSymmetricMatrix( 3.14 )\n false\n > bool = isSkewSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSkewSymmetricMatrix, isSquareMatrix\n","isSlice":"\nisSlice( value )\n Tests if a value is a Slice object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a Slice object.\n\n Examples\n --------\n > var bool = isSlice( new Slice( 10 ) )\n true\n > bool = isSlice( 3.14 )\n false\n > bool = isSlice( {} )\n false\n\n See Also\n --------\n isMultiSlice, Slice\n","isSquareMatrix":"\nisSquareMatrix( value )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object having equal dimensions.\n\n Examples\n --------\n > var buf = [ 0, 0, 0, 0 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSquareMatrix( M )\n true\n > bool = isSquareMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSquareMatrix( 3.14 )\n false\n > bool = isSquareMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSymmetricMatrix\n","isSquareNumber":"\nisSquareNumber( value )\n Tests if a value is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber( 4.0 )\n true\n > bool = isSquareNumber( new Number( 4.0 ) )\n true\n > bool = isSquareNumber( 3.14 )\n false\n > bool = isSquareNumber( -5.0 )\n false\n > bool = isSquareNumber( null )\n false\n\n\nisSquareNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isPrimitive( 4.0 )\n true\n > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n false\n\n\nisSquareNumber.isObject( value )\n Tests if a value is a number object having a value which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isObject( 4.0 )\n false\n > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isCubeNumber, isInteger, isNumber, isTriangularNumber\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isPrimitive( 4.0 )\n true\n > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n false","isSquareNumber.isObject":"\nisSquareNumber.isObject( value )\n Tests if a value is a number object having a value which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isObject( 4.0 )\n false\n > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isCubeNumber, isInteger, isNumber, isTriangularNumber","isSquareTriangularNumber":"\nisSquareTriangularNumber( value )\n Tests if a value is a square triangular number.\n\n Return values are not reliable for numbers greater than 1125899906842624.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber( 36.0 )\n true\n > bool = isSquareTriangularNumber( new Number( 36.0 ) )\n true\n > bool = isSquareTriangularNumber( 3.14 )\n false\n > bool = isSquareTriangularNumber( -5.0 )\n false\n > bool = isSquareTriangularNumber( null )\n false\n\n\nisSquareTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false\n\n\nisSquareTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a square\n triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isObject( 36.0 )\n false\n > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isTriangularNumber\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a square\n triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isObject( 36.0 )\n false\n > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isTriangularNumber","isStrictEqual":"\nisStrictEqual( a, b )\n Tests if two arguments are strictly equal.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are strictly equal.\n\n Examples\n --------\n > var bool = isStrictEqual( true, true )\n true\n > bool = isStrictEqual( {}, {} )\n false\n > bool = isStrictEqual( -0.0, -0.0 )\n true\n > bool = isStrictEqual( -0.0, 0.0 )\n false\n > bool = isStrictEqual( NaN, NaN )\n false\n\n See Also\n --------\n isSameValue\n","isString":"\nisString( value )\n Tests if a value is a string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string.\n\n Examples\n --------\n > var bool = isString( 'beep' )\n true\n > bool = isString( new String( 'beep' ) )\n true\n > bool = isString( 5 )\n false\n\n\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false\n\n\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false\n\n","isString.isPrimitive":"\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false","isString.isObject":"\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false","isStringArray":"\nisStringArray( value )\n Tests if a value is an array of strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of strings.\n\n Examples\n --------\n > var bool = isStringArray( [ 'abc', 'def' ] )\n true\n > bool = isStringArray( [ 'abc', 123 ] )\n false\n\n\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false\n\n\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isString\n","isStringArray.primitives":"\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false","isStringArray.objects":"\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isString","isSymbol":"\nisSymbol( value )\n Tests if a value is a symbol.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symbol.\n\n Examples\n --------\n > var bool = isSymbol( Symbol( 'beep' ) )\n true\n > bool = isSymbol( Object( Symbol( 'beep' ) ) )\n true\n > bool = isSymbol( {} )\n false\n > bool = isSymbol( null )\n false\n > bool = isSymbol( true )\n false\n\n","isSymbolArray":"\nisSymbolArray( value )\n Tests if a value is an array-like object containing only symbols.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only symbols.\n\n Examples\n --------\n > var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\n true\n > bool = isSymbolArray( Symbol( 'beep' ) )\n false\n > bool = isSymbolArray( [] )\n false\n > bool = isSymbolArray( {} )\n false\n > bool = isSymbolArray( null )\n false\n > bool = isSymbolArray( true )\n false\n\n\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false\n\n\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n See Also\n --------\n isArray, isSymbol\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false","isSymbolArray.objects":"\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n See Also\n --------\n isArray, isSymbol","isSymmetricMatrix":"\nisSymmetricMatrix( value )\n Tests if a value is a square matrix which equals its transpose.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symmetric matrix.\n\n Examples\n --------\n > var buf = [ 0, 1, 1, 2 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSymmetricMatrix( M )\n true\n > bool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSymmetricMatrix( 3.14 )\n false\n > bool = isSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isNonSymmetricMatrix, isSquareMatrix\n","isSyntaxError":"\nisSyntaxError( value )\n Tests if a value is a SyntaxError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a SyntaxError (or a descendant) object,\n false positives may occur due to the fact that the SyntaxError constructor\n inherits from Error and has no internal class of its own. Hence, SyntaxError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SyntaxError object.\n\n Examples\n --------\n > var bool = isSyntaxError( new SyntaxError( 'beep' ) )\n true\n > bool = isSyntaxError( {} )\n false\n\n See Also\n --------\n isError\n","isTriangularNumber":"\nisTriangularNumber( value )\n Tests if a value is a triangular number.\n\n Return values are not reliable for numbers greater than 1125899906842624.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber( 36.0 )\n true\n > bool = isTriangularNumber( new Number( 36.0 ) )\n true\n > bool = isTriangularNumber( 3.14 )\n false\n > bool = isTriangularNumber( -5.0 )\n false\n > bool = isTriangularNumber( null )\n false\n\n\nisTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false\n\n\nisTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a triangular\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isObject( 36.0 )\n false\n > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isSquareTriangularNumber\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a triangular\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isObject( 36.0 )\n false\n > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isSquareTriangularNumber","isTruthy":"\nisTruthy( value )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is truthy.\n\n Examples\n --------\n > var bool = isTruthy( true )\n true\n > bool = isTruthy( {} )\n true\n > bool = isTruthy( [] )\n true\n > bool = isTruthy( false )\n false\n > bool = isTruthy( '' )\n false\n > bool = isTruthy( 0 )\n false\n > bool = isTruthy( null )\n false\n > bool = isTruthy( void 0 )\n false\n > bool = isTruthy( NaN )\n false\n\n See Also\n --------\n isFalsy\n","isTruthyArray":"\nisTruthyArray( value )\n Tests if a value is an array-like object containing only truthy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only truthy values.\n\n Examples\n --------\n > var bool = isTruthyArray( [ {}, [] ] )\n true\n > bool = isTruthyArray( [ null, '' ] )\n false\n > bool = isTruthyArray( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n","isTypedArray":"\nisTypedArray( value )\n Tests if a value is a typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a typed array.\n\n Examples\n --------\n > var bool = isTypedArray( new Int8Array( 10 ) )\n true\n\n See Also\n --------\n isArray, isTypedArrayLike\n","isTypedArrayLength":"\nisTypedArrayLength( value )\n Tests if a value is a valid typed array length.\n\n A valid length property for a typed array instance is any integer value on\n the interval [0, 2^53-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a valid typed array length.\n\n Examples\n --------\n > var bool = isTypedArrayLength( 5 )\n true\n > bool = isTypedArrayLength( 2.0e200 )\n false\n > bool = isTypedArrayLength( -3.14 )\n false\n > bool = isTypedArrayLength( null )\n false\n\n See Also\n --------\n isArrayLength, isTypedArray\n","isTypedArrayLike":"\nisTypedArrayLike( value )\n Tests if a value is typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is typed-array-like.\n\n Examples\n --------\n > var bool = isTypedArrayLike( new Int16Array() )\n true\n > bool = isTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4\n ... })\n true\n\n See Also\n --------\n isTypedArray\n","isTypeError":"\nisTypeError( value )\n Tests if a value is a TypeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a TypeError (or a descendant) object,\n false positives may occur due to the fact that the TypeError constructor\n inherits from Error and has no internal class of its own. Hence, TypeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a TypeError object.\n\n Examples\n --------\n > var bool = isTypeError( new TypeError( 'beep' ) )\n true\n > bool = isTypeError( {} )\n false\n\n See Also\n --------\n isError\n","isUint8Array":"\nisUint8Array( value )\n Tests if a value is a Uint8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8Array.\n\n Examples\n --------\n > var bool = isUint8Array( new Uint8Array( 10 ) )\n true\n > bool = isUint8Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint32Array\n","isUint8ClampedArray":"\nisUint8ClampedArray( value )\n Tests if a value is a Uint8ClampedArray.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8ClampedArray.\n\n Examples\n --------\n > var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\n true\n > bool = isUint8ClampedArray( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint8Array\n","isUint16Array":"\nisUint16Array( value )\n Tests if a value is a Uint16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint16Array.\n\n Examples\n --------\n > var bool = isUint16Array( new Uint16Array( 10 ) )\n true\n > bool = isUint16Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint32Array, isUint8Array\n","isUint32Array":"\nisUint32Array( value )\n Tests if a value is a Uint32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint32Array.\n\n Examples\n --------\n > var bool = isUint32Array( new Uint32Array( 10 ) )\n true\n > bool = isUint32Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint8Array\n","isUNCPath":"\nisUNCPath( value )\n Tests if a value is a UNC path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a UNC path.\n\n Examples\n --------\n > var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isUNCPath( '/foo/bar/baz' )\n false\n\n","isUndefined":"\nisUndefined( value )\n Tests if a value is undefined.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined.\n\n Examples\n --------\n > var bool = isUndefined( void 0 )\n true\n > bool = isUndefined( null )\n false\n\n See Also\n --------\n isNull, isUndefinedOrNull\n","isUndefinedOrNull":"\nisUndefinedOrNull( value )\n Tests if a value is undefined or null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined or null.\n\n Examples\n --------\n > var bool = isUndefinedOrNull( void 0 )\n true\n > bool = isUndefinedOrNull( null )\n true\n > bool = isUndefinedOrNull( false )\n false\n\n See Also\n --------\n isNull, isUndefined\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value )\n Tests if a value is an array of probabilities that sum to one.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of probabilities that sum\n to one.\n\n Examples\n --------\n > var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\n true\n > bool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\n true\n > bool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\n false\n > bool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n false\n\n See Also\n --------\n isProbability, isProbabilityArray\n","isUppercase":"\nisUppercase( value )\n Tests if a value is an uppercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an uppercase string.\n\n Examples\n --------\n > var bool = isUppercase( 'HELLO' )\n true\n > bool = isUppercase( 'World' )\n false\n\n See Also\n --------\n isLowercase, isString\n","isURI":"\nisURI( value )\n Tests if a value is a URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URI.\n\n Examples\n --------\n > var bool = isURI( 'http://google.com' )\n true\n > bool = isURI( 'http://localhost/' )\n true\n > bool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\n true\n > bool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\n true\n\n // No scheme:\n > bool = isURI( '' )\n false\n > bool = isURI( 'foo@bar' )\n false\n > bool = isURI( '://foo/' )\n false\n\n // Illegal characters:\n > bool = isURI( 'http://' )\n false\n\n // Invalid path:\n > bool = isURI( 'http:////foo.html' )\n false\n\n // Incomplete hex escapes:\n > bool = isURI( 'http://example.w3.org/%a' )\n false\n\n","isURIError":"\nisURIError( value )\n Tests if a value is a URIError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a URIError (or a descendant) object,\n false positives may occur due to the fact that the URIError constructor\n inherits from Error and has no internal class of its own. Hence, URIError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URIError object.\n\n Examples\n --------\n > var bool = isURIError( new URIError( 'beep' ) )\n true\n > bool = isURIError( {} )\n false\n\n See Also\n --------\n isError\n","isVectorLike":"\nisVectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isVectorLike( M )\n true\n > bool = isVectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isVectorLike( 3.14 )\n false\n > bool = isVectorLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isndarrayLike, isTypedArrayLike\n","isWhitespace":"\nisWhitespace( str )\n Tests whether a string contains only white space characters.\n\n A white space character is defined as one of the 25 characters defined as a\n white space (\"WSpace=Y\",\"WS\") character in the Unicode 9.0 character\n database, as well as one related white space character without the Unicode\n character property \"WSpace=Y\" (zero width non-breaking space which was\n deprecated as of Unicode 3.2).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only white space\n characters.\n\n Examples\n --------\n > var bool = isWhitespace( ' ' )\n true\n > bool = isWhitespace( 'abcdef' )\n false\n > bool = isWhitespace( '' )\n false\n\n See Also\n --------\n reWhitespace\n","isWritableProperty":"\nisWritableProperty( value, property )\n Tests if an object's own property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritableProperty( obj, 'boop' )\n true\n > bool = isWritableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadableProperty, isReadWriteProperty, isWritablePropertyIn, isWriteOnlyProperty\n","isWritablePropertyIn":"\nisWritablePropertyIn( value, property )\n Tests if an object's own or inherited property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritablePropertyIn( obj, 'boop' )\n true\n > bool = isWritablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadablePropertyIn, isReadWritePropertyIn, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value, property )\n Tests if an object's own property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is write-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyProperty( obj, 'boop' )\n false\n > bool = isWriteOnlyProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is write-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyPropertyIn( obj, 'boop' )\n false\n > bool = isWriteOnlyPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isWritablePropertyIn, isWriteOnlyProperty\n","iterAbs":"\niterAbs( iterator )\n Returns an iterator which iteratively computes the absolute value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAbs( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.abs, iterAbs2\n","iterAbs2":"\niterAbs2( iterator )\n Returns an iterator which iteratively computes the squared absolute value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAbs2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.abs2, iterAbs\n","iterAcos":"\niterAcos( iterator )\n Returns an iterator which iteratively computes the arccosine.\n\n The domain of arccosine is restricted to [-1,1]. If an iterated value is\n outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acos, iterAcosh, iterAsin, iterAtan\n","iterAcosh":"\niterAcosh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arccosine.\n\n The domain of the hyperbolic arccosine is restricted to [1,+infinity). If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acosh, iterAcos, iterAsinh, iterAtanh\n","iterAcot":"\niterAcot( iterator )\n Returns an iterator which iteratively computes the inverse cotangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acot, iterAcos, iterAcoth, iterAsin, iterAtan\n","iterAcoth":"\niterAcoth( iterator )\n Returns an iterator which iteratively computes the inverse hyperbolic\n cotangent.\n\n The domain of the inverse hyperbolic cotangent is restricted to (-inf,-1]\n and [1,inf). If an iterated value is outside of the domain, the returned\n iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acoth, iterAcosh, iterAcot, iterAsinh, iterAtanh\n","iterAcovercos":"\niterAcovercos( iterator )\n Returns an iterator which iteratively computes the inverse coversed cosine.\n\n The domain of inverse coversed cosine is restricted to [-2,0]. If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcovercos( random.iterators.uniform( -2.0, 0.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acovercos, iterAcoversin, iterAvercos, iterCovercos, iterVercos\n","iterAcoversin":"\niterAcoversin( iterator )\n Returns an iterator which iteratively computes the inverse coversed sine.\n\n The domain of inverse coversed sine is restricted to [0,2]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acoversin, iterAcovercos, iterAversin, iterCoversin, iterVersin\n","iterAdd":"\niterAdd( iter0, ...iterator )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to add.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterAdd( it1, it2 );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide, iterMultiply, iterSubtract\n","iterAdvance":"\niterAdvance( iterator[, n] )\n Advances an entire iterator.\n\n The function *eagerly* advances an input iterator `n` iterations or until\n the input iterator finishes, whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Input iterator to advance.\n\n n: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Input iterator.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var it = iterAdvance( arr, 4 );\n > var v = it.next().value\n 1\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterHead, iterSlice\n","iterAhavercos":"\niterAhavercos( iterator )\n Returns an iterator which iteratively computes the inverse half-value versed\n cosine.\n\n The domain of inverse half-value versed cosine is restricted to [0,1]. If\n an iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ahavercos, iterAhaversin, iterHavercos, iterVercos\n","iterAhaversin":"\niterAhaversin( iterator )\n Returns an iterator which iteratively computes the inverse half-value versed\n sine.\n\n The domain of inverse half-value versed sine is restricted to [-2,0]. If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ahaversin, iterAhavercos, iterHaversin, iterVersin\n","iterAny":"\niterAny( iterator )\n Tests whether at least one iterated value is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a value is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterAny( arr )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNone, iterSome\n","iterAnyBy":"\niterAnyBy( iterator, predicate[, thisArg ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for any iterated value. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > function fcn( v ) { return ( v === 1 ); };\n > var bool = iterAnyBy( arr, fcn )\n true\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNoneBy, iterSomeBy\n","iterAsin":"\niterAsin( iterator )\n Returns an iterator which iteratively computes the arcsine.\n\n The domain of arcsine is restricted to [-1,1]. If an iterated value is\n outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.asin, iterAcos, iterAsinh, iterAtan\n","iterAsinh":"\niterAsinh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arcsine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.asinh, iterAcosh, iterAsin, iterAtanh\n","iterAtan":"\niterAtan( iterator )\n Returns an iterator which iteratively computes the arctangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atan, iterAcos, iterAsin, iterAtanh\n","iterAtan2":"\niterAtan2( y, x )\n Returns an iterator which iteratively computes the angle in the plane (in\n radians) between the positive x-axis and the ray from (0,0) to the point\n (x,y).\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n y: Object|number\n Input iterator.\n\n x: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( -2.0, 2.0 );\n > var y = random.iterators.uniform( -2.0, 2.0 );\n > var it = iterAtan2( y, x );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atan2, iterAtan\n","iterAtanh":"\niterAtanh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arctangent.\n\n The domain of hyperbolic arctangent is restricted to [-1,1]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atanh, iterAcosh, iterAsinh, iterAtan\n","iterator2array":"\niterator2array( iterator[, out][, mapFcn[, thisArg]] )\n Creates (or fills) an array from an iterator.\n\n When invoked, an input function is provided two arguments:\n\n - value: iterated value\n - index: iterated value index (zero-based)\n\n If provided an output array, the function fills the output array with\n iterated values.\n\n Iteration stops when an output array is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n out: ArrayLikeObject (optional)\n Output array-like object.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var opts = { 'iter': 10 };\n > var arr = iterator2array( random.iterators.randu( opts ) )\n\n See Also\n --------\n array2iterator, iterator2arrayview\n","iterator2arrayview":"\niterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view with values returned from an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: destination index (zero-based)\n - n: iteration index (zero-based)\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayview( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iterator, iterator2arrayviewRight\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: destination index (zero-based)\n - n: iteration index (zero-based)\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayviewRight( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iteratorRight, iterator2arrayview\n","iteratorStream":"\niteratorStream( iterator[, options] )\n Creates a readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n In binary mode, if an iterator generates `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n explicitly map `undefined` values to a different value by wrapping the\n provided iterator with another iterator.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream( it );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );\n\n\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n","iteratorStream.factory":"\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream","IteratorSymbol":"\nIteratorSymbol\n Iterator symbol.\n\n This symbol specifies the default iterator for an object.\n\n The symbol is only supported in ES6/ES2015+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = IteratorSymbol\n\n See Also\n --------\n Symbol\n","iterAvercos":"\niterAvercos( iterator )\n Returns an iterator which iteratively computes the inverse versed cosine.\n\n The domain of inverse versed cosine is restricted to [-2,0]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.avercos, iterAversin, iterVersin\n","iterAversin":"\niterAversin( iterator )\n Returns an iterator which iteratively computes the inverse versed sine.\n\n The domain of inverse versed sine is restricted to [0,2]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.aversin, iterAvercos, iterVercos\n","iterawgn":"\niterawgn( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating pseudorandom numbers\n drawn from a standard normal distribution. If provided, the `state` and\n `seed` options are ignored. In order to seed the returned iterator, one\n must seed the provided `prng` (assuming the provided `prng` is\n seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function|null\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawgn( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawln, iterawun\n","iterawln":"\niterawln( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawln( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawun\n","iterawun":"\niterawun( iterator, sigma[, options] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawun( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawln\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettPulse, iterHannPulse, iterPulse, iterTriangleWave\n","iterBartlettPulse":"\niterBartlettPulse( [options] )\n Returns an iterator which generates a Bartlett pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterTriangleWave\n","iterBesselj0":"\niterBesselj0( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBesselj0( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.besselj0, iterBesselj1, iterBessely0, iterBessely1\n","iterBesselj1":"\niterBesselj1( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order one.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBesselj1( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.besselj1, iterBesselj0, iterBessely0, iterBessely1\n","iterBessely0":"\niterBessely0( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBessely0( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.bessely0, iterBesselj0, iterBesselj1, iterBessely1\n","iterBessely1":"\niterBessely1( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order one.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBessely1( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.bessely1, iterBesselj0, iterBesselj1, iterBessely0\n","iterBeta":"\niterBeta( x, y )\n Returns an iterator which iteratively evaluates the beta function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n y: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( 0.0, 2.0 );\n > var it = iterBeta( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.beta, iterBetaln\n","iterBetaln":"\niterBetaln( x, y )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n beta function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n y: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( 0.0, 2.0 );\n > var it = iterBetaln( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.betaln, iterBeta\n","iterBinet":"\niterBinet( iterator )\n Returns an iterator which iteratively evaluates Binet's formula extended to\n real numbers.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBinet( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.binet\n","iterCbrt":"\niterCbrt( iterator )\n Returns an iterator which iteratively computes the cube root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCbrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cbrt, iterPow, iterSqrt\n","iterCeil":"\niterCeil( iterator )\n Returns an iterator which rounds each iterated value toward positive\n infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil, iterFloor, iterRound\n","iterCeil2":"\niterCeil2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward positive infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil2, iterCeil, iterCeil10, iterFloor2, iterRound2\n","iterCeil10":"\niterCeil10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward positive infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil10, iterCeil, iterCeil2, iterFloor10, iterRound10\n","iterCompositesSeq":"\niterCompositesSeq( [options] )\n Returns an iterator which generates a sequence of composite numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCompositesSeq();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n > v = it.next().value\n 8\n\n See Also\n --------\n iterIntegersSeq, iterPositiveIntegersSeq, iterPrimesSeq\n","iterConcat":"\niterConcat( iter0, ...iterator )\n Returns an iterator which iterates over the values of two or more iterators.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to concatenate.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = array2iterator( [ 3, 4 ] );\n > var it = iterConcat( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n","iterConstant":"\niterConstant( value[, options] )\n Returns an iterator which always returns the same value.\n\n When provided an object reference, the returned iterator always returns the\n same reference.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n value: any\n Value to return.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterConstant( 3.14 );\n > var v = it.next().value\n 3.14\n > v = it.next().value\n 3.14\n\n See Also\n --------\n constantFunction\n","iterContinuedFraction":"\niterContinuedFraction( iterator[, options] )\n Evaluates the terms of a continued fraction.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Maximum number of iterations. Default: 1e308.\n\n options.tol: number (optional)\n Tolerance at which to terminate further evaluation of the continued\n fraction. Default: floating-point epsilon.\n\n Returns\n -------\n out: number|null\n Result.\n\n Examples\n --------\n > var terms = array2iterator( [ 3, 4, 12, 4 ] );\n > var v = iterContinuedFraction( terms )\n ~3.245\n\n See Also\n --------\n iterContinuedFractionSeq\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x[, options] )\n Returns an iterator which generates a list of all continued fraction terms\n which can be obtained given the precision of `x`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x: number\n Input value.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Maximum number of iterations. Default: 1e308.\n\n options.tol: number (optional)\n Tolerance at which to terminate further evaluation of the continued\n fraction. Default: floating-point epsilon.\n\n options.returns: string (optional)\n Specifies the type of result to return. Must be one of\n\n - terms: return continued fraction terms\n - convergents: return continued fraction convergents\n - *: return both continued fraction terms and their associated\n convergents as a two-element array.\n\n Default: 'terms'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n // Return continued fraction terms...\n > var it = iterContinuedFractionSeq( 3.245 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 4\n > v = it.next().value\n 12\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n // Return continued fraction convergents...\n > it = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\n > v = it.next().value\n 3.0\n > v = it.next().value\n 3.25\n > v = it.next().value\n ~3.2449\n > v = it.next().value\n 3.245\n > bool = it.next().done\n true\n\n See Also\n --------\n iterContinuedFraction\n","iterCos":"\niterCos( iterator )\n Returns an iterator which iteratively computes the cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCos( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cos, iterCospi, iterSin, iterTan\n","iterCosh":"\niterCosh( iterator )\n Returns an iterator which iteratively computes the hyperbolic cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterCosh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.cosh, iterCos, iterSinh, iterTanh\n","iterCosineWave":"\niterCosineWave( [options] )\n Returns an iterator which generates a cosine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a cosine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCosineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterCosm1":"\niterCosm1( iterator )\n Returns an iterator which iteratively computes `cos(x) - 1`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCosm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.cosm1, iterCos\n","iterCospi":"\niterCospi( iterator )\n Returns an iterator which computes the cosine of each iterated value times\n π.\n\n Computes cos(πx) more accurately than cos(pi*x), especially for large x.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCospi( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cospi, iterCos\n","iterCounter":"\niterCounter( iterator )\n Returns an iterator which iteratively computes the number of iterated\n values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCounter( random.iterators.randu() );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterLength\n","iterCovercos":"\niterCovercos( iterator )\n Returns an iterator which iteratively computes the coversed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCovercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.covercos, iterCoversin, iterVercos\n","iterCoversin":"\niterCoversin( iterator )\n Returns an iterator which iteratively computes the coversed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCoversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.coversin, iterCovercos, iterVersin\n","iterCubesSeq":"\niterCubesSeq( [options] )\n Returns an iterator which generates a sequence of cubes.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 208063.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCubesSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 8\n\n See Also\n --------\n iterFourthPowersSeq, iterSquaresSeq\n","itercugmean":"\nitercugmean( iterator )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n\n If provided a negative value, the iterated value is `NaN` for all future\n invocations.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercugmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~3.16\n > v = it.next().value\n ~3.11\n > v = it.next().value\n ~3.50\n\n See Also\n --------\n itercuhmean, itercumean\n","itercuhmean":"\nitercuhmean( iterator )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercuhmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~2.86\n > v = it.next().value\n ~2.90\n > v = it.next().value\n ~3.24\n\n See Also\n --------\n itercugmean, itercumean\n","itercumax":"\nitercumax( iterator )\n Returns an iterator which iteratively computes a cumulative maximum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumax( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumidrange, itercumin, itercurange, itermax\n","itercumaxabs":"\nitercumaxabs( iterator )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumaxabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumax, itercuminabs, itermaxabs\n","itercumean":"\nitercumean( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumean( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.25\n\n See Also\n --------\n itercumidrange, itercusum, itermean\n","itercumeanabs":"\nitercumeanabs( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n 3.75\n\n See Also\n --------\n itercumean, itercumeanabs2, itercusumabs, itermeanabs\n","itercumeanabs2":"\nitercumeanabs2( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs2( arr );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n 15.75\n\n See Also\n --------\n itercumean, itercumeanabs, itercusumabs2, itermeanabs2\n","itercumidrange":"\nitercumidrange( iterator )\n Returns an iterator which iteratively computes a cumulative mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumidrange( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itercumean, itercumax, itercumin, itercurange, itermidrange\n","itercumin":"\nitercumin( iterator )\n Returns an iterator which iteratively computes a cumulative minimum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumin( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itercumax, itercumidrange, itercurange, itermin\n","itercuminabs":"\nitercuminabs( iterator )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuminabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n\n See Also\n --------\n itercumaxabs, itercumin, iterminabs\n","itercuprod":"\nitercuprod( iterator )\n Returns an iterator which iteratively computes a cumulative product.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuprod( arr );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -150.0\n\n See Also\n --------\n itercusum, iterprod\n","itercurange":"\nitercurange( iterator )\n Returns an iterator which iteratively computes a cumulative range.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercurange( arr );\n > var r = it.next().value\n 0.0\n > r = it.next().value\n 7.0\n > r = it.next().value\n 8.0\n > r = it.next().value\n 10.0\n\n See Also\n --------\n itercumax, itercumean, itercumin, iterrange\n","itercusum":"\nitercusum( iterator )\n Returns an iterator which iteratively computes a cumulative sum.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusum( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 5.0\n\n See Also\n --------\n itercumean, itersum, itercuprod\n","itercusumabs":"\nitercusumabs( iterator )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 15.0\n\n See Also\n --------\n itercumeanabs, itercusum, itersumabs\n","itercusumabs2":"\nitercusumabs2( iterator )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs2( arr );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 63.0\n\n See Also\n --------\n itercumeanabs2, itercusumabs, itersumabs2\n","iterDatespace":"\niterDatespace( start, stop[, N][, options] )\n Returns an iterator which returns evenly spaced dates over a specified\n interval.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: integer|string|Date\n Starting date either as a `Date` object, JavaScript timestamp, or a date\n string (inclusive).\n\n stop: integer|string|Date\n Stopping value either as a `Date` object, JavaScript timestamp, or a\n date string (inclusive).\n\n N: integer (optional)\n Number of values. Default: 100.\n\n options: Object (optional)\n Function options.\n\n options.round: string (optional)\n Specifies how sub-millisecond times should be rounded. Must be one of\n the following: 'floor', 'ceil', or 'round'. Default: 'floor'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var t1 = new Date();\n > var it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterator2array, iterIncrspace, iterLinspace, iterLogspace, iterStep\n","iterDedupe":"\niterDedupe( iterator[, limit] )\n Returns an iterator which removes consecutive duplicated values.\n\n `NaN` values are considered distinct.\n\n Uniqueness is determined according to strict equality. Accordingly, objects\n are *not* checked for deep equality.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > var it = iterDedupe( arr );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupeBy, iterUnique\n","iterDedupeBy":"\niterDedupeBy( iterator, [limit,] fcn )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n\n The provided function is provided five arguments:\n\n - curr: current source iterated value\n - sprev: previous source iterated value\n - dprev: previous downstream iterated value\n - index: source iteration index (zero-based)\n - acc: previous resolved value\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n fcn: Function\n Function indicating whether an iterated value is a \"duplicate\".\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > function fcn( v ) { return v; };\n > var it = iterDedupeBy( arr, fcn );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupe, iterUnique\n","iterDeg2rad":"\niterDeg2rad( iterator )\n Returns an iterator which iteratively converts an angle from degrees to\n radians.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -360.0, 360.0 );\n > var it = iterDeg2rad( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.deg2rad, iterRad2deg\n","iterDigamma":"\niterDigamma( iterator )\n Returns an iterator which iteratively evaluates the digamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.01, 5.0 );\n > var it = iterDigamma( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.digamma, iterGamma, iterTrigamma\n","iterDiracComb":"\niterDiracComb( [options] )\n Returns an iterator which generates a Dirac comb.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracComb();\n > var v = it.next().value\n Infinity\n > v = it.next().value\n 0.0\n\n See Also\n --------\n iterPulse\n","iterDiracDelta":"\niterDiracDelta( iterator )\n Returns an iterator which iteratively evaluates the Dirac delta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracDelta( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.diracDelta\n","iterDivide":"\niterDivide( iter0, ...iterator )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterDivide( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 0.5\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterMultiply\n","iterEllipe":"\niterEllipe( iterator )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the second kind.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.0, 1.0 );\n > var it = iterEllipe( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.ellipe, iterEllipk\n","iterEllipk":"\niterEllipk( iterator )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the first kind.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.0, 1.0 );\n > var it = iterEllipk( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.ellipk, iterEllipe\n","iterEmpty":"\niterEmpty()\n Returns an empty iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEmpty();\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterConstant\n","iterErf":"\niterErf( iterator )\n Returns an iterator which iteratively evaluates the error function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErf( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erf, iterErfc, iterErfinv, iterErfcinv\n","iterErfc":"\niterErfc( iterator )\n Returns an iterator which iteratively evaluates the complementary error\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfc( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfc, iterErf, iterErfinv, iterErfcinv\n","iterErfcinv":"\niterErfcinv( iterator )\n Returns an iterator which iteratively evaluates the inverse complementary\n error function.\n\n The domain of inverse complementary error function is restricted to [0,2].\n If an iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfcinv, iterErf, iterErfc, iterErfinv\n","iterErfinv":"\niterErfinv( iterator )\n Returns an iterator which iteratively evaluates the inverse error function.\n\n The domain of inverse error function is restricted to [-1,1]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfinv, iterErf, iterErfc, iterErfcinv\n","iterEta":"\niterEta( iterator )\n Returns an iterator which iteratively evaluates the Dirichlet eta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEta( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.eta\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options] )\n Returns an iterator which generates an interleaved sequence of even\n integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n > v = it.next().value\n -2\n\n See Also\n --------\n iterIntegersSeq, iterOddIntegersSeq\n","iterEvery":"\niterEvery( iterator )\n Tests whether all iterated values are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is falsy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\n > var bool = iterEvery( arr )\n false\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNone, iterSome\n","iterEveryBy":"\niterEveryBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a falsy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterEveryBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNoneBy, iterSomeBy\n","iterExp":"\niterExp( iterator )\n Returns an iterator which iteratively evaluates the natural exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterExp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.exp, iterExp10, iterExp2, iterExpm1, iterLn\n","iterExp2":"\niterExp2( iterator )\n Returns an iterator which iteratively evaluates the base `2` exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExp2( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.exp2, iterExp, iterExp10, iterLog2\n","iterExp10":"\niterExp10( iterator )\n Returns an iterator which iteratively evaluates the base `10` exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExp10( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.exp10, iterExp, iterExp2, iterLog10\n","iterExpit":"\niterExpit( iterator )\n Returns an iterator which iteratively evaluates the standard logistic\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 1.0 );\n > var it = iterExpit( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expit, iterExp, iterLogit\n","iterExpm1":"\niterExpm1( iterator )\n Returns an iterator which iteratively computes `exp(x) - 1`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterExpm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expm1, iterExp, iterExpm1rel\n","iterExpm1rel":"\niterExpm1rel( iterator )\n Returns an iterator which iteratively evaluates the relative error\n exponential.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExpm1rel( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expm1rel, iterExp, iterExpm1\n","iterFactorial":"\niterFactorial( iterator )\n Returns an iterator which iteratively evaluates the factorial function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorial( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.factorial, iterFactorialln\n","iterFactorialln":"\niterFactorialln( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n factorial function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorialln( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.factorialln, iterFactorial\n","iterFactorialsSeq":"\niterFactorialsSeq( [options] )\n Returns an iterator which generates a sequence of factorials.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorialsSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterFactorial\n","iterFibonacciSeq":"\niterFibonacciSeq( [options] )\n Returns an iterator which generates a Fibonacci sequence.\n\n The returned iterator can only generate the first 79 Fibonacci numbers, as\n larger Fibonacci numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFibonacciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n base.fibonacci, iterLucasSeq, iterNegaFibonacciSeq, iterNonFibonacciSeq\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options] )\n Returns an iterator which generates a sequence of fifth powers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9741.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFifthPowersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 32\n\n See Also\n --------\n iterCubesSeq, iterFourthPowersSeq, iterSquaresSeq\n","iterFill":"\niterFill( iterator, value[, begin[, end]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n replaces the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n value: any\n Static value.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\n > var r = it.next().value\n 3.14\n > r = it.next().value\n 3.14\n > r = it.next().value\n \n\n","iterFilter":"\niterFilter( iterator, predicate[, thisArg] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilter( it1, f );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterFilterMap, iterMap, iterReject\n","iterFilterMap":"\niterFilterMap( iterator, fcn[, thisArg] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n\n When invoked, the callback function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If the callback returns `undefined`, the iterator invokes the function for\n the next value of the provided iterator; otherwise, the iterator returns\n the callback's return value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Callback function which both filters and maps.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v > 2 ) { return v * 10 }; };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilterMap( it1, f );\n > var v = it2.next().value\n 30\n > v = it2.next().value\n 40\n\n See Also\n --------\n iterFilter, iterMap\n","iterFirst":"\niterFirst( iterator )\n Returns the first iterated value.\n\n The function does *not* consume an entire iterator before returning.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The first iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\n > var v = iterFirst( arr )\n 1\n\n See Also\n --------\n iterHead, iterLast, iterNth\n","iterFlatTopPulse":"\niterFlatTopPulse( [options] )\n Returns an iterator which generates a flat top pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFlatTopPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse\n","iterFloor":"\niterFloor( iterator )\n Returns an iterator which rounds each iterated value toward negative\n infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor, iterCeil, iterRound\n","iterFloor2":"\niterFloor2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward negative infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor2, iterCeil2, iterFloor, iterFloor10, iterRound2\n","iterFloor10":"\niterFloor10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward negative infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor10, iterCeil10, iterFloor, iterFloor2, iterRound10\n","iterFlow":"\niterFlow( methods )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n\n The methods argument should be an object which maps constructor method names\n to iterator functions.\n\n Each iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n When a fluent interface iterator method is invoked, the method invokes the\n corresponding iterator function with an iterator and provided method\n arguments.\n\n If an iterator function returns an iterator, the corresponding fluent\n interface method returns a new fluent interface instance; otherwise, the\n corresponding fluent interface method returns the iterator function result.\n\n The iterator function evaluation context is always `null`.\n\n Iterator functions which return iterators are expected to return iterator\n protocol-compliant objects (i.e., an object having a `next` method which\n returns the next iterated value (if one exists) assigned to a `value`\n property and a `done` property having a boolean value indicating whether the\n iterator is finished).\n\n If an environment supports `Symbol.iterator`, the returned constructor\n returns iterators which are iterable.\n\n Parameters\n ----------\n methods: Object\n An object mapping method names to iterator functions.\n\n Returns\n -------\n FluentIterator: Function\n Fluent interface iterator constructor.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o )\n\n\nFluentIterator( iterator )\n Returns a new fluent interface iterator from a source iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n Returns\n -------\n iterator: Object\n Fluent interface iterator.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var bool = it.head( 3 ).some( 2 )\n false\n\n\nFluentIterator.prototype.next()\n Returns the next iterated value.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > v = it2.next().value\n 0\n > v = it2.next().value\n 1\n\n\nFluentIterator.prototype.return( [value] )\n Finishes an iterator and returns a provided value.\n\n Parameters\n ----------\n value: any (optional)\n Value to return.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > var bool = it2.return().done\n true\n > v = it2.next().value\n undefined\n\n See Also\n --------\n iterPipeline\n","iterForEach":"\niterForEach( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterForEach( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterMap\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options] )\n Returns an iterator which generates a sequence of fourth powers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9741.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFourthPowersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 16\n\n See Also\n --------\n iterCubesSeq, iterFifthPowersSeq, iterSquaresSeq\n","iterFresnelc":"\niterFresnelc( iterator )\n Returns an iterator which iteratively computes the Fresnel integral C(x).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterFresnelc( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.fresnelc, iterFresnels\n","iterFresnels":"\niterFresnels( iterator )\n Returns an iterator which iteratively computes the Fresnel integral S(x).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterFresnels( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.fresnels, iterFresnelc\n","iterGamma":"\niterGamma( iterator )\n Returns an iterator which iteratively evaluates the gamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterGamma( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.gamma, iterGamma1pm1, iterGammaln\n","iterGamma1pm1":"\niterGamma1pm1( iterator )\n Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n cancellation errors for small `x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterGamma1pm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.gamma1pm1, iterGamma\n","iterGammaln":"\niterGammaln( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n gamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterGammaln( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.gammaln, iterGamma\n","iterHacovercos":"\niterHacovercos( iterator )\n Returns an iterator which iteratively computes the half-value coversed\n cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHacovercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.hacovercos, iterCovercos, iterHacoversin\n","iterHacoversin":"\niterHacoversin( iterator )\n Returns an iterator which iteratively computes the half-value coversed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHacoversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.hacoversin, iterCoversin, iterHacovercos\n","iterHannPulse":"\niterHannPulse( [options] )\n Returns an iterator which generates a Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterSineWave\n","iterHavercos":"\niterHavercos( iterator )\n Returns an iterator which iteratively computes the half-value versed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHavercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.havercos, iterHaversin, iterVercos\n","iterHaversin":"\niterHaversin( iterator )\n Returns an iterator which iteratively computes the half-value versed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHaversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.haversin, iterHavercos, iterVersin\n","iterHead":"\niterHead( iterator, n )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n\n If a provided iterator only generates `m` values and `m` is less than `n`,\n the returned iterator only returns `m` values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of values.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHead( random.iterators.randu(), 5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterSlice\n","iterIncrspace":"\niterIncrspace( start, stop[, increment] )\n Returns an iterator which returns evenly spaced numbers according to a\n specified increment.\n\n Beware that values which follow the starting value are subject to floating-\n point rounding errors.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number\n Stopping value (exclusive).\n\n increment: number (optional)\n Increment. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterIncrspace( 0, 101, 2 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, iterDatespace, iterLinspace, iterLogspace, iterStep, iterUnitspace\n","iterIntegersSeq":"\niterIntegersSeq( [options] )\n Returns an iterator which generates an interleaved integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 18014398509481984.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n -1\n\n See Also\n --------\n iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterIntersection":"\niterIntersection( iter0, ...iterator )\n Returns an iterator which returns the intersection of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterIntersection( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersectionByHash, iterUnion, iterUnique\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n A returned iterator internally buffers unique hashes, along with the *first*\n iterated value resolving to a hash, and, thus, has O(N) memory requirements,\n where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > function f( v ) { return v.toString(); };\n > var it = iterIntersectionByHash( it1, it2, f );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUniqueByHash\n","iterInv":"\niterInv( iterator )\n Returns an iterator which iteratively computes the multiplicative inverse.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterInv( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.inv, iterPow\n","iterLanczosPulse":"\niterLanczosPulse( [options] )\n Returns an iterator which generates a Lanczos pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLanczosPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterPeriodicSinc\n","iterLast":"\niterLast( iterator )\n Consumes an entire iterator and returns the last iterated value.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The last iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var v = iterLast( arr )\n 1\n\n See Also\n --------\n iterFirst, iterNth\n","iterLength":"\niterLength( iterator )\n Consumes an entire iterator and returns the number of iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n len: integer\n Iterator length.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var len = iterLength( arr )\n 5\n\n See Also\n --------\n iterCounter\n","iterLinspace":"\niterLinspace( start, stop[, N] )\n Returns an iterator which returns evenly spaced numbers over a specified\n interval.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number\n Stopping value (inclusive).\n\n N: integer (optional)\n Number of values. Default: 100.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLinspace( 0, 99, 100 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLogspace, iterStep, iterUnitspace\n","iterLn":"\niterLn( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLn( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ln, iterExp, iterLog10, iterLog1p, iterLog2\n","iterLog":"\niterLog( x, b )\n Returns an iterator which iteratively computes the base `b` logarithm.\n\n For negative `b` or `x` iterated values, the returned iterator returns\n `NaN`.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n b: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 100.0 );\n > var y = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterLog( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log, iterLog10, iterLog1p, iterLog2, iterPow\n","iterLog1mexp":"\niterLog1mexp( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1-exp(-|x|)`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1mexp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1mexp, iterLog, iterLog1p, iterLog1pexp, iterPow\n","iterLog1p":"\niterLog1p( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1p( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1p, iterLog, iterLog10, iterLog2, iterPow\n","iterLog1pexp":"\niterLog1pexp( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+exp(x)`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1pexp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1pexp, iterLog, iterLog1p, iterLog1mexp, iterPow\n","iterLog2":"\niterLog2( iterator )\n Returns an iterator which iteratively evaluates the binary logarithm.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log2, iterLog, iterLog10, iterLog1p, iterPow\n","iterLog10":"\niterLog10( iterator )\n Returns an iterator which iteratively evaluates the common logarithm\n (logarithm with base 10).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog10( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log10, iterLog, iterLog1p, iterLog2, iterPow\n","iterLogit":"\niterLogit( iterator )\n Returns an iterator which iteratively evaluates the logit function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 1.0 );\n > var it = iterLogit( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.logit\n","iterLogspace":"\niterLogspace( start, stop[, N][, options] )\n Returns an iterator which returns evenly spaced numbers on a log scale.\n\n In linear space, the sequence starts at `base` raised to the power of\n `start` and ends with `base` raised to the power of `stop`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Exponent of starting value.\n\n stop: number\n Exponent of stopping value.\n\n N: integer (optional)\n Number of values. Default: 100.\n\n options: Object (optional)\n Function options.\n\n options.base: number (optional)\n Base of log space. Default: 10.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLogspace( 0, 3, 4 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 10\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterStep\n","iterLucasSeq":"\niterLucasSeq( [options] )\n Returns an iterator which generates a Lucas sequence.\n\n The returned iterator can only generate the first 77 Lucas numbers, as\n larger Lucas numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 77.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLucasSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 1\n\n See Also\n --------\n base.lucas, iterFibonacciSeq, iterNegaLucasSeq\n","iterMap":"\niterMap( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return v * 10.0; };\n > var it = iterMap( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFilter, iterFilterMap, iterForEach, iterReject\n","iterMapN":"\niterMapN( iter0, ...iterator, fcn[, thisArg] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n\n When invoked, the callback function is provided `N+1` arguments, where `N`\n is the number of provided iterators and the last argument is the iteration\n index:\n\n - ...value: iterated values\n - index: iteration index (zero-based)\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators.\n\n fcn: Function\n Function to invoke with iterated values.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > function fcn( x, y ) { return x + y; };\n > var it = iterMapN( it1, it2, fcn );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterMap\n","itermax":"\nitermax( iterator )\n Computes the maximum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermax( arr )\n 3.0\n\n See Also\n --------\n itermidrange, itermin, itermmax, iterrange\n","itermaxabs":"\nitermaxabs( iterator )\n Computes the maximum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermaxabs( arr )\n 4.0\n\n See Also\n --------\n itermax, iterminabs, itermmaxabs\n","itermean":"\nitermean( iterator )\n Computes an arithmetic mean over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = itermean( arr )\n 2.5\n\n See Also\n --------\n itermidrange, itermmean, iterstdev, itersum, itervariance\n","itermeanabs":"\nitermeanabs( iterator )\n Computes an arithmetic mean of absolute values for all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs( arr )\n 2.5\n\n See Also\n --------\n itermean, itermmeanabs, itersumabs\n","itermeanabs2":"\nitermeanabs2( iterator )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs2( arr )\n 7.5\n\n See Also\n --------\n itermean, itermeanabs, itermmeanabs2, itersumabs2\n","itermidrange":"\nitermidrange( iterator )\n Computes the mid-range of all iterated values.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Mid-range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = itermidrange( arr )\n -0.5\n\n See Also\n --------\n itermean, itermax, itermin, iterrange\n","itermin":"\nitermin( iterator )\n Computes the minimum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermin( arr )\n -3.0\n\n See Also\n --------\n itermax, itermidrange, itermmin, iterrange\n","iterminabs":"\niterminabs( iterator )\n Computes the minimum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = iterminabs( arr )\n 1.0\n\n See Also\n --------\n itermaxabs, itermin, itermminabs\n","itermmax":"\nitermmax( iterator, W )\n Returns an iterator which iteratively computes a moving maximum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmax( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermax, itermmidrange, itermmin, itermrange\n","itermmaxabs":"\nitermmaxabs( iterator, W )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmaxabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermaxabs, itermmax, itermminabs\n","itermmean":"\nitermmean( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmean( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.0\n\n See Also\n --------\n itermean, itermsum\n","itermmeanabs":"\nitermmeanabs( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n ~4.33\n\n See Also\n --------\n itermeanabs, itermmean, itermsumabs\n","itermmeanabs2":"\nitermmeanabs2( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of squared absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs2( arr, 3 );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n ~19.67\n\n See Also\n --------\n itermeanabs2, itermmeanabs, itermsumabs2\n","itermmidrange":"\nitermmidrange( iterator, W )\n Returns an iterator which iteratively computes a moving mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmidrange( arr, 3 );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itermidrange, itermmean, itermmax, itermmin, itermrange\n","itermmin":"\nitermmin( iterator, W )\n Returns an iterator which iteratively computes a moving minimum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmin( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itermin, itermmax, itermmidrange, itermrange\n","itermminabs":"\nitermminabs( iterator, W )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermminabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n\n See Also\n --------\n iterminabs, itermmaxabs, itermmin\n","iterMod":"\niterMod( iter0, ...iterator )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterMod( it1, it2 );\n > var v = it.next().value\n 0.0\n > v = it.next().value\n 2.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide\n","itermprod":"\nitermprod( iterator, W )\n Returns an iterator which iteratively computes a moving product.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermprod( arr, 3 );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -75.0\n\n See Also\n --------\n itermsum, iterprod\n","itermrange":"\nitermrange( iterator, W )\n Returns an iterator which iteratively computes a moving range.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermrange( arr, 3 );\n > var m = it.next().value\n 0.0\n > m = it.next().value\n 7.0\n > m = it.next().value\n 8.0\n > m = it.next().value\n 10.0\n\n See Also\n --------\n itermmax, itermmean, itermmin, iterrange\n","itermsum":"\nitermsum( iterator, W )\n Returns an iterator which iteratively computes a moving sum.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsum( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 3.0\n\n See Also\n --------\n itermmean, itersum\n","itermsumabs":"\nitermsumabs( iterator, W )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 13.0\n\n See Also\n --------\n itermmeanabs, itermsum, itersum, itersumabs\n","itermsumabs2":"\nitermsumabs2( iterator, W )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs2( arr, 3 );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 59.0\n\n See Also\n --------\n itermmeanabs2, itermsumabs, itersumabs, itersumabs2\n","iterMultiply":"\niterMultiply( iter0, ...iterator )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to multiply.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterMultiply( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 8.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterSubtract\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options] )\n Returns an iterator which generates a negaFibonacci sequence.\n\n The returned iterator can only generate the first 79 negaFibonacci numbers,\n as larger negaFibonacci numbers cannot be safely represented in double-\n precision floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegaFibonacciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n base.negafibonacci, iterFibonacciSeq, iterNonFibonacciSeq\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options] )\n Returns an iterator which generates a negaLucas sequence.\n\n The returned iterator can only generate the first 77 negaLucas numbers, as\n larger negaLucas numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 77.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegaLucasSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n -1\n\n See Also\n --------\n base.negalucas, iterLucasSeq, iterNegaFibonacciSeq\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of negative even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeEvenIntegersSeq();\n > var v = it.next().value\n -2\n > v = it.next().value\n -4\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterNonPositiveEvenIntegersSeq\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options] )\n Returns an iterator which generates a negative integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740991.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeIntegersSeq();\n > var v = it.next().value\n -1\n > v = it.next().value\n -2\n\n See Also\n --------\n iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options] )\n Returns an iterator which generates a sequence of negative odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeOddIntegersSeq();\n > var v = it.next().value\n -1\n > v = it.next().value\n -3\n\n See Also\n --------\n iterOddIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeEvenIntegersSeq, iterPositiveOddIntegersSeq\n","iterNone":"\niterNone( iterator )\n Tests whether all iterated values are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is truthy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterNone( arr )\n false\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNoneBy, iterSome\n","iterNoneBy":"\niterNoneBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a falsy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v <= 0 ); };\n > var bool = iterNoneBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNone, iterSomeBy\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonFibonacciSeq();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n\n See Also\n --------\n base.nonfibonacci, iterFibonacciSeq\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of nonnegative even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370497.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonNegativeEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveEvenIntegersSeq, iterPositiveEvenIntegersSeq\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options] )\n Returns an iterator which generates a nonnegative integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonNegativeIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterIntegersSeq, iterNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of nonpositive even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370497.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonPositiveEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n -2\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeEvenIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeEvenIntegersSeq\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options] )\n Returns an iterator which generates a nonpositive integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonPositiveIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n -1\n\n See Also\n --------\n iterIntegersSeq, iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterPositiveIntegersSeq\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options] )\n Returns an iterator which generates a sequence of nonsquares.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199349647256.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonSquaresSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 5\n\n See Also\n --------\n iterCubesSeq, iterSquaresSeq\n","iterNth":"\niterNth( iterator, n )\n Returns the nth iterated value.\n\n If `n` exceeds the total number of iterations, the function returns\n `undefined`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Iteration number.\n\n Returns\n -------\n v: any\n The nth iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\n > var v = iterNth( arr, 3 )\n 1\n\n See Also\n --------\n iterFirst, iterLast\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options] )\n Returns an iterator which generates an interleaved sequence of odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterOddIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n -1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq\n","iterPeriodicSinc":"\niterPeriodicSinc( n[, options] )\n Returns an iterator which generates a periodic sinc waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Order.\n\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 100.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPeriodicSinc( 7 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterSineWave\n","iterPipeline":"\niterPipeline( iterFcn[, ...iterFcn] )\n Returns an iterator pipeline.\n\n Parameters\n ----------\n iterFcn: Function|Array\n Iterator function or an array of iterator functions.\n\n iterFcn: ...Function (optional)\n Iterator functions.\n\n Returns\n -------\n fcn( src ): Function\n Iterator pipeline which accepts a single argument, a source iterator.\n\n Examples\n --------\n > var it1 = iterThunk( iterHead, 100 );\n > function f( r ) { return ( r > 0.95 ); };\n > var it2 = iterThunk( iterSomeBy, 5, f );\n > var p = iterPipeline( it1, it2 );\n > var bool = p( random.iterators.randu() )\n \n\n See Also\n --------\n iterFlow, iterThunk\n","iterPop":"\niterPop( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the last value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPop( it1 );\n > var v = it2.next().value\n 1\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPush, iterShift, iterSlice\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of positive even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveEvenIntegersSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 4\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNegativeEvenIntegersSeq, iterNonNegativeEvenIntegersSeq, iterPositiveIntegersSeq, iterPositiveOddIntegersSeq\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options] )\n Returns an iterator which generates a positive integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740991.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeIntegersSeq\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options] )\n Returns an iterator which generates a sequence of positive odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveOddIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterOddIntegersSeq, iterIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterPositiveIntegersSeq\n","iterPow":"\niterPow( base, exponent )\n Returns an iterator which iteratively evaluates the exponential function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n base: Object|number\n Input iterator.\n\n exponent: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( -2.0, 2.0 );\n > var it = iterPow( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.pow, iterExp, iterLog\n","iterPrimesSeq":"\niterPrimesSeq( [options] )\n Returns an iterator which generates a sequence of prime numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 245181918813464.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPrimesSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 5\n\n See Also\n --------\n iterCompositesSeq, iterIntegersSeq, iterPositiveIntegersSeq\n","iterprod":"\niterprod( iterator )\n Computes the product of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Product.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = iterprod( arr )\n 24.0\n\n See Also\n --------\n itermprod, itersum\n","iterPulse":"\niterPulse( [options] )\n Returns an iterator which generates a pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 10.\n\n options.duration: integer (optional)\n Pulse duration (i.e., the number of consecutive iterations of maximum\n amplitude during one period). Default: floor(options.period/2).\n\n options.min: number (optional)\n Minimum amplitude. Default: 0.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPulse();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterPush":"\niterPush( iterator, ...items )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to append.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPush( it1, 3, 4 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterUnshift\n","iterRad2deg":"\niterRad2deg( iterator )\n Returns an iterator which iteratively converts an angle from radians to\n degrees.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterRad2deg( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.rad2deg, iterDeg2rad\n","iterRamp":"\niterRamp( iterator )\n Returns an iterator which iteratively evaluates the ramp function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRamp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ramp\n","iterrange":"\niterrange( iterator )\n Computes the range of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = iterrange( arr )\n 7.0\n\n See Also\n --------\n itermax, itermean, itermin, itermrange\n","iterReject":"\niterReject( iterator, predicate[, thisArg] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterReject( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterFilter, iterMap\n","iterReplicate":"\niterReplicate( iterator, n )\n Returns an iterator which replicates each iterated value `n` times.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of times each iterated value is replicated.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > var it2 = iterReplicate( it1, 2 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterReplicateBy\n","iterReplicateBy":"\niterReplicateBy( iterator, fcn[, thisArg] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n\n The callback function is provided three arguments:\n\n - value: iterated value\n - index: source iteration index (zero-based)\n - n: iteration index (zero-based)\n\n The callback function is invoked *once* per iterated value of the provided\n iterator.\n\n The callback function *must* return an integer value. If the return value is\n less than or equal to zero, the returned iterator skips an iterated value\n and invokes the callback for the next iterated value of the provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function which returns the number of times an iterated value should be\n replicated.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > function f( v, i ) { return i + 1; };\n > var it2 = iterReplicateBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterReplicate\n","iterRound":"\niterRound( iterator )\n Returns an iterator which rounds each iterated value to the nearest integer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round, iterCeil, iterFloor, iterTrunc\n","iterRound2":"\niterRound2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two on a linear scale.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round2, iterCeil2, iterFloor2, iterRound, iterRound10, iterTrunc2\n","iterRound10":"\niterRound10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 on a linear scale.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round10, iterCeil10, iterFloor10, iterRound, iterRound2, iterTrunc10\n","iterRsqrt":"\niterRsqrt( iterator )\n Returns an iterator which iteratively computes the reciprocal (inverse)\n square root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRsqrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.rsqrt, iterSqrt\n","iterSawtoothWave":"\niterSawtoothWave( [options] )\n Returns an iterator which generates a sawtooth wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSawtoothWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSineWave, iterSquareWave, iterTriangleWave\n","iterShift":"\niterShift( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the first value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterShift( it1 );\n > var v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPop, iterSlice, iterUnshift\n","iterSignum":"\niterSignum( iterator )\n Returns an iterator which iteratively evaluates the signum function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSignum( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.signum\n","iterSin":"\niterSin( iterator )\n Returns an iterator which iteratively computes the sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSin( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sin, iterCos, iterSinpi, iterTan\n","iterSinc":"\niterSinc( iterator )\n Returns an iterator which iteratively computes the normalized cardinal sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterSinc( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sinc, iterSin\n","iterSineWave":"\niterSineWave( [options] )\n Returns an iterator which generates a sine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a sine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterCosineWave, iterPulse, iterSawtoothWave, iterSquareWave, iterTriangleWave\n","iterSinh":"\niterSinh( iterator )\n Returns an iterator which iteratively evaluates the hyperbolic sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterSinh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sinh, iterCosh, iterTanh\n","iterSinpi":"\niterSinpi( iterator )\n Returns an iterator which computes the sine of each iterated value times π.\n\n Computes sin(πx) more accurately than sin(pi*x), especially for large x.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSinpi( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sinpi, iterSin\n","iterSlice":"\niterSlice( iterator[, begin[, end]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n returns the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSlice( random.iterators.randu(), 5, 10 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterHead\n","iterSome":"\niterSome( iterator, n )\n Tests whether at least `n` iterated values are truthy.\n\n The function immediately returns upon finding `n` truthy values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an iterator returns at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = iterSome( arr, 3 )\n true\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNone, iterSomeBy\n","iterSomeBy":"\niterSomeBy( iterator, n, predicate[, thisArg ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering `n` truthy return values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Minimum number of successful values.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for at least `n` iterated values. Otherwise, the function returns\n `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterSomeBy( arr, 3, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNoneBy, iterSome\n","iterSpence":"\niterSpence( iterator )\n Returns an iterator which iteratively evaluates Spence's function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 100.0 );\n > var it = iterSpence( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.spence\n","iterSqrt":"\niterSqrt( iterator )\n Returns an iterator which iteratively computes the principal square root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSqrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sqrt, iterCbrt, iterRsqrt\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator )\n Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n accurately for small `x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 100.0 );\n > var it = iterSqrt1pm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sqrt1pm1, iterSqrt\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options] )\n Returns an iterator which generates a sequence of squared triangular\n numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 11585.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquaredTriangularSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 9\n\n See Also\n --------\n iterTriangularSeq\n","iterSquaresSeq":"\niterSquaresSeq( [options] )\n Returns an iterator which generates a sequence of squares.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 94906265.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquaresSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 4\n\n See Also\n --------\n iterCubesSeq, iterNonSquaresSeq\n","iterSquareWave":"\niterSquareWave( [options] )\n Returns an iterator which generates a square wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a square wave repeats).\n This must be an even integer in order to ensure a 50% duty cycle.\n Default: 10.\n\n options.min: number (optional)\n Minimum amplitude. Default: -1.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquareWave();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterTriangleWave\n","iterstdev":"\niterstdev( iterator[, mean] )\n Computes a correct sample standard deviation over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Corrected sample standard deviation.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var m = iterstdev( arr )\n ~4.95\n\n See Also\n --------\n itermean, itervariance\n","iterStep":"\niterStep( start, increment[, N] )\n Returns an iterator which returns a sequence of numbers according to a\n specified increment.\n\n Beware that values which follow the starting value are subject to floating-\n point rounding errors.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n increment: number\n Increment.\n\n N: number (optional)\n Number of values. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterStep( 0, 2, 10 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterLogspace, iterUnitspace\n","iterStrided":"\niterStrided( iterator, stride[, offset[, eager]] )\n Returns an iterator which steps by a specified amount.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n stride: integer\n Stride (i.e., step amount).\n\n offset: integer (optional)\n Index of the first iterated value. Default: 0.\n\n eager: boolean (optional)\n Boolean indicating whether to eagerly advance the input iterator when\n provided a non-zero offset. Default: false.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n > var it = iterStrided( arr, 2, 1 );\n > var r = it.next().value\n 1\n > r = it.next().value\n 3\n\n See Also\n --------\n iterAdvance, iterNth, iterStridedBy\n","iterStridedBy":"\niterStridedBy( iterator, fcn[, offset[, eager]][, thisArg] )\n Returns an iterator which steps according to a provided callback function.\n\n When invoked, the input function is provided four arguments:\n\n - value: iterated value\n - i: input iteration index (zero-based)\n - n: output (strided) iteration index (zero-based)\n - curr: current stride\n\n The return value of the input function specifies the next stride.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Stride function (i.e., a function which returns the step amount).\n\n offset: integer (optional)\n Index of the first iterated value. Default: 0.\n\n eager: boolean (optional)\n Boolean indicating whether to eagerly advance the input iterator when\n provided a non-zero offset. Default: false.\n\n thisArg: any (optional)\n Stride function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n > function stride( v, i ) { return (i % 10)+1; };\n > var it = iterStridedBy( arr, stride );\n > var r = it.next().value\n 0\n > r = it.next().value\n 1\n > r = it.next().value\n 3\n\n See Also\n --------\n iterAdvance, iterNth, iterStrided\n","iterSubtract":"\niterSubtract( iter0, ...iterator )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to subtract.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 5.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterSubtract( it1, it2 );\n > var v = it.next().value\n -2.0\n > v = it.next().value\n 1.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterMultiply\n","itersum":"\nitersum( iterator )\n Computes the sum of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = itersum( arr )\n 10.0\n\n See Also\n --------\n itermean, itermsum, iterprod\n","itersumabs":"\nitersumabs( iterator )\n Computes the sum of absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs( arr )\n 10.0\n\n See Also\n --------\n itermeanabs, itermsumabs, itersum\n","itersumabs2":"\nitersumabs2( iterator )\n Computes the sum of squared absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs2( arr )\n 30.0\n\n See Also\n --------\n itermeanabs2, itermsumabs2, itersumabs\n","iterTan":"\niterTan( iterator )\n Returns an iterator which iteratively evaluates the tangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.57, 1.57 );\n > var it = iterTan( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.tan, iterCos, iterSin\n","iterTanh":"\niterTanh( iterator )\n Returns an iterator which iteratively evaluates the hyperbolic tangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -4.0, 4.0 );\n > var it = iterTanh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.tanh, iterCosh, iterSinh, iterTan\n","iterThunk":"\niterThunk( iterFcn[, ...args] )\n Returns an iterator \"thunk\".\n\n A provided iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n The returned function expects a single argument, an iterator.\n\n This function is useful within the context of iterator pipelines as a means\n to defer execution until a pipeline is ready for data flow.\n\n Parameters\n ----------\n iterFcn: Function\n Iterator function.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n fcn( iter ): Function\n Function which accepts a single argument, an iterator, and invokes a\n previously provided iterator function with the provided iterator and any\n previously provided arguments.\n\n Examples\n --------\n > var fcn = iterThunk( iterSome, 3 );\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = fcn( arr )\n true\n\n See Also\n --------\n iterPipeline\n","iterTriangleWave":"\niterTriangleWave( [options] )\n Returns an iterator which generates a triangle wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangleWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave\n","iterTriangularSeq":"\niterTriangularSeq( [options] )\n Returns an iterator which generates a sequence of triangular numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 134217727.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangularSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterSquaredTriangularSeq\n","iterTrigamma":"\niterTrigamma( iterator )\n Returns an iterator which iteratively evaluates the trigamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.01, 50.0 );\n > var it = iterTrigamma( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.trigamma, iterDigamma, iterGamma\n","iterTrunc":"\niterTrunc( iterator )\n Returns an iterator which rounds each iterated value toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc, iterCeil, iterFloor, iterRound\n","iterTrunc2":"\niterTrunc2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc2, iterCeil2, iterFloor2, iterRound2, iterTrunc\n","iterTrunc10":"\niterTrunc10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc10, iterCeil10, iterFloor10, iterRound10, iterTrunc\n","iterUnion":"\niterUnion( iter0, ...iterator )\n Returns an iterator which returns the union of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the total number of source iterator\n values.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterUnion( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 4\n > v = it.next().value\n 5\n > v = it.next().value\n 3\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUnique\n","iterUnique":"\niterUnique( iterator )\n Returns an iterator which returns unique values.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = iterUnique( it1 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUniqueBy, iterUniqueByHash\n","iterUniqueBy":"\niterUniqueBy( iterator, predicate[, thisArg] )\n Returns an iterator which returns unique values according to a predicate\n function.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n A predicate function is invoked for each iterated value against each value\n in an internal buffer consisting of previously identified unique values.\n Thus, as the number of unique values grows, so, too, does the number of\n predicate function invocations per iterated value.\n\n An iterated value is considered \"unique\" if the predicate function returns\n truthy values for all comparisons of the iterated value with each value in\n the internal buffer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n A binary function with parameters `a` and `b` corresponding to iterated\n values. If the values are the same, the function should return `false`\n (i.e., non-unique); otherwise, if the values are distinct, the function\n should return `true` (i.e., unique).\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( a, b ) { return ( a !== b ); };\n > var it2 = iterUniqueBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueByHash\n","iterUniqueByHash":"\niterUniqueByHash( iterator, hashFcn[, thisArg] )\n Returns an iterator which returns unique values according to a hash\n function.\n\n A returned iterator internally buffers unique hashes and, thus, has O(N)\n memory requirements.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( v ) { return v.toString(); };\n > var it2 = iterUniqueByHash( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueBy\n","iterUnitspace":"\niterUnitspace( start[, stop] )\n Returns an iterator which returns numbers incremented by one.\n\n The iterator stops once the `stop` value is exceeded.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number (optional)\n Stopping value. Default: +infinity.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterUnitspace( 0, 99 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterator2array, iterIncrspace, iterLinspace, iterStep\n","iterUnshift":"\niterUnshift( iterator, ...items )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to prepend.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterUnshift( it1, 3, 4 );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterPush, iterShift\n","itervariance":"\nitervariance( iterator[, mean] )\n Computes an unbiased sample variance over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Unbiased sample variance.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var s2 = itervariance( arr )\n 24.5\n\n See Also\n --------\n itermean, iterstdev\n","iterVercos":"\niterVercos( iterator )\n Returns an iterator which iteratively computes the versed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterVercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.vercos, iterCos, iterSin, iterVersin\n","iterVersin":"\niterVersin( iterator )\n Returns an iterator which iteratively computes the versed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterVersin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.versin, iterCos, iterSin, iterVercos\n","iterZeta":"\niterZeta( iterator )\n Returns an iterator which iteratively evaluates the Riemann zeta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 1.1, 50.0 );\n > var it = iterZeta( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.zeta\n","joinStream":"\njoinStream( [options] )\n Returns a transform stream which joins streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = joinStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n splitStream\n","joinStream.factory":"\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","joinStream.objectMode":"\njoinStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n splitStream","kde2d":"\nkde2d( x, y[, options] )\n Two-dimensional kernel density estimation.\n\n Parameters\n ----------\n x: Array\n Array of x values.\n\n y: Array\n Array of y values.\n\n options: Object (optional)\n Function options.\n\n options.h: number (optional)\n Array of length two containing the bandwidth values for x and y.\n\n options.n: number (optional)\n Number of partitions on the x- and y-axes. Default: `25`.\n\n options.xMin: number (optional)\n Lower limit of x.\n\n options.xMax: number (optional)\n Upper limit of x.\n\n options.yMin: number (optional)\n Lower limit of y.\n\n options.yMax: number (optional)\n Upper limit of y.\n\n options.kernel: string|Function\n A string or function to specifying the used kernel function. Default:\n `'gaussian'`.\n\n Returns\n -------\n out: Object\n Object containing the density estimates (`z`) along grid points (`x` and\n `y` values).\n\n Examples\n --------\n > var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\n > var y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\n > var out = kde2d( x, y )\n { 'x': [1, ... ], 'y': [0.05, ...], 'z': ndarray{Float64Array[0.031, ...] }\n\n","kebabcase":"\nkebabcase( str )\n Converts a string to kebab case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Kebab-cased string.\n\n Examples\n --------\n > var out = kebabcase( 'Hello World!' )\n 'hello-world'\n > out = kebabcase( 'I am a tiny little teapot' )\n 'i-am-a-tiny-little-teapot'\n\n See Also\n --------\n camelcase, constantcase, pascalcase, snakecase","keyBy":"\nkeyBy( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n\n When invoked, the input function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyBy( arr, toKey )\n { '1': { 'a': 1 }, '2': { 'a': 2 } }\n\n See Also\n --------\n forEach\n","keyByRight":"\nkeyByRight( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n\n When invoked, the input function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyByRight( arr, toKey )\n { '2': { 'a': 2 }, '1': { 'a': 1 } }\n\n See Also\n --------\n forEachRight, keyBy\n","keysIn":"\nkeysIn( obj )\n Returns an array of an object's own and inherited enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = keysIn( obj )\n e.g., [ 'beep', 'foo' ]\n\n See Also\n --------\n objectEntriesIn, objectKeys, objectValuesIn\n","kruskalTest":"\nkruskalTest( ...x[, options] )\n Computes the Kruskal-Wallis test for equal medians.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = kruskalTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = kruskalTest( arr, { 'groups': groups } )\n\n","kstest":"\nkstest( x, y[, ...params][, options] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n\n For a numeric array or typed array `x`, a Kolmogorov-Smirnov goodness-of-fit\n is computed for the null hypothesis that the values of `x` come from the\n distribution specified by `y`. `y` can be either a string with the name of\n the distribution to test against, or a function.\n\n In the latter case, `y` is expected to be the cumulative distribution\n function (CDF) of the distribution to test against, with its first parameter\n being the value at which to evaluate the CDF and the remaining parameters\n constituting the parameters of the distribution. The parameters of the\n distribution are passed as additional arguments after `y` from `kstest` to\n the chosen CDF. The function returns an object holding the calculated test\n statistic `statistic` and the `pValue` of the test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the hypothesis test results.\n\n Parameters\n ----------\n x: Array\n Input array holding numeric values.\n\n y: Function|string\n Either a CDF function or a string denoting the name of a distribution.\n\n params: ...number (optional)\n Distribution parameters passed to reference CDF.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array is already in sorted order.\n Default: `false`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that the true distribution of `x` is not equal\n to the reference distribution specified by `y` (`two-sided`), whether it\n is `less` than the reference distribution or `greater` than the\n reference distribution. Default: `'two-sided'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.alternative: string\n Used test alternative. Either `two-sided`, `less` or `greater`.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Verify that data is drawn from a normal distribution:\n > var rnorm = base.random.normal.factory({ 'seed': 4839 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n // Test against N(0,1)\n > var out = kstest( x, 'normal', 0.0, 1.0 )\n { pValue: 0.0, statistic: 0.847, ... }\n\n // Test against N(3,1)\n > out = kstest( x, 'normal', 3.0, 1.0 )\n { pValue: 0.6282, statistic: 0.0733, ... }\n\n // Verify that data is drawn from a uniform distribution:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0 )\n { pValue: ~0.703, statistic: ~0.069, ... }\n\n // Print output:\n > out.print()\n Kolmogorov-Smirnov goodness-of-fit test.\n\n Null hypothesis: the CDF of `x` is equal equal to the reference CDF.\n\n pValue: 0.7039\n statistic: 0.0689\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Set custom significance level:\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\n { pValue: ~0.7039, statistic: ~0.069, ... }\n\n // Carry out one-sided hypothesis tests:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\n { pValue: ~0.358, statistic: ~0.07, ... }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\n { pValue: ~0.907, statistic: ~0.02, ... }\n\n // Set `sorted` option to true when data is in increasing order:\n > x = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n { pValue: ~1, statistic: 0.1, ... }\n\n","leveneTest":"\nleveneTest( x[, ...y[, options]] )\n Computes Levene's test for equal variances.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n y: ...Array (optional)\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Array\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = leveneTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = leveneTest( arr, { 'groups': groups } )\n\n See Also\n --------\n vartest, bartlettTest\n","LinkedList":"\nLinkedList()\n Linked list constructor.\n\n Returns\n -------\n list: Object\n Linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the last node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = LinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n DoublyLinkedList, Stack\n","linspace":"\nlinspace( start, stop, length[, options] )\n Generates a linearly spaced array over a specified interval.\n\n If the specified length is zero, the function returns an empty array.\n\n If the specified length is one, the function returns an array containing\n `stop`, but not `start`, when `endpoint` is true; otherwise, the function\n returns an array containing `start`, but not `stop`.\n\n For real-valued `start` and `stop`, if `start` is less than `stop`, the\n output array will contain ascending values, and, if `start` is greater than\n `stop`, the output array will contain descending values.\n\n When the output array length is greater than one and `endpoint` is true, the\n output array is guaranteed to include the `start` and `stop` values. Beware,\n however, that values between `start` and `stop` are subject to floating-\n point rounding errors.\n\n If both `start` and `stop` are real-valued, the output array data type may\n be any floating-point data type or 'generic'. However, if either `start` or\n `stop` are complex numbers, the output array type must be a complex\n floating-point data type or 'generic'.\n\n When writing to a complex floating-point output array, real-valued `start`\n and `stop` values are treated as complex numbers having a real component\n equaling the provided value and having an imaginary component equaling zero.\n\n When generating linearly spaced complex floating-point numbers, the real and\n imaginary components are generated separately.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n length: integer\n Length of output array.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Must be a floating-point data type or 'generic'.\n If both `start` and `stop` are the same type (either 'float64',\n 'complex64', or 'complex128'), the default output array data type is\n the same type as the input values (either 'float64', 'complex64', or\n 'complex128', respectively). Otherwise, the default output array data\n type is 'complex128'.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `length + 1` linearly spaced\n values over the interval `[start, stop]` and only writes `length` values\n to the output array, thus excluding `stop` from the output array.\n Accordingly, for a fixed `length`, the spacing between adjacent values\n in the output array changes depending on the value of `endpoint`.\n Default: true.\n\n Returns\n -------\n arr: Array\n Linearly spaced array.\n\n Examples\n --------\n > var arr = linspace( 0.0, 100.0, 6 )\n [ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n > arr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\n [ 0.0, 20.0, 40.0, 60.0, 80.0 ]\n > arr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n [ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n\n\nlinspace.assign( start, stop, out[, options] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n\n If the provided output array is empty, the function returns the provided\n output array unchanged.\n\n If the provided output array contains a single element, the function writes\n the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n function writes the `start` value, but not `stop`.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n out: ArrayLikeObject\n Output array.\n\n options: Object (optional)\n Options.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `N+1` linearly spaced values\n (where `N` is the length of the provided output array) over the interval\n `[start, stop]` and only writes `N` values to the output array, thus\n excluding `stop` from the output array. Accordingly, for a fixed `N`,\n the spacing between adjacent values in the output array changes\n depending on the value of `endpoint`. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0, 0 ];\n > var out = linspace.assign( 0, 100, arr )\n [ 0, 20, 40, 60, 80, 100 ]\n > var bool = ( arr === out )\n true\n > arr = [ 0, 0, 0, 0, 0 ];\n > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n [ 0, 20, 40, 60, 80 ]\n\n See Also\n --------\n incrspace, logspace\n","linspace.assign":"\nlinspace.assign( start, stop, out[, options] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n\n If the provided output array is empty, the function returns the provided\n output array unchanged.\n\n If the provided output array contains a single element, the function writes\n the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n function writes the `start` value, but not `stop`.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n out: ArrayLikeObject\n Output array.\n\n options: Object (optional)\n Options.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `N+1` linearly spaced values\n (where `N` is the length of the provided output array) over the interval\n `[start, stop]` and only writes `N` values to the output array, thus\n excluding `stop` from the output array. Accordingly, for a fixed `N`,\n the spacing between adjacent values in the output array changes\n depending on the value of `endpoint`. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0, 0 ];\n > var out = linspace.assign( 0, 100, arr )\n [ 0, 20, 40, 60, 80, 100 ]\n > var bool = ( arr === out )\n true\n > arr = [ 0, 0, 0, 0, 0 ];\n > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n [ 0, 20, 40, 60, 80 ]\n\n See Also\n --------\n incrspace, logspace","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of negative opinion words.\n\n Examples\n --------\n > var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n [ '2-faced', '2-faces', 'abnormal', 'abolish', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. \"Mining and Summarizing Customer\n Reviews.\" In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. \"Opinion Observer:\n Analyzing and Comparing Opinions on the Web.\" In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_POSITIVE_OPINION_WORDS_EN\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of positive opinion words.\n\n Examples\n --------\n > var list = LIU_POSITIVE_OPINION_WORDS_EN()\n [ 'a+', 'abound', 'abounds', 'abundance', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. 'Mining and Summarizing Customer\n Reviews.' In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. 'Opinion Observer:\n Analyzing and Comparing Opinions on the Web.' In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_NEGATIVE_OPINION_WORDS_EN\n","LN_HALF":"\nLN_HALF\n Natural logarithm of `1/2`.\n\n Examples\n --------\n > LN_HALF\n -0.6931471805599453\n\n","LN_PI":"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n\n Examples\n --------\n > LN_PI\n 1.1447298858494002\n\n See Also\n --------\n PI\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n\n Examples\n --------\n > LN_SQRT_TWO_PI\n 0.9189385332046728\n\n See Also\n --------\n PI\n","LN_TWO_PI":"\nLN_TWO_PI\n Natural logarithm of `2π`.\n\n Examples\n --------\n > LN_TWO_PI\n 1.8378770664093456\n\n See Also\n --------\n TWO_PI\n","LN2":"\nLN2\n Natural logarithm of `2`.\n\n Examples\n --------\n > LN2\n 0.6931471805599453\n\n See Also\n --------\n LN10\n","LN10":"\nLN10\n Natural logarithm of `10`.\n\n Examples\n --------\n > LN10\n 2.302585092994046\n\n See Also\n --------\n LN2\n","LOG2E":"\nLOG2E\n Base 2 logarithm of Euler's number.\n\n Examples\n --------\n > LOG2E\n 1.4426950408889634\n\n See Also\n --------\n E, LOG10E\n","LOG10E":"\nLOG10E\n Base 10 logarithm of Euler's number.\n\n Examples\n --------\n > LOG10E\n 0.4342944819032518\n\n See Also\n --------\n E, LOG2E\n","logspace":"\nlogspace( a, b[, length] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n\n If a `length` is not provided, the default output array length is `10`.\n\n The output array includes the values `10^a` and `10^b`.\n\n Parameters\n ----------\n a: number\n Exponent of start value.\n\n b: number\n Exponent of end value.\n\n length: integer (optional)\n Length of output array. Default: `10`.\n\n Returns\n -------\n arr: Array\n Logarithmically spaced numeric array.\n\n Examples\n --------\n > var arr = logspace( 0, 2, 6 )\n [ 1, ~2.5, ~6.31, ~15.85, ~39.81, 100 ]\n\n See Also\n --------\n incrspace, linspace\n","lowercase":"\nlowercase( str )\n Converts a string to lowercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Lowercase string.\n\n Examples\n --------\n > var out = lowercase( 'bEEp' )\n 'beep'\n\n See Also\n --------\n uncapitalize, uppercase\n","lowercaseKeys":"\nlowercaseKeys( obj )\n Converts each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'A': 1, 'B': 2 };\n > var out = lowercaseKeys( obj )\n { 'a': 1, 'b': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n","lowess":"\nlowess( x, y[, options] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n\n Parameters\n ----------\n x: Array\n x-axis values (abscissa values).\n\n y: Array\n Corresponding y-axis values (ordinate values).\n\n options: Object (optional)\n Function options.\n\n options.f: number (optional)\n Positive number specifying the smoothing span, i.e., the proportion of\n points which influence smoothing at each value. Larger values\n correspond to more smoothing. Default: `2/3`.\n\n options.nsteps: number (optional)\n Number of iterations in the robust fit (fewer iterations translates to\n faster function execution). If set to zero, the nonrobust fit is\n returned. Default: `3`.\n\n options.delta: number (optional)\n Nonnegative number which may be used to reduce the number of\n computations. Default: 1/100th of the range of `x`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array `x` is sorted. Default: `false`.\n\n Returns\n -------\n out: Object\n Object with ordered x-values and fitted values.\n\n Examples\n --------\n > var x = new Float64Array( 100 );\n > var y = new Float64Array( x.length );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = i;\n ... y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n ... }\n > var out = lowess( x, y );\n > var yhat = out.y;\n\n > var h = Plot( [ x, x ], [ y, yhat ] );\n > h.lineStyle = [ 'none', '-' ];\n > h.symbols = [ 'closed-circle', 'none' ];\n\n > h.view( 'window' );\n\n","lpad":"\nlpad( str, len[, pad] )\n Left pads a string such that the padded string has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = lpad( 'a', 5 )\n ' a'\n > out = lpad( 'beep', 10, 'b' )\n 'bbbbbbbeep'\n > out = lpad( 'boop', 12, 'beep' )\n 'beepbeepboop'\n\n See Also\n --------\n pad, rpad\n","ltrim":"\nltrim( str )\n Trims whitespace from the beginning of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n 'Beep \\t\\t\\n '\n\n See Also\n --------\n trim, rtrim\n","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common male first names.\n\n Examples\n --------\n > var list = MALE_FIRST_NAMES_EN()\n [ 'Aaron', 'Ab', 'Abba', 'Abbe', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. 'Moby Word II.' .\n\n See Also\n --------\n FEMALE_FIRST_NAMES_EN\n","map":"\nmap( arr, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = map( arr, f )\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = map( arr, f );\n > var v = out.get( 1, 1 )\n 5\n\n\nmap.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n mapRight, reduce\n","map.assign":"\nmap.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n mapRight, reduce","map2":"\nmap2( x, y, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to a new array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Input arrays must be either both array-like objects or both ndarray-like\n objects.\n\n If input arrays are array-like objects, the arrays must have the same number\n of elements.\n\n If input arrays are ndarray-like objects, the arrays must be broadcast\n compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = map2( x, y, f )\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > x = array( x, { 'shape': [ 2, 3 ] } );\n > y = array( y, { 'shape': [ 2, 3 ] } );\n > out = map2( x, y, f );\n > var v = out.get( 1, 1 )\n 6\n\n\nmap2.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n map\n","map2.assign":"\nmap2.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n map","map2d":"\nmap2d( arr, fcn[, thisArg] )\n Applies a function to each nested element in an array of arrays and assigns\n the result to a nested element in a new array of arrays.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array of arrays.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\n > var out = map2d( arr, f );\n > out[ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map3d, map4d, map5d, reduce2d\n","map2Right":"\nmap2Right( x, y, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to a new array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Input arrays must be either both array-like objects or both ndarray-like\n objects.\n\n If input arrays are array-like objects, the arrays must have the same number\n of elements.\n\n If input arrays are ndarray-like objects, the arrays must be broadcast\n compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = map2Right( x, y, f )\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > x = array( x, { 'shape': [ 2, 3 ] } );\n > y = array( y, { 'shape': [ 2, 3 ] } );\n > out = map2Right( x, y, f );\n > var v = out.get( 1, 1 )\n 6\n\n\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2Right.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2Right.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n mapRight, map2\n","map2Right.assign":"\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2Right.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2Right.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n mapRight, map2","map3d":"\nmap3d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a three-dimensional nested\n array and assigns the result to a nested element in a new three-dimensional\n nested array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject>\n Input three-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>\n Three-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\n > var out = map3d( arr, f );\n > out[ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map4d, map5d\n","map4d":"\nmap4d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a four-dimensional nested array\n and assigns the result to a nested element in a new four-dimensional nested\n array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input four-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>>\n Four-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\n > var out = map4d( arr, f );\n > out[ 0 ][ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map3d, map5d\n","map5d":"\nmap5d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a five-dimensional nested array\n and assigns the result to a nested element in a new five-dimensional nested\n array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input five-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>>>\n Five-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\n > var out = map5d( arr, f );\n > out[ 0 ][ 0 ][ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ][ 0 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map3d, map4d\n","mapArguments":"\nmapArguments( fcn, clbk[, thisArg] )\n Returns a function that applies arguments to a provided function after\n transforming arguments according to a callback function.\n\n The callback function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > function clbk( v ) { return v * 2; };\n > var bar = mapArguments( foo, clbk );\n > var out = bar( 1, 2, 3 )\n [ 2, 4, 6 ]\n\n See Also\n --------\n filterArguments\n","mapFun":"\nmapFun( fcn, n[, thisArg] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n The invoked function is provided a single argument: the invocation index\n (zero-based).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n thisArg: any (optional)\n Function execution context.\n\n Returns\n -------\n out: Array\n Array of accumulated function return values.\n\n Examples\n --------\n > function fcn( i ) { return i; };\n > var arr = mapFun( fcn, 5 )\n [ 0, 1, 2, 3, 4 ]\n\n See Also\n --------\n mapFunAsync\n","mapFunAsync":"\nmapFunAsync( fcn, n, [options,] done )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n For each iteration, the provided function is invoked with two arguments:\n\n - `index`: invocation index (starting from zero)\n - `next`: callback to be invoked upon function completion\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n done: Function\n A callback invoked upon executing a provided function `n` times or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > mapFunAsync( fcn, 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Limit number of concurrent invocations:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'limit': 2 };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Sequential invocation:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'series': true };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n See Also\n --------\n mapFun\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n See Also\n --------\n mapFun","mapKeys":"\nmapKeys( obj, transform )\n Maps keys from one object to a new object having the same values.\n\n The transform function is provided three arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n\n The value returned by a transform function should be a value which can be\n serialized as an object key.\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values specify the keys of the output object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapKeys( obj, transform )\n { 'a1': 1, 'b2': 2 }\n\n See Also\n --------\n mapValues\n","mapKeysAsync":"\nmapKeysAsync( obj, [options,] transform, done )\n Maps keys from one object to a new object having the same values.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n - `next`: a callback to be invoked after processing an object `key`\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - `key`\n - `next`\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - `key`\n - `value`\n - `next`\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `key`: transformed key\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The key returned by a transform function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapKeysAsync( obj, transform, done )\n { 'a:1': 1, 'b:2': 2 }\n\n // Limit number of concurrent invocations:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n // Process sequentially:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n See Also\n --------\n mapKeys, mapValuesAsync\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n See Also\n --------\n mapKeys, mapValuesAsync","mapReduce":"\nmapReduce( arr, initial, mapper, reducer[, thisArg] )\n Performs a map-reduce operation for each element in an array and returns the\n accumulated result.\n\n When invoked, the mapping function is provided three arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n When invoked, the reducing function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: result after applying the mapping function to the current array\n element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a single-pass map-reduce\n operation over the entire input ndarray (i.e., higher-order ndarray\n dimensions are flattened to a single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n mapper: Function\n Mapping function.\n\n reducer: Function\n Reducing function.\n\n thisArg: any (optional)\n Execution context for the reducing function.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f1 = naryFunction( base.abs, 1 );\n > var f2 = naryFunction( base.add, 2 );\n > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n > var out = mapReduce( arr, 0.0, f1, f2 )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapReduce( arr, 0.0, f1, f2 )\n 21.0\n\n See Also\n --------\n map, mapReduceRight, reduce\n","mapReduceRight":"\nmapReduceRight( arr, initial, mapper, reducer[, thisArg] )\n Performs a map-reduce operation for each element in an array while iterating\n from right to left and returns the accumulated result.\n\n When invoked, the mapping function is provided three arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n When invoked, the reducing function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: result after applying the mapping function to the current array\n element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a single-pass map-reduce\n operation over the entire input ndarray (i.e., higher-order ndarray\n dimensions are flattened to a single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n mapper: Function\n Mapping function.\n\n reducer: Function\n Reducing function.\n\n thisArg: any (optional)\n Execution context for the reducing function.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f1 = naryFunction( base.abs, 1 );\n > var f2 = naryFunction( base.add, 2 );\n > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n > var out = mapReduceRight( arr, 0.0, f1, f2 )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapReduceRight( arr, 0.0, f1, f2 )\n 21.0\n\n See Also\n --------\n mapRight, mapReduce, reduceRight\n","mapRight":"\nmapRight( arr, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = mapRight( arr, f )\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapRight( arr, f );\n > var v = out.get( 1, 1 )\n 5\n\n\nmapRight.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > mapRight.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > mapRight.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n map, reduce\n","mapRight.assign":"\nmapRight.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > mapRight.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > mapRight.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n map, reduce","mapValues":"\nmapValues( obj, transform )\n Maps values from one object to a new object having the same keys.\n\n The transform function is provided three arguments:\n\n - `value`: object value corresponding to `key`\n - `key`: object key\n - `obj`: the input object\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( value, key ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapValues( obj, transform )\n { 'a': 'a1', 'b': 'b2' }\n\n See Also\n --------\n mapKeys, omitBy, pickBy\n","mapValuesAsync":"\nmapValuesAsync( obj, [options,] transform, done )\n Maps values from one object to a new object having the same keys.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - `value`: object value corresponding to `key`\n - `key`: object key\n - `obj`: the input object\n - `next`: a callback to be invoked after processing an object `value`\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - `value`\n - `next`\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - `value`\n - `key`\n - `next`\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `value`: transformed value\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapValuesAsync( obj, transform, done )\n { 'a': 'a:1', 'b': 'b:2' }\n\n // Limit number of concurrent invocations:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n // Process sequentially:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n See Also\n --------\n mapKeysAsync, mapValues\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n See Also\n --------\n mapKeysAsync, mapValues","maskArguments":"\nmaskArguments( fcn, mask[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a specified mask.\n\n Only those arguments having a truthy mask value are applied to a provided\n function.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n mask: ArrayLikeObject\n Mask array.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > var bar = maskArguments( foo, [ 1, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n filterArguments, rejectArguments, reorderArguments, reverseArguments\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n\n Examples\n --------\n > MAX_ARRAY_LENGTH\n 4294967295\n\n See Also\n --------\n MAX_TYPED_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n\n Examples\n --------\n > MAX_TYPED_ARRAY_LENGTH\n 9007199254740991\n\n See Also\n --------\n MAX_ARRAY_LENGTH\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x, shape )\n Broadcasts an ndarray to a specified shape if and only if the specified\n shape differs from the provided ndarray's shape.\n\n If a provided ndarray has the same shape as the specified shape, the\n function returns the provided ndarray.\n\n If a provided ndarray has a different (broadcast compatible) shape than the\n specified shape, the function returns a new *read-only* ndarray view of the\n provided ndarray's data. The view is typically *not* contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to the input ndarray may affect multiple elements. If you need to\n write to the input ndarray, copy the input ndarray before broadcasting.\n\n The function throws an error if a provided ndarray is incompatible with a\n provided shape.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n shape: ArrayLikeObject\n Desired shape.\n\n Returns\n -------\n out: ndarray\n Broadcasted array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\n \n > sh = y.shape\n [ 3, 2, 2 ]\n > var v = y.get( 0, 0, 0 )\n 1\n > v = y.get( 0, 0, 1 )\n 2\n > v = y.get( 0, 1, 0 )\n 3\n > v = y.get( 0, 1, 1 )\n 4\n > v = y.get( 1, 0, 0 )\n 1\n > v = y.get( 1, 1, 0 )\n 3\n > v = y.get( 2, 0, 0 )\n 1\n > v = y.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, ndarray, broadcastArray, maybeBroadcastArrays\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays )\n Broadcasts ndarrays to a common shape.\n\n The function supports two (mutually exclusive) means of providing ndarray\n arguments:\n\n 1. Providing a single array containing ndarray arguments.\n 2. Providing ndarray arguments as separate arguments.\n\n If a provided ndarray has a shape matching the common shape, the function\n returns the provided ndarray.\n\n If a provided ndarray has a different (broadcast compatible) shape than the\n common shape, the function returns a new *read-only* ndarray view of the\n provided ndarray's data. The view is typically *not* contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to a view may affect multiple elements. If you need to write to an\n input ndarray, copy the input ndarray before broadcasting.\n\n The function throws an error if a provided broadcast-incompatible ndarrays.\n\n Parameters\n ----------\n arrays: ...ndarray|ArrayLikeObject\n Array arguments.\n\n Returns\n -------\n out: Array\n Broadcasted arrays.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = ndzeros( [ 3, 2, 2 ] )\n \n > var out = maybeBroadcastArrays( [ x, y ] )\n [ , ]\n\n // Retrieve the broadcasted \"x\" array:\n > var bx = out[ 0 ]\n \n > sh = bx.shape\n [ 3, 2, 2 ]\n\n // Retrieve broadcasted elements...\n > var v = bx.get( 0, 0, 0 )\n 1\n > v = bx.get( 0, 0, 1 )\n 2\n > v = bx.get( 0, 1, 0 )\n 3\n > v = bx.get( 0, 1, 1 )\n 4\n > v = bx.get( 1, 0, 0 )\n 1\n > v = bx.get( 1, 1, 0 )\n 3\n > v = bx.get( 2, 0, 0 )\n 1\n > v = bx.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, ndarray, broadcastArrays, maybeBroadcastArray\n","memoize":"\nmemoize( fcn[, hashFunction] )\n Returns a memoized function.\n\n The function does not set the `length` property of the returned function.\n Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n The function serializes provided arguments as a string and stores results\n using the string as an identifier. To use a custom hash function, provide a\n hash function argument.\n\n Parameters\n ----------\n fcn: Function\n Function to memoize.\n\n hashFunction: Function (optional)\n Function to map a set of arguments to a single value identifying that\n set.\n\n Returns\n -------\n out: Function\n Memoized function.\n\n Examples\n --------\n > function factorial( n ) {\n ... var prod;\n ... var i;\n ... prod = 1;\n ... for ( i = n; i > 1; i-- ) {\n ... prod *= i;\n ... }\n ... return prod;\n ... };\n > var memoized = memoize( factorial );\n > var v = memoized( 5 )\n 120\n > v = memoized( 5 )\n 120\n\n","merge":"\nmerge( target, ...source )\n Merges objects into a target object.\n\n The target object is mutated.\n\n Only plain objects are merged and extended. Other values/types are either\n deep copied or assigned.\n\n Support for deep merging class instances is inherently fragile.\n\n `Number`, `String`, and `Boolean` objects are merged as primitives.\n\n Functions are not deep copied.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n source: ...Object\n Source objects (i.e., objects to be merged into the target object).\n\n Returns\n -------\n out: Object\n Merged (target) object.\n\n Examples\n --------\n > var target = { 'a': 'beep' };\n > var source = { 'a': 'boop', 'b': 'bap' };\n > var out = merge( target, source )\n { 'a': 'boop', 'b': 'bap' }\n > var bool = ( out === target )\n true\n\n\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n See Also\n --------\n copy\n","merge.factory":"\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n See Also\n --------\n copy","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var ms = days * MILLISECONDS_IN_DAY\n 271296000\n\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var ms = hrs * MILLISECONDS_IN_HOUR\n 11304000\n\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var ms = mins * MILLISECONDS_IN_MINUTE\n 188400\n\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n Number of milliseconds in a second.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var secs = 3.14;\n > var ms = secs * MILLISECONDS_IN_SECOND\n 3140\n\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n Number of milliseconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var weeks = 3.14;\n > var ms = weeks * MILLISECONDS_IN_WEEK\n 1899072000\n\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options] )\n Returns data for Charles Joseph Minard's cartographic depiction of\n Napoleon's Russian campaign of 1812.\n\n Data includes the following:\n\n - army: army size\n - cities: cities\n - labels: map labels\n - temperature: temperature during the army's return from Russia\n - rivers: river data\n\n Temperatures are on the Réaumur scale. Multiply each temperature by `1.25`\n to convert to Celsius.\n\n River data is formatted as GeoJSON.\n\n River data is incomplete, with portions of rivers missing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n Minard's data.\n\n Examples\n --------\n > var data = MINARD_NAPOLEONS_MARCH();\n > var army = data.army\n [...]\n > var cities = data.cities\n [...]\n > var labels = data.labels\n [...]\n > var river = data.river\n {...}\n > var t = data.temperature\n [...]\n\n References\n ----------\n - Minard, Charles Joseph. 1869. *Tableaux graphiques et cartes figuratives*.\n Ecole nationale des ponts et chaussées.\n - Wilkinson, Leland. 2005. *The Grammar of Graphics*. Springer-Verlag New\n York. doi:10.1007/0-387-28695-0.\n\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n Number of minutes in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var mins = days * MINUTES_IN_DAY\n 4521.6\n\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var mins = hrs * MINUTES_IN_HOUR\n 188.4\n\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n Number of minutes in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var mins = wks * MINUTES_IN_WEEK\n 31651.2\n\n","minutesInMonth":"\nminutesInMonth( [month[, year]] )\n Returns the number of minutes in a month.\n\n By default, the function returns the number of minutes in the current month\n of the current year (according to local time). To determine the number of\n minutes for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Minutes in a month.\n\n Examples\n --------\n > var num = minutesInMonth()\n \n > num = minutesInMonth( 2 )\n \n > num = minutesInMonth( 2, 2016 )\n 41760\n > num = minutesInMonth( 2, 2017 )\n 40320\n\n // Other ways to supply month:\n > num = minutesInMonth( 'feb', 2016 )\n 41760\n > num = minutesInMonth( 'february', 2016 )\n 41760\n\n See Also\n --------\n minutesInYear\n","minutesInYear":"\nminutesInYear( [value] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n\n By default, the function returns the number of minutes in the current year\n (according to local time). To determine the number of minutes for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of minutes in a year.\n\n Examples\n --------\n > var num = minutesInYear()\n \n > num = minutesInYear( 2016 )\n 527040\n > num = minutesInYear( 2017 )\n 525600\n\n See Also\n --------\n minutesInMonth\n","MOBY_DICK":"\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n\n Each array element has the following fields:\n\n - chapter: book chapter (number or identifier)\n - title: chapter title (if available; otherwise, empty)\n - text: chapter text\n\n Returns\n -------\n out: Array\n Book text.\n\n Examples\n --------\n > var data = MOBY_DICK()\n [ {...}, {...}, ... ]\n\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n\n Returns\n -------\n out: Array\n List of month names.\n\n Examples\n --------\n > var list = MONTH_NAMES_EN()\n [ 'January', 'February', 'March', 'April', ... ]\n\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n Number of months in a year.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var yrs = 3.14;\n > var mons = yrs * MONTHS_IN_YEAR\n 37.68\n\n","moveProperty":"\nmoveProperty( source, prop, target )\n Moves a property from one object to another object.\n\n The property is deleted from the source object and the property's descriptor\n is preserved during transfer.\n\n If a source property is not configurable, the function throws an error, as\n the property cannot be deleted from the source object.\n\n Parameters\n ----------\n source: Object\n Source object.\n\n prop: string\n Property to move.\n\n target: Object\n Target object.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether operation was successful.\n\n Examples\n --------\n > var obj1 = { 'a': 'b' };\n > var obj2 = {};\n > var bool = moveProperty( obj1, 'a', obj2 )\n true\n > bool = moveProperty( obj1, 'c', obj2 )\n false\n\n","MultiSlice":"\nMultiSlice( ...slice )\n Returns a multi-slice.\n\n Parameters\n ----------\n ...slice: Slice|integer|null|undefined\n Slice arguments.\n\n Returns\n -------\n s: MultiSlice\n MultiSlice instance.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n\n\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n\n Returns\n -------\n ndims: integer\n Number of slice dimensions.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.ndims\n 3\n\n\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n\n Returns\n -------\n data: Array\n Slice data.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.data\n [ 2, , 1 ]\n\n\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n\n Returns\n -------\n str: string\n Serialized multi-slice string.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.toString()\n 'MultiSlice(2,Slice(2,10,null),1)'\n\n\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 2, 10, 1 );\n > var ms = new MultiSlice( 2, s );\n > ms.toJSON()\n {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n See Also\n --------\n ndarray, Slice\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n\n Returns\n -------\n ndims: integer\n Number of slice dimensions.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.ndims\n 3","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n\n Returns\n -------\n data: Array\n Slice data.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.data\n [ 2, , 1 ]","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n\n Returns\n -------\n str: string\n Serialized multi-slice string.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.toString()\n 'MultiSlice(2,Slice(2,10,null),1)'","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 2, 10, 1 );\n > var ms = new MultiSlice( 2, s );\n > ms.toJSON()\n {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n See Also\n --------\n ndarray, Slice","namedtypedtuple":"\nnamedtypedtuple( fields[, options] )\n Returns a named typed tuple factory.\n\n Named tuples assign a property name, and thus a meaning, to each position in\n a tuple and allow for more readable, self-documenting code.\n\n Named typed tuples can be used wherever typed arrays are used, with the\n added benefit that they allow accessing fields by both field name and\n position index.\n\n Named typed tuples may be one the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n fields: Array\n Field (property) names.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Default tuple data type. If a data type is not provided to a named typed\n tuple factory, this option specifies the underlying tuple data type.\n Default: 'float64'.\n\n options.name: string (optional)\n Tuple name. Default: 'tuple'.\n\n Returns\n -------\n factory: Function\n Named typed tuple factory.\n\n Examples\n --------\n > var opts = {};\n > opts.name = 'Point';\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var tuple = factory();\n\n\nfactory()\n Returns a named typed tuple of the default data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory();\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory( dtype )\n Returns a named typed tuple of the specified data type.\n\n Parameters\n ----------\n dtype: string\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( 'int32' );\n > p.x\n 0\n > p.y\n 0\n > p[ 0 ]\n 0\n > p[ 1 ]\n 0\n\n\nfactory( typedarray[, dtype] )\n Creates a named typed tuple from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a named typed tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( Float64Array[ 1.0, -1.0 ] );\n > p.x\n 1.0\n > p.y\n -1.0\n > p[ 0 ]\n 1.0\n > p[ 1 ]\n -1.0\n\n\nfactory( obj[, dtype] )\n Creates a named typed tuple from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a named typed\n tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( [ 1, -1 ], 'int32' );\n > p.x\n 1\n > p.y\n -1\n > p[ 0 ]\n 1\n > p[ 1 ]\n -1\n\n\nfactory( buffer[, byteOffset][, dtype] )\n Returns a named typed tuple view of an ArrayBuffer.\n\n The view length equals the number of tuple fields.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first tuple element.\n Default: 0.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var buf = new ArrayBuffer( 16 );\n > var p = factory( buf, 4, 'float32' );\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory.from( src[, map[, thisArg]] )\n Creates a new named typed tuple from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n - field: tuple field.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of tuple elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > function mapFcn( v ) { return v * 2.0; };\n > var p = factory.from( [ 1.0, -1.0 ], mapFcn );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.fromObject( obj[, map[, thisArg]] )\n Creates a new named typed tuple from an object containing tuple fields.\n\n A callback is provided the following arguments:\n\n - value: source object tuple field value.\n - field: source object tuple field name.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n map: Function (optional)\n Callback to invoke for each source object tuple field.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.fromObject( { 'x': 2.0, 'y': -2.0 } );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.of( element0[, element1[, ...elementN]] )\n Creates a new named typed tuple from a variable number of arguments.\n\n The number of arguments *must* equal the number of tuple fields.\n\n Parameters\n ----------\n element0: number\n Tuple element.\n\n element1: number (optional)\n Tuple element.\n\n elementN: number (optional)\n Tuple elements.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.of( 2.0, -2.0 );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\ntuple.BYTES_PER_ELEMENT\n Size (in bytes) of each tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.BYTES_PER_ELEMENT\n 8\n\n\ntuple.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.buffer\n \n\n\ntuple.byteLength\n Length (in bytes) of the tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteLength\n 16\n\n\ntuple.byteOffset\n Offset (in bytes) of a tuple from the start of its underlying ArrayBuffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteOffset\n 0\n\n\ntuple.length\n Tuple length (i.e., number of elements).\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.length\n 2\n\n\ntuple.name\n Tuple name.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.name\n 'Point'\n\n\ntuple.fields\n Returns the list of tuple fields.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fields\n [ 'x', 'y' ]\n\n\ntuple.orderedFields\n Returns the list of tuple fields in index order.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.sort();\n > p[ 0 ]\n -1.0\n > p.fields\n [ 'x', 'y' ]\n > p.orderedFields\n [ 'y', 'x' ]\n\n\ntuple.copyWithin( target, start[, end] )\n Copies a sequence of elements within the tuple starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > p.copyWithin( 3, 0, 2 );\n > p.w\n 2.0\n > p.v\n -2.0\n\n\ntuple.entries()\n Returns an iterator for iterating over tuple key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple key-value pairs.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.entries();\n > it.next().value\n [ 0, 'x', 1.0 ]\n > it.next().value\n [ 1, 'y', -1.0 ]\n > it.next().done\n true\n\n\ntuple.every( predicate[, thisArg] )\n Tests whether all tuple elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all tuple elements pass.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > p.every( predicate )\n false\n\n\ntuple.fieldOf( searchElement[, fromIndex] )\n Returns the field of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var f = p.fieldOf( 2.0 )\n undefined\n > f = p.fieldOf( -1.0 )\n 'z'\n\n\ntuple.fill( value[, start[, end]] )\n Fills a tuple from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last tuple element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fill( 2.0 );\n > p.x\n 2.0\n > p.y\n 2.0\n\n\ntuple.filter( predicate[, thisArg] )\n Creates a new tuple which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n If a predicate function does not return a truthy value for any tuple\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters tuple elements. If a predicate function\n returns a truthy value, a tuple element is included in the output tuple;\n otherwise, a tuple element is not included in the output tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var p2 = p1.filter( predicate );\n > p2.fields\n [ 'x', 'y' ]\n\n\ntuple.find( predicate[, thisArg] )\n Returns the first tuple element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = p.find( predicate )\n -1.0\n\n\ntuple.findField( predicate[, thisArg] )\n Returns the field of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var f = p.findField( predicate )\n 'z'\n\n\ntuple.findIndex( predicate[, thisArg] )\n Returns the index of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = p.findIndex( predicate )\n 2\n\n\ntuple.forEach( fcn[, thisArg] )\n Invokes a callback for each tuple element.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each tuple element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > var str = ' ';\n > function fcn( v, i, f ) { str += f + '=' + v + ' '; };\n > p.forEach( fcn );\n > str\n ' x=1 y=0 z=-1 '\n\n\ntuple.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether a tuple includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a tuple includes a search element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var bool = p.includes( 2.0 )\n false\n > bool = p.includes( -1.0 )\n true\n\n\ntuple.indexOf( searchElement[, fromIndex] )\n Returns the index of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var idx = p.indexOf( 2.0 )\n -1\n > idx = p.indexOf( -1.0 )\n 2\n\n\ntuple.ind2key( ind )\n Converts a tuple index to a field name.\n\n If provided an out-of-bounds index, the method returns `undefined`.\n\n Parameters\n ----------\n ind: integer\n Tuple index. If less than zero, the method resolves the index relative\n to the last tuple element.\n\n Returns\n -------\n field: string|undefined\n Field name.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.ind2key( 1 )\n 'y'\n > p.ind2key( 100 )\n undefined\n\n\ntuple.join( [separator] )\n Serializes a tuple by joining all tuple elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating tuple elements. Default: ','.\n\n Returns\n -------\n str: string\n Tuple serialized as a string.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > p.join( '|' )\n '1|0|-1'\n\n\ntuple.keys()\n Returns an iterator for iterating over tuple keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple keys.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.keys();\n > it.next().value\n [ 0, 'x' ]\n > it.next().value\n [ 1, 'y' ]\n > it.next().done\n true\n\n\ntuple.key2ind( field )\n Converts a field name to a tuple index.\n\n If provided an unknown field name, the method returns `-1`.\n\n Parameters\n ----------\n field: string\n Tuple field name.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.key2ind( 'y' )\n 1\n\n\ntuple.lastFieldOf( searchElement[, fromIndex] )\n Returns the field of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var f = p.lastFieldOf( 2.0 )\n undefined\n > f = p.lastFieldOf( 0.0 )\n 'w'\n\n\ntuple.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = p.lastIndexOf( 2.0 )\n -1\n > idx = p.lastIndexOf( 0.0 )\n 3\n\n\ntuple.map( fcn[, thisArg] )\n Maps each tuple element to an element in a new tuple.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n Parameters\n ----------\n fcn: Function\n Function which maps tuple elements to elements in the new tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var p2 = p1.map( fcn );\n > p2.x\n 2.0\n > p2.y\n 0.0\n > p2.z\n -2.0\n\n\ntuple.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first tuple element as the first argument and the second tuple\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduce( fcn, 0.0 )\n 2.0\n\n\ntuple.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last tuple element as the first argument and the second-to-last\n tuple element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduceRight( fcn, 0.0 )\n 2.0\n\n\ntuple.reverse()\n Reverses a tuple *in-place*.\n\n This method mutates the tuple on which the method is invoked.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.x\n 1.0\n > p.reverse();\n > p[ 0 ]\n -1.0\n > p.x\n 1.0\n\n\ntuple.set( arr[, offset] )\n Sets tuple elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing tuple values to set.\n\n offset: integer (optional)\n Tuple index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 1 ]\n 0.0\n > p.y\n 0.0\n > p.set( [ -2.0, 2.0 ], 1 );\n > p[ 1 ]\n -2.0\n > p.y\n -2.0\n > p[ 2 ]\n 2.0\n > p.z\n 2.0\n\n\ntuple.slice( [begin[, end]] )\n Copies tuple elements to a new tuple with the same underlying data type as\n the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > p1.fields\n [ 'x', 'y', 'z' ]\n > var p2 = p1.slice( 1 );\n > p2.fields\n [ 'y', 'z' ]\n > p2.y\n 0.0\n > p2.z\n -1.0\n\n\ntuple.some( predicate[, thisArg] )\n Tests whether at least one tuple element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one tuple element passes.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > p.some( predicate )\n true\n\n\ntuple.sort( [compareFunction] )\n Sorts a tuple *in-place*.\n\n Sorting a tuple does *not* affect field assignments. Accessing a tuple field\n before and after sorting will always return the same tuple element. However,\n this behavior is generally not true when accessing tuple elements according\n to tuple index. In summary, sorting affects index order but not field\n assignments.\n\n The comparison function is provided two tuple elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the tuple on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > p.sort();\n > p.orderedFields\n [ 'v', 'y', 'z', 'x', 'w' ]\n > p[ 0 ]\n -2.0\n > p.x\n 1.0\n > p[ 1 ]\n -1.0\n > p.y\n -1.0\n > p.key2ind( 'x' )\n 3\n\n\ntuple.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n arr: TypedArray\n A new typed array view.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr = p.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n > arr.length\n 3\n\n\ntuple.subtuple( [begin[, end]] )\n Creates a new named typed tuple over the same underlying ArrayBuffer and\n with the same underlying data type as the host tuple.\n\n If the function is unable to resolve indices to a non-empty tuple\n subsequence, the function returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray|null\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p1 = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var p2 = p1.subtuple( 2 );\n > p2.fields\n [ 'z', 'w', 'v' ]\n > p2[ 0 ]\n 0.0\n > p2.z\n 0.0\n > p2[ 1 ]\n 2.0\n > p2.w\n 2.0\n > p2[ 2 ]\n -2.0\n > p2.v\n -2.0\n > p2.length\n 3\n\n\ntuple.toJSON()\n Serializes a tuple as JSON.\n\n Returns\n -------\n obj: Object\n A tuple JSON representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toJSON()\n { 'x': 1.0, 'y': -1.0, 'z': 0.0 }\n\n\ntuple.toLocaleString( [locales[, options]] )\n Serializes a tuple as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ], 'int32' );\n > p.toLocaleString()\n '1,-1,0'\n\n\ntuple.toString()\n Serializes a tuple as a string.\n\n Returns\n -------\n str: string\n A tuple string representation.\n\n Examples\n --------\n > opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toString()\n 'Point(x=1, y=-1, z=0)'\n\n\ntuple.values()\n Returns an iterator for iterating over tuple elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple elements.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n See Also\n --------\n typedarray\n","NAN":"\nNAN\n Double-precision floating-point NaN.\n\n Examples\n --------\n > NAN\n NaN\n\n See Also\n --------\n FLOAT32_NAN\n","naryFunction":"\nnaryFunction( fcn, arity[, thisArg] )\n Returns a function that applies a specified number of arguments to a\n provided function.\n\n The returned function *always* invokes the wrapped function with a specified\n number of arguments, even when the returned function is provided fewer\n arguments.\n\n The value for the missing arguments is equal to `undefined`.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n arity: integer\n Number of arguments.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = naryFunction( foo, 2 );\n > var out = bar( 1, 2, 3 )\n [ 1, 2, undefined ]\n\n See Also\n --------\n maskArguments, pickArguments\n","nativeClass":"\nnativeClass( value )\n Returns a string value indicating a specification defined classification of\n an object.\n\n The function is *not* robust for ES2015+ environments. In ES2015+,\n `Symbol.toStringTag` allows overriding the default description of an object.\n While measures are taken to uncover the default description, such measures\n can be thwarted. While this function remains useful for type-checking, be\n aware that value impersonation is possible. Where possible, prefer functions\n tailored to checking for particular value types, as specialized functions\n are better equipped to address `Symbol.toStringTag`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n String value indicating a specification defined classification of the\n input value.\n\n Examples\n --------\n > var str = nativeClass( 'a' )\n '[object String]'\n > str = nativeClass( 5 )\n '[object Number]'\n > function Beep(){};\n > str = nativeClass( new Beep() )\n '[object Object]'\n\n See Also\n --------\n constructorName, typeOf\n","ndarray":"\nndarray( dtype, buffer, shape, strides, offset, order[, options] )\n Returns an ndarray.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n ndarray: ndarray\n ndarray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nndarray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, FancyArray\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","ndarray.prototype.data":"\nndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","ndarray.prototype.flags":"\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","ndarray.prototype.length":"\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","ndarray.prototype.offset":"\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","ndarray.prototype.order":"\nndarray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","ndarray.prototype.shape":"\nndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","ndarray.prototype.strides":"\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","ndarray.prototype.get":"\nndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","ndarray.prototype.iget":"\nndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","ndarray.prototype.set":"\nndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","ndarray.prototype.iset":"\nndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","ndarray.prototype.toString":"\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, FancyArray","ndarray2array":"\nndarray2array( x )\n Converts an ndarray to a generic array.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n Returns\n -------\n out: Array|Array\n Generic array (which may include nested arrays).\n\n Examples\n --------\n > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var out = ndarray2array( arr )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n array, ndarray\n","ndarrayCastingModes":"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n\n The output array contains the following modes:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow \"safe\" casts.\n - 'mostly-safe': allow \"safe\" casts and, for floating-point data types,\n downcasts.\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers and\n floats).\n\n Returns\n -------\n out: Array\n List of ndarray casting modes.\n\n Examples\n --------\n > var out = ndarrayCastingModes()\n [ 'none', 'equiv', 'safe', 'mostly-safe', 'same-kind', 'unsafe' ]\n\n See Also\n --------\n array, ndarray\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x )\n Returns the underlying data buffer of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: ArrayLikeObject\n Underlying data buffer.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n \n\n See Also\n --------\n array, ndarray, ndarrayDataType\n","ndarrayDataType":"\nndarrayDataType( x )\n Returns the data type of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n dt: string\n Data type.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n 'float64'\n\n See Also\n --------\n array, ndarray, ndarrayDataTypes\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind] )\n Returns a list of ndarray data types.\n\n The function supports the following data type \"kinds\":\n\n - floating_point: floating-point data types.\n - real_floating_point: real-valued floating-point data types.\n - complex_floating_point: complex-valued floating-point data types.\n - integer: integer data types.\n - signed_integer: signed integer data types.\n - unsigned_integer: unsigned integer data types.\n - real: real-valued data types.\n - numeric: numeric data types.\n - typed: typed data types.\n - all: all data types.\n\n Parameters\n ----------\n kind: string (optional)\n Data type kind.\n\n Returns\n -------\n out: Array\n List of ndarray data types.\n\n Examples\n --------\n > var out = ndarrayDataTypes()\n \n > out = ndarrayDataTypes( 'floating_point' )\n \n\n See Also\n --------\n arrayDataTypes, array, ndarray, typedarrayDataTypes\n","ndarrayDispatch":"\nndarrayDispatch( fcns, types, data, nargs, nin, nout )\n Returns an ndarray function interface which performs multiple dispatch.\n\n An ndarray function interface has the following signature:\n\n f( x, y, ... )\n\n where\n\n - x: ndarray.\n - y: ndarray.\n - ...: additional ndarrays.\n\n The number of parameters is derived from `nargs`, the number of input\n ndarrays is derived from `nin`, and the number of output ndarrays is derived\n from `nout`.\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of ndarray functions. An ndarray function should have the following\n signature:\n\n f( arrays, data )\n\n where\n\n - arrays: array containing input and output ndarrays.\n - data: ndarray function data (e.g., a callback).\n\n For convenience, a single ndarray function may be provided which will be\n invoked whenever the ndarray argument data types match a sequence of\n types in `types`. Providing a single ndarray function is particularly\n convenient for the case where, regardless of array data types,\n traversing arrays remains the same, but the ndarray function `data`\n differs (e.g., callbacks which differ based on the array data types).\n\n types: ArrayLikeObject\n One-dimensional list of ndarray argument data types.\n\n data: ArrayLikeObject|null\n ndarray function data (e.g., callbacks). If `null`, a returned ndarray\n function interface does **not** provide a `data` argument to an invoked\n ndarray function.\n\n nargs: integer\n Total number of ndarray function interface arguments.\n\n nin: integer\n Number of input ndarrays.\n\n nout: integer\n Number of output ndarrays.\n\n Returns\n -------\n fcn: Function\n ndarray function interface.\n\n Examples\n --------\n // Define ndarray argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of ndarray function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create an ndarray function interface for applying unary callbacks:\n > var f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\n\n // Create an input ndarray:\n > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n // Create an output ndarray:\n > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n // Compute the element-wise absolute value:\n > f( x, y );\n > ybuf\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n array, ndarray\n","ndarrayFlag":"\nndarrayFlag( x, name )\n Returns a specified flag for a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n name: string|symbol\n Flag name.\n\n Returns\n -------\n out: any\n Flag value.\n\n Examples\n --------\n > var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n \n\n See Also\n --------\n array, ndarray, ndarrayFlags\n","ndarrayFlags":"\nndarrayFlags( x )\n Returns the flags of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Object\n Flags.\n\n Examples\n --------\n > var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n {...}\n\n See Also\n --------\n array, ndarray, ndarrayFlag\n","ndarrayIndexModes":"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n\n The output array contains the following modes:\n\n - throw: specifies that a function should throw an error when an index is\n outside a restricted interval.\n - normalize: specifies that a function should normalize negative indices and\n throw an error when an index is outside a restricted interval.\n - wrap: specifies that a function should wrap around an index using modulo\n arithmetic.\n - clamp: specifies that a function should set an index less than zero to\n zero (minimum index) and set an index greater than a maximum index value to\n the maximum possible index.\n\n Returns\n -------\n out: Array\n List of ndarray index modes.\n\n Examples\n --------\n > var out = ndarrayIndexModes()\n [ 'throw', 'normalize', 'clamp', 'wrap' ]\n\n See Also\n --------\n array, ndarray\n","ndarrayMinDataType":"\nndarrayMinDataType( value )\n Returns the minimum ndarray data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n real numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n ndarray data type.\n\n Examples\n --------\n > var dt = ndarrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = ndarrayMinDataType( 3 )\n 'uint8'\n > dt = ndarrayMinDataType( -3 )\n 'int8'\n > dt = ndarrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast and, for floating-point data types, can be downcast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be cast.\n\n Examples\n --------\n > var out = ndarrayMostlySafeCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts, ndarraySameKindCasts\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype] )\n Returns the next larger ndarray data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = ndarrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayOffset":"\nndarrayOffset( x )\n Returns the index offset specifying the underlying buffer index of the first\n iterated ndarray element.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Index offset.\n\n Examples\n --------\n > var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n 0\n\n See Also\n --------\n array, ndarray, ndarrayShape, ndarrayStrides\n","ndarrayOrder":"\nndarrayOrder( x )\n Returns the layout order of a provided ndarray.\n\n If unable to resolve a layout order, the function returns `null`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: string|null\n Layout order.\n\n Examples\n --------\n > var opts = { 'order': 'row-major' };\n > var dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n 'row-major'\n\n See Also\n --------\n array, ndarray, ndarrayOrders, ndarrayShape, ndarrayStrides\n","ndarrayOrders":"\nndarrayOrders()\n Returns a list of ndarray orders.\n\n The output array contains the following orders:\n\n - row-major: row-major (C-style) order.\n - column-major: column-major (Fortran-style) order.\n\n Returns\n -------\n out: Array\n List of ndarray orders.\n\n Examples\n --------\n > var out = ndarrayOrders()\n [ 'row-major', 'column-major' ]\n\n See Also\n --------\n array, ndarray\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1, dtype2] )\n Returns the ndarray data type with the smallest size and closest \"kind\" to\n which ndarray data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: any (optional)\n ndarray data type value.\n\n dtype2: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = ndarrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = ndarraySafeCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySameKindCasts\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same \"kind\".\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast or cast\n within the same \"kind\".\n\n Examples\n --------\n > var out = ndarraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarrayShape":"\nndarrayShape( x )\n Returns the shape of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Array\n Shape.\n\n Examples\n --------\n > var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n [ 3, 3, 3 ]\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayStrides\n","ndarrayStride":"\nndarrayStride( x, dim )\n Returns the stride along a specified dimension for a provided ndarray.\n\n A \"stride\" is the linear distance (i.e., number of elements) between\n adjacent elements along a specified dimension.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n Returns\n -------\n out: integer\n Stride.\n\n Examples\n --------\n > var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n 9\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape, ndarrayStrides\n","ndarrayStrides":"\nndarrayStrides( x )\n Returns the strides of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Array\n Strides.\n\n Examples\n --------\n > var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n [ 9, 3, 1 ]\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape\n","ndat":"\nndat( x[, ...indices] )\n Returns an ndarray element.\n\n Negative indices are resolved relative to the last element along the\n respective dimension, with the last element corresponding to `-1`.\n\n If provided out-of-bounds indices, the function always returns `undefined`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n indices: ...integer (optional)\n Index arguments. The number of index arguments must equal the number of\n dimensions.\n\n Returns\n -------\n out: any\n Element value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > ndat( x, 0, 1 )\n 2\n > ndat( x, 1, 0 )\n 3\n\n See Also\n --------\n array, ndslice\n","ndempty":"\nndempty( shape[, options] )\n Returns an uninitialized ndarray having a specified shape and data type.\n\n In browser environments, the function always returns zero-filled ndarrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n For returned ndarrays whose underlying memory is *not* initialized, memory\n contents are unknown and may contain *sensitive* data.\n\n Parameters\n ----------\n shape: ArrayLikeObject|integer\n Array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Underlying data type. Default: 'float64'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = ndempty( [ 2, 2 ] )\n \n > var sh = arr.shape\n [ 2, 2 ]\n > var dt = arr.dtype\n 'float64'\n\n See Also\n --------\n ndemptyLike, ndzeros\n","ndemptyLike":"\nndemptyLike( x[, options] )\n Returns an uninitialized ndarray having the same shape and data type as a\n provided input ndarray.\n\n The function infers the following attributes from the input array:\n\n - shape: array shape.\n - dtype: underlying array data type.\n - order: whether the array order is row-major (C-style) or column-major\n (Fortran-style).\n\n In browser environments, the function always returns zero-filled ndarrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n For returned ndarrays whose underlying memory is *not* initialized, memory\n contents are unknown and may contain *sensitive* data.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.shape: ArrayLikeObject|integer (optional)\n Array shape. Overrides the input array's inferred shape.\n\n options.dtype: string (optional)\n Array data type. Overrides the input array's inferred data type.\n\n options.order: string (optional)\n Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n style)). Overrides the input array's inferred order.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var dt = x.dtype\n 'float64'\n > var y = ndemptyLike( x )\n \n > sh = y.shape\n [ 2, 2 ]\n > dt = y.dtype\n 'float64'\n\n See Also\n --------\n ndempty, ndzerosLike\n","ndims":"\nndims( x )\n Returns the number of ndarray dimensions.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Number of dimensions.\n\n Examples\n --------\n > var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n 3\n\n See Also\n --------\n array, ndarray, numel, ndarrayShape\n","nditerColumnEntries":"\nnditerColumnEntries( x[, options] )\n Returns an iterator which returns [index, column] pairs for each column in a\n matrix (or stack of matrices).\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerColumnEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ null, 0 ]\n > ndarray2array( v[ 1 ] )\n [ 1, 3 ]\n > v = it.next().value;\n > v[ 0 ]\n [ null, 1 ]\n > ndarray2array( v[ 1 ] )\n [ 2, 4 ]\n\n See Also\n --------\n nditerColumns, nditerEntries, nditerRowEntries, ndslice\n","nditerColumns":"\nnditerColumns( x[, options] )\n Returns an iterator which iterates over each column in a matrix (or stack of\n matrices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerColumns( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ 1, 3 ]\n > v = it.next().value;\n > ndarray2array( v )\n [ 2, 4 ]\n\n See Also\n --------\n nditerColumnEntries, nditerRows, ndslice\n","nditerEntries":"\nnditerEntries( x[, options] )\n Returns an iterator which returns [index, value] pairs for each element in a\n provided ndarray.\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator returns values\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manor, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerEntries( x );\n > var v = it.next().value\n [ [ 0, 0 ], 1 ]\n > v = it.next().value\n [ [ 0, 1 ], 2 ]\n\n See Also\n --------\n ndarray, nditerIndices, nditerValues\n","nditerIndices":"\nnditerIndices( shape[, options] )\n Returns an iterator which returns indices for use indexing into an ndarray\n having a specified shape.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n shape: Array\n Input shape.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator iterates over\n the last dimensions first, thus corresponding to iteration over\n contiguous data stored in row-major order. Must be either 'row-major'\n or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerIndices( x.shape );\n > var v = it.next().value\n [ 0, 0 ]\n > v = it.next().value\n [ 0, 1 ]\n\n See Also\n --------\n ndarray, nditerEntries, nditerValues\n","nditerMatrices":"\nnditerMatrices( x[, options] )\n Returns an iterator which iterates over each matrix in a stack of matrices.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerMatrices( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrixEntries, nditerRows, ndslice\n","nditerMatrixEntries":"\nnditerMatrixEntries( x[, options] )\n Returns an iterator which returns [index, matrix] pairs for each matrix in a\n stack of matrices.\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerMatrixEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ 0, null, null ]\n > ndarray2array( v[ 1 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumnEntries, nditerEntries, nditerMatrices, nditerRowEntries, ndslice\n","nditerRowEntries":"\nnditerRowEntries( x[, options] )\n Returns an iterator which returns [index, row] pairs for each row in a\n matrix (or stack of matrices).\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerRowEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ 0, null ]\n > ndarray2array( v[ 1 ] )\n [ 1, 2 ]\n > v = it.next().value;\n > v[ 0 ]\n [ 1, null ]\n > ndarray2array( v[ 1 ] )\n [ 3, 4 ]\n\n See Also\n --------\n nditerColumnEntries, nditerEntries, nditerRows, ndslice\n","nditerRows":"\nnditerRows( x[, options] )\n Returns an iterator which iterates over each row in a matrix (or stack of\n matrices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerRows( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ 1, 2 ]\n > v = it.next().value;\n > ndarray2array( v )\n [ 3, 4 ]\n\n See Also\n --------\n nditerColumns, nditerRowEntries, ndslice\n","nditerValues":"\nnditerValues( x[, options] )\n Returns an iterator which returns individual elements from a provided\n ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator returns values\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manor, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerValues( x );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n ndarray, nditerEntries, nditerIndices\n","ndslice":"\nndslice( x, ...s[, options] )\n Returns a read-only view of an input ndarray.\n\n The function supports three (mutually exclusive) means of providing slice\n arguments:\n\n 1. Providing a single MultiSlice object.\n 2. Providing a single array containing slice arguments.\n 3. Providing slice arguments as separate arguments.\n\n An individual slice argument must be either a Slice, an integer, null, or\n undefined.\n\n In all cases, the number of slice dimensions must match the number of array\n dimensions.\n\n If providing a MultiSlice object or an array of slice arguments, no other\n slice arguments should be provided.\n\n Mixing function invocation styles (e.g., providing multiple MultiSlice\n objects or providing an array of slice arguments followed by additional\n slice arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n Slice arguments.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var s = new MultiSlice( null, 1 )\n \n > var y = ndslice( x, s )\n \n > y.shape\n [ 2 ]\n > ndarray2array( y )\n [ 2, 4 ]\n\n See Also\n --------\n array, ndat, ndarray, ndsliceAssign, ndsliceDimension\n","ndsliceAssign":"\nndsliceAssign( x, y, ...s[, options] )\n Assigns element values from a broadcasted input ndarray to corresponding\n elements in an output ndarray view.\n\n The function supports three (mutually exclusive) means of providing slice\n arguments:\n\n 1. Providing a single MultiSlice object.\n 2. Providing a single array containing slice arguments.\n 3. Providing slice arguments as separate arguments.\n\n An individual slice argument must be either a Slice, an integer, null, or\n undefined.\n\n In all cases, the number of slice dimensions must match the number of output\n array dimensions.\n\n If providing a MultiSlice object or an array of slice arguments, no other\n slice arguments should be provided.\n\n Mixing function invocation styles (e.g., providing multiple MultiSlice\n objects or providing an array of slice arguments followed by additional\n slice arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array. The input array must be broadcast compatible with the\n output array view and must have a data type which can be safely cast to\n the output array data type. Floating-point data types (both real and\n complex) are allowed to downcast to a lower precision data type of the\n same kind (e.g., element values from a 'float64' input array can be\n assigned to corresponding elements in a 'float32' output array).\n\n y: ndarray\n Output array. The output array must be writable.\n\n s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n Slice arguments.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var y = ndzeros( [ 2, 2 ] )\n \n > var x = scalar2ndarray( 3.0 )\n \n > var s = new MultiSlice( null, 1 )\n \n > var out = ndsliceAssign( x, y, s )\n \n > var bool = ( out === y )\n true\n > ndarray2array( y )\n [ [ 0.0, 3.0 ], [ 0.0, 3.0 ] ]\n\n See Also\n --------\n array, ndarray, ndslice\n","ndsliceDimension":"\nndsliceDimension( x, dim, slice[, options] )\n Returns a read-only view of an input ndarray when sliced along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n slice: Slice|integer|null|undefined\n Slice object or an integer. If provided `null` or `undefined`, the\n returned view includes all elements along a specified dimension. If\n provided an integer less than zero, the corresponding element along the\n specified dimension is resolved relative to the last element along that\n dimension. For negative integers, the last element corresponds to the\n value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimension( x, 1, 1 )\n \n > y.shape\n [ 2 ]\n > ndarray2array( y )\n [ 2, 4 ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceDimensionTo\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x, dim, start[, options] )\n Returns a read-only shifted view of an input ndarray along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n start: integer\n Starting index (inclusive). If less than zero, the corresponding element\n along the specified dimension is resolved relative to the last element\n along that dimension. For negative integers, the last element\n corresponds to the value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimensionFrom( x, 1, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 2 ], [ 4 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionTo, ndsliceFrom\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x, dim, stop[, options] )\n Returns a read-only truncated view of an input ndarray along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n stop: integer\n Ending index (exclusive). If less than zero, the corresponding element\n along the specified dimension is resolved relative to the last element\n along that dimension. For negative integers, the last element\n corresponds to the value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimensionTo( x, 1, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 1 ], [ 3 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionFrom, ndsliceTo\n","ndsliceFrom":"\nndsliceFrom( x, ...start[, options] )\n Returns a read-only shifted view of an input ndarray.\n\n The function supports two (mutually exclusive) means of providing starting\n indices:\n\n 1. Providing a single array containing start arguments.\n 2. Providing start arguments as separate arguments.\n\n An individual start argument must be either an integer, null, or undefined.\n\n In all cases, the number of start indices must match the number of array\n dimensions.\n\n If providing an array of start arguments, no other start arguments should be\n provided.\n\n Mixing function invocation styles (e.g., providing an array of start\n arguments followed by additional start arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n start: ...null|void|integer\n Starting indices (inclusive). If an element is either `null` or\n `undefined`, the function returns a view containing all elements along\n that dimension. A negative integer indicates to resolve a starting index\n relative to the last element along a corresponding dimension, with the\n last element having index `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceFrom( x, 0, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 2 ], [ 4 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceTo\n","ndsliceTo":"\nndsliceTo( x, ...stop[, options] )\n Returns a read-only truncated view of an input ndarray.\n\n The function supports two (mutually exclusive) means of providing ending\n indices:\n\n 1. Providing a single array containing stop arguments.\n 2. Providing stop arguments as separate arguments.\n\n An individual stop argument must be either an integer, null, or undefined.\n\n In all cases, the number of stop indices must match the number of array\n dimensions.\n\n If providing an array of stop arguments, no other stop arguments should be\n provided.\n\n Mixing function invocation styles (e.g., providing an array of stop\n arguments followed by additional stop arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n stop: ...null|void|integer\n Ending indices (exclusive). If an ending index is either `null` or\n `undefined`, the function returns a view containing all elements along\n that dimension. A negative integer indicates to resolve an ending index\n relative to the last element along a corresponding dimension, with the\n last element having index `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceTo( x, 1, 1 )\n \n > y.shape\n [ 1, 1 ]\n > ndarray2array( y )\n [ [ 1 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionTo, ndsliceFrom\n","ndzeros":"\nndzeros( shape[, options] )\n Returns a zero-filled ndarray having a specified shape and data type.\n\n Parameters\n ----------\n shape: ArrayLikeObject|integer\n Array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Underlying data type. Default: 'float64'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = ndzeros( [ 2, 2 ] )\n \n > var sh = arr.shape\n [ 2, 2 ]\n > var dt = arr.dtype\n 'float64'\n\n See Also\n --------\n ndempty, ndzerosLike\n","ndzerosLike":"\nndzerosLike( x[, options] )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n\n The function infers the following attributes from the input array:\n\n - shape: array shape.\n - dtype: underlying array data type.\n - order: whether the array order is row-major (C-style) or column-major\n (Fortran-style).\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.shape: ArrayLikeObject|integer (optional)\n Array shape. Overrides the input array's inferred shape.\n\n options.dtype: string (optional)\n Array data type. Overrides the input array's inferred data type.\n\n options.order: string (optional)\n Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n style)). Overrides the input array's inferred order.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var dt = x.dtype\n 'float64'\n > var y = ndzerosLike( x )\n \n > sh = y.shape\n [ 2, 2 ]\n > dt = y.dtype\n 'float64'\n\n See Also\n --------\n ndemptyLike, ndzeros\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str[, fromIndex] )\n Returns the next extended grapheme cluster break in a string after a\n specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n fromIndex: integer (optional)\n Position. Default: 0.\n\n Returns\n -------\n out: integer\n Next extended grapheme cluster break position.\n\n Examples\n --------\n > var out = nextGraphemeClusterBreak( 'last man standing', 4 )\n 5\n > out = nextGraphemeClusterBreak( 'presidential election', 8 )\n 9\n > out = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\n 3\n > out = nextGraphemeClusterBreak( '🌷' )\n -1\n\n See Also\n --------\n numGraphemeClusters, prevGraphemeClusterBreak","nextTick":"\nnextTick( clbk[, ...args] )\n Adds a callback to the \"next tick queue\".\n\n The queue is fully drained after the current operation on the JavaScript\n stack runs to completion and before the event loop is allowed to continue.\n\n Parameters\n ----------\n clbk: Function\n Callback to invoke.\n\n ...args: any (optional)\n Arguments to provide to the callback upon invocation.\n\n Examples\n --------\n > function f() { console.log( 'beep' ); };\n > nextTick( f )\n\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n\n Returns\n -------\n out: Array\n Nightingale's data.\n\n Examples\n --------\n > var data = NIGHTINGALES_ROSE()\n [{...}, {...}, ...]\n\n References\n ----------\n - Nightingale, Florence. 1859. *A contribution to the sanitary history of\n the British army during the late war with Russia*. London, United Kingdom:\n John W. Parker and Son..\n\n","NINF":"\nNINF\n Double-precision floating-point negative infinity.\n\n Examples\n --------\n > NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_NINF, PINF\n","NODE_VERSION":"\nNODE_VERSION\n Node version.\n\n Examples\n --------\n > NODE_VERSION\n \n\n","none":"\nnone( collection )\n Tests whether all elements in a collection are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are falsy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0 ];\n > var bool = none( arr )\n true\n\n See Also\n --------\n any, every, forEach, noneBy, some\n","noneBy":"\nnoneBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = noneBy( arr, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, none, noneByRight, someBy\n","noneByAsync":"\nnoneByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync\n","noneByAsync.factory":"\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync","noneByRight":"\nnoneByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ -1, -2, -3, -4 ];\n > var bool = noneByRight( arr, positive )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, none, noneBy, someByRight\n","noneByRightAsync":"\nnoneByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync","nonEnumerableProperties":"\nnonEnumerableProperties( value )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own non-enumerable properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var props = nonEnumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerableProperties, inheritedNonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited non-enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = nonEnumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerablePropertiesIn, inheritedNonEnumerableProperties, nonEnumerableProperties, propertiesIn\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value )\n Returns an array of an object's own non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNames( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n objectKeys, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNamesIn( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n keysIn, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNames, propertyNamesIn\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value )\n Returns an array of an object's own non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNames, nonEnumerablePropertySymbolsIn, propertySymbols\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertySymbolsIn\n","nonIndexKeys":"\nnonIndexKeys( obj )\n Returns an array of an object's own enumerable property names which are not\n integer indices.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; this[0] = 3.14; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = nonIndexKeys( obj )\n e.g., [ 'beep' ]\n\n See Also\n --------\n objectEntries, objectKeys, objectValues\n","noop":"\nnoop()\n A function which does nothing.\n\n Examples\n --------\n > noop();\n\n","now":"\nnow()\n Returns the time in seconds since the epoch.\n\n The Unix epoch is 00:00:00 UTC on 1 January 1970.\n\n Returns\n -------\n out: integer\n Time in seconds since the epoch.\n\n Examples\n --------\n > var ts = now()\n \n\n","NUM_CPUS":"\nNUM_CPUS\n Number of CPUs.\n\n In browser environments, the number of CPUs is determined by querying the\n hardware concurrency API.\n\n In Node.js environments, the number of CPUs is determined via the `os`\n module.\n\n Examples\n --------\n > NUM_CPUS\n \n\n","num2words":"\nnum2words( value[, options] )\n Converts a number to a word representation.\n\n Parameters\n ----------\n value: integer\n Input value.\n\n options: Object (optional)\n Options.\n\n options.lang: string (optional)\n Language code. Supported languages:\n\n - en: English.\n - de: German.\n\n Default: `'en'`.\n\n Returns\n -------\n out: string\n Word representation of number.\n\n Examples\n --------\n > var out = num2words( 123 )\n 'one hundred twenty-three'\n\n > out = num2words( 16.31 )\n 'sixteen point three one'\n\n > out = num2words( 123, { 'lang': 'de' } )\n 'einhundertdreiundzwanzig'\n\n","Number":"\nNumber( value )\n Returns a Number object.\n\n This constructor should be used sparingly. Always prefer number primitives.\n\n Parameters\n ----------\n value: number\n Value to wrap in a Number object.\n\n Returns\n -------\n out: Number\n Number object.\n\n Examples\n --------\n > var v = new Number( 5 )\n \n\n","numel":"\nnumel( x )\n Returns the number of elements in an ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Number of elements.\n\n Examples\n --------\n > var n = numel( ndzeros( [ 3, 3, 3 ] ) )\n 27\n\n See Also\n --------\n array, ndarray, numelDimension\n","numelDimension":"\nnumelDimension( x, dim )\n Returns the size (i.e., number of elements) of a specified dimension for a\n provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n Returns\n -------\n out: integer\n Dimension size.\n\n Examples\n --------\n > var out = numelDimension( ndzeros( [ 4, 2, 3 ] ), 0 )\n 4\n\n See Also\n --------\n array, ndarray, numel\n","numGraphemeClusters":"\nnumGraphemeClusters( str )\n Returns the number of grapheme clusters in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Number of grapheme clusters.\n\n Examples\n --------\n > var out = numGraphemeClusters( 'beep' )\n 4\n > out = numGraphemeClusters( '🌷' )\n 1\n\n See Also\n --------\n nextGraphemeClusterBreak\n","Object":"\nObject( value )\n Returns an object.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n If provided an existing object, the function returns the input value\n unchanged.\n\n Otherwise, if provided any other value (e.g., a number, string, etc), the\n function will return an object of the corresponding type.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > var o = new Object( null )\n {}\n > o = new Object( 5.0 )\n \n > o = new Object( 'beep' )\n \n\nObject.assign( target, ...sources )\n Assigns enumerable and own properties from source objects to a target\n object.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n sources: ...Object\n Source objects.\n\n Returns\n -------\n out: Object\n Target object.\n\n Examples\n --------\n > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n { 'a': 1, 'b': 2 }\n\nObject.create( prototype, properties )\n Creates a new object with a specified prototype object and properties.\n\n Parameters\n ----------\n prototype: Object\n Prototype object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }\n\nObject.defineProperties( obj, properties )\n Defines properties for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }\n\nObject.defineProperty( obj, key, descriptor )\n Defines a property for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n descriptor: Object\n Property descriptor.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperty( {}, 'a', {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': false\n })\n { 'a': 1 }\n\nObject.entries( obj )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of [key, value] pairs.\n\n Examples\n --------\n > var o = Object.entries( { 'a': 1, 'b': 2 } )\n [ [ 'a', 1 ], [ 'b', 2 ] ]\n\nObject.freeze( obj )\n Freezes an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.freeze( { 'a': 1 } )\n { 'a': 1 }\n\nObject.getOwnPropertyDescriptor( obj, key )\n Returns an object's own property descriptor.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n Returns\n -------\n out: Object\n Property descriptor.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }\n\nObject.getOwnPropertyDescriptors( obj )\n Returns an object's own property descriptors.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Property descriptors.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n {\n 'a': {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n },\n 'b': {\n 'value': 2,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n }\n }\n\nObject.getOwnPropertyNames( obj )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]\n\nObject.getOwnPropertySymbols( obj )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of symbol property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n []\n\nObject.getPrototypeOf( obj )\n Returns an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Prototype.\n\n Examples\n --------\n > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n \n\nObject.hasOwn( obj, p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n true\n\nObject.is( value1, value2 )\n Returns a boolean indicating whether two values are the same value.\n\n Parameters\n ----------\n value1: any\n First value.\n\n value2: any\n Second value.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether two values are the same value.\n\n Examples\n --------\n > var o = Object.is( 1, 1 )\n true\n > var o = Object.is( 1, '1' )\n false\n\nObject.isExtensible( obj )\n Returns a boolean indicating whether an object is extensible.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is extensible.\n\n Examples\n --------\n > var o = Object.isExtensible( { 'a': 1 } )\n true\n\nObject.isFrozen( obj )\n Returns a boolean indicating whether an object is frozen.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is frozen.\n\n Examples\n --------\n > var o = Object.isFrozen( { 'a': 1 } )\n false\n > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n true\n\nObject.isSealed( obj )\n Returns a boolean indicating whether an object is sealed.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is sealed.\n\n Examples\n --------\n > var o = Object.isSealed( { 'a': 1 } )\n false\n > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n true\n\nObject.keys( obj )\n Returns an array of an object's own enumerable string-keyed property\n names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.keys( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]\n\nObject.preventExtensions( obj )\n Prevents the addition of new properties to an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.preventExtensions( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n\nObject.seal( obj )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.seal( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n > delete o.a;\n > o\n { 'a': 1 }\n\nObject.setPrototypeOf( obj, proto )\n Sets an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n proto: Object\n Prototype.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n { 'a': 1 }\n > o.b\n 2\n\nObject.values( obj )\n Returns an array of an object's own enumerable property values.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property values.\n\n Examples\n --------\n > var o = Object.values( { 'a': 1, 'b': 2 } )\n [ 1, 2 ]\n\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n \n\nObject.prototype.toString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n \n\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n\n Returns\n -------\n out: any\n Primitive value of the object.\n\n Examples\n --------\n > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n {}\n\nObject.prototype.hasOwnProperty( p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n true\n\nObject.prototype.isPrototypeOf( obj )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object exists in another object's\n prototype chain.\n\n Examples\n --------\n > var p = { 'a': 1 };\n > var o = { '__proto__': p };\n > var b = o.isPrototypeOf( p );\n true\n\nObject.prototype.propertyIsEnumerable( p )\n Returns a boolean indicating whether an object's property is enumerable.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object's property is enumerable.\n\n Examples\n --------\n > var o = { 'a': 1, 'b': 2 };\n > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n true\n\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n\n Examples\n --------\n > var o = new Object( null );\n > var ctr = o.constructor;\n \n\n","Object.assign":"\nObject.assign( target, ...sources )\n Assigns enumerable and own properties from source objects to a target\n object.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n sources: ...Object\n Source objects.\n\n Returns\n -------\n out: Object\n Target object.\n\n Examples\n --------\n > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n { 'a': 1, 'b': 2 }","Object.create":"\nObject.create( prototype, properties )\n Creates a new object with a specified prototype object and properties.\n\n Parameters\n ----------\n prototype: Object\n Prototype object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }","Object.defineProperties":"\nObject.defineProperties( obj, properties )\n Defines properties for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }","Object.defineProperty":"\nObject.defineProperty( obj, key, descriptor )\n Defines a property for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n descriptor: Object\n Property descriptor.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperty( {}, 'a', {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': false\n })\n { 'a': 1 }","Object.entries":"\nObject.entries( obj )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of [key, value] pairs.\n\n Examples\n --------\n > var o = Object.entries( { 'a': 1, 'b': 2 } )\n [ [ 'a', 1 ], [ 'b', 2 ] ]","Object.freeze":"\nObject.freeze( obj )\n Freezes an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.freeze( { 'a': 1 } )\n { 'a': 1 }","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj, key )\n Returns an object's own property descriptor.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n Returns\n -------\n out: Object\n Property descriptor.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj )\n Returns an object's own property descriptors.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Property descriptors.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n {\n 'a': {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n },\n 'b': {\n 'value': 2,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n }\n }","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of symbol property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n []","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj )\n Returns an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Prototype.\n\n Examples\n --------\n > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n ","Object.hasOwn":"\nObject.hasOwn( obj, p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n true","Object.is":"\nObject.is( value1, value2 )\n Returns a boolean indicating whether two values are the same value.\n\n Parameters\n ----------\n value1: any\n First value.\n\n value2: any\n Second value.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether two values are the same value.\n\n Examples\n --------\n > var o = Object.is( 1, 1 )\n true\n > var o = Object.is( 1, '1' )\n false","Object.isExtensible":"\nObject.isExtensible( obj )\n Returns a boolean indicating whether an object is extensible.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is extensible.\n\n Examples\n --------\n > var o = Object.isExtensible( { 'a': 1 } )\n true","Object.isFrozen":"\nObject.isFrozen( obj )\n Returns a boolean indicating whether an object is frozen.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is frozen.\n\n Examples\n --------\n > var o = Object.isFrozen( { 'a': 1 } )\n false\n > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n true","Object.isSealed":"\nObject.isSealed( obj )\n Returns a boolean indicating whether an object is sealed.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is sealed.\n\n Examples\n --------\n > var o = Object.isSealed( { 'a': 1 } )\n false\n > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n true","Object.keys":"\nObject.keys( obj )\n Returns an array of an object's own enumerable string-keyed property\n names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.keys( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]","Object.preventExtensions":"\nObject.preventExtensions( obj )\n Prevents the addition of new properties to an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.preventExtensions( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }","Object.seal":"\nObject.seal( obj )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.seal( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n > delete o.a;\n > o\n { 'a': 1 }","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj, proto )\n Sets an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n proto: Object\n Prototype.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n { 'a': 1 }\n > o.b\n 2","Object.values":"\nObject.values( obj )\n Returns an array of an object's own enumerable property values.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property values.\n\n Examples\n --------\n > var o = Object.values( { 'a': 1, 'b': 2 } )\n [ 1, 2 ]","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n ","Object.prototype.toString":"\nObject.prototype.toString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n ","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n\n Returns\n -------\n out: any\n Primitive value of the object.\n\n Examples\n --------\n > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n {}","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n true","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object exists in another object's\n prototype chain.\n\n Examples\n --------\n > var p = { 'a': 1 };\n > var o = { '__proto__': p };\n > var b = o.isPrototypeOf( p );\n true","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p )\n Returns a boolean indicating whether an object's property is enumerable.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object's property is enumerable.\n\n Examples\n --------\n > var o = { 'a': 1, 'b': 2 };\n > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n true","Object.prototype.constructor":"\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n\n Examples\n --------\n > var o = new Object( null );\n > var ctr = o.constructor;\n ","objectEntries":"\nobjectEntries( obj )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var entries = objectEntries( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntriesIn, objectFromEntries, objectKeys, objectValues\n","objectEntriesIn":"\nobjectEntriesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var entries = objectEntriesIn( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntries, objectFromEntries, keysIn, objectValuesIn\n","objectFromEntries":"\nobjectFromEntries( entries )\n Creates an object from an array of key-value pairs.\n\n Parameters\n ----------\n entries: Array\n Input object.\n\n Returns\n -------\n out: Object\n Object created from `[key, value]` pairs.\n\n Examples\n --------\n > var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\n > var obj = objectFromEntries( entries )\n { 'beep': 'boop', 'foo': 'bar' }\n\n See Also\n --------\n objectEntries\n","objectInverse":"\nobjectInverse( obj[, options] )\n Inverts an object, such that keys become values and values become keys.\n\n Beware when providing objects having values which are themselves objects.\n The function relies on native object serialization (`#toString`) when\n converting values to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverse( obj )\n { 'beep': 'a', 'boop': 'b' }\n\n // Duplicate values:\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverse( obj )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverse( obj, { 'duplicates': false } )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverseBy\n","objectInverseBy":"\nobjectInverseBy( obj, [options,] transform )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n\n The transform function is provided three arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n\n The value returned by a transform function should be a value which can be\n serialized as an object key. Hence, beware when providing objects having\n values which are themselves objects. The function relies on native object\n serialization (`#toString`) when converting transform function return values\n to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n transform: Function\n Transform function.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverseBy( obj, transform )\n { 'abeep': 'a', 'bboop': 'b' }\n\n // Duplicate values:\n > function transform( key, value ) { return value; };\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverseBy( obj, transform )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverseBy( obj, { 'duplicates': false }, transform )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverse\n","objectKeys":"\nobjectKeys( value )\n Returns an array of an object's own enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = objectKeys( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectEntries, keysIn, nonIndexKeys, objectValues\n","objectValues":"\nobjectValues( obj )\n Returns an array of an object's own enumerable property values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var vals = objectValues( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntries, objectKeys\n","objectValuesIn":"\nobjectValuesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var values = objectValuesIn( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntriesIn, keysIn, objectValues\n","omit":"\nomit( obj, keys )\n Returns a partial object copy excluding specified keys.\n\n The function returns a shallow copy.\n\n The function ignores non-existent keys.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to exclude.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omit( obj1, 'b' )\n { 'a': 1 }\n\n See Also\n --------\n omitBy\n","omitBy":"\nomitBy( obj, predicate )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n\n The function returns a shallow copy.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) { return ( value > 1 ); };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omitBy( obj1, predicate )\n { 'a': 1 }\n\n See Also\n --------\n omit\n","open":"\nopen( path[, flags[, mode]], clbk )\n Asynchronously opens a file.\n\n Some characters, such as <>:\"/\\|?*, are reserved under Windows.\n Under NTFS, if the path contains a colon, Node.js will open a file system\n stream.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon opening a file.\n\n Examples\n --------\n > function onOpen( error, fd ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... close.sync( fd );\n ... }\n ... };\n > open( './beep/boop.txt', onOpen );\n\n\nopen.sync( path[, flags[, mode]] )\n Synchronously opens a file.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n Returns\n -------\n fd: Error|integer\n File descriptor.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.txt' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n close, exists, readFile\n","open.sync":"\nopen.sync( path[, flags[, mode]] )\n Synchronously opens a file.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n Returns\n -------\n fd: Error|integer\n File descriptor.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.txt' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n close, exists, readFile","openURL":"\nopenURL( url )\n Opens a URL in a user's default browser.\n\n In a non-browser environment, the function returns an unreferenced child\n process. In a browser environment, the function returns a reference to a\n `window` object.\n\n Parameters\n ----------\n url: string\n URL to open.\n\n Returns\n -------\n out: process|Window\n Child process or `window` object.\n\n Examples\n --------\n > var out = openURL( 'https://google.com' );\n\n","ordinalize":"\nordinalize( value[, options] )\n Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n\n Parameters\n ----------\n value: string|integer\n Input value.\n\n options: Object (optional)\n Options.\n\n options.lang: string (optional)\n Language code. Supported languages:\n\n - en: English.\n - es: Spanish.\n - fin: Finnish.\n - fr: French.\n - de: Dutch.\n - it: Italian.\n - pt: Portuguese.\n - swe: Swedish.\n\n Default: `'en'`.\n\n options.suffixOnly: boolean (optional)\n Boolean indicating whether to return only the suffix. Default: `false`.\n\n options.gender: string (optional)\n Grammatical gender (used if applicable); must be either 'masculine' or\n 'feminine'. Default: `'masculine'`.\n\n Returns\n -------\n out: string\n Ordinal string or suffix.\n\n Examples\n --------\n > var out = ordinalize( '1' )\n '1st'\n > out = ordinalize( 2, { 'suffixOnly': true } )\n 'nd'\n > out = ordinalize( '3', { 'lang': 'es' } )\n '3º'\n\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 21 attributes:\n\n - obs: observation number\n - town: town name\n - town_id: town identifier\n - tract: tract identifier\n - lon: longitude\n - lat: latitude\n - medv: median value of owner-occupied homes in $1000's\n - cmedv: corrected median value of owner-occupied homes in $1000's\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n The dataset augments the original dataset from Harrison and Rubinfeld (1978)\n by including geo-referencing and spatial estimation for each observation.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = PACE_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n - Pace, R. Kelley, and Otis W. Gilley. 1997. \"Using the Spatial\n Configuration of the Data to Improve Estimation.\" _The Journal of Real\n Estate Finance and Economics_ 14 (3): 333–40. doi:10.1023/A:1007762613901.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, HARRISON_BOSTON_HOUSE_PRICES_CORRECTED\n","pad":"\npad( str, len[, options] )\n Pads a `string` such that the padded `string` has length `len`.\n\n Any padding which does not evenly divide available space is trimmed such\n that the returned string length is always `len`.\n\n If `len < str.length`, the input string is trimmed.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n options: Object (optional)\n Options.\n\n options.lpad: string (optional)\n String used to left pad.\n\n options.rpad: string (optional)\n String used to right pad.\n\n options.centerRight: boolean (optional)\n Boolean indicating whether to center right in the event of a tie.\n Default: `false` (i.e., center left).\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n // Standard usage:\n > var out = pad( 'a', 5 )\n 'a '\n\n // Left pad:\n > out = pad( 'a', 10, { 'lpad': 'b' } )\n 'bbbbbbbbba'\n\n // Right pad:\n > out = pad( 'a', 12, { 'rpad': 'b' } )\n 'abbbbbbbbbbb'\n\n // Center an input string:\n > var opts = { 'lpad': 'a', 'rpad': 'c' };\n > out = pad( 'b', 11, opts )\n 'aaaaabccccc'\n\n // Left center:\n > opts.centerRight = false;\n > out = pad( 'b', 10, opts )\n 'aaaabccccc'\n\n // Right center:\n > opts.centerRight = true;\n > out = pad( 'b', 10, opts )\n 'aaaaabcccc'\n\n // Output string always length `len`:\n > opts = { 'lpad': 'boop', 'rpad': 'woot' };\n > out = pad( 'beep', 10, opts )\n 'boobeepwoo'\n\n // Pad right, trim right:\n > out = pad( 'beep', 2 )\n 'be'\n\n // Pad left, trim left:\n > opts = { 'lpad': 'b' };\n > out = pad( 'beep', 2, opts )\n 'ep'\n\n // Pad both, trim both:\n > opts = { 'lpad': '@', 'rpad': '!' };\n > out = pad( 'beep', 2, opts )\n 'ee'\n\n // Pad both, trim both starting from left:\n > out = pad( 'abcdef', 3, opts )\n 'cde'\n\n // Pad both, trim both starting from right:\n > opts.centerRight = true;\n > out = pad( 'abcdef', 3, opts )\n 'bcd'\n\n See Also\n --------\n lpad, rpad\n","padjust":"\npadjust( pvals, method[, comparisons] )\n Adjusts supplied p-values for multiple comparisons via a specified method.\n\n The `method` parameter can be one of the following values:\n\n - **bh**: Benjamini-Hochberg procedure controlling the False Discovery\n Rate (FDR).\n - **bonferroni**: Bonferroni correction fixing the family-wise error rate\n by multiplying the p-values with the number of comparisons. The Bonferroni\n correction is usually a too conservative adjustment compared to the others.\n - **by**: Procedure by Benjamini & Yekutieli for controlling the False\n Discovery Rate (FDR) under dependence.\n - **holm**: Hommel's method controlling family-wise error rate. It is\n uniformly more powerful than the Bonferroni correction.\n - **hommel**: Hommel's method, which is valid when hypothesis tests are\n independent. It is more expensive to compute than the other methods.\n\n By default, the number of comparisons for which the p-values should be\n corrected is equal to the number of provided p-values. Alternatively, it is\n possible to set `comparisons` to a number greater than the length of\n `pvals`. In that case, the methods assume `comparisons - pvals.length`\n unobserved p-values that are greater than all observed p-values (for Holm's\n method and the Bonferroni correction) or equal to `1` for the remaining\n methods.\n\n Parameters\n ----------\n pvals: Array\n P-values to be adjusted.\n\n method: string\n Correction method.\n\n comparisons: integer (optional)\n Number of comparisons. Default value: `pvals.length`.\n\n Returns\n -------\n out: Array\n Array containing the corrected p-values.\n\n Examples\n --------\n > var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\n > var out = padjust( pvalues, 'bh' )\n [ 0.04, 0.075, ~0.205, 0.6, 0.25 ]\n\n > out = padjust( pvalues, 'bonferroni' )\n [ 0.04, 0.15, 0.615, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'by' )\n [ ~0.457, ~0.856, 1.0, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'holm' )\n [ 0.2, 0.6, 1.0, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'hommel' )\n [ 0.16, 0.6, 1.0, 1.0, 1.0 ]\n\n","papply":"\npapply( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var add2 = papply( add, 2 );\n > var sum = add2( 3 )\n 5\n\n See Also\n --------\n papplyRight\n","papplyRight":"\npapplyRight( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function say( text, name ) { return text + ', ' + name + '.'; };\n > var toGrace = papplyRight( say, 'Grace Hopper' );\n > var str = toGrace( 'Hello' )\n 'Hello, Grace Hopper.'\n > str = toGrace( 'Thank you' )\n 'Thank you, Grace Hopper.'\n\n See Also\n --------\n papply\n","parallel":"\nparallel( files, [options,] clbk )\n Executes scripts in parallel.\n\n Relative file paths are resolved relative to the current working directory.\n\n Ordered script output does not imply that scripts are executed in order. To\n preserve script order, execute the scripts sequentially via some other\n means.\n\n Parameters\n ----------\n files: Array\n Script file paths.\n\n options: Object (optional)\n Options.\n\n options.cmd: string (optional)\n Executable file/command. Default: `'node'`.\n\n options.concurrency: integer (optional)\n Number of scripts to execute concurrently. Script concurrency cannot\n exceed the number of scripts. By specifying a concurrency greater than\n the number of workers, a worker may be executing more than `1` script at\n any one time. While not likely to be advantageous for synchronous\n scripts, setting a higher concurrency may be advantageous for scripts\n performing asynchronous tasks. If the script concurrency is less than\n the number of workers, the number of workers is reduced to match the\n specified concurrency. Default: `options.workers`.\n\n options.workers: integer (optional)\n Number of workers. Default: number of CPUs minus `1`.\n\n options.ordered: boolean (optional)\n Boolean indicating whether to preserve the order of script output. By\n default, the `stdio` output for each script is interleaved; i.e., the\n `stdio` output from one script may be interleaved with the `stdio`\n output from one or more other scripts. To preserve the `stdio` output\n order for each script, set the `ordered` option to `true`. Default:\n `false`.\n\n options.uid: integer (optional)\n Process user identity.\n\n options.gid: integer (optional)\n Process group identity.\n\n options.maxBuffer: integer (optional)\n Max child process `stdio` buffer size. This option is only applied when\n `options.ordered = true`. Default: `200*1024*1024`.\n\n clbk: Function\n Callback to invoke after executing all scripts.\n\n Examples\n --------\n > function done( error ) { if ( error ) { throw error; } };\n > var files = [ './a.js', './b.js' ];\n > parallel( files, done );\n\n // Specify the number of workers:\n > var opts = { 'workers': 8 };\n > parallel( files, opts, done );\n\n","parseJSON":"\nparseJSON( str[, reviver] )\n Attempts to parse a string as JSON.\n\n Function behavior differs from `JSON.parse()` as follows:\n\n - throws a `TypeError` if provided any value which is not a string.\n - throws a `TypeError` if provided a `reviver` argument which is not a\n function.\n - returns, rather than throws, a `SyntaxError` if unable to parse a string\n as JSON.\n\n Parameters\n ----------\n str: string\n String to parse.\n\n reviver: Function (optional)\n Transformation function.\n\n Returns\n -------\n out: any|Error\n Parsed value or an error.\n\n Examples\n --------\n > var obj = parseJSON( '{\"beep\":\"boop\"}' )\n { 'beep': 'boop' }\n\n // Provide a reviver:\n > function reviver( key, value ) {\n ... if ( key === '' ) { return value; }\n ... if ( key === 'beep' ) { return value; }\n ... };\n > var str = '{\"beep\":\"boop\",\"a\":\"b\"}';\n > var out = parseJSON( str, reviver )\n { 'beep': 'boop' }\n\n","pascalcase":"\npascalcase( str )\n Converts a string to Pascal case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Pascal-cased string.\n\n Examples\n --------\n > var out = pascalcase( 'Hello World!' )\n 'HelloWorld'\n > out = pascalcase( 'beep boop' )\n 'BeepBoop'\n\n See Also\n --------\n camelcase, constantcase, kebabcase, snakecase","PATH_DELIMITER":"\nPATH_DELIMITER\n Platform-specific path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER\n \n\n // POSIX environment:\n > var path = '/usr/bin:/bin:/usr/sbin';\n > var parts = path.split( PATH_DELIMITER )\n [ '/usr/bin', '/bin', '/usr/sbin' ]\n\n // Windows environment:\n > path = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\n > parts = path.split( PATH_DELIMITER )\n [ 'C:\\\\Windows\\system32', 'C:\\\\Windows' ]\n\n See Also\n --------\n PATH_DELIMITER_POSIX, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_POSIX\n ':'\n > var PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\n > var paths = PATH.split( PATH_DELIMITER_POSIX )\n [ '/usr/bin', '/bin', '/usr/sbin', '/sbin', '/usr/local/bin' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_WIN32\n ';'\n > var PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\n > var paths = PATH.split( PATH_DELIMITER_WIN32 )\n [ 'C:\\\\Windows\\\\system32', 'C:\\\\Windows', 'C:\\\\Program Files\\\\node\\\\' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_POSIX\n","PATH_SEP":"\nPATH_SEP\n Platform-specific path segment separator.\n\n Examples\n --------\n > PATH_SEP\n \n\n // Windows environment:\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n // POSIX environment:\n > parts = 'foo/bar/baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP_POSIX, PATH_SEP_WIN32\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n POSIX path segment separator.\n\n Examples\n --------\n > PATH_SEP_POSIX\n '/'\n > var parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_WIN32\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n Windows path segment separator.\n\n Examples\n --------\n > PATH_SEP_WIN32\n '\\\\'\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_POSIX\n","pcorrtest":"\npcorrtest( x, y[, options] )\n Computes a Pearson product-moment correlation test between paired samples.\n\n By default, the function performs a t-test for the null hypothesis that the\n data in arrays or typed arrays `x` and `y` is not correlated. A test against\n a different population correlation can be carried out by supplying the `rho`\n option. In this case, a test using the Fisher's z transform is conducted.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Nnumber in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.rho: number (optional)\n Number denoting the correlation under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the Pearson product-moment correlation\n coefficient. The confidence interval is calculated using Fisher's\n z-transform.\n\n out.nullValue: number\n Assumed correlation under H0 (equal to the supplied `rho` option).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var rho = 0.5;\n > var x = new Array( 300 );\n > var y = new Array( 300 );\n > for ( var i = 0; i < 300; i++ ) {\n ... x[ i ] = base.random.normal( 0.0, 1.0 );\n ... y[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\n ... base.sqrt( 1.0 - (rho*rho) ) );\n ... }\n > var out = pcorrtest( x, y )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 10.115805615994121,\n ci: [ 0.4161679018930295, 0.5853122968949995 ],\n alternative: 'two-sided',\n method: 't-test for Pearson correlation coefficient',\n nullValue: 0,\n pcorr: 0.505582072355616,\n }\n\n // Print output:\n > var table = out.print()\n t-test for Pearson correlation coefficient\n\n Alternative hypothesis: True correlation coefficient is not equal to 0\n\n pValue: 0\n statistic: 9.2106\n 95% confidence interval: [0.3776,0.5544]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n","percentEncode":"\npercentEncode( str )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: string\n Percent-encoded string.\n\n Examples\n --------\n > var out = percentEncode( '☃' )\n '%E2%98%83'\n\n","PHI":"\nPHI\n Golden ratio.\n\n Examples\n --------\n > PHI\n 1.618033988749895\n\n","PI":"\nPI\n The mathematical constant `π`.\n\n Examples\n --------\n > PI\n 3.141592653589793\n\n See Also\n --------\n TWO_PI\n","PI_SQUARED":"\nPI_SQUARED\n Square of the mathematical constant `π`.\n\n Examples\n --------\n > PI_SQUARED\n 9.869604401089358\n\n See Also\n --------\n PI\n","pick":"\npick( obj, keys )\n Returns a partial object copy containing only specified keys.\n\n If a key does not exist as an own property in a source object, the key is\n ignored.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to copy.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pick( obj1, 'b' )\n { 'b': 2 }\n\n See Also\n --------\n pickBy\n","pickArguments":"\npickArguments( fcn, indices[, thisArg] )\n Returns a function that applies specified arguments to a provided function.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > var bar = pickArguments( foo, [ 0, 2 ] );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n reorderArguments, reverseArguments\n","pickBy":"\npickBy( obj, predicate )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) {\n ... return ( value > 1 );\n ... };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pickBy( obj1, predicate )\n { 'b': 2 }\n\n See Also\n --------\n pick\n","PINF":"\nPINF\n Double-precision floating-point positive infinity.\n\n Examples\n --------\n > PINF\n Infinity\n\n See Also\n --------\n NINF\n","pkg2alias":"\npkg2alias( pkg )\n Returns the alias associated with a specified package name.\n\n The function supports both internal and standalone package names.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Alias.\n\n Examples\n --------\n > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n \n > v = pkg2alias( '@stdlib/math-base-special-sin' )\n \n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n","pkg2related":"\npkg2related( pkg )\n Returns package names related to a specified package name.\n\n The function supports both internal and standalone package names.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: Array|null\n Related package names.\n\n Examples\n --------\n > var v = pkg2related( '@stdlib/math/base/special/sin' )\n [...]\n > v = pkg2related( '@stdlib/math-base-special-sin' )\n [...]\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n","pkg2standalone":"\npkg2standalone( pkg )\n Returns the standalone package name associated with a provided internal\n package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Standalone package name.\n\n Examples\n --------\n > var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n '@stdlib/math-base-special-sin'\n\n See Also\n --------\n alias2pkg, alias2standalone, aliases, pkg2alias, pkg2related\n","PLATFORM":"\nPLATFORM\n Platform on which the current process is running.\n\n Possible values:\n\n - win32\n - darwin\n - linux\n - freebsd\n - sunos\n\n Examples\n --------\n > PLATFORM\n \n\n See Also\n --------\n ARCH\n","plot":"\nplot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = plot( x, y )\n \n\n See Also\n --------\n Plot\n","Plot":"\nPlot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = Plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = Plot( x, y )\n \n\n See Also\n --------\n plot\n","pluck":"\npluck( arr, prop[, options] )\n Extracts a property value from each element of an object array.\n\n The function skips `null` and `undefined` array elements.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n prop: string\n Property to access.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. To mutate the\n input data structure (e.g., when input values can be discarded or when\n optimizing memory usage), set the `copy` option to `false`. Default:\n true.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > var out = pluck( arr, 'a' )\n [ 1, 0.5 ]\n\n > arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > out = pluck( arr, 'a', { 'copy': false } )\n [ 1, 0.5 ]\n > var bool = ( arr[ 0 ] === out[ 0 ] )\n true\n\n See Also\n --------\n deepPluck, pick\n","pop":"\npop( collection )\n Removes and returns the last element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = pop( arr )\n [ [ 1.0, 2.0, 3.0, 4.0 ], 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = pop( arr )\n [ [ 1.0 ], 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = pop( arr )\n [ { 'length': 1, '0': 1.0 }, 2.0 ]\n\n See Also\n --------\n push, shift, unshift\n","porterStemmer":"\nporterStemmer( word )\n Extracts the stem of a given word.\n\n Parameters\n ----------\n word: string\n Input word.\n\n Returns\n -------\n out: string\n Word stem.\n\n Examples\n --------\n > var out = porterStemmer( 'walking' )\n 'walk'\n > out = porterStemmer( 'walked' )\n 'walk'\n > out = porterStemmer( 'walks' )\n 'walk'\n > out = porterStemmer( '' )\n ''\n\n","prepend":"\nprepend( collection1, collection2 )\n Adds the elements of one collection to the beginning of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = prepend( arr, [ 6.0, 7.0 ] )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = prepend( arr, [ 3.0, 4.0 ] )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = prepend( arr, [ 2.0, 3.0 ] )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n append, unshift\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str[, fromIndex] )\n Returns the previous extended grapheme cluster break in a string before a\n specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n fromIndex: integer (optional)\n Position. Default: str.length-1.\n\n Returns\n -------\n out: integer\n Previous extended grapheme cluster break position.\n\n Examples\n --------\n > var out = prevGraphemeClusterBreak( 'last man standing', 4 )\n 3\n > out = prevGraphemeClusterBreak( 'presidential election', 8 )\n 7\n > out = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\n 0\n > out = prevGraphemeClusterBreak( '🌷', 1 )\n -1\n\n See Also\n --------\n numGraphemeClusters, nextGraphemeClusterBreak","PRIMES_100K":"\nPRIMES_100K()\n Returns an array containing the first 100,000 prime numbers.\n\n Returns\n -------\n out: Array\n List of primes.\n\n Examples\n --------\n > var list = PRIMES_100K()\n [ 2, 3, 5, ... ]\n\n See Also\n --------\n iterPrimesSeq\n","properties":"\nproperties( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable and non-enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = properties( obj )\n [ 'beep' ]\n\n See Also\n --------\n defineProperties, inheritedProperties, propertiesIn, propertyNames, propertySymbols\n","propertiesIn":"\npropertiesIn( value )\n Returns an array of an object's own and inherited property names and\n symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited property names and symbols.\n\n Examples\n --------\n > var props = propertiesIn( [] )\n\n See Also\n --------\n defineProperties, inheritedProperties, properties, propertyNamesIn, propertySymbolsIn\n","propertyDescriptor":"\npropertyDescriptor( value, property )\n Returns a property descriptor for an object's own property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptor( obj, 'a' )\n {...}\n\n See Also\n --------\n hasOwnProp, defineProperty, propertyDescriptorIn, propertyDescriptors\n","propertyDescriptorIn":"\npropertyDescriptorIn( value, property )\n Returns a property descriptor for an object's own or inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptorIn( obj, 'a' )\n {...}\n\n See Also\n --------\n hasProp, defineProperty, propertyDescriptor, propertyDescriptorsIn\n","propertyDescriptors":"\npropertyDescriptors( value )\n Returns an object's own property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n Property descriptors.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptors( obj )\n { 'a': {...} }\n\n See Also\n --------\n defineProperty, defineProperties, propertyDescriptor, propertyDescriptorsIn, propertyNames, propertySymbols\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value )\n Returns an object's own and inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n An object's own and inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = propertyDescriptorsIn( obj )\n { 'beep': {...}, 'foo': {...}, ... }\n\n See Also\n --------\n defineProperties, propertyDescriptorIn, propertyDescriptors, propertyNamesIn, propertySymbolsIn\n","propertyNames":"\npropertyNames( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable and non-enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNames( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNames, propertyNamesIn, propertySymbols\n","propertyNamesIn":"\npropertyNamesIn( value )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable and non-enumerable\n property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNamesIn( obj )\n e.g., [ 'beep', 'foo', ... ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNamesIn, propertyNames, propertySymbolsIn\n","propertySymbols":"\npropertySymbols( value )\n Returns an array of an object's own symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own symbol properties.\n\n Examples\n --------\n > var s = propertySymbols( {} )\n\n See Also\n --------\n propertyNames, propertySymbolsIn\n","propertySymbolsIn":"\npropertySymbolsIn( value )\n Returns an array of an object's own and inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited symbol properties.\n\n Examples\n --------\n > var s = propertySymbolsIn( [] )\n\n See Also\n --------\n propertyNamesIn, propertySymbols\n","Proxy":"\nProxy( target, handlers )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n\n The following \"traps\" are supported:\n\n - getPrototypeOf( target )\n Trap for `Object.getPrototypeOf()`. Can be used to intercept the\n `instanceof` operator. The method must return an object or `null`.\n\n - setPrototypeOf( target, prototype )\n Trap for `Object.setPrototypeOf()`. The method must return a boolean\n indicating if prototype successfully set.\n\n - isExtensible( target )\n Trap for `Object.isExtensible()`. The method must return a boolean.\n\n - preventExtensions( target )\n Trap for `Object.preventExtensions()`. The method must return a boolean.\n\n - getOwnPropertyDescriptor( target, property )\n Trap for `Object.getOwnPropertyDescriptor()`. The method must return an\n object or `undefined`.\n\n - defineProperty( target, property, descriptor )\n Trap for `Object.defineProperty()`. The method must return a boolean\n indicating whether the operation succeeded.\n\n - has( target, property )\n Trap for the `in` operator. The method must return a boolean.\n\n - get( target, property, receiver )\n Trap for retrieving property values. The method can return any value.\n\n - set( target, property, value, receiver )\n Trap for setting property values. The method should return a boolean\n indicating whether assignment succeeded.\n\n - deleteProperty( target, property )\n Trap for the `delete` operator. The method must return a boolean\n indicating whether operation succeeded.\n\n - ownKeys( target )\n Trap for `Object.keys`, `Object.getOwnPropertyNames()`, and\n `Object.getOwnPropertySymbols()`. The method must return an enumerable\n object.\n\n - apply( target, thisArg, argumentsList )\n Trap for a function call. The method can return any value.\n\n - construct( target, argumentsList, newTarget )\n Trap for the `new` operator. The method must return an object.\n\n All traps are optional. If a trap is not defined, the default behavior is to\n forward the operation to the target.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Proxy object.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = new Proxy( {}, h );\n > p.a = 3.14;\n > p.a\n 6.28\n\n\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();\n\n","Proxy.revocable":"\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();","push":"\npush( collection, ...items )\n Adds one or more elements to the end of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = push( arr, 6.0, 7.0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = push( arr, 3.0, 4.0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = push( arr, 1.0, 2.0 )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n pop, shift, unshift\n","quarterOfYear":"\nquarterOfYear( [month] )\n Returns the quarter of the year.\n\n By default, the function returns the quarter of the year for the current\n month in the current year (according to local time). To determine the\n quarter for a particular month, provide either a month or a `Date`\n object.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n Parameters\n ----------\n month: integer|string|Date (optional)\n Month (or `Date`).\n\n Returns\n -------\n out: integer\n Quarter of the year.\n\n Examples\n --------\n > var q = quarterOfYear( new Date() )\n \n > q = quarterOfYear( 4 )\n 2\n > q = quarterOfYear( 'June' )\n 2\n\n // Other ways to supply month:\n > q = quarterOfYear( 'April' )\n 2\n > q = quarterOfYear( 'apr' )\n 2\n\n See Also\n --------\n dayOfYear\n","random.array.arcsine":"\nrandom.array.arcsine( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from an arcsine\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.arcsine.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.arcsine.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.arcsine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.arcsine.PRNG;\n\n\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.arcsine.seed;\n\n\nrandom.array.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.arcsine.seedLength;\n\n\nrandom.array.arcsine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.arcsine.state\n \n\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.arcsine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.arcsine.stateLength;\n\n\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.arcsine.byteLength;\n\n See Also\n --------\n base.random.arcsine, random.strided.arcsine\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.arcsine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.arcsine.PRNG;","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.arcsine.seed;","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.arcsine.seedLength;","random.array.arcsine.state":"\nrandom.array.arcsine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.arcsine.state\n \n\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.arcsine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n ","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.arcsine.stateLength;","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.arcsine.byteLength;\n\n See Also\n --------\n base.random.arcsine, random.strided.arcsine","random.array.bernoulli":"\nrandom.array.bernoulli( len, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n\nrandom.array.bernoulli.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.bernoulli.assign( 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.bernoulli.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.bernoulli.factory();\n > var out = fcn( 3, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.bernoulli.factory( 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.bernoulli.PRNG;\n\n\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.bernoulli.seed;\n\n\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.bernoulli.seedLength;\n\n\nrandom.array.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.bernoulli.state\n \n\n > out = random.array.bernoulli( 3, 0.5 )\n \n > out = random.array.bernoulli( 3, 0.5 )\n \n\n // Set the state:\n > random.array.bernoulli.state = state;\n\n // Regenerate a previous array:\n > out = random.array.bernoulli( 3, 0.5 )\n \n\n\nrandom.array.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.bernoulli.stateLength;\n\n\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.strided.bernoulli\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.bernoulli.assign( 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.bernoulli.factory();\n > var out = fcn( 3, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.bernoulli.factory( 0.5 );\n > out = fcn( 3 )\n ","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.bernoulli.PRNG;","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.bernoulli.seed;","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.bernoulli.seedLength;","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.bernoulli.state\n \n\n > out = random.array.bernoulli( 3, 0.5 )\n \n > out = random.array.bernoulli( 3, 0.5 )\n \n\n // Set the state:\n > random.array.bernoulli.state = state;\n\n // Regenerate a previous array:\n > out = random.array.bernoulli( 3, 0.5 )\n ","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.bernoulli.stateLength;","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.strided.bernoulli","random.array.beta":"\nrandom.array.beta( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a beta\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n\nrandom.array.beta.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.beta.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.beta.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.beta.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.beta.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.beta.PRNG;\n\n\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.beta.seed;\n\n\nrandom.array.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.beta.seedLength;\n\n\nrandom.array.beta.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.beta.state\n \n\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.beta.state = state;\n\n // Regenerate a previous array:\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n\nrandom.array.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.beta.stateLength;\n\n\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.beta.byteLength;\n\n See Also\n --------\n base.random.beta, random.strided.beta\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.beta.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.beta.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.beta.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.beta.PRNG;","random.array.beta.seed":"\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.beta.seed;","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.beta.seedLength;","random.array.beta.state":"\nrandom.array.beta.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.beta.state\n \n\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.beta.state = state;\n\n // Regenerate a previous array:\n > out = random.array.beta( 3, 2.0, 5.0 )\n ","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.beta.stateLength;","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.beta.byteLength;\n\n See Also\n --------\n base.random.beta, random.strided.beta","random.array.betaprime":"\nrandom.array.betaprime( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n\nrandom.array.betaprime.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.betaprime.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.betaprime.PRNG;\n\n\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.betaprime.seed;\n\n\nrandom.array.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.betaprime.seedLength;\n\n\nrandom.array.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.betaprime.state\n \n\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n\nrandom.array.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.betaprime.stateLength;\n\n\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.betaprime.byteLength;\n\n See Also\n --------\n base.random.betaprime, random.strided.betaprime\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.betaprime.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.betaprime.PRNG;","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.betaprime.seed;","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.betaprime.seedLength;","random.array.betaprime.state":"\nrandom.array.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.betaprime.state\n \n\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n ","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.betaprime.stateLength;","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.betaprime.byteLength;\n\n See Also\n --------\n base.random.betaprime, random.strided.betaprime","random.array.binomial":"\nrandom.array.binomial( len, n, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a binomial\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n\nrandom.array.binomial.assign( n, p, out )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n Parameters\n ----------\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.binomial.assign( 17, 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.binomial.factory( [n, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n n: number (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.binomial.factory();\n > var out = fcn( 3, 17, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.binomial.factory( 17, 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.binomial.PRNG;\n\n\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.binomial.seed;\n\n\nrandom.array.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.binomial.seedLength;\n\n\nrandom.array.binomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.binomial.state\n \n\n > out = random.array.binomial( 3, 17, 0.5 )\n \n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Set the state:\n > random.array.binomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n\nrandom.array.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.binomial.stateLength;\n\n\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.binomial.byteLength;\n\n See Also\n --------\n random.array.negativeBinomial, base.random.binomial\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n, p, out )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n Parameters\n ----------\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.binomial.assign( 17, 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n n: number (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.binomial.factory();\n > var out = fcn( 3, 17, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.binomial.factory( 17, 0.5 );\n > out = fcn( 3 )\n ","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.binomial.PRNG;","random.array.binomial.seed":"\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.binomial.seed;","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.binomial.seedLength;","random.array.binomial.state":"\nrandom.array.binomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.binomial.state\n \n\n > out = random.array.binomial( 3, 17, 0.5 )\n \n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Set the state:\n > random.array.binomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.binomial( 3, 17, 0.5 )\n ","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.binomial.stateLength;","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.binomial.byteLength;\n\n See Also\n --------\n random.array.negativeBinomial, base.random.binomial","random.array.cauchy":"\nrandom.array.cauchy( len, x0, gamma[, options] )\n Returns an array containing pseudorandom numbers drawn from a Cauchy\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cauchy.assign( x0, gamma, out )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n gamma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cauchy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cauchy.PRNG;\n\n\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cauchy.seed;\n\n\nrandom.array.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cauchy.seedLength;\n\n\nrandom.array.cauchy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cauchy.state\n \n\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cauchy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cauchy.stateLength;\n\n\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cauchy.byteLength;\n\n See Also\n --------\n base.random.cauchy\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0, gamma, out )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n gamma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cauchy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cauchy.PRNG;","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cauchy.seed;","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cauchy.seedLength;","random.array.cauchy.state":"\nrandom.array.cauchy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cauchy.state\n \n\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cauchy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n ","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cauchy.stateLength;","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cauchy.byteLength;\n\n See Also\n --------\n base.random.cauchy","random.array.chi":"\nrandom.array.chi( len, k[, options] )\n Returns an array containing pseudorandom numbers drawn from a chi\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n\nrandom.array.chi.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chi.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.chi.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chi.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chi.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chi.PRNG;\n\n\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chi.seed;\n\n\nrandom.array.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chi.seedLength;\n\n\nrandom.array.chi.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chi.state\n \n\n > out = random.array.chi( 3, 2.0 )\n \n > out = random.array.chi( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chi.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chi( 3, 2.0 )\n \n\n\nrandom.array.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chi.stateLength;\n\n\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.strided.chi\n","random.array.chi.assign":"\nrandom.array.chi.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chi.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.chi.factory":"\nrandom.array.chi.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chi.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chi.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chi.PRNG;","random.array.chi.seed":"\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chi.seed;","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chi.seedLength;","random.array.chi.state":"\nrandom.array.chi.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chi.state\n \n\n > out = random.array.chi( 3, 2.0 )\n \n > out = random.array.chi( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chi.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chi( 3, 2.0 )\n ","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chi.stateLength;","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.strided.chi","random.array.chisquare":"\nrandom.array.chisquare( len, k[, options] )\n Returns an array containing pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n\nrandom.array.chisquare.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chisquare.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.chisquare.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chisquare.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chisquare.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chisquare.PRNG;\n\n\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chisquare.seed;\n\n\nrandom.array.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chisquare.seedLength;\n\n\nrandom.array.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chisquare.state\n \n\n > out = random.array.chisquare( 3, 2.0 )\n \n > out = random.array.chisquare( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chisquare.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chisquare( 3, 2.0 )\n \n\n\nrandom.array.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chisquare.stateLength;\n\n\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.strided.chisquare\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chisquare.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chisquare.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chisquare.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chisquare.PRNG;","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chisquare.seed;","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chisquare.seedLength;","random.array.chisquare.state":"\nrandom.array.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chisquare.state\n \n\n > out = random.array.chisquare( 3, 2.0 )\n \n > out = random.array.chisquare( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chisquare.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chisquare( 3, 2.0 )\n ","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chisquare.stateLength;","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.strided.chisquare","random.array.cosine":"\nrandom.array.cosine( len, mu, s[, options] )\n Returns an array containing pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cosine.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cosine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.cosine.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cosine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cosine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cosine.PRNG;\n\n\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cosine.seed;\n\n\nrandom.array.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cosine.seedLength;\n\n\nrandom.array.cosine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cosine.state\n \n\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cosine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cosine.stateLength;\n\n\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cosine.byteLength;\n\n See Also\n --------\n base.random.cosine, random.strided.cosine\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cosine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cosine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cosine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cosine.PRNG;","random.array.cosine.seed":"\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cosine.seed;","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cosine.seedLength;","random.array.cosine.state":"\nrandom.array.cosine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cosine.state\n \n\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cosine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cosine( 3, 2.0, 5.0 )\n ","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cosine.stateLength;","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cosine.byteLength;\n\n See Also\n --------\n base.random.cosine, random.strided.cosine","random.array.discreteUniform":"\nrandom.array.discreteUniform( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n\nrandom.array.discreteUniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.discreteUniform.assign( -10, 10, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.discreteUniform.factory();\n > var out = fcn( 3, -10, 10 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.discreteUniform.factory( -10, 10 );\n > out = fcn( 3 )\n \n\n\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.discreteUniform.PRNG;\n\n\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.discreteUniform.seed;\n\n\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.discreteUniform.seedLength;\n\n\nrandom.array.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Get a copy of the current state:\n > var state = random.array.discreteUniform.state\n \n\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Set the state:\n > random.array.discreteUniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.discreteUniform.stateLength;\n\n\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.discreteUniform.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.discreteUniform, random.strided.discreteUniform\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.discreteUniform.assign( -10, 10, x )\n \n > var bool = ( out === x )\n true","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.discreteUniform.factory();\n > var out = fcn( 3, -10, 10 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.discreteUniform.factory( -10, 10 );\n > out = fcn( 3 )\n ","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.discreteUniform.PRNG;","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.discreteUniform.seed;","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.discreteUniform.seedLength;","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Get a copy of the current state:\n > var state = random.array.discreteUniform.state\n \n\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Set the state:\n > random.array.discreteUniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.discreteUniform( 3, -10, 10 )\n ","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.discreteUniform.stateLength;","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.discreteUniform.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.discreteUniform, random.strided.discreteUniform","random.array.erlang":"\nrandom.array.erlang( len, k, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from an Erlang\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n\nrandom.array.erlang.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.erlang.assign( 2, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.erlang.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.erlang.factory();\n > var out = fcn( 3, 2, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.erlang.factory( 2, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.erlang.PRNG;\n\n\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.erlang.seed;\n\n\nrandom.array.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.erlang.seedLength;\n\n\nrandom.array.erlang.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.erlang.state\n \n\n > out = random.array.erlang( 3, 2, 5.0 )\n \n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Set the state:\n > random.array.erlang.state = state;\n\n // Regenerate a previous array:\n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n\nrandom.array.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.erlang.stateLength;\n\n\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.erlang.byteLength;\n\n See Also\n --------\n base.random.erlang\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.erlang.assign( 2, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.erlang.factory();\n > var out = fcn( 3, 2, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.erlang.factory( 2, 5.0 );\n > out = fcn( 3 )\n ","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.erlang.PRNG;","random.array.erlang.seed":"\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.erlang.seed;","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.erlang.seedLength;","random.array.erlang.state":"\nrandom.array.erlang.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.erlang.state\n \n\n > out = random.array.erlang( 3, 2, 5.0 )\n \n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Set the state:\n > random.array.erlang.state = state;\n\n // Regenerate a previous array:\n > out = random.array.erlang( 3, 2, 5.0 )\n ","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.erlang.stateLength;","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.erlang.byteLength;\n\n See Also\n --------\n base.random.erlang","random.array.exponential":"\nrandom.array.exponential( len, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n lambda: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n\nrandom.array.exponential.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.exponential.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.exponential.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.exponential.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.exponential.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.exponential.PRNG;\n\n\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.exponential.seed;\n\n\nrandom.array.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.exponential.seedLength;\n\n\nrandom.array.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.exponential.state\n \n\n > out = random.array.exponential( 3, 2.0 )\n \n > out = random.array.exponential( 3, 2.0 )\n \n\n // Set the state:\n > random.array.exponential.state = state;\n\n // Regenerate a previous array:\n > out = random.array.exponential( 3, 2.0 )\n \n\n\nrandom.array.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.exponential.stateLength;\n\n\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.strided.exponential\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.exponential.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.exponential.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.exponential.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.exponential.PRNG;","random.array.exponential.seed":"\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.exponential.seed;","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.exponential.seedLength;","random.array.exponential.state":"\nrandom.array.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.exponential.state\n \n\n > out = random.array.exponential( 3, 2.0 )\n \n > out = random.array.exponential( 3, 2.0 )\n \n\n // Set the state:\n > random.array.exponential.state = state;\n\n // Regenerate a previous array:\n > out = random.array.exponential( 3, 2.0 )\n ","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.exponential.stateLength;","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.strided.exponential","random.array.f":"\nrandom.array.f( len, d1, d2[, options] )\n Returns an array containing pseudorandom numbers drawn from an F\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n\nrandom.array.f.assign( d1, d2, out )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.f.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.f.factory( [d1, d2, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.f.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.f.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.f.PRNG;\n\n\nrandom.array.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.f.seed;\n\n\nrandom.array.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.f.seedLength;\n\n\nrandom.array.f.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.f.state\n \n\n > out = random.array.f( 3, 2.0, 5.0 )\n \n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.f.state = state;\n\n // Regenerate a previous array:\n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n\nrandom.array.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.f.stateLength;\n\n\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.f.byteLength;\n\n See Also\n --------\n base.random.f\n","random.array.f.assign":"\nrandom.array.f.assign( d1, d2, out )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.f.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.f.factory":"\nrandom.array.f.factory( [d1, d2, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.f.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.f.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.f.PRNG":"\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.f.PRNG;","random.array.f.seed":"\nrandom.array.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.f.seed;","random.array.f.seedLength":"\nrandom.array.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.f.seedLength;","random.array.f.state":"\nrandom.array.f.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.f.state\n \n\n > out = random.array.f( 3, 2.0, 5.0 )\n \n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.f.state = state;\n\n // Regenerate a previous array:\n > out = random.array.f( 3, 2.0, 5.0 )\n ","random.array.f.stateLength":"\nrandom.array.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.f.stateLength;","random.array.f.byteLength":"\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.f.byteLength;\n\n See Also\n --------\n base.random.f","random.array.frechet":"\nrandom.array.frechet( len, alpha, s, m[, options] )\n Returns an array containing pseudorandom numbers drawn from a Fréchet\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.frechet.assign( alpha, s, m, out )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.frechet.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.frechet.PRNG;\n\n\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.frechet.seed;\n\n\nrandom.array.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.frechet.seedLength;\n\n\nrandom.array.frechet.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.frechet.state\n \n\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.frechet.state = state;\n\n // Regenerate a previous array:\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.frechet.stateLength;\n\n\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.frechet.byteLength;\n\n See Also\n --------\n base.random.frechet\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha, s, m, out )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.frechet.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n ","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.frechet.PRNG;","random.array.frechet.seed":"\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.frechet.seed;","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.frechet.seedLength;","random.array.frechet.state":"\nrandom.array.frechet.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.frechet.state\n \n\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.frechet.state = state;\n\n // Regenerate a previous array:\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n ","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.frechet.stateLength;","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.frechet.byteLength;\n\n See Also\n --------\n base.random.frechet","random.array.gamma":"\nrandom.array.gamma( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a gamma\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gamma.PRNG;\n\n\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gamma.seed;\n\n\nrandom.array.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gamma.seedLength;\n\n\nrandom.array.gamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gamma.state\n \n\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gamma.stateLength;\n\n\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gamma.byteLength;\n\n See Also\n --------\n base.random.gamma, random.strided.gamma\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gamma.PRNG;","random.array.gamma.seed":"\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gamma.seed;","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gamma.seedLength;","random.array.gamma.state":"\nrandom.array.gamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gamma.state\n \n\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gamma( 3, 2.0, 5.0 )\n ","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gamma.stateLength;","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gamma.byteLength;\n\n See Also\n --------\n base.random.gamma, random.strided.gamma","random.array.geometric":"\nrandom.array.geometric( len, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n\nrandom.array.geometric.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.geometric.assign( 0.01, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.geometric.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.geometric.factory();\n > var out = fcn( 3, 0.01 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.geometric.factory( 0.01 );\n > out = fcn( 3 )\n \n\n\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.geometric.PRNG;\n\n\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.geometric.seed;\n\n\nrandom.array.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.geometric.seedLength;\n\n\nrandom.array.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n // Get a copy of the current state:\n > var state = random.array.geometric.state\n \n\n > out = random.array.geometric( 3, 0.01 )\n \n > out = random.array.geometric( 3, 0.01 )\n \n\n // Set the state:\n > random.array.geometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.geometric( 3, 0.01 )\n \n\n\nrandom.array.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.geometric.stateLength;\n\n\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.strided.geometric\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.geometric.assign( 0.01, x )\n \n > var bool = ( out === x )\n true","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.geometric.factory();\n > var out = fcn( 3, 0.01 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.geometric.factory( 0.01 );\n > out = fcn( 3 )\n ","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.geometric.PRNG;","random.array.geometric.seed":"\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.geometric.seed;","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.geometric.seedLength;","random.array.geometric.state":"\nrandom.array.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n // Get a copy of the current state:\n > var state = random.array.geometric.state\n \n\n > out = random.array.geometric( 3, 0.01 )\n \n > out = random.array.geometric( 3, 0.01 )\n \n\n // Set the state:\n > random.array.geometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.geometric( 3, 0.01 )\n ","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.geometric.stateLength;","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.strided.geometric","random.array.gumbel":"\nrandom.array.gumbel( len, mu, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a Gumbel\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gumbel.assign( mu, beta, out )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gumbel.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gumbel.PRNG;\n\n\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gumbel.seed;\n\n\nrandom.array.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gumbel.seedLength;\n\n\nrandom.array.gumbel.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gumbel.state\n \n\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gumbel.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gumbel.stateLength;\n\n\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gumbel.byteLength;\n\n See Also\n --------\n base.random.gumbel\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu, beta, out )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gumbel.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gumbel.PRNG;","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gumbel.seed;","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gumbel.seedLength;","random.array.gumbel.state":"\nrandom.array.gumbel.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gumbel.state\n \n\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gumbel.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n ","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gumbel.stateLength;","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gumbel.byteLength;\n\n See Also\n --------\n base.random.gumbel","random.array.hypergeometric":"\nrandom.array.hypergeometric( len, N, K, n[, options] )\n Returns an array containing pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n\nrandom.array.hypergeometric.assign( N, K, n, out )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n N: number (optional)\n Population size.\n\n K: number (optional)\n Subpopulation size.\n\n n: number (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.hypergeometric.factory();\n > var out = fcn( 3, 20, 10, 7 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n > out = fcn( 3 )\n \n\n\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.hypergeometric.PRNG;\n\n\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.hypergeometric.seed;\n\n\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.hypergeometric.seedLength;\n\n\nrandom.array.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Get a copy of the current state:\n > var state = random.array.hypergeometric.state\n \n\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Set the state:\n > random.array.hypergeometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.hypergeometric.stateLength;\n\n\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.hypergeometric.byteLength;\n\n See Also\n --------\n base.random.hypergeometric\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N, K, n, out )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n \n > var bool = ( out === x )\n true","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n N: number (optional)\n Population size.\n\n K: number (optional)\n Subpopulation size.\n\n n: number (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.hypergeometric.factory();\n > var out = fcn( 3, 20, 10, 7 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n > out = fcn( 3 )\n ","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.hypergeometric.PRNG;","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.hypergeometric.seed;","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.hypergeometric.seedLength;","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Get a copy of the current state:\n > var state = random.array.hypergeometric.state\n \n\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Set the state:\n > random.array.hypergeometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n ","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.hypergeometric.stateLength;","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.hypergeometric.byteLength;\n\n See Also\n --------\n base.random.hypergeometric","random.array.invgamma":"\nrandom.array.invgamma( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.invgamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.invgamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.invgamma.PRNG;\n\n\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.invgamma.seed;\n\n\nrandom.array.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.invgamma.seedLength;\n\n\nrandom.array.invgamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.invgamma.state\n \n\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.invgamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.invgamma.stateLength;\n\n\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.invgamma.byteLength;\n\n See Also\n --------\n base.random.invgamma, random.strided.invgamma\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.invgamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.invgamma.PRNG;","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.invgamma.seed;","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.invgamma.seedLength;","random.array.invgamma.state":"\nrandom.array.invgamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.invgamma.state\n \n\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.invgamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n ","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.invgamma.stateLength;","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.invgamma.byteLength;\n\n See Also\n --------\n base.random.invgamma, random.strided.invgamma","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n double bounded distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.kumaraswamy.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.kumaraswamy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.kumaraswamy.PRNG;\n\n\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.kumaraswamy.seed;\n\n\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.seedLength;\n\n\nrandom.array.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.kumaraswamy.state\n \n\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.kumaraswamy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.stateLength;\n\n\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.kumaraswamy.byteLength;\n\n See Also\n --------\n base.random.kumaraswamy\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.kumaraswamy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.kumaraswamy.PRNG;","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.kumaraswamy.seed;","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.seedLength;","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.kumaraswamy.state\n \n\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.kumaraswamy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n ","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.stateLength;","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.kumaraswamy.byteLength;\n\n See Also\n --------\n base.random.kumaraswamy","random.array.laplace":"\nrandom.array.laplace( len, mu, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n\nrandom.array.laplace.assign( mu, b, out )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.laplace.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.laplace.factory( [mu, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.laplace.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.laplace.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.laplace.PRNG;\n\n\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.laplace.seed;\n\n\nrandom.array.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.laplace.seedLength;\n\n\nrandom.array.laplace.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.laplace.state\n \n\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.laplace.state = state;\n\n // Regenerate a previous array:\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n\nrandom.array.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.laplace.stateLength;\n\n\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.laplace.byteLength;\n\n See Also\n --------\n base.random.laplace\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu, b, out )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.laplace.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.laplace.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.laplace.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.laplace.PRNG;","random.array.laplace.seed":"\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.laplace.seed;","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.laplace.seedLength;","random.array.laplace.state":"\nrandom.array.laplace.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.laplace.state\n \n\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.laplace.state = state;\n\n // Regenerate a previous array:\n > out = random.array.laplace( 3, 2.0, 5.0 )\n ","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.laplace.stateLength;","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.laplace.byteLength;\n\n See Also\n --------\n base.random.laplace","random.array.levy":"\nrandom.array.levy( len, mu, c[, options] )\n Returns an array containing pseudorandom numbers drawn from a Lévy\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.levy.assign( mu, c, out )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.levy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.levy.factory( [mu, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.levy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.levy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.levy.PRNG;\n\n\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.levy.seed;\n\n\nrandom.array.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.levy.seedLength;\n\n\nrandom.array.levy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.levy.state\n \n\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.levy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.levy.stateLength;\n\n\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.levy.byteLength;\n\n See Also\n --------\n base.random.levy\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu, c, out )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.levy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.levy.factory":"\nrandom.array.levy.factory( [mu, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.levy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.levy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.levy.PRNG;","random.array.levy.seed":"\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.levy.seed;","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.levy.seedLength;","random.array.levy.state":"\nrandom.array.levy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.levy.state\n \n\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.levy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.levy( 3, 2.0, 5.0 )\n ","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.levy.stateLength;","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.levy.byteLength;\n\n See Also\n --------\n base.random.levy","random.array.logistic":"\nrandom.array.logistic( len, mu, s[, options] )\n Returns an array containing pseudorandom numbers drawn from a logistic\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n\nrandom.array.logistic.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n Parameters\n ----------\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.logistic.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.logistic.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.logistic.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.logistic.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.logistic.PRNG;\n\n\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.logistic.seed;\n\n\nrandom.array.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.logistic.seedLength;\n\n\nrandom.array.logistic.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.logistic.state\n \n\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.logistic.state = state;\n\n // Regenerate a previous array:\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n\nrandom.array.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.logistic.stateLength;\n\n\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.logistic.byteLength;\n\n See Also\n --------\n base.random.logistic\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n Parameters\n ----------\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.logistic.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.logistic.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.logistic.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.logistic.PRNG;","random.array.logistic.seed":"\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.logistic.seed;","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.logistic.seedLength;","random.array.logistic.state":"\nrandom.array.logistic.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.logistic.state\n \n\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.logistic.state = state;\n\n // Regenerate a previous array:\n > out = random.array.logistic( 3, 2.0, 5.0 )\n ","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.logistic.stateLength;","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.logistic.byteLength;\n\n See Also\n --------\n base.random.logistic","random.array.lognormal":"\nrandom.array.lognormal( len, mu, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.lognormal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.lognormal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.lognormal.PRNG;\n\n\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.lognormal.seed;\n\n\nrandom.array.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.lognormal.seedLength;\n\n\nrandom.array.lognormal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.lognormal.state\n \n\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.lognormal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.lognormal.stateLength;\n\n\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.lognormal.byteLength;\n\n See Also\n --------\n base.random.lognormal, random.strided.lognormal\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.lognormal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.lognormal.PRNG;","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.lognormal.seed;","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.lognormal.seedLength;","random.array.lognormal.state":"\nrandom.array.lognormal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.lognormal.state\n \n\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.lognormal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n ","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.lognormal.stateLength;","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.lognormal.byteLength;\n\n See Also\n --------\n base.random.lognormal, random.strided.lognormal","random.array.minstd":"\nrandom.array.minstd( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n\nrandom.array.minstd.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd.normalized( 3 )\n \n\n\nrandom.array.minstd.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstd.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstd.PRNG;\n\n\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstd.seed;\n\n\nrandom.array.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstd.seedLength;\n\n\nrandom.array.minstd.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstd.state;\n\n > out = random.array.minstd( 3 )\n \n > out = random.array.minstd( 3 )\n \n\n // Set the state:\n > random.array.minstd.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstd( 3 )\n \n\n\nrandom.array.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstd.stateLength;\n\n\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstd.byteLength;\n\n See Also\n --------\n random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd.normalized( 3 )\n ","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstd.factory();\n > var out = fcn( 3 )\n ","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstd.PRNG;","random.array.minstd.seed":"\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstd.seed;","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstd.seedLength;","random.array.minstd.state":"\nrandom.array.minstd.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstd.state;\n\n > out = random.array.minstd( 3 )\n \n > out = random.array.minstd( 3 )\n \n\n // Set the state:\n > random.array.minstd.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstd( 3 )\n ","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstd.stateLength;","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstd.byteLength;\n\n See Also\n --------\n random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n\nrandom.array.minstdShuffle.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle.normalized( 3 )\n \n\n\nrandom.array.minstdShuffle.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstdShuffle.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstdShuffle.PRNG;\n\n\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstdShuffle.seed;\n\n\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.seedLength;\n\n\nrandom.array.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstdShuffle.state;\n\n > out = random.array.minstdShuffle( 3 )\n \n > out = random.array.minstdShuffle( 3 )\n \n\n // Set the state:\n > random.array.minstdShuffle.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstdShuffle( 3 )\n \n\n\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.stateLength;\n\n\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstdShuffle.byteLength;\n\n See Also\n --------\n random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle.normalized( 3 )\n ","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstdShuffle.factory();\n > var out = fcn( 3 )\n ","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstdShuffle.PRNG;","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstdShuffle.seed;","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.seedLength;","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstdShuffle.state;\n\n > out = random.array.minstdShuffle( 3 )\n \n > out = random.array.minstdShuffle( 3 )\n \n\n // Set the state:\n > random.array.minstdShuffle.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstdShuffle( 3 )\n ","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.stateLength;","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstdShuffle.byteLength;\n\n See Also\n --------\n random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle","random.array.mt19937":"\nrandom.array.mt19937( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[0, 4294967295]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n\nrandom.array.mt19937.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937.normalized( 3 )\n \n\n\nrandom.array.mt19937.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.mt19937.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.mt19937.PRNG;\n\n\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.mt19937.seed;\n\n\nrandom.array.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.mt19937.seedLength;\n\n\nrandom.array.mt19937.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.mt19937.state;\n\n > out = random.array.mt19937( 3 )\n \n > out = random.array.mt19937( 3 )\n \n\n // Set the state:\n > random.array.mt19937.state = state;\n\n // Regenerate a previous array:\n > out = random.array.mt19937( 3 )\n \n\n\nrandom.array.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.mt19937.stateLength;\n\n\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.mt19937.byteLength;\n\n See Also\n --------\n random.array.randu, base.random.mt19937, random.strided.mt19937\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937.normalized( 3 )\n ","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.mt19937.factory();\n > var out = fcn( 3 )\n ","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.mt19937.PRNG;","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.mt19937.seed;","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.mt19937.seedLength;","random.array.mt19937.state":"\nrandom.array.mt19937.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.mt19937.state;\n\n > out = random.array.mt19937( 3 )\n \n > out = random.array.mt19937( 3 )\n \n\n // Set the state:\n > random.array.mt19937.state = state;\n\n // Regenerate a previous array:\n > out = random.array.mt19937( 3 )\n ","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.mt19937.stateLength;","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.mt19937.byteLength;\n\n See Also\n --------\n random.array.randu, base.random.mt19937, random.strided.mt19937","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len, r, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a negative\n binomial distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n\nrandom.array.negativeBinomial.assign( r, p, out )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.negativeBinomial.factory();\n > var out = fcn( 3, 10, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.negativeBinomial.PRNG;\n\n\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.negativeBinomial.seed;\n\n\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.seedLength;\n\n\nrandom.array.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.negativeBinomial.state\n \n\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Set the state:\n > random.array.negativeBinomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.stateLength;\n\n\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.negativeBinomial.byteLength;\n\n See Also\n --------\n random.array.binomial, base.random.negativeBinomial\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r, p, out )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.negativeBinomial.factory();\n > var out = fcn( 3, 10, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n > out = fcn( 3 )\n ","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.negativeBinomial.PRNG;","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.negativeBinomial.seed;","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.seedLength;","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.negativeBinomial.state\n \n\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Set the state:\n > random.array.negativeBinomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n ","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.stateLength;","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.negativeBinomial.byteLength;\n\n See Also\n --------\n random.array.binomial, base.random.negativeBinomial","random.array.normal":"\nrandom.array.normal( len, mu, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a normal\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.normal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.normal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.normal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n sigma: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.normal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.normal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.normal.PRNG;\n\n\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.normal.seed;\n\n\nrandom.array.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.normal.seedLength;\n\n\nrandom.array.normal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.normal.state\n \n\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.normal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.normal.stateLength;\n\n\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.normal.byteLength;\n\n See Also\n --------\n base.random.normal, random.strided.normal\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.normal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.normal.factory":"\nrandom.array.normal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n sigma: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.normal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.normal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.normal.PRNG;","random.array.normal.seed":"\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.normal.seed;","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.normal.seedLength;","random.array.normal.state":"\nrandom.array.normal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.normal.state\n \n\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.normal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.normal( 3, 2.0, 5.0 )\n ","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.normal.stateLength;","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.normal.byteLength;\n\n See Also\n --------\n base.random.normal, random.strided.normal","random.array.pareto1":"\nrandom.array.pareto1( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n I) distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n\nrandom.array.pareto1.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.pareto1.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.pareto1.PRNG;\n\n\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.pareto1.seed;\n\n\nrandom.array.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.pareto1.seedLength;\n\n\nrandom.array.pareto1.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.pareto1.state\n \n\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.pareto1.state = state;\n\n // Regenerate a previous array:\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n\nrandom.array.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.pareto1.stateLength;\n\n\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.pareto1.byteLength;\n\n See Also\n --------\n base.random.pareto1\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.pareto1.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.pareto1.PRNG;","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.pareto1.seed;","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.pareto1.seedLength;","random.array.pareto1.state":"\nrandom.array.pareto1.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.pareto1.state\n \n\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.pareto1.state = state;\n\n // Regenerate a previous array:\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n ","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.pareto1.stateLength;","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.pareto1.byteLength;\n\n See Also\n --------\n base.random.pareto1","random.array.poisson":"\nrandom.array.poisson( len, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from a Poisson\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n lambda: number\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n\nrandom.array.poisson.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n Parameters\n ----------\n lambda: number\n Mean parameter.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.poisson.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.poisson.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.poisson.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.poisson.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.poisson.PRNG;\n\n\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.poisson.seed;\n\n\nrandom.array.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.poisson.seedLength;\n\n\nrandom.array.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.poisson.state\n \n\n > out = random.array.poisson( 3, 2.0 )\n \n > out = random.array.poisson( 3, 2.0 )\n \n\n // Set the state:\n > random.array.poisson.state = state;\n\n // Regenerate a previous array:\n > out = random.array.poisson( 3, 2.0 )\n \n\n\nrandom.array.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.poisson.stateLength;\n\n\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.strided.poisson\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n Parameters\n ----------\n lambda: number\n Mean parameter.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.poisson.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.poisson.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.poisson.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.poisson.PRNG;","random.array.poisson.seed":"\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.poisson.seed;","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.poisson.seedLength;","random.array.poisson.state":"\nrandom.array.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.poisson.state\n \n\n > out = random.array.poisson( 3, 2.0 )\n \n > out = random.array.poisson( 3, 2.0 )\n \n\n // Set the state:\n > random.array.poisson.state = state;\n\n // Regenerate a previous array:\n > out = random.array.poisson( 3, 2.0 )\n ","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.poisson.stateLength;","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.strided.poisson","random.array.randu":"\nrandom.array.randu( len[, options] )\n Returns an array containing uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n\nrandom.array.randu.factory( [options] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.randu.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.randu.PRNG;\n\n\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.randu.seed;\n\n\nrandom.array.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.randu.seedLength;\n\n\nrandom.array.randu.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.randu.state;\n\n > out = random.array.randu( 3 )\n \n > out = random.array.randu( 3 )\n \n\n // Set the state:\n > random.array.randu.state = state;\n\n // Regenerate a previous array:\n > out = random.array.randu( 3 )\n \n\n\nrandom.array.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.randu.stateLength;\n\n\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.randu.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.randu, random.strided.randu\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.randu.factory();\n > var out = fcn( 3 )\n ","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.randu.PRNG;","random.array.randu.seed":"\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.randu.seed;","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.randu.seedLength;","random.array.randu.state":"\nrandom.array.randu.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.randu.state;\n\n > out = random.array.randu( 3 )\n \n > out = random.array.randu( 3 )\n \n\n // Set the state:\n > random.array.randu.state = state;\n\n // Regenerate a previous array:\n > out = random.array.randu( 3 )\n ","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.randu.stateLength;","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.randu.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.randu, random.strided.randu","random.array.rayleigh":"\nrandom.array.rayleigh( len, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n sigma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n\nrandom.array.rayleigh.assign( sigma, out )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.rayleigh.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.rayleigh.factory( [sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.rayleigh.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.rayleigh.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.rayleigh.PRNG;\n\n\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.rayleigh.seed;\n\n\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.rayleigh.seedLength;\n\n\nrandom.array.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.rayleigh.state\n \n\n > out = random.array.rayleigh( 3, 2.0 )\n \n > out = random.array.rayleigh( 3, 2.0 )\n \n\n // Set the state:\n > random.array.rayleigh.state = state;\n\n // Regenerate a previous array:\n > out = random.array.rayleigh( 3, 2.0 )\n \n\n\nrandom.array.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.rayleigh.stateLength;\n\n\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.strided.rayleigh\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma, out )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.rayleigh.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.rayleigh.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.rayleigh.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.rayleigh.PRNG;","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.rayleigh.seed;","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.rayleigh.seedLength;","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.rayleigh.state\n \n\n > out = random.array.rayleigh( 3, 2.0 )\n \n > out = random.array.rayleigh( 3, 2.0 )\n \n\n // Set the state:\n > random.array.rayleigh.state = state;\n\n // Regenerate a previous array:\n > out = random.array.rayleigh( 3, 2.0 )\n ","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.rayleigh.stateLength;","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.strided.rayleigh","random.array.t":"\nrandom.array.t( len, v[, options] )\n Returns an array containing pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n\nrandom.array.t.assign( v, out )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.t.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.t.factory( [v, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.t.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.t.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.t.PRNG;\n\n\nrandom.array.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.t.seed;\n\n\nrandom.array.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.t.seedLength;\n\n\nrandom.array.t.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.t.state\n \n\n > out = random.array.t( 3, 2.0 )\n \n > out = random.array.t( 3, 2.0 )\n \n\n // Set the state:\n > random.array.t.state = state;\n\n // Regenerate a previous array:\n > out = random.array.t( 3, 2.0 )\n \n\n\nrandom.array.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.t.stateLength;\n\n\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.t.byteLength;\n\n See Also\n --------\n base.random.t, random.strided.t\n","random.array.t.assign":"\nrandom.array.t.assign( v, out )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.t.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.t.factory":"\nrandom.array.t.factory( [v, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.t.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.t.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.t.PRNG":"\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.t.PRNG;","random.array.t.seed":"\nrandom.array.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.t.seed;","random.array.t.seedLength":"\nrandom.array.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.t.seedLength;","random.array.t.state":"\nrandom.array.t.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.t.state\n \n\n > out = random.array.t( 3, 2.0 )\n \n > out = random.array.t( 3, 2.0 )\n \n\n // Set the state:\n > random.array.t.state = state;\n\n // Regenerate a previous array:\n > out = random.array.t( 3, 2.0 )\n ","random.array.t.stateLength":"\nrandom.array.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.t.stateLength;","random.array.t.byteLength":"\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.t.byteLength;\n\n See Also\n --------\n base.random.t, random.strided.t","random.array.triangular":"\nrandom.array.triangular( len, a, b, c[, options] )\n Returns an array containing pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.triangular.assign( a, b, c, out )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.triangular.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.triangular.PRNG;\n\n\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.triangular.seed;\n\n\nrandom.array.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.triangular.seedLength;\n\n\nrandom.array.triangular.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.triangular.state\n \n\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.triangular.state = state;\n\n // Regenerate a previous array:\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.triangular.stateLength;\n\n\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.triangular.byteLength;\n\n See Also\n --------\n base.random.triangular\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a, b, c, out )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.triangular.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n ","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.triangular.PRNG;","random.array.triangular.seed":"\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.triangular.seed;","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.triangular.seedLength;","random.array.triangular.state":"\nrandom.array.triangular.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.triangular.state\n \n\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.triangular.state = state;\n\n // Regenerate a previous array:\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n ","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.triangular.stateLength;","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.triangular.byteLength;\n\n See Also\n --------\n base.random.triangular","random.array.uniform":"\nrandom.array.uniform( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a continuous\n uniform distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n\nrandom.array.uniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.uniform.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.uniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.uniform.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.uniform.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.uniform.PRNG;\n\n\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.uniform.seed;\n\n\nrandom.array.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.uniform.seedLength;\n\n\nrandom.array.uniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.uniform.state\n \n\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.uniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n\nrandom.array.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.uniform.stateLength;\n\n\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.uniform.byteLength;\n\n See Also\n --------\n random.array.discreteUniform, base.random.uniform, random.strided.uniform\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.uniform.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.uniform.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.uniform.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.uniform.PRNG;","random.array.uniform.seed":"\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.uniform.seed;","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.uniform.seedLength;","random.array.uniform.state":"\nrandom.array.uniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.uniform.state\n \n\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.uniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.uniform( 3, 2.0, 5.0 )\n ","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.uniform.stateLength;","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.uniform.byteLength;\n\n See Also\n --------\n random.array.discreteUniform, base.random.uniform, random.strided.uniform","random.array.weibull":"\nrandom.array.weibull( len, k, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from a Weibull\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n\nrandom.array.weibull.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.weibull.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.weibull.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n lambda: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.weibull.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.weibull.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.weibull.PRNG;\n\n\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.weibull.seed;\n\n\nrandom.array.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.weibull.seedLength;\n\n\nrandom.array.weibull.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.weibull.state\n \n\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.weibull.state = state;\n\n // Regenerate a previous array:\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n\nrandom.array.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.weibull.stateLength;\n\n\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.weibull.byteLength;\n\n See Also\n --------\n base.random.weibull\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.weibull.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n lambda: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.weibull.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.weibull.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.weibull.PRNG;","random.array.weibull.seed":"\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.weibull.seed;","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.weibull.seedLength;","random.array.weibull.state":"\nrandom.array.weibull.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.weibull.state\n \n\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.weibull.state = state;\n\n // Regenerate a previous array:\n > out = random.array.weibull( 3, 2.0, 5.0 )\n ","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.weibull.stateLength;","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.weibull.byteLength;\n\n See Also\n --------\n base.random.weibull","random.iterators.arcsine":"\nrandom.iterators.arcsine( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.arcsine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.arcsine\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.bernoulli( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.bernoulli\n","random.iterators.beta":"\nrandom.iterators.beta( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.beta( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.beta\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.betaprime( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.betaprime\n","random.iterators.binomial":"\nrandom.iterators.binomial( n, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.binomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.binomial\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.boxMuller();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.boxMuller\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0, Ɣ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cauchy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cauchy\n","random.iterators.chi":"\nrandom.iterators.chi( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chi( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chi\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chisquare( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chisquare\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cosine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cosine\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned iterator, one must\n seed the provided `prng` (assuming the provided `prng` is seedable). The\n provided PRNG must have `MIN` and `MAX` properties specifying the\n minimum and maximum possible pseudorandom integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.discreteUniform( 0, 3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.discreteUniform\n","random.iterators.erlang":"\nrandom.iterators.erlang( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If `k` is not a positive integer or `λ <= 0`, the function throws an error.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.erlang( 1, 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.erlang\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.exponential( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.exponential\n","random.iterators.f":"\nrandom.iterators.f( d1, d2[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `d1 <= 0` or `d2 <= 0`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.f( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.f\n","random.iterators.frechet":"\nrandom.iterators.frechet( α, s, m[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `s <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.frechet\n","random.iterators.gamma":"\nrandom.iterators.gamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gamma\n","random.iterators.geometric":"\nrandom.iterators.geometric( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.geometric( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.geometric\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gumbel( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gumbel\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N, K, n[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n throws an error.\n\n If `n > N` or `K > N`, the function throws an error.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.hypergeometric( 20, 10, 7 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.hypergeometric\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.improvedZiggurat();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.improvedZiggurat\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.invgamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.invgamma\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `a <= 0` or `b <= 0`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.kumaraswamy( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.kumaraswamy\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.laplace( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.laplace\n","random.iterators.levy":"\nrandom.iterators.levy( μ, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.levy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.levy\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.logistic( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.logistic\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.lognormal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.lognormal\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstd();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstd, random.iterators.minstdShuffle, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstdShuffle();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstd, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Uint32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Uint32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.mt19937();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.mt19937, random.iterators.minstd, random.iterators.minstdShuffle, random.iterators.randi, random.iterators.randu\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.negativeBinomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.negativeBinomial\n","random.iterators.normal":"\nrandom.iterators.normal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.normal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.normal\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.pareto1( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.pareto1\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.poisson( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.poisson\n","random.iterators.randi":"\nrandom.iterators.randi( [options] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randi();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randi, random.iterators.randu\n","random.iterators.randn":"\nrandom.iterators.randn( [options] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: `'improved-ziggurat'`.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randn();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randn\n","random.iterators.randu":"\nrandom.iterators.randu( [options] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randu();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randu, random.iterators.randi\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.rayleigh( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.rayleigh\n","random.iterators.t":"\nrandom.iterators.t( v[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.t( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.t\n","random.iterators.triangular":"\nrandom.iterators.triangular( a, b, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.triangular\n","random.iterators.uniform":"\nrandom.iterators.uniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.uniform( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.uniform\n","random.iterators.weibull":"\nrandom.iterators.weibull( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `k <= 0` or `λ <= 0`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.weibull( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.weibull\n","random.streams.arcsine":"\nrandom.streams.arcsine( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );\n\n\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.arcsine, random.iterators.arcsine\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.arcsine, random.iterators.arcsine","random.streams.bernoulli":"\nrandom.streams.bernoulli( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );\n\n\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.bernoulli, random.iterators.bernoulli\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.bernoulli, random.iterators.bernoulli","random.streams.beta":"\nrandom.streams.beta( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );\n\n\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.beta, random.iterators.beta\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.beta, random.iterators.beta","random.streams.betaprime":"\nrandom.streams.betaprime( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );\n\n\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.betaprime, random.iterators.betaprime\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.betaprime, random.iterators.betaprime","random.streams.binomial":"\nrandom.streams.binomial( n, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial( 20, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );\n\n\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.binomial, random.iterators.binomial\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.binomial, random.iterators.binomial","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );\n\n\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn","random.streams.cauchy":"\nrandom.streams.cauchy( x0, γ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );\n\n\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cauchy, random.iterators.cauchy\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cauchy, random.iterators.cauchy","random.streams.chi":"\nrandom.streams.chi( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );\n\n\nrandom.streams.chi.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chi, random.iterators.chi\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chi, random.iterators.chi","random.streams.chisquare":"\nrandom.streams.chisquare( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );\n\n\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chisquare, random.iterators.chisquare\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chisquare, random.iterators.chisquare","random.streams.cosine":"\nrandom.streams.cosine( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );\n\n\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cosine, random.iterators.cosine\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cosine, random.iterators.cosine","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform( 2, 5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );\n\n\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.discreteUniform, random.iterators.discreteUniform\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.discreteUniform, random.iterators.discreteUniform","random.streams.erlang":"\nrandom.streams.erlang( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang( 2, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );\n\n\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.erlang, random.iterators.erlang\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.erlang, random.iterators.erlang","random.streams.exponential":"\nrandom.streams.exponential( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );\n\n\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.exponential, random.iterators.exponential\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.exponential, random.iterators.exponential","random.streams.f":"\nrandom.streams.f( d1, d2[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );\n\n\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.f, random.iterators.f\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.f, random.iterators.f","random.streams.frechet":"\nrandom.streams.frechet( α, s, m[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Fréchet distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.frechet.factory( [α, s, m,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.frechet.factory( opts );\n\n\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.frechet, random.iterators.frechet\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α, s, m,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.frechet.factory( opts );","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.frechet, random.iterators.frechet","random.streams.gamma":"\nrandom.streams.gamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );\n\n\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gamma, random.iterators.gamma\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gamma, random.iterators.gamma","random.streams.geometric":"\nrandom.streams.geometric( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );\n\n\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.geometric, random.iterators.geometric\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.geometric, random.iterators.geometric","random.streams.gumbel":"\nrandom.streams.gumbel( μ, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );\n\n\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gumbel, random.iterators.gumbel\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gumbel, random.iterators.gumbel","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N, K, n[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric( 5, 3, 2, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.hypergeometric.factory( opts );\n\n\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.hypergeometric, random.iterators.hypergeometric\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.hypergeometric.factory( opts );","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.hypergeometric, random.iterators.hypergeometric","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );\n\n\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn","random.streams.invgamma":"\nrandom.streams.invgamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );\n\n\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.invgamma, random.iterators.invgamma\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.invgamma, random.iterators.invgamma","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );\n\n\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.kumaraswamy, random.iterators.kumaraswamy\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.kumaraswamy, random.iterators.kumaraswamy","random.streams.laplace":"\nrandom.streams.laplace( μ, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );\n\n\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.laplace, random.iterators.laplace\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.laplace, random.iterators.laplace","random.streams.levy":"\nrandom.streams.levy( μ, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );\n\n\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.levy, random.iterators.levy\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.levy, random.iterators.levy","random.streams.logistic":"\nrandom.streams.logistic( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );\n\n\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.logistic, random.iterators.logistic\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.logistic, random.iterators.logistic","random.streams.lognormal":"\nrandom.streams.lognormal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );\n\n\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.lognormal, random.iterators.lognormal\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.lognormal, random.iterators.lognormal","random.streams.minstd":"\nrandom.streams.minstd( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );\n\n\nrandom.streams.minstd.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );\n\n\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.mt19937":"\nrandom.streams.mt19937( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a 32-bit Mersenne\n Twister pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );\n\n\nrandom.streams.mt19937.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial( 20.0, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );\n\n\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.negativeBinomial, random.iterators.negativeBinomial\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.negativeBinomial, random.iterators.negativeBinomial","random.streams.normal":"\nrandom.streams.normal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );\n\n\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.normal, random.iterators.normal\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.normal, random.iterators.normal","random.streams.pareto1":"\nrandom.streams.pareto1( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );\n\n\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.pareto1, random.iterators.pareto1\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.pareto1, random.iterators.pareto1","random.streams.poisson":"\nrandom.streams.poisson( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );\n\n\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.poisson, random.iterators.poisson\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.poisson, random.iterators.poisson","random.streams.randi":"\nrandom.streams.randi( [options] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );\n\n\nrandom.streams.randi.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randi, random.iterators.randi, random.streams.randu\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randi, random.iterators.randi, random.streams.randu","random.streams.randn":"\nrandom.streams.randn( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );\n\n\nrandom.streams.randn.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat","random.streams.randu":"\nrandom.streams.randu( [options] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );\n\n\nrandom.streams.randu.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randu, random.iterators.randu, random.streams.randi\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randu, random.iterators.randu, random.streams.randi","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );\n\n\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.rayleigh, random.iterators.rayleigh\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.rayleigh, random.iterators.rayleigh","random.streams.t":"\nrandom.streams.t( v[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );\n\n\nrandom.streams.t.objectMode( v[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.t, random.iterators.t\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.t, random.iterators.t","random.streams.triangular":"\nrandom.streams.triangular( a, b, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.triangular.factory( opts );\n\n\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.triangular, random.iterators.triangular\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.triangular.factory( opts );","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.triangular, random.iterators.triangular","random.streams.uniform":"\nrandom.streams.uniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );\n\n\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.uniform, random.iterators.uniform\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.uniform, random.iterators.uniform","random.streams.weibull":"\nrandom.streams.weibull( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );\n\n\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.weibull, random.iterators.weibull\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.weibull, random.iterators.weibull","random.strided.arcsine":"\nrandom.strided.arcsine( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.arcsine, random.array.arcsine\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.arcsine, random.array.arcsine","random.strided.bernoulli":"\nrandom.strided.bernoulli( N, p, sp, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.bernoulli.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.bernoulli.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.bernoulli.PRNG;\n\n\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.bernoulli.seed;\n\n\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.bernoulli.seedLength;\n\n\nrandom.strided.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.bernoulli.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.bernoulli.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.bernoulli.stateLength;\n\n\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.array.bernoulli\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n [...]","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.bernoulli.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.5 ], 0, out, 1 )\n [...]","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.bernoulli.PRNG;","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.bernoulli.seed;","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.bernoulli.seedLength;","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.bernoulli.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.bernoulli.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.bernoulli.stateLength;","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.array.bernoulli","random.strided.beta":"\nrandom.strided.beta( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.beta, random.array.beta\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.beta, random.array.beta","random.strided.betaprime":"\nrandom.strided.betaprime( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.betaprime, random.array.betaprime\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.betaprime, random.array.betaprime","random.strided.chi":"\nrandom.strided.chi( N, k, sk, out, so )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.chi.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chi.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chi.PRNG;\n\n\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chi.seed;\n\n\nrandom.strided.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chi.seedLength;\n\n\nrandom.strided.chi.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chi.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chi.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chi.stateLength;\n\n\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.array.chi\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chi.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chi.PRNG;","random.strided.chi.seed":"\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chi.seed;","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chi.seedLength;","random.strided.chi.state":"\nrandom.strided.chi.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chi.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chi.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chi.stateLength;","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.array.chi","random.strided.chisquare":"\nrandom.strided.chisquare( N, k, sk, out, so )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.chisquare.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chisquare.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chisquare.PRNG;\n\n\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chisquare.seed;\n\n\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chisquare.seedLength;\n\n\nrandom.strided.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chisquare.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chisquare.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chisquare.stateLength;\n\n\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.array.chisquare\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chisquare.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chisquare.PRNG;","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chisquare.seed;","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chisquare.seedLength;","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chisquare.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chisquare.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chisquare.stateLength;","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.array.chisquare","random.strided.cosine":"\nrandom.strided.cosine( N, mu, sm, s, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n [...]\n\n\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n os: integer\n Starting index for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.cosine, random.array.cosine\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n os: integer\n Starting index for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.cosine, random.array.cosine","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform","random.strided.exponential":"\nrandom.strided.exponential( N, lambda, sl, out, so )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.exponential.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.exponential.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.exponential.PRNG;\n\n\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.exponential.seed;\n\n\nrandom.strided.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.exponential.seedLength;\n\n\nrandom.strided.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.exponential.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.exponential.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.exponential.stateLength;\n\n\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.array.exponential\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.exponential.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.exponential.PRNG;","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.exponential.seed;","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.exponential.seedLength;","random.strided.exponential.state":"\nrandom.strided.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.exponential.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.exponential.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.exponential.stateLength;","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.array.exponential","random.strided.gamma":"\nrandom.strided.gamma( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.gamma, random.array.gamma\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.gamma, random.array.gamma","random.strided.geometric":"\nrandom.strided.geometric( N, p, sp, out, so )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.geometric.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.geometric.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.geometric.PRNG;\n\n\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.geometric.seed;\n\n\nrandom.strided.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.geometric.seedLength;\n\n\nrandom.strided.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.geometric.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.geometric.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.geometric.stateLength;\n\n\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.array.geometric\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n [...]","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.geometric.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.01 ], 0, out, 1 )\n [...]","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.geometric.PRNG;","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.geometric.seed;","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.geometric.seedLength;","random.strided.geometric.state":"\nrandom.strided.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.geometric.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.geometric.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.geometric.stateLength;","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.array.geometric","random.strided.invgamma":"\nrandom.strided.invgamma( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.invgamma, random.array.invgamma\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.invgamma, random.array.invgamma","random.strided.lognormal":"\nrandom.strided.lognormal( N, mu, sm, sigma, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n [...]\n\n\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.lognormal, random.array.lognormal\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.lognormal, random.array.lognormal","random.strided.minstd":"\nrandom.strided.minstd( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.minstd.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized( out.length, out, 1 )\n [...]","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n [...]","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu","random.strided.mt19937":"\nrandom.strided.mt19937( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937( out.length, out, 1 )\n [...]\n\n\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.mt19937, random.array.mt19937, random.strided.randu\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized( out.length, out, 1 )\n [...]","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.mt19937, random.array.mt19937, random.strided.randu","random.strided.normal":"\nrandom.strided.normal( N, mu, sm, sigma, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n [...]\n\n\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.normal, random.array.normal\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.normal, random.array.normal","random.strided.poisson":"\nrandom.strided.poisson( N, lambda, sl, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.poisson.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.poisson.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.poisson.PRNG;\n\n\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.poisson.seed;\n\n\nrandom.strided.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.poisson.seedLength;\n\n\nrandom.strided.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.poisson.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.poisson.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.poisson.stateLength;\n\n\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.array.poisson\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.poisson.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.poisson.PRNG;","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.poisson.seed;","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.poisson.seedLength;","random.strided.poisson.state":"\nrandom.strided.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.poisson.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.poisson.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.poisson.stateLength;","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.array.poisson","random.strided.randu":"\nrandom.strided.randu( N, out, so[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu( out.length, out, 1 )\n [...]\n\n\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.randu, random.array.randu, random.strided.uniform\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.randu, random.array.randu, random.strided.uniform","random.strided.rayleigh":"\nrandom.strided.rayleigh( N, sigma, ss, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.rayleigh.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.rayleigh.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.rayleigh.PRNG;\n\n\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.rayleigh.seed;\n\n\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.rayleigh.seedLength;\n\n\nrandom.strided.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.rayleigh.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.rayleigh.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.rayleigh.stateLength;\n\n\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.array.rayleigh\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.rayleigh.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.rayleigh.PRNG;","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.rayleigh.seed;","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.rayleigh.seedLength;","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.rayleigh.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.rayleigh.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.rayleigh.stateLength;","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.array.rayleigh","random.strided.t":"\nrandom.strided.t( N, v, sv, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n ov: integer\n Starting index for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.t.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.t.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.t.PRNG;\n\n\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.t.seed;\n\n\nrandom.strided.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.t.seedLength;\n\n\nrandom.strided.t.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.t.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.t.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.t.stateLength;\n\n\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.t.byteLength;\n\n See Also\n --------\n base.random.t, random.array.t\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n ov: integer\n Starting index for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.t.factory":"\nrandom.strided.t.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.t.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.t.PRNG;","random.strided.t.seed":"\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.t.seed;","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.t.seedLength;","random.strided.t.state":"\nrandom.strided.t.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.t.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.t.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.t.stateLength;","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.t.byteLength;\n\n See Also\n --------\n base.random.t, random.array.t","random.strided.uniform":"\nrandom.strided.uniform( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.uniform, random.array.uniform, random.strided.discreteUniform\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.uniform, random.array.uniform, random.strided.discreteUniform","ranks":"\nranks( arr[, options] )\n Computes the sample ranks for the values of an array-like object.\n\n When all elements of the `array` are different, the ranks are uniquely\n determined. When there are equal elements (called *ties*), the `method`\n option determines how they are handled. The default, `'average'`, replaces\n the ranks of the ties by their mean. Other possible options are `'min'` and\n `'max'`, which replace the ranks of the ties by their minimum and maximum,\n respectively. `'dense'` works like `'min'`, with the difference that the\n next highest element after a tie is assigned the next smallest integer.\n Finally, `ordinal` gives each element in `arr` a distinct rank, according to\n the position they appear in.\n\n The `missing` option is used to specify how to handle missing data.\n By default, `NaN` or `null` are treated as missing values. `'last'`specifies\n that missing values are placed last, `'first'` that the are assigned the\n lowest ranks and `'remove'` means that they are removed from the array\n before the ranks are calculated.\n\n Parameters\n ----------\n arr: Array\n Input values.\n\n options: Object (optional)\n Function options.\n\n options.method (optional)\n Method name determining how ties are treated (`average`, `min`, `max`,\n `dense`, or `ordinal`). Default: `'average'`.\n\n options.missing (optional)\n Determines where missing values go (`first`, `last`, or `remove`).\n Default: `'last'`.\n\n options.encoding (optional)\n Array of values encoding missing values. Default: `[ null, NaN ]`.\n\n Returns\n -------\n out: Array\n Array containing the computed ranks for the elements of the input array.\n\n Examples\n --------\n > var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\n > var out = ranks( arr )\n [ 2, 3, 5, 1, 4 ]\n\n // Ties are averaged:\n > arr = [ 2, 2, 1, 4, 3 ];\n > out = ranks( arr )\n [ 2.5, 2.5, 1, 5, 4 ]\n\n // Missing values are placed last:\n > arr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\n > out = ranks( arr )\n [ 6, 2.5, 2.5, 1, 5, 4, 7 ,8 ]\n\n","readDir":"\nreadDir( path, clbk )\n Asynchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n clbk: Function\n Callback to invoke after reading directory contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readDir( './beep/boop', onRead );\n\n\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n See Also\n --------\n exists, readFile\n","readDir.sync":"\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n See Also\n --------\n exists, readFile","readFile":"\nreadFile( file[, options], clbk )\n Asynchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readFile( './beep/boop.js', onRead );\n\n\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n See Also\n --------\n exists, open, readDir, readJSON, writeFile\n","readFile.sync":"\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n See Also\n --------\n exists, open, readDir, readJSON, writeFile","readFileList":"\nreadFileList( filepaths[, options], clbk )\n Asynchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Each file is represented by an object with the following fields:\n\n - file: file path\n - data: file contents as either a Buffer or string\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > readFileList( filepaths, onRead );\n\n\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );\n\n","readFileList.sync":"\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );","readJSON":"\nreadJSON( file[, options], clbk )\n Asynchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readJSON( './beep/boop.json', onRead );\n\n\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n See Also\n --------\n readFile\n","readJSON.sync":"\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n See Also\n --------\n readFile","readWASM":"\nreadWASM( file[, options], clbk )\n Asynchronously reads a file as WebAssembly.\n\n The function returns file contents as a Uint8Array.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readWASM( './beep/boop.wasm', onRead );\n\n\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n See Also\n --------\n readFile\n","readWASM.sync":"\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n See Also\n --------\n readFile","real":"\nreal( z )\n Returns the real component of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var re = real( z )\n 5.0\n\n See Also\n --------\n imag, reim\n","realarray":"\nrealarray( [dtype] )\n Creates a typed array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = realarray()\n \n > arr = realarray( 'float32' )\n \n\n\nrealarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = realarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = realarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\nrealarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = realarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\nrealarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = realarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\nrealarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = realarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","realarrayCtors":"\nrealarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = realarrayCtors( 'float64' )\n \n > ctor = realarrayCtors( 'float' )\n null\n\n See Also\n --------\n arrayCtors, complexarrayCtors\n","realarrayDataTypes":"\nrealarrayDataTypes()\n Returns a list of typed array real-valued data types.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = realarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, complexarrayDataTypes\n","realf":"\nrealf( z )\n Returns the real component of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var re = realf( z )\n 5.0\n\n See Also\n --------\n imagf, real, reimf\n","realmax":"\nrealmax( dtype )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum finite value.\n\n Examples\n --------\n > var m = realmax( 'float16' )\n 65504.0\n > m = realmax( 'float32' )\n 3.4028234663852886e+38\n\n See Also\n --------\n realmin, typemax\n","realmin":"\nrealmin( dtype )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Smallest finite normal value.\n\n Examples\n --------\n > var m = realmin( 'float16' )\n 0.00006103515625\n > m = realmin( 'float32' )\n 1.1754943508222875e-38\n\n See Also\n --------\n realmax, typemin\n","reBasename":"\nreBasename( [platform] )\n Returns a regular expression to capture the last part of a path.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reBasename()\n \n > var RE_POSIX = reBasename( 'posix' );\n > var RE_WIN32 = reBasename( 'win32' );\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var RE = reBasename.REGEXP\n \n\n\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasenamePosix, reBasenameWindows\n","reBasename.REGEXP":"\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var RE = reBasename.REGEXP\n ","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasenamePosix, reBasenameWindows","reBasenamePosix":"\nreBasenamePosix()\n Returns a regular expression to capture the last part of a POSIX path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_BASENAME_POSIX = reBasenamePosix();\n > var base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( './' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n ''\n\n\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasename, reBasenameWindows\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasename, reBasenameWindows","reBasenameWindows":"\nreBasenameWindows()\n Returns a regular expression to capture the last part of a Windows path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_BASENAME_WINDOWS = reBasenameWindows();\n > var base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n\n See Also\n --------\n reBasename, reBasenamePosix\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n\n See Also\n --------\n reBasename, reBasenamePosix","reColorHexadecimal":"\nreColorHexadecimal( [mode] )\n Returns a regular expression to match a hexadecimal color.\n\n Parameters\n ----------\n mode: string (optional)\n Color format (`full`, `shorthand`, or `either`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reColorHexadecimal();\n > var bool = RE.test( 'ffffff' )\n true\n > bool = RE.test( '000' )\n false\n > bool = RE.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP.test( '000' )\n false\n > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n false\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n false\n\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP.test( '000' )\n false\n > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n false","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n false\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n false","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n false","reDecimalNumber":"\nreDecimalNumber( [options] )\n Returns a regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to create a capture group for the match.\n Default: false.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDecimalNumber();\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true\n > bool = RE.test( '0.0' )\n true\n > bool = RE.test( '.0' )\n true\n > bool = RE.test( '0' )\n false\n > bool = RE.test( 'beep' )\n false\n\n // Create a RegExp to capture all decimal numbers:\n > var re = reDecimalNumber({ 'flags': 'g' });\n > var str = '1.234 5.6, 7.8';\n > var out = str.match( re )\n [ '1.234', '5.6', '7.8' ]\n\n\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP;\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true\n\n\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP_CAPTURE;\n > var str = '1.02';\n > var out = replace( str, RE, '$1 x $1' )\n '1.02 x 1.02'\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP;\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP_CAPTURE;\n > var str = '1.02';\n > var out = replace( str, RE, '$1 x $1' )\n '1.02 x 1.02'","reDirname":"\nreDirname( [platform] )\n Returns a regular expression to capture a path dirname.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirname()\n \n > var RE_POSIX = reDirname( 'posix' );\n > var dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > var RE_WIN32 = reDirname( 'win32' );\n > dir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n\n Examples\n --------\n > var RE = reDirname.REGEXP\n \n\n\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n\n See Also\n --------\n reDirnamePosix, reDirnameWindows, dirname\n","reDirname.REGEXP":"\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n\n Examples\n --------\n > var RE = reDirname.REGEXP\n ","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n\n See Also\n --------\n reDirnamePosix, reDirnameWindows, dirname","reDirnamePosix":"\nreDirnamePosix()\n Returns a regular expression to capture a POSIX path dirname.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirnamePosix();\n > var dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > dir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n './foo/bar'\n > dir = RE.exec( 'foo/file.pdf' )[ 1 ]\n 'foo'\n > dir = RE.exec( '/foo/bar/file' )[ 1 ]\n '/foo/bar'\n > dir = RE.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE.exec( '.' )[ 1 ]\n '.'\n > dir = RE.exec( './' )[ 1 ]\n '.'\n > dir = RE.exec( '' )[ 1 ]\n ''\n\n\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n See Also\n --------\n reDirname, reDirnameWindows, dirname\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n See Also\n --------\n reDirname, reDirnameWindows, dirname","reDirnameWindows":"\nreDirnameWindows()\n Returns a regular expression to capture a Windows path dirname.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirnameWindows();\n > var dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n > dir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n 'C:\\foo\\bar'\n > dir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'foo'\n > dir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n '\\foo\\bar'\n > dir = RE.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE.exec( '' )[ 1 ]\n ''\n\n\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n\n See Also\n --------\n reDirname, reDirnamePosix, dirname\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n\n See Also\n --------\n reDirname, reDirnamePosix, dirname","reduce":"\nreduce( arr, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a reduction over the entire\n input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input array.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > var out = reduce( arr, 0.0, f )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = reduce( arr, 0.0, f )\n 21.0\n\n See Also\n --------\n forEach, map, reduceAsync, reduceRight\n","reduce2d":"\nreduce2d( arr, initial, reducer[, thisArg] )\n Reduces the number of dimensions by one of a two-dimensional nested array by\n applying a function against an accumulator and each element along the\n innermost dimension and returning the accumulation results as a one-\n dimensional array.\n\n The applied function is provided the following arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array of arrays.\n\n initial: ArrayLikeObject\n Initial values. Must have a length equal to the size of the outermost\n input array dimension.\n\n reducer: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array\n Accumulation results.\n\n Examples\n --------\n > var f = naryFunction( base.add, 2 );\n > var arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\n > var out = reduce2d( arr, [ 0, 0 ], f )\n [ 6, 15 ]\n\n See Also\n --------\n map2d, reduce\n","reduceAsync":"\nreduceAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `next`\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `index`\n - `next`\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `accumulator`: accumulated value\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachAsync, reduce, reduceRightAsync\n","reduceAsync.factory":"\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachAsync, reduce, reduceRightAsync","reduceRight":"\nreduceRight( arr, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in an array while\n iterating from right to left and returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a reduction over the entire\n input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input array.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > var out = reduceRight( arr, 0.0, f )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = reduceRight( arr, 0.0, f )\n 21.0\n\n See Also\n --------\n forEachRight, mapRight, reduce, reduceRightAsync\n","reduceRightAsync":"\nreduceRightAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `next`\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `index`\n - `next`\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `accumulator`: accumulated value\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachRightAsync, reduceAsync, reduceRight\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachRightAsync, reduceAsync, reduceRight","reEOL":"\nreEOL( [options] )\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to create a capture group for the match.\n Default: false.\n\n Returns\n -------\n regexp: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_EOL = reEOL();\n > var bool = RE_EOL.test( '\\n' )\n true\n > bool = RE_EOL.test( '\\r\\n' )\n true\n > bool = RE_EOL.test( '\\\\r\\\\n' )\n false\n\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var bool = reEOL.REGEXP.test( 'abc' )\n false\n\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n [ '\\n', '\\n' ]\n\n","reEOL.REGEXP":"\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var bool = reEOL.REGEXP.test( 'abc' )\n false","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n [ '\\n', '\\n' ]","reExtendedLengthPath":"\nreExtendedLengthPath()\n Returns a regular expression to test if a string is an extended-length path.\n\n Extended-length paths are Windows paths which begin with `\\\\?\\`.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtendedLengthPath();\n > var path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\n > var bool = RE.test( path )\n true\n > path = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\n > bool = RE.test( path )\n true\n > path = 'C:\\\\foo\\\\bar';\n > bool = RE.test( path )\n false\n > path = '/c/foo/bar';\n > bool = RE.test( path )\n false\n > path = '/foo/bar';\n > bool = RE.test( path )\n false\n\n\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n\n Examples\n --------\n > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n false\n\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n\n Examples\n --------\n > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n false","reExtname":"\nreExtname( [platform] )\n Returns a regular expression to capture a filename extension.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtname()\n \n > var RE_POSIX = reExtname( 'posix' );\n > var ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > var RE_WIN32 = reExtname( 'win32' );\n > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n\n Examples\n --------\n > var RE = reExtname.REGEXP\n \n\n\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtnamePosix, reExtnameWindows, extname\n","reExtname.REGEXP":"\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n\n Examples\n --------\n > var RE = reExtname.REGEXP\n ","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtnamePosix, reExtnameWindows, extname","reExtnamePosix":"\nreExtnamePosix\n Returns a regular expression to capture a POSIX filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtnamePosix();\n > var ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n ''\n > ext = RE.exec( 'foo/file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE.exec( '/foo/bar/file' )[ 1 ]\n ''\n > ext = RE.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( '.' )[ 1 ]\n ''\n > ext = RE.exec( './' )[ 1 ]\n ''\n > ext = RE.exec( '' )[ 1 ]\n ''\n\n\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnameWindows, extname\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnameWindows, extname","reExtnameWindows":"\nreExtnameWindows\n Returns a regular expression to capture a Windows filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtnameWindows();\n > var ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n ''\n > ext = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n ''\n > ext = RE.exec( 'beep\\\\boop.' )[ 1 ]\n '.'\n > ext = RE.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( '' )[ 1 ]\n ''\n\n\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnamePosix, extname\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnamePosix, extname","reFilename":"\nreFilename( [platform] )\n Regular expression to split a filename.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilename()\n \n > var RE_POSIX = reFilename( 'posix' );\n > var parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\n \n > var RE_WIN32 = reFilename( 'win32' );\n > parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n \n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreFilename.REGEXP\n Regular expression to split a filename.\n\n Examples\n --------\n > var RE = reFilename.REGEXP\n \n\n\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilenamePosix, reFilenameWindows\n","reFilename.REGEXP":"\nreFilename.REGEXP\n Regular expression to split a filename.\n\n Examples\n --------\n > var RE = reFilename.REGEXP\n ","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilenamePosix, reFilenameWindows","reFilenamePosix":"\nreFilenamePosix()\n Returns a regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilenamePosix();\n > var parts = RE.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n > parts = RE.exec( './foo/bar/.gitignore' ).slice()\n [ './foo/bar/.gitignore', '', './foo/bar/', '.gitignore', '' ]\n > parts = RE.exec( 'foo/file.pdf' ).slice()\n [ 'foo/file.pdf', '', 'foo/', 'file.pdf', '.pdf' ]\n > parts = RE.exec( '/foo/bar/file' ).slice()\n [ '/foo/bar/file', '/', 'foo/bar/', 'file', '' ]\n > parts = RE.exec( 'index.js' ).slice()\n [ 'index.js', '', '', 'index.js', '.js' ]\n > parts = RE.exec( '.' ).slice()\n [ '.', '', '', '.', '' ]\n > parts = RE.exec( './' ).slice()\n [ './', '', ..., '.', '' ]\n > parts = RE.exec( '' ).slice()\n [ '', '', '', '', '' ]\n\n\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n\n Examples\n --------\n > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenameWindows\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n\n Examples\n --------\n > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenameWindows","reFilenameWindows":"\nreFilenameWindows()\n Returns a regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilenameWindows();\n > var parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n > parts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\n [ '\\\\foo\\\\bar\\\\.gitignore', '', '\\\\', 'foo\\\\bar\\\\', '.gitignore', '' ]\n > parts = RE.exec( 'foo\\\\file.pdf' ).slice()\n [ 'foo\\\\file.pdf', '', '', 'foo\\\\', 'file.pdf', '.pdf' ]\n > parts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\n [ '\\\\foo\\\\bar\\\\file', '', '\\\\', 'foo\\\\bar\\\\', 'file', '' ]\n > parts = RE.exec( 'index.js' ).slice()\n [ 'index.js', '', '', '', 'index.js', '.js' ]\n > parts = RE.exec( '.' ).slice()\n [ '.', '', '', '', '.', '' ]\n > parts = RE.exec( './' ).slice()\n [ './', '', ..., '.', '' ]\n > parts = RE.exec( '' ).slice()\n [ '', '', '', '', '', '' ]\n\n\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n\n Examples\n --------\n > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenamePosix","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n\n Examples\n --------\n > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenamePosix","reFromString":"\nreFromString( str )\n Parses a regular expression string and returns a new regular expression.\n\n Provided strings should be properly escaped.\n\n If unable to parse a string as a regular expression, the function returns\n `null`.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: RegExp|null\n Regular expression or null.\n\n Examples\n --------\n > var re = reFromString( '/beep/' )\n /beep/\n > re = reFromString( '/beep' )\n null\n\n","reFunctionName":"\nreFunctionName()\n Return a regular expression to capture a function name.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_FUNCTION_NAME = reFunctionName();\n > function beep() { return 'boop'; };\n > var name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\n 'beep'\n > name = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n ''\n\n\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n\n Examples\n --------\n > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n 'sqrt'\n\n See Also\n --------\n functionName\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n\n Examples\n --------\n > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n 'sqrt'\n\n See Also\n --------\n functionName","regexp2json":"\nregexp2json( re )\n Returns a JSON representation of a regular expression.\n\n Parameters\n ----------\n re: RegExp\n Regular expression to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n \n out.type: string\n Value type. The assigned value is always 'RegExp'.\n \n out.pattern: string\n Regular expression pattern.\n \n out.flags: string\n Regular expression flags.\n\n Examples\n --------\n > var json = regexp2json( /ab+c/ )\n {...}\n\n See Also\n --------\n reviveRegExp \n","reim":"\nreim( z )\n Returns the real and imaginary components of a double-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Float64Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var out = reim( z )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n imag, real\n","reimf":"\nreimf( z )\n Returns the real and imaginary components of a single-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Float32Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var out = reimf( z )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n imagf, realf, reim\n","rejectArguments":"\nrejectArguments( fcn, predicate[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n\n Only those arguments in which the predicate function returns a falsy value\n are applied to a provided function.\n\n The predicate function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > function predicate( v ) { return ( v === 2 ); };\n > var bar = rejectArguments( foo, predicate );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n filterArguments, maskArguments\n","removeFirst":"\nremoveFirst( str[, n][, options] )\n Removes the first character(s) of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to remove. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeFirst( 'beep' )\n 'eep'\n > out = removeFirst( 'Boop' )\n 'oop'\n > out = removeFirst( 'foo bar', 4 )\n 'bar'\n\n See Also\n --------\n removeLast\n","removeLast":"\nremoveLast( str[, n][, options] )\n Removes the last character(s) of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to remove. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to remove. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeLast( 'beep' )\n 'bee'\n > out = removeLast( 'Boop' )\n 'Boo'\n > out = removeLast( 'foo bar', 4 )\n 'foo'\n\n See Also\n --------\n removeFirst\n","removePunctuation":"\nremovePunctuation( str )\n Removes punctuation characters from a `string`.\n\n The function removes the following characters:\n\n - Apostrophe: `\n - Braces : { }\n - Brackets: [ ]\n - Colon: :\n - Comma: ,\n - Exclamation Mark: !\n - Fraction Slash: /\n - Guillemets: < >\n - Parentheses: ( )\n - Period: .\n - Semicolon: ;\n - Tilde: ~\n - Vertical Bar: |\n - Question Mark: ?\n - Quotation Marks: ' \"\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with punctuation characters removed.\n\n Examples\n --------\n > var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\n > var out = removePunctuation( str )\n 'Sun Tzu said A leader leads by example not by force'\n\n > str = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\n > out = removePunctuation( str )\n 'This function removes these characters '\n\n","removeUTF8BOM":"\nremoveUTF8BOM( str )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with BOM removed.\n\n Examples\n --------\n > var out = removeUTF8BOM( '\\ufeffbeep' )\n 'beep'\n\n","removeWords":"\nremoveWords( str, words[, ignoreCase] )\n Removes all occurrences of the given words from a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n words: Array\n Array of words to be removed.\n\n ignoreCase: boolean (optional)\n Boolean indicating whether to perform a case-insensitive operation.\n Default: `false`.\n\n Returns\n -------\n out: string\n String with words removed.\n\n Examples\n --------\n > var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\n 'beep Foo bar'\n\n // Case-insensitive:\n > out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n 'beep bar'\n\n","rename":"\nrename( oldPath, newPath, clbk )\n Asynchronously renames a file.\n\n The old path can specify a directory. In this case, the new path must either\n not exist, or it must specify an empty directory.\n\n The old pathname should not name an ancestor directory of the new pathname.\n\n If the old path points to the pathname of a file that is not a directory,\n the new path should not point to the pathname of a directory.\n\n Write access permission is required for both the directory containing the\n old path and the directory containing the new path.\n\n If the link named by the new path exists, the new path is removed and the\n old path is renamed to the new path. The link named by the new path will\n remain visible to other threads throughout the renaming operation and refer\n to either the file referred to by the new path or to the file referred to by\n the old path before the operation began.\n\n If the old path and the new path resolve to either the same existing\n directory entry or to different directory entries for the same existing\n file, no action is taken, and no error is returned.\n\n If the old path points to a pathname of a symbolic link, the symbolic link\n is renamed. If the new path points to a pathname of a symbolic link, the\n symbolic link is removed.\n\n If a link named by the new path exists and the file's link count becomes 0\n when it is removed and no process has the file open, the space occupied by\n the file is freed and the file is no longer accessible. If one or more\n processes have the file open when the last link is removed, the link is\n removed before the function returns, but the removal of file contents is\n postponed until all references to the file are closed.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n clbk: Function\n Callback to invoke upon renaming a file.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > rename( './beep/boop.txt', './beep/foo.txt', done );\n\n\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n See Also\n --------\n exists, readFile, writeFile, unlink\n","rename.sync":"\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n See Also\n --------\n exists, readFile, writeFile, unlink","reNativeFunction":"\nreNativeFunction()\n Returns a regular expression to match a native function.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reNativeFunction();\n > var bool = RE.test( Date.toString() )\n true\n > bool = RE.test( (function noop() {}).toString() )\n false\n\n\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n true\n > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n false\n\n See Also\n --------\n reFunctionName, functionName\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n true\n > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n false\n\n See Also\n --------\n reFunctionName, functionName","reorderArguments":"\nreorderArguments( fcn, indices[, thisArg] )\n Returns a function that invokes a provided function with reordered\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reordered arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reorderArguments( foo, [ 2, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 3, 1, 2 ]\n\n See Also\n --------\n maskArguments, reverseArguments\n","repeat":"\nrepeat( str, n )\n Repeats a string `n` times and returns the concatenated result.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of repetitions.\n\n Returns\n -------\n out: string\n Repeated string.\n\n Examples\n --------\n > var out = repeat( 'a', 5 )\n 'aaaaa'\n > out = repeat( '', 100 )\n ''\n > out = repeat( 'beep', 0 )\n ''\n\n See Also\n --------\n pad\n","replace":"\nreplace( str, search, newval )\n Replaces search occurrences with a replacement string.\n\n When provided a string as the search value, the function replaces *all*\n occurrences. To remove only the first match, use a regular expression.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string|RegExp\n Search expression.\n\n newval: string|Function\n Replacement value or function.\n\n Returns\n -------\n out: string\n String containing replacement(s).\n\n Examples\n --------\n // Standard usage:\n > var out = replace( 'beep', 'e', 'o' )\n 'boop'\n\n // Replacer function:\n > function replacer( match, p1 ) { return '/'+p1+'/'; };\n > var str = 'Oranges and lemons';\n > out = replace( str, /([^\\s]+)/gi, replacer )\n '/Oranges/ /and/ /lemons/'\n\n // Replace only first match:\n > out = replace( 'beep', /e/, 'o' )\n 'boep'\n\n","reRegExp":"\nreRegExp()\n Returns a regular expression to parse a regular expression string.\n\n Regular expression strings should be escaped.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reRegExp();\n > var bool = RE.test( '/^beep$/' )\n true\n > bool = RE.test( '/boop' )\n false\n\n // Escape regular expression strings:\n > bool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\n false\n > bool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n true\n\n\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n\n Examples\n --------\n > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n true\n > bool = reRegExp.REGEXP.test( '/boop' )\n false\n\n See Also\n --------\n reFromString\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n\n Examples\n --------\n > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n true\n > bool = reRegExp.REGEXP.test( '/boop' )\n false\n\n See Also\n --------\n reFromString","rescape":"\nrescape( str )\n Escapes a regular expression string.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: string\n Escaped string.\n\n Examples\n --------\n > var str = rescape( '[A-Z]*' )\n '\\\\[A\\\\-Z\\\\]\\\\*'\n\n","reSemVer":"\nreSemVer()\n Returns a regular expression to match a semantic version string.\n\n Returns\n -------\n out: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_SEMVER = reSemVer()\n \n > var bool = RE_SEMVER.test( '1.0.0' )\n true\n > bool = RE_SEMVER.test( '1.0.0-alpha.1' )\n true\n > bool = RE_SEMVER.test( 'abc' )\n false\n > bool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n true\n\n\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n\n Examples\n --------\n > var bool = reSemVer.REGEXP.test( '1.0.0' )\n true\n > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n false\n\n","reSemVer.REGEXP":"\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n\n Examples\n --------\n > var bool = reSemVer.REGEXP.test( '1.0.0' )\n true\n > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n false","resolveParentPath":"\nresolveParentPath( path[, options], clbk )\n Asynchronously resolves a path by walking parent directories.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPath( 'package.json', onPath );\n\n\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n See Also\n --------\n resolveParentPathBy\n","resolveParentPath.sync":"\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n See Also\n --------\n resolveParentPathBy","resolveParentPathBy":"\nresolveParentPathBy( path[, options], predicate, clbk )\n Asynchronously resolves a path according to a predicate function by walking\n parent directories.\n\n When invoked, the predicate function is provided two arguments:\n\n - `path`: a resolved path\n - `next`: a callback to be invoked after processing a resolved path\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided predicate function calls the `next` callback with a truthy\n `error` argument, the function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n the resolved path as the second argument.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function predicate( path, next ) {\n ... setTimeout( onTimeout, path );\n ... function onTimeout() {\n ... console.log( path );\n ... next( null, false );\n ... }\n ... };\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPathBy( 'package.json', predicate, onPath );\n\n\nresolveParentPathBy.sync( path[, options], predicate )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n\n The predicate function is provided one argument:\n\n - `path`: a resolved path\n\n The function immediately returns upon encountering a truthy return value.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > function predicate() { return false; };\n > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n See Also\n --------\n resolveParentPath\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path[, options], predicate )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n\n The predicate function is provided one argument:\n\n - `path`: a resolved path\n\n The function immediately returns upon encountering a truthy return value.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > function predicate() { return false; };\n > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n See Also\n --------\n resolveParentPath","reUncPath":"\nreUncPath()\n Return a regular expression to parse a UNC path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUncPath();\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\\\\\share';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\\\\\\\\\server\\\\share';\n > bool = RE.test( path )\n false\n > path = 'beep boop \\\\\\\\server\\\\share';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server';\n > bool = RE.test( path )\n false\n > path = '\\\\';\n > bool = RE.test( path )\n false\n > path = '';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\n > bool = RE.test( path )\n false\n > path = '//server/share';\n > bool = RE.test( path )\n false\n > path = '/foo/bar';\n > bool = RE.test( path )\n false\n > path = 'foo/bar';\n > bool = RE.test( path )\n false\n > path = './foo/bar';\n > bool = RE.test( path )\n false\n > path = '/foo/../bar';\n > bool = RE.test( path )\n false\n\n\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = reUncPath.REGEXP.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = reUncPath.REGEXP.test( path )\n true\n\n See Also\n --------\n isUNCPath\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = reUncPath.REGEXP.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = reUncPath.REGEXP.test( path )\n true\n\n See Also\n --------\n isUNCPath","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n Returns a regular expression to match a UTF-16 surrogate pair.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair();\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair.REGEXP;\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n See Also\n --------\n reUtf16UnpairedSurrogate","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair.REGEXP;\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n See Also\n --------\n reUtf16UnpairedSurrogate","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n Returns a regular expression to match an unpaired UTF-16 surrogate.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate();\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate.REGEXP;\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n See Also\n --------\n reUtf16SurrogatePair","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate.REGEXP;\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n See Also\n --------\n reUtf16SurrogatePair","reverseArguments":"\nreverseArguments( fcn[, thisArg] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reversed arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reverseArguments( foo );\n > var out = bar( 1, 2, 3 )\n [ 3, 2, 1 ]\n\n See Also\n --------\n maskArguments, reorderArguments\n","reverseString":"\nreverseString( str[, options] )\n Reverses a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to reverse. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Reversed string.\n\n Examples\n --------\n > var out = reverseString( 'foo' )\n 'oof'\n > out = reverseString( 'abcdef' )\n 'fedcba'\n\n","reviveBasePRNG":"\nreviveBasePRNG( key, value )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or PRNG.\n\n Examples\n --------\n > var str = JSON.stringify( base.random.mt19937 );\n > var r = parseJSON( str, reviveBasePRNG )\n \n\n","reviveBuffer":"\nreviveBuffer( key, value )\n Revives a JSON-serialized Buffer.\n\n The serialization format for a Buffer is an object having the following\n fields:\n\n - type: value type (Buffer)\n - data: buffer data as an array of integers\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or Buffer.\n\n Examples\n --------\n > var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\n > var buf = parseJSON( str, reviveBuffer )\n [ 5, 3 ]\n\n See Also\n --------\n buffer2json\n","reviveComplex":"\nreviveComplex( key, value )\n Revives a JSON-serialized complex number.\n\n The serialization format for complex numbers is an object having the\n following fields:\n\n - type: complex number type (e.g., \"Complex128\", \"Complex64\")\n - re: real component (number)\n - im: imaginary component (number)\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex )\n \n\n See Also\n --------\n Complex128, Complex64, reviveComplex128, reviveComplex64\n","reviveComplex64":"\nreviveComplex64( key, value )\n Revives a JSON-serialized 64-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex64 )\n \n\n See Also\n --------\n Complex64, reviveComplex128, reviveComplex\n","reviveComplex128":"\nreviveComplex128( key, value )\n Revives a JSON-serialized 128-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex128 )\n \n\n See Also\n --------\n Complex128, reviveComplex64, reviveComplex\n","reviveError":"\nreviveError( key, value )\n Revives a JSON-serialized error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or error object.\n\n Examples\n --------\n > var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\n > var err = JSON.parse( str, reviveError )\n \n\n See Also\n --------\n error2json\n","reviveRegExp":"\nreviveRegExp( key, value )\n Revives a JSON-serialized regular expression.\n\n The serialization format for a regular expression is an object having the\n following fields:\n\n - type: value type (RegExp)\n - pattern: regular expression pattern\n - flags: regular expression flags\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or regular expression.\n\n Examples\n --------\n > var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\n > var v = parseJSON( str, reviveRegExp )\n \n\n See Also\n --------\n regexp2json","reviveTypedArray":"\nreviveTypedArray( key, value )\n Revives a JSON-serialized typed array.\n\n The serialization format for typed array is an object having the following\n fields:\n\n - type: typed array type (e.g., \"Float64Array\", \"Int8Array\")\n - data: typed array data as an array of numbers\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or typed array.\n\n Examples\n --------\n > var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\n > var arr = parseJSON( str, reviveTypedArray )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n typedarray2json\n","reWhitespace":"\nreWhitespace( [options] )\n Returns a regular expression to match a white space character.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to wrap a regular expression matching a white\n space character with a capture group. Default: false.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reWhitespace();\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false\n\n\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP;\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false\n\n\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP_CAPTURE;\n > var str = 'Duplicate capture';\n > var out = replace( str, RE, '$1$1' )\n 'Duplicate capture'\n\n See Also\n --------\n isWhitespace","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP;\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP_CAPTURE;\n > var str = 'Duplicate capture';\n > var out = replace( str, RE, '$1$1' )\n 'Duplicate capture'\n\n See Also\n --------\n isWhitespace","rpad":"\nrpad( str, len[, pad] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = rpad( 'a', 5 )\n 'a '\n > out = rpad( 'beep', 10, 'p' )\n 'beeppppppp'\n > out = rpad( 'beep', 12, 'boop' )\n 'beepboopboop'\n\n See Also\n --------\n lpad, pad\n","rtrim":"\nrtrim( str )\n Trims whitespace from the end of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n ' \\t\\t\\n Beep'\n\n See Also\n --------\n ltrim, trim\n","safeintmax":"\nsafeintmax( dtype )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: integer\n Maximum safe integer.\n\n Examples\n --------\n > var m = safeintmax( 'float16' )\n 2047\n > m = safeintmax( 'float32' )\n 16777215\n\n See Also\n --------\n safeintmin, realmax, typemax\n","safeintmin":"\nsafeintmin( dtype )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: integer\n Minimum safe integer.\n\n Examples\n --------\n > var m = safeintmin( 'float16' )\n -2047\n > m = safeintmin( 'float32' )\n -16777215\n\n See Also\n --------\n safeintmax, realmin, typemin\n","sample":"\nsample( x[, options] )\n Samples elements from an array-like object.\n\n Parameters\n ----------\n x: ArrayLike\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.size: integer (optional)\n Sample size. By default, the function returns an array having the same\n length as `x`. Specify the `size` option to generate a sample of a\n different size.\n\n options.probs: Array (optional)\n Element probabilities. By default, the probability of sampling an\n element is the same for all elements. To assign elements different\n probabilities, set the `probs` option. The `probs` option must be a\n numeric array consisting of nonnegative values which sum to one. When\n sampling without replacement, note that the `probs` option denotes the\n initial element probabilities which are then updated after each draw.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. If the `replace`\n option is set to `false`, the `size` option cannot be an integer larger\n than the number of elements in `x`. Default: `true`.\n\n Returns\n -------\n out: Array\n Sample.\n\n Examples\n --------\n > var out = sample( 'abc' )\n e.g., [ 'a', 'a', 'b' ]\n > out = sample( [ 3, 6, 9 ] )\n e.g., [ 3, 9, 6 ]\n > var bool = ( out.length === 3 )\n true\n\n > out = sample( [ 3, null, NaN, 'abc', function(){} ] )\n e.g., [ 3, 'abc', null, 3, null ]\n\n // Set sample size:\n > out = sample( [ 3, 6, 9 ], { 'size': 10 } )\n e.g., [ 6, 3, 9, 9, 9, 6, 9, 6, 9, 3 ]\n > out = sample( [ 0, 1 ], { 'size': 20 } )\n e.g., [ 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0 ]\n\n // Draw without replacement:\n > out = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\n e.g., [ 6, 1, 5 ]\n > out = sample( [ 0, 1 ], { 'replace': false } )\n e.g., [ 0, 1 ]\n\n // Assigning non-uniform element probabilities:\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\n > out = sample( x, { 'probs': probs } )\n e.g., [ 5, 6, 6, 5, 6, 4 ]\n > out = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n e.g., [ 6, 4, 1 ]\n\n\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 } );\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]\n\n","sample.factory":"\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 } );\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FIN()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FR()\n [ 'a', 'à', 'â', 'abord', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_GER()\n [ 'a', 'ab', 'aber', 'ach', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_IT()\n [ 'a', 'abbastanza', 'accidenti', 'ad', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_POR()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SP()\n [ 'a', 'acuerdo', 'adelante', 'ademas', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SWE()\n [ 'aderton', 'adertonde', 'adjö', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","scalar2array":"\nscalar2array( value[, dtype] )\n Returns a single-element array containing a provided scalar value.\n\n If `value` is a number and `dtype` is a complex number data type, the\n function returns a complex number array containing a complex number whose\n real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n dtype: string (optional)\n Data type. If not provided and `value`\n\n - is a number, the default data type is the default real-valued\n floating-point data type.\n - is a complex number object of a known complex data type, the data type\n is the same as the provided value.\n - is a complex number object of an unknown data type, the default data\n type is the default complex-valued floating-point data type.\n - is any other value type, the default data type is 'generic'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = scalar2array( 1.0 )\n [ 1.0 ]\n\n See Also\n --------\n iterator2array\n","scalar2ndarray":"\nscalar2ndarray( value[, options] )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n\n If `value` is a number and `options.dtype` is a complex number data type,\n the function returns a zero-dimensional ndarray containing a complex number\n whose real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Data type. If not provided and `value`\n\n - is a number, the default data type is the default real-valued\n floating-point data type.\n - is a complex number object of a known complex data type, the data type\n is the same as the provided value.\n - is a complex number object of an unknown data type, the default data\n type is the default complex-valued floating-point data type.\n - is any other value type, the default data type is 'generic'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = scalar2ndarray( 1.0 )\n \n > var sh = x.shape\n []\n > var dt = x.dtype\n 'float64'\n > var v = x.get()\n 1.0\n\n See Also\n --------\n array, ndarray\n","sdot":"\nsdot( x, y )\n Computes the dot product of two single-precision floating-point vectors.\n\n If provided empty vectors, the function returns `0.0`.\n\n Parameters\n ----------\n x: ndarray\n First input array whose underlying data type is 'float32'.\n\n y: ndarray\n Second input array whose underlying data type is 'float32'.\n\n Returns\n -------\n dot: number\n The dot product.\n\n Examples\n --------\n > var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > sdot( x, y )\n -5.0\n\n See Also\n --------\n base.strided.sdot, ddot, gdot\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n Number of seconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var secs = days * SECONDS_IN_DAY\n 271296\n\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var secs = hrs * SECONDS_IN_HOUR\n 11304\n\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var secs = mins * SECONDS_IN_MINUTE\n 188.4\n\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n Number of seconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var secs = wks * SECONDS_IN_WEEK\n 1899072\n\n","secondsInMonth":"\nsecondsInMonth( [month[, year]] )\n Returns the number of seconds in a month.\n\n By default, the function returns the number of seconds in the current month\n of the current year (according to local time). To determine the number of\n seconds for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Seconds in a month.\n\n Examples\n --------\n > var num = secondsInMonth()\n \n > num = secondsInMonth( 2 )\n \n > num = secondsInMonth( 2, 2016 )\n 2505600\n > num = secondsInMonth( 2, 2017 )\n 2419200\n\n // Other ways to supply month:\n > num = secondsInMonth( 'feb', 2016 )\n 2505600\n > num = secondsInMonth( 'february', 2016 )\n 2505600\n\n See Also\n --------\n secondsInYear\n","secondsInYear":"\nsecondsInYear( [value] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n\n By default, the function returns the number of seconds in the current year\n (according to local time). To determine the number of seconds for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of seconds in a year.\n\n Examples\n --------\n > var num = secondsInYear()\n \n > num = secondsInYear( 2016 )\n 31622400\n > num = secondsInYear( 2017 )\n 31536000\n\n See Also\n --------\n secondsInMonth\n","seq2slice":"\nseq2slice( str, len, strict )\n Converts a subsequence string to a Slice object.\n\n A subsequence string has the following format:\n\n ::\n\n If an increment is not specified, the default increment is one. An increment\n of zero is not allowed.\n\n The start index is inclusive.\n\n The stop index is exclusive.\n\n Both start and stop indices are optional. If not provided, the start and\n stop indices default to index extremes. Which extremes correspond to which\n index depends on whether the increment is positive or negative.\n\n Both start and stop indices can be negative; in which case, the\n corresponding index is resolved by subtracting the respective value from the\n provided length.\n\n Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n 'end-3:', etc), which supports basic subtraction and division.\n\n The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n exception is when performing a division operation when the increment is less\n than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n user expectations when 'end/d' equals a whole number and slicing from right-\n to-left. The result from a division operation is rounded down to the nearest\n integer value.\n\n In non-strict mode, the resolved slice start is clamped to the slice index\n bounds [0, len).\n\n In non-strict mode, Tte resolved slice end is upper bound clamped to the\n provided length (i.e., one greater than the last possible index).\n\n When the increment is negative, the resolved slice end value may be `null`,\n thus indicating that a non-empty slice should include the first index.\n\n The function ensures that results satisfy the convention that ':n' combined\n with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n When the provided length is zero, the function always returns a slice object\n equivalent to '0:0:'.\n\n Parameters\n ----------\n str: string\n Subsequence string.\n\n len: integer\n Maximum number of elements allowed in the slice.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new seq2slice( '1:10', 10, false );\n > s.start\n 1\n > s.stop\n 10\n > s.step\n 1\n > s = new seq2slice( '2:5:2', 10, false );\n > s.start\n 2\n > s.stop\n 5\n > s.step\n 2\n\n See Also\n --------\n Slice\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj, prop, value )\n Defines a configurable read-only property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setConfigurableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setReadOnly\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n Defines a configurable read-only accessor.\n\n Configurable read-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadWriteAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadOnlyAccessor\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj, prop, getter, setter )\n Defines a configurable property having read-write accessors.\n\n Configurable read-write accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadWriteAccessor\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n Defines a configurable write-only accessor.\n\n Configurable write-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setWriteOnlyAccessor\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj, prop, fcn )\n Defines a configurable memoized read-only object property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedConfigurableReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setMemoizedReadOnly, setReadOnly\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj, prop, fcn )\n Defines a memoized read-only object property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n See Also\n --------\n defineMemoizedProperty, setReadOnly\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj, prop, value )\n Defines a non-enumerable property.\n\n Non-enumerable properties are writable and configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableProperty( obj, 'foo', 'bar' );\n > obj.foo\n 'bar'\n > objectKeys( obj )\n []\n\n See Also\n --------\n setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj, prop, value )\n Defines a non-enumerable read-only property.\n\n Non-enumerable read-only properties are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n Defines a non-enumerable read-only accessor.\n\n Non-enumerable read-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnlyAccessor\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj, prop, getter, setter )\n Defines a non-enumerable property having read-write accessors.\n\n Non-enumerable read-write accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableWriteOnlyAccessor, setReadWriteAccessor\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj, prop, setter )\n Defines a non-enumerable write-only accessor.\n\n Non-enumerable write-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnly":"\nsetReadOnly( obj, prop, value )\n Defines a read-only property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setReadOnlyAccessor, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj, prop, getter )\n Defines a read-only accessor.\n\n Read-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj, prop, getter, setter )\n Defines a property having read-write accessors.\n\n Read-write accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setWriteOnlyAccessor\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj, prop, setter )\n Defines a write-only accessor.\n\n Write-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setReadWriteAccessor\n","SharedArrayBuffer":"\nSharedArrayBuffer( size )\n Returns a shared array buffer having a specified number of bytes.\n\n A shared array buffer behaves similarly to a non-shared array buffer, except\n that a shared array buffer allows creating views of memory shared between\n threads.\n\n Buffer contents are initialized to 0.\n\n If an environment does not support shared array buffers, the function throws\n an error.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: SharedArrayBuffer\n A shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 )\n \n\n\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1\n\n\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","shift":"\nshift( collection )\n Removes and returns the first element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = shift( arr )\n [ [ 2.0, 3.0, 4.0, 5.0 ], 1.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = shift( arr )\n [ [ 2.0 ], 1.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = shift( arr )\n [ { 'length': 1, '0': 2.0 }, 1.0 ]\n\n See Also\n --------\n pop, push, unshift\n","shuffle":"\nshuffle( arr[, options] )\n Shuffles elements of an array-like object.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object to shuffle.\n\n options: Object (optional)\n Options.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n out: ArrayLike\n Shuffled array-like object.\n\n Examples\n --------\n > var data = [ 1, 2, 3 ];\n > var out = shuffle( data )\n e.g., [ 3, 1, 2 ]\n > out = shuffle( data, { 'copy': 'none' } );\n > var bool = ( data === out )\n true\n\n\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' } );\n > bool = ( arr === out )\n false\n\n See Also\n --------\n sample\n","shuffle.factory":"\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' } );\n > bool = ( arr === out )\n false\n\n See Also\n --------\n sample","sizeOf":"\nsizeOf( dtype )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - complex128: 128-bit complex numbers\n - complex64: 64-bit complex numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Size (in bytes).\n\n Examples\n --------\n > var s = sizeOf( 'int8' )\n 1\n > s = sizeOf( 'uint32' )\n 4\n\n See Also\n --------\n realmax, typemax\n","Slice":"\nSlice( [stop] )\n Returns a Slice.\n\n Parameters\n ----------\n stop: integer|null|undefined (optional)\n Ending index (exclusive).\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new Slice();\n > s = new Slice( 10 );\n\n\nSlice( start, stop[, step] )\n Returns a Slice.\n\n Parameters\n ----------\n start: integer|null|undefined\n Starting index (inclusive).\n\n stop: integer|null|undefined\n Ending index (exclusive).\n\n step: integer|null|undefined (optional)\n Index increment. A numeric index increment argument should be a non-zero\n integer value. Default: null.\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > s = new Slice( 2, 10, 1 );\n\n\nSlice.prototype.start\n Read-only property returning the starting slice index.\n\n Returns\n -------\n start: integer|null\n Starting index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.start\n null\n > s = new Slice( 2, 10 );\n > s.start\n 2\n\n\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n\n Returns\n -------\n stop: integer|null\n Ending index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.stop\n 10\n > s = new Slice( 2, 10 );\n > s.stop\n 10\n\n\nSlice.prototype.step\n Read-only property returning the index increment.\n\n Returns\n -------\n step: integer|null\n Index increment.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.step\n null\n > s = new Slice( 2, 10 );\n > s.step\n null\n > s = new Slice( 2, 10, 1 );\n > s.step\n 1\n\n\nSlice.prototype.toString()\n Serializes a Slice as a string.\n\n Returns\n -------\n str: string\n Serialized Slice string.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toString()\n 'Slice(null,10,null)'\n > s = new Slice( 2, 10, 1 );\n > s.toString()\n 'Slice(2,10,1)'\n\n\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ null, 10, null ] }\n > s = new Slice( 2, 10, 1 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n See Also\n --------\n ndarray, MultiSlice\n","Slice.prototype.start":"\nSlice.prototype.start\n Read-only property returning the starting slice index.\n\n Returns\n -------\n start: integer|null\n Starting index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.start\n null\n > s = new Slice( 2, 10 );\n > s.start\n 2","Slice.prototype.stop":"\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n\n Returns\n -------\n stop: integer|null\n Ending index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.stop\n 10\n > s = new Slice( 2, 10 );\n > s.stop\n 10","Slice.prototype.step":"\nSlice.prototype.step\n Read-only property returning the index increment.\n\n Returns\n -------\n step: integer|null\n Index increment.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.step\n null\n > s = new Slice( 2, 10 );\n > s.step\n null\n > s = new Slice( 2, 10, 1 );\n > s.step\n 1","Slice.prototype.toString":"\nSlice.prototype.toString()\n Serializes a Slice as a string.\n\n Returns\n -------\n str: string\n Serialized Slice string.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toString()\n 'Slice(null,10,null)'\n > s = new Slice( 2, 10, 1 );\n > s.toString()\n 'Slice(2,10,1)'","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ null, 10, null ] }\n > s = new Slice( 2, 10, 1 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n See Also\n --------\n ndarray, MultiSlice","snakecase":"\nsnakecase( str )\n Converts a string to snake case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Snake-cased string.\n\n Examples\n --------\n > var out = snakecase( 'Hello World!' )\n 'hello_world'\n > out = snakecase( 'I am a tiny little teapot' )\n 'i_am_a_tiny_little_teapot'\n\n See Also\n --------\n camelcase, constantcase, kebabcase, pascalcase","some":"\nsome( collection, n )\n Tests whether at least `n` elements in a collection are truthy.\n\n The function immediately returns upon finding `n` truthy elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 1, 2, 3 ];\n > var bool = some( arr, 3 )\n true\n\n See Also\n --------\n any, every, forEach, none, someBy\n","someBy":"\nsomeBy( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, -3, 4, -1 ];\n > var bool = someBy( arr, 2, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, noneBy, someByAsync, someByRight\n","someByAsync":"\nsomeByAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync\n","someByAsync.factory":"\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync","someByRight":"\nsomeByRight( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, -2, 3, 4 ];\n > var bool = someByRight( arr, 2, negative )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, noneByRight, someBy, someByRightAsync\n","someByRightAsync":"\nsomeByRightAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight","SOTU":"\nSOTU( [options] )\n Returns State of the Union (SOTU) addresses.\n\n Each State of the Union address is represented by an object with the\n following fields:\n\n - year: speech year\n - name: President name\n - party: the President's political party\n - text: speech text\n\n The following political parties are recognized:\n\n - Democratic\n - Republican\n - Democratic-Republican\n - Federalist\n - National Union\n - Whig\n - Whig & Democratic\n - none\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.name: String|Array (optional)\n President name(s).\n\n options.party: String|Array (optional)\n Political party (or parties).\n\n options.year: integer|Array (optional)\n Year(s).\n\n options.range: Array (optional)\n Two-element array specifying a year range.\n\n Returns\n -------\n out: Array\n State of the Union addresses.\n\n Examples\n --------\n > var out = SOTU()\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more Presidents...\n > var opts = { 'name': 'Barack Obama' };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more political parties...\n > opts = { 'party': [ 'Democratic', 'Federalist' ] };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses from one or more years...\n > opts = { 'year': [ 2008, 2009, 2011 ] };\n > out = SOTU( opts )\n [ {...}, {...}, {...} ]\n\n // Retrieve addresses from a range of consecutive years...\n > opts = { 'range': [ 2008, 2016 ] }\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n\n Returns\n -------\n out: Array\n List of simple American-English words.\n\n Examples\n --------\n > var list = SPACHE_REVISED()\n [ 'a', 'able', 'about', 'above', ... ]\n\n References\n ----------\n - Spache, George. 1953. \"A New Readability Formula for Primary-Grade Reading\n Materials.\" *The Elementary School Journal* 53 (7): 410–13. doi:10.1086/\n 458513.\n - Klare, George R. 1974. \"Assessing Readability.\" *Reading Research\n Quarterly* 10 (1). Wiley, International Reading Association: 62–102.\n .\n - Stone, Clarence R. 1956. \"Measuring Difficulty of Primary Reading\n Material: A Constructive Criticism of Spache's Measure.\" *The Elementary\n School Journal* 57 (1). University of Chicago Press: 36–41.\n .\n - Perera, Katherine. 2012. \"The assessment of linguistic difficulty in\n reading material.\" In *Linguistics and the Teacher*, edited by Ronald\n Carter, 101–13. Routledge Library Editions: Education. Taylor & Francis.\n .\n\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n\n Each array element has the following fields:\n\n - id: message id (relative to message group)\n - group: message group\n - checksum: object containing checksum info\n - text: message text (including headers)\n\n The message group may be one of the following:\n\n - easy-ham-1: easier to detect non-spam e-mails (2500 messages)\n - easy-ham-2: easier to detect non-spam e-mails collected at a later date\n (1400 messages)\n - hard-ham-1: harder to detect non-spam e-mails (250 messages)\n - spam-1: spam e-mails (500 messages)\n - spam-2: spam e-mails collected at a later date (1396 messages)\n\n The checksum object contains the following fields:\n\n - type: checksum type (e.g., MD5)\n - value: checksum value\n\n Returns\n -------\n out: Array\n Corpus.\n\n Examples\n --------\n > var data = SPAM_ASSASSIN()\n [ {...}, {...}, ... ]\n\n","SparklineBase":"\nSparklineBase( [data,] [options] )\n Returns a Sparkline instance.\n\n This constructor is a base Sparkline constructor from which constructors\n tailored to generating particular types of Sparkline graphics should be\n derived.\n\n At a minimum, descendants should implement a private `_render()` method\n which will be automatically invoked by the public `render()` method.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options.description: string (optional)\n Sparkline description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n sparkline: Sparkline\n Sparkline instance.\n\n sparkline.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n sparkline.bufferSize\n Data buffer size.\n\n sparkline.description\n Sparkline description.\n\n sparkline.data\n Sparkline data.\n\n sparkline.label\n Data label.\n\n sparkline.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n sparkline.render()\n Renders a sparkline. This method calls `_render()` which must be\n implemented by instances and child classes. The default behavior is\n throw an error.\n\n Examples\n --------\n > var sparkline = new SparklineBase()\n \n\n // Provide sparkline data at instantiation:\n > var data = [ 1, 2, 3 ];\n > sparkline = new SparklineBase( data )\n \n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","sparsearray2iterator":"\nsparsearray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iterator( [ 1, , 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, sparsearray2iteratorRight\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, sparsearray2iterator\n","splitStream":"\nsplitStream( [options] )\n Returns a transform stream which splits streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream.Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = splitStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\\nb\\c' );\n > s.end();\n\n See Also\n --------\n joinStream\n","splitStream.factory":"\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();","splitStream.objectMode":"\nsplitStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\\nb\\c' );\n > s.end();\n\n See Also\n --------\n joinStream","SQRT_EPS":"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n\n Examples\n --------\n > SQRT_EPS\n 0.14901161193847656e-7\n\n See Also\n --------\n EPS\n","SQRT_HALF":"\nSQRT_HALF\n Square root of `1/2`.\n\n Examples\n --------\n > SQRT_HALF\n 0.7071067811865476\n\n See Also\n --------\n LN_HALF\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n\n Examples\n --------\n > SQRT_HALF_PI\n 1.2533141373155003\n\n See Also\n --------\n PI\n","SQRT_PHI":"\nSQRT_PHI\n Square root of the golden ratio.\n\n Examples\n --------\n > SQRT_PHI\n 1.272019649514069\n\n See Also\n --------\n PHI\n","SQRT_PI":"\nSQRT_PI\n Square root of the mathematical constant `π`.\n\n Examples\n --------\n > SQRT_PI\n 1.7724538509055160\n\n See Also\n --------\n PI\n","SQRT_THREE":"\nSQRT_THREE\n Square root of `3`.\n\n Examples\n --------\n > SQRT_THREE\n 1.7320508075688772\n\n","SQRT_TWO":"\nSQRT_TWO\n Square root of `2`.\n\n Examples\n --------\n > SQRT_TWO\n 1.4142135623730951\n\n See Also\n --------\n LN2\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n\n Examples\n --------\n > SQRT_TWO_PI\n 2.5066282746310007\n\n See Also\n --------\n TWO_PI\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n Returns US birth data from 2000 to 2014, as provided by the Social Security\n Administration.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = SSA_US_BIRTHS_2000_2014()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1969_1988, CDC_NCHS_US_BIRTHS_1994_2003\n","sswap":"\nsswap( x, y )\n Interchanges two single-precision floating-point vectors.\n\n Parameters\n ----------\n x: ndarray\n First input array whose underlying data type is 'float32'.\n\n y: ndarray\n Second input array whose underlying data type is 'float32'.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n > var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > sswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.sswap, dswap, gswap\n","Stack":"\nStack()\n Stack constructor.\n\n A stack is also referred to as a \"last-in-first-out\" queue.\n\n Returns\n -------\n stack: Object\n Stack data structure.\n\n stack.clear: Function\n Clears the stack.\n\n stack.first: Function\n Returns the \"newest\" stack value (i.e., the value which is \"first-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.iterator: Function\n Returns an iterator for iterating over a stack. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from stack mutation during\n iteration, a returned iterator **always** iterates over a stack\n \"snapshot\", which is defined as the list of stack elements at the time\n of the method's invocation.\n\n stack.last: Function\n Returns the \"oldest\" stack value (i.e., the value which is \"last-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.length: integer\n Stack length.\n\n stack.pop: Function\n Removes and returns the current \"first-out\" value from the stack. If the\n stack is empty, the returned value is `undefined`.\n\n stack.push: Function\n Adds a value to the stack.\n\n stack.toArray: Function\n Returns an array of stack values.\n\n stack.toJSON: Function\n Serializes a stack as JSON.\n\n Examples\n --------\n > var s = Stack();\n > s.push( 'foo' ).push( 'bar' );\n > s.length\n 2\n > s.pop()\n 'bar'\n > s.length\n 1\n > s.pop()\n 'foo'\n > s.length\n 0\n\n See Also\n --------\n FIFO\n","standalone2pkg":"\nstandalone2pkg( pkg )\n Returns the internal package name associated with a provided standalone\n package name.\n\n Parameters\n ----------\n pkg: string\n Standalone package name.\n\n Returns\n -------\n out: string|null\n Internal package name.\n\n Examples\n --------\n > var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n alias2standalone, pkg2alias, pkg2standalone\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n Returns a string array containing two or three letter abbreviations for each\n card in a standard 52-card deck.\n\n Abbreviation format: \n\n Cards: A, 2, 3, 4, 5, 6, 7, 8, 9, 10, J, Q, K, where\n\n - A: ace\n - J: jack\n - Q: queen\n - K: king\n\n Suit abbreviations:\n\n - C: clubs\n - D: diamonds\n - H: hearts\n - S: spades\n\n Returns\n -------\n out: Array\n List of cards.\n\n Examples\n --------\n > var list = STANDARD_CARD_DECK()\n [ 'AC', '2C', '3C', ... ]\n\n","startcase":"\nstartcase( str )\n Capitalizes the first letter of each word in an input string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String containing words where each first letter is capitalized.\n\n Examples\n --------\n > var out = startcase( 'beep boop' )\n 'Beep Boop'\n\n See Also\n --------\n lowercase, uppercase\n","startsWith":"\nstartsWith( str, search[, position] )\n Tests if a string starts with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n position: integer (optional)\n Position at which to start searching for `search`. If less than `0`, the\n start position is determined relative to the end of the input string.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string starts with the characters of\n another string.\n\n Examples\n --------\n > var bool = startsWith( 'Beep', 'Be' )\n true\n > bool = startsWith( 'Beep', 'ep' )\n false\n > bool = startsWith( 'Beep', 'ee', 1 )\n true\n > bool = startsWith( 'Beep', 'ee', -3 )\n true\n > bool = startsWith( 'Beep', '' )\n true\n\n See Also\n --------\n endsWith\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n Returns a list of English stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = STOPWORDS_EN()\n [ 'a', 'about', 'above', 'across', ... ]\n\n","strided.abs":"\nstrided.abs( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs( 2, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs","strided.abs2":"\nstrided.abs2( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 9.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs2\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs2","strided.abs2By":"\nstrided.abs2By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element\n - idx: iteration index\n - xi: strided index (offsetX + idx*sx)\n - yi: strided index (offsetY + idx*sy)\n - x: the input array\n - y: the destination array\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By( x.length, x, 1, y, 1, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By( 2, x, 2, y, -1, clbk )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs2By( 2, x1, -2, y1, 1, clbk )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = [ -1.0, -2.0, -3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.absBy, strided.abs2\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = [ -1.0, -2.0, -3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.absBy, strided.abs2","strided.absBy":"\nstrided.absBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element\n - idx: iteration index\n - xi: strided index (offsetX + idx*sx)\n - yi: strided index (offsetY + idx*sy)\n - x: the input array\n - y: the destination array\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy( x.length, x, 1, y, 1, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy( 2, x, 2, y, -1, clbk )\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.absBy( 2, x1, -2, y1, 1, clbk )\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n strided.abs, strided.abs2By\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n strided.abs, strided.abs2By","strided.add":"\nstrided.add( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ 1.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -2.0, 5.0 ]\n > z0\n [ 0.0, 0.0, -2.0, 5.0 ]\n\n\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 5.0, -2.0, 0.0 ]\n\n See Also\n --------\n strided.mul, strided.sub\n","strided.add.ndarray":"\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 5.0, -2.0, 0.0 ]\n\n See Also\n --------\n strided.mul, strided.sub","strided.cbrt":"\nstrided.cbrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.scbrt, strided.sqrt\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.scbrt, strided.sqrt","strided.ceil":"\nstrided.ceil( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil","strided.deg2rad":"\nstrided.deg2rad( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~1.571, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.sdeg2rad\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.sdeg2rad","strided.dataTypes":"\nstrided.dataTypes()\n Returns a list of strided array data types.\n\n The output array contains the following data types:\n\n - binary: binary.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of strided array data types.\n\n Examples\n --------\n > var out = strided.dataTypes()\n \n\n","strided.dispatch":"\nstrided.dispatch( fcns, types, data, nargs, nin, nout )\n Returns a strided array function interface which performs multiple dispatch.\n\n Without offsets, a strided array function interface has the following\n signature:\n\n f( N, dtypeX, x, strideX, dtypeY, y, strideY, ... )\n\n where\n\n - N: number of indexed elements.\n - dtypeX: data type for `x`.\n - x: strided array.\n - strideX: index increment for `x`.\n - dtypeY: data type for `y`.\n - y: strided array.\n - strideY: index increment for `y`.\n - ...: additional strided arrays, data types, and associated strides.\n\n The number of parameters is derived from `nargs`, the number of input\n strided arrays is derived from `nin`, and the number of output strided\n arrays is derived from `nout`.\n\n Without offsets, the number of parameters must obey the following relation:\n\n nargs = 3*(nout+nin) + 1\n\n With offsets, the number of parameters must obey the following relation:\n\n nargs = 4*(nout+nin) + 1\n\n With offsets, a strided array function interface has the following\n signature:\n\n f( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY, ... )\n\n where\n\n - N: number of indexed elements.\n - dtypeX: data type for `x`.\n - x: strided array.\n - strideX: index increment for `x`.\n - offsetX: starting index for `x`.\n - dtypeY: data type for `y`.\n - y: strided array.\n - strideY: index increment for `y`.\n - offsetY: starting index for `y`.\n - ...: additional strided arrays and associated data types, strides, and\n offsets.\n\n The choice of which strided array function interface to return depends on\n the use case. The former is suitable for typed array views; while the latter\n affords alternative indexing semantics more suitable for n-dimensional\n arrays (ndarrays).\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of strided array functions. Without offsets, a strided array\n function should have the following signature:\n\n f( arrays, shape, strides, data )\n\n where\n\n - arrays: array containing strided input and output arrays.\n - shape: array containing a single element, the number of indexed\n elements.\n - strides: array containing the stride lengths for the strided input and\n output arrays.\n - data: strided array function data (e.g., a callback).\n\n With offsets, a strided array function should have the following\n signature:\n\n f( arrays, shape, strides, offsets, data )\n\n where\n\n - offsets: array containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n For convenience, a single strided array function may be provided which\n will be invoked whenever the strided array argument data types match a\n sequence of types in `types`. Providing a single strided array function\n is particularly convenient for the case where, regardless of array data\n types, traversing arrays remains the same, but the strided array\n function `data` differs (e.g., callbacks which differ based on the array\n data types).\n\n types: ArrayLikeObject\n One-dimensional list of strided array argument data types.\n\n data: ArrayLikeObject|null\n Strided array function data (e.g., callbacks). If `null`, a returned\n strided array function interface does **not** provide a `data` argument\n to an invoked strided array function.\n\n nargs: integer\n Total number of strided array function interface arguments (including\n data types, strides, and offsets).\n\n nin: integer\n Number of input strided arrays.\n\n nout: integer\n Number of output strided arrays.\n\n Returns\n -------\n fcn: Function\n Strided array function interface.\n\n Examples\n --------\n // Define strided array argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of strided array function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create a strided array function interface for applying unary callbacks:\n > var f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\n\n // Create an input strided array:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value:\n > f( x.length, 'float64', x, 1, 'float64', y, 1 );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Create a strided array function interface supporting offsets:\n > f = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\n\n // Create an input strided array:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value starting from the third element:\n > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\n > y\n [ 0.0, 0.0, 3.0, 4.0 ]\n\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns, types, data, nargs, nin, nout )\n Returns a strided array function interface which accepts a callback function\n and performs multiple dispatch.\n\n Without offsets, a strided array function interface has the following\n signature:\n\n f( N, dx, x, sx, dy, y, sy, ..., clbk[, thisArg] )\n\n where\n\n - N: number of indexed elements.\n - dx: data type for `x`.\n - x: strided array.\n - sx: index increment for `x`.\n - dy: data type for `y`.\n - y: strided array.\n - sy: index increment for `y`.\n - ...: additional strided arrays, data types, and associated strides.\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n The number of parameters is derived from `nargs`, the number of input\n strided arrays is derived from `nin`, and the number of output strided\n arrays is derived from `nout`.\n\n Without offsets, the number of parameters must obey the following relation:\n\n nargs = 3*(nout+nin) + 2\n\n With offsets, the number of parameters must obey the following relation:\n\n nargs = 4*(nout+nin) + 2\n\n With offsets, a strided array function interface has the following\n signature:\n\n f( N, dx, x, sx, ox, dy, y, sy, oy, ..., clbk[, thisArg] )\n\n where\n\n - N: number of indexed elements.\n - dx: data type for `x`.\n - x: strided array.\n - sx: index increment for `x`.\n - ox: starting index for `x`.\n - dy: data type for `y`.\n - y: strided array.\n - sy: index increment for `y`.\n - oy: starting index for `y`.\n - ...: additional strided arrays and associated data types, strides, and\n offsets.\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n The choice of which strided array function interface to return depends on\n the use case. The former is suitable for typed array views; while the latter\n affords alternative indexing semantics more suitable for n-dimensional\n arrays (ndarrays).\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of strided array functions. Without offsets, a strided array\n function should have the following signature:\n\n f( arrays, shape, strides, data, clbk, thisArg )\n\n where\n\n - arrays: array containing strided input and output arrays.\n - shape: array containing a single element, the number of indexed\n elements.\n - strides: array containing the stride lengths for the strided input and\n output arrays.\n - data: strided array function data (e.g., a callback).\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n With offsets, a strided array function should have the following\n signature:\n\n f( arrays, shape, strides, offsets, data, clbk, thisArg )\n\n where\n\n - offsets: array containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n For convenience, a single strided array function may be provided which\n will be invoked whenever the strided array argument data types match a\n sequence of types in `types`. Providing a single strided array function\n is particularly convenient for the case where, regardless of array data\n types, traversing arrays remains the same, but the strided array\n function `data` differs (e.g., callbacks which differ based on the array\n data types).\n\n types: ArrayLikeObject\n One-dimensional list of strided array argument data types.\n\n data: ArrayLikeObject|null\n Strided array function data (e.g., callbacks). If `null`, a returned\n strided array function interface does **not** provide a `data` argument\n to an invoked strided array function.\n\n nargs: integer\n Total number of strided array function interface arguments (including\n data types, strides, offsets, and the callback function).\n\n nin: integer\n Number of input strided arrays.\n\n nout: integer\n Number of output strided arrays.\n\n Returns\n -------\n fcn: Function\n Strided array function interface.\n\n Examples\n --------\n // Define strided array argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of strided array function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create a strided array function interface for applying unary callbacks:\n > var f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\n\n // Create an input strided array:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value:\n > f( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Create a strided array function interface supporting offsets:\n > f = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\n\n // Create an input strided array:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value starting from the third element:\n > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\n > y\n [ 0.0, 0.0, 3.0, 4.0 ]\n\n See Also\n --------\n strided.dispatch\n","strided.floor":"\nstrided.floor( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -4.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor","strided.inv":"\nstrided.inv( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 0.5, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.sinv\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.sinv","strided.mul":"\nstrided.mul( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ -6.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -15.0, 4.0 ]\n > z0\n [ 0.0, 0.0, -15.0, 4.0 ]\n\n\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 4.0, -15.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.sub\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 4.0, -15.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.sub","strided.ramp":"\nstrided.ramp( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.sramp\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.sramp","strided.rsqrt":"\nstrided.rsqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ ~0.333, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.sqrt, base.strided.srsqrt\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.sqrt, base.strided.srsqrt","strided.sqrt":"\nstrided.sqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt","strided.sub":"\nstrided.sub( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ -5.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -8.0, -3.0 ]\n > z0\n [ 0.0, 0.0, -8.0, -3.0 ]\n\n\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, -3.0, -8.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.mul\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, -3.0, -8.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.mul","strided.trunc":"\nstrided.trunc( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc","stridedarray2iterator":"\nstridedarray2iterator( N, src, stride, offset[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n N: integer\n Number of values to iterate.\n\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iterator\n","stridedArrayStream":"\nstridedArrayStream( N, buffer, stride, offset[, options] )\n Creates a readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );\n\n\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream","string2buffer":"\nstring2buffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = string2buffer( 'beep boop' )\n \n > b = string2buffer( '7468697320697320612074c3a97374', 'hex' );\n > b.toString()\n 'this is a tést'\n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer\n","sub2ind":"\nsub2ind( shape, ...subscript[, options] )\n Converts subscripts to a linear index.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n subscript: ...integer\n Subscripts.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string|Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If\n equal to 'throw', the function throws an error when a subscript exceeds\n array dimensions. If equal to 'normalize', the function normalizes\n negative subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', the function wraps around subscripts\n exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', the function sets subscripts exceeding array dimensions to\n either `0` (minimum index) or the maximum index along a particular\n dimension. If provided a mode array, each array element specifies the\n mode for a corresponding array dimension. If provided fewer modes than\n dimensions, the function recycles modes using modulo arithmetic.\n Default: [ 'throw' ].\n\n Returns\n -------\n idx: integer\n Linear index.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var idx = sub2ind( d, 1, 2, 2 )\n 17\n\n See Also\n --------\n array, ndarray, ind2sub\n","substringAfter":"\nsubstringAfter( str, search[, fromIndex] )\n Returns the part of a string after a specified substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n fromIndex: integer (optional)\n Index from which to start the search. Default: `0`.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var out = substringAfter( 'Hello World!', 'World' )\n '!'\n > out = substringAfter( 'Hello World!', 'Hello ' )\n 'World!'\n > out = substringAfter( 'Hello World!', 'l', 5 )\n 'd!'\n\n See Also\n --------\n substringBefore, substringBeforeLast, substringAfterLast","substringAfterLast":"\nsubstringAfterLast( str, search[, fromIndex] )\n Returns the part of a string after the last occurrence of a specified\n substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search value.\n\n fromIndex: integer (optional)\n Index of last character to be considered beginning of a match.\n Default: `str.length`.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var out = substringAfterLast( 'beep boop beep baz', 'beep' )\n ' baz'\n > out = substringAfterLast( 'Hello World!', 'Hello ' )\n 'World!'\n > out = substringAfterLast( 'Hello World!', 'o', 5 )\n ' World!'\n\n See Also\n --------\n substringBefore, substringBeforeLast, substringAfter","substringBefore":"\nsubstringBefore( str, search )\n Returns the part of a string before a specified substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = substringBefore( str, ' ' )\n 'beep'\n > out = substringBefore( str, 'o' )\n 'beep b'\n\n See Also\n --------\n substringBeforeLast, substringAfter, substringAfterLast","substringBeforeLast":"\nsubstringBeforeLast( str, search )\n Returns the part of a string before the last occurrence of a specified\n substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search value.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var str = 'Beep Boop Beep';\n > var out = substringBeforeLast( str, 'Beep' )\n 'Beep Boop '\n > out = substringBeforeLast( str, 'Boop' )\n 'Beep '\n\n See Also\n --------\n substringBefore, substringAfter, substringAfterLast","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on July 10, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on May 9, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK\n","Symbol":"\nSymbol( [description] )\n Returns a symbol.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support symbols.\n\n Parameters\n ----------\n description: string (optional)\n Symbol description which can be used for debugging but not to access the\n symbol itself.\n\n Returns\n -------\n out: symbol\n Symbol.\n\n Examples\n --------\n > var s = ( Symbol ) ? Symbol( 'beep' ) : null\n\n","tabulate":"\ntabulate( collection )\n Generates a frequency table.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulate( collection )\n [ [ 'beep', 2, 0.5 ], [ 'boop', 1, 0.25 ], [ 'foo', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulateBy\n","tabulateBy":"\ntabulateBy( collection, [options,] indicator )\n Generates a frequency table according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > function indicator( value ) { return value[ 0 ]; };\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulateBy( collection, indicator )\n [ [ 'b', 3, 0.75 ], [ 'f', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulate\n","tabulateByAsync":"\ntabulateByAsync( collection, [options,] indicator, done )\n Generates a frequency table according to an indicator function.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, indicator, done )\n 750\n 1000\n 2500\n 3000\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n 750\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n See Also\n --------\n countByAsync, groupByAsync, tabulateBy\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n See Also\n --------\n countByAsync, groupByAsync, tabulateBy","thunk":"\nthunk( fcn[, ...args] )\n Returns a thunk.\n\n Parameters\n ----------\n fcn: Function\n Function to convert to a thunk.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n out: Function\n Thunk.\n\n Examples\n --------\n > var fcn = thunk( base.add, 2, 3 );\n > var v = fcn()\n 5\n > v = fcn()\n 5\n\n","tic":"\ntic()\n Returns a high-resolution time.\n\n The returned array has the following format: `[seconds, nanoseconds]`.\n\n Returns\n -------\n out: Array\n High resolution time.\n\n Examples\n --------\n > var t = tic()\n [ , ]\n\n See Also\n --------\n toc\n","timeit":"\ntimeit( code, [options,] clbk )\n Times a snippet.\n\n If the `asynchronous` option is set to `true`, the implementation assumes\n that `before`, `after`, and `code` snippets are all asynchronous.\n Accordingly, these snippets should invoke a `next( [error] )` callback\n once complete. The implementation wraps the snippet within a function\n accepting two arguments: `state` and `next`.\n\n The `state` parameter is simply an empty object which allows the `before`,\n `after`, and `code` snippets to share state.\n\n Notes:\n\n - Snippets always run in strict mode.\n - Always verify results. Doing so prevents the compiler from performing dead\n code elimination and other optimization techniques, which would render\n timing results meaningless.\n - Executed code is not sandboxed and has access to the global state. You are\n strongly advised against timing untrusted code. To time untrusted code,\n do so in an isolated environment (e.g., a separate process with restricted\n access to both global state and the host environment).\n - Wrapping asynchronous code does add overhead, but, in most cases, the\n overhead should be negligible compared to the execution cost of the timed\n snippet.\n - When the `asynchronous` option is `true`, ensure that the main `code`\n snippet is actually asynchronous. If a snippet releases the zalgo, an\n error complaining about exceeding the maximum call stack size is highly\n likely.\n - While many benchmark frameworks calculate various statistics over raw\n timing results (e.g., mean and standard deviation), do not do this.\n Instead, consider the fastest time an approximate lower bound for how fast\n an environment can execute a snippet. Slower times are more likely\n attributable to other processes interfering with timing accuracy rather\n than attributable to variability in JavaScript's speed. In which case, the\n minimum time is most likely the only result of interest. When considering\n all raw timing results, apply common sense rather than statistics.\n\n Parameters\n ----------\n code: string\n Snippet to time.\n\n options: Object (optional)\n Options.\n\n options.before: string (optional)\n Setup code. Default: `''`.\n\n options.after: string (optional)\n Cleanup code. Default: `''`.\n\n options.iterations: integer|null (optional)\n Number of iterations. If `null`, the number of iterations is determined\n by trying successive powers of `10` until the total time is at least\n `0.1` seconds. Default: `1e6`.\n\n options.repeats: integer (optional)\n Number of repeats. Default: `3`.\n\n options.asynchronous: boolean (optional)\n Boolean indicating whether a snippet is asynchronous. Default: `false`.\n\n clbk: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > var code = 'var x = Math.pow( Math.random(), 3 );';\n > code += 'if ( x !== x ) {';\n > code += 'throw new Error( \\'Something went wrong.\\' );';\n > code += '}';\n > function done( error, results ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.dir( results );\n ... };\n > timeit( code, done )\n e.g.,\n {\n \"iterations\": 1000000,\n \"repeats\": 3,\n \"min\": [ 0, 135734733 ], // [seconds,nanoseconds]\n \"elapsed\": 0.135734733, // seconds\n \"rate\": 7367311.062526641, // iterations/second\n \"times\": [ // raw timing results\n [ 0, 145641393 ],\n [ 0, 135734733 ],\n [ 0, 140462721 ]\n ]\n }\n\n","tmpdir":"\ntmpdir()\n Returns the directory for storing temporary files.\n\n Returns\n -------\n dir: string\n Directory for temporary files.\n\n Examples\n --------\n > var dir = tmpdir()\n e.g., '/path/to/temporary/files/directory'\n\n See Also\n --------\n configdir, homedir\n","toc":"\ntoc( time )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n\n Similar to `time`, the returned array has format `[seconds, nanoseconds]`.\n\n Parameters\n ----------\n time: Array\n High-resolution time.\n\n Returns\n -------\n out: Array\n High resolution time difference.\n\n Examples\n --------\n > var start = tic();\n > var delta = toc( start )\n [ , ]\n\n See Also\n --------\n tic\n","tokenize":"\ntokenize( str[, keepWhitespace] )\n Tokenizes a string.\n\n To include whitespace characters (spaces, tabs, line breaks) in the output\n array, set `keepWhitespace` to `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n keepWhitespace: boolean (optional)\n Boolean indicating whether whitespace characters should be returned as\n part of the token array. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of tokens.\n\n Examples\n --------\n > var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\n [ 'Hello', 'Mrs.', 'Maple', ',', 'could', 'you', 'call', 'me', 'back', '?' ]\n\n > out = tokenize( 'Hello World!', true )\n [ 'Hello', ' ', 'World', '!' ]\n\n","transformStream":"\ntransformStream( [options] )\n Returns a transform stream.\n\n If a transform function is not provided, the returned stream will be a\n simple pass through stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = transformStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n","transformStream.factory":"\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","transformStream.objectMode":"\ntransformStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();","transformStream.ctor":"\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","trim":"\ntrim( str )\n Trims whitespace from the beginning and end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n 'Beep'\n\n See Also\n --------\n ltrim, pad, rtrim\n","truncate":"\ntruncate( str, len[, ending] )\n Truncates a string to a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n ending: string (optional)\n Custom ending. Default: '...'.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = truncate( str, 5 )\n 'be...'\n\n > out = truncate( str, 5, '|' )\n 'beep|'\n\n See Also\n --------\n truncateMiddle","truncateMiddle":"\ntruncateMiddle( str, len[, seq] )\n Truncates a string in the middle to a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n seq: string (optional)\n Custom replacement sequence. Default: '...'.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = truncateMiddle( str, 5 )\n 'b...p'\n\n > out = truncateMiddle( str, 5, '|' )\n 'be|op'\n\n See Also\n --------\n truncate","trycatch":"\ntrycatch( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: any\n Value to return if a function throws an error.\n\n Returns\n -------\n z: any\n Either the return value of `x` or the provided argument `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > var z = trycatch( x, -1.0 )\n \n\n See Also\n --------\n trycatchAsync, trythen\n","trycatchAsync":"\ntrycatchAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts two arguments:\n\n - error: error object\n - result: function result\n\n The `done` callback is invoked upon function completion and is provided two\n arguments:\n\n - error: error object\n - result: either the result of `x` or the provided argument `y`\n\n If `x` invokes `clbk` with an error argument, the function invokes the\n `done` callback with both the error and the argument `y`.\n\n If `x` does not invoke `clbk` with an error argument, the function invokes\n the `done` callback with a first argument equal to `null` and the function\n `result`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: any\n Value to return if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... // process error...\n ... }\n ... console.log( result );\n ... };\n > trycatchAsync( x, 'boop', done )\n 'boop'\n\n See Also\n --------\n trycatch, trythenAsync\n","tryFunction":"\ntryFunction( fcn[, thisArg] )\n Wraps a function in a try/catch block.\n\n If provided an asynchronous function, the returned function only traps\n errors which occur during the current event loop tick.\n\n If a function throws a literal, the literal is serialized as a string and\n returned as an `Error` object.\n\n Parameters\n ----------\n fcn: Function\n Function to wrap.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Wrapped function.\n\n Examples\n --------\n > function fcn() { throw new Error( 'beep boop' ); };\n > var f = tryFunction( fcn );\n > var out = f();\n > out.message\n 'beep boop'\n\n","tryRequire":"\ntryRequire( id )\n Wraps `require` in a `try/catch` block.\n\n This function traps and returns any errors encountered when attempting to\n require a module.\n\n Use caution when attempting to resolve a relative path or a local module.\n This function attempts to resolve a module from its current path. Thus, the\n function is unable to resolve anything which is not along its search path.\n For local requires, use an absolute file path.\n\n Parameters\n ----------\n id: string\n Module id.\n\n Returns\n -------\n out: any|Error\n Resolved module or an `Error`.\n\n Examples\n --------\n > var out = tryRequire( '_unknown_module_id_' )\n \n\n","trythen":"\ntrythen( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n\n The function `y` is provided a single argument:\n\n - error: the error thrown by `x`\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: Function\n Function to invoke if an initial function throws an error.\n\n Returns\n -------\n z: any\n The return value of either `x` or `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > function y() {\n ... return -1.0;\n ... };\n > var z = trythen( x, y )\n \n\n See Also\n --------\n trycatch, trythenAsync\n","trythenAsync":"\ntrythenAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the function invokes a `done` callback with\n its first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the function invokes a function `y`. The\n number of arguments provided to `y` depends on the function's length. If `y`\n is a unary function, `y` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n Otherwise, `y` is provided two arguments:\n\n - error: the error from `x`\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument equal to `null` and all other arguments provided by `y`.\n\n If the error argument is truthy, the `done` callback is invoked with only\n the error argument provided by `y`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: Function\n Function to invoke if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > trythenAsync( x, y, done )\n 'boop'\n\n See Also\n --------\n trycatchAsync, trythen\n","ttest":"\nttest( x[, y][, options] )\n Computes a one-sample or paired Student's t test.\n\n When no `y` is supplied, the function performs a one-sample t-test for the\n null hypothesis that the data in array or typed array `x` is drawn from a\n normal distribution with mean zero and unknown variance.\n\n When array or typed array `y` is supplied, the function tests whether the\n differences `x - y` come from a normal distribution with mean zero and\n unknown variance via the paired t-test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n y: Array (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed mean under H0 (or difference in means when `y` is supplied).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.mean: number\n Sample mean of `x` or `x - y`, respectively.\n\n out.sd: number\n Standard error of the mean.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample t-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ttest( x )\n {\n rejected: false,\n pValue: ~0.722,\n statistic: ~0.357,\n ci: [~-0.333,~0.479],\n // ...\n }\n\n // Paired t-test:\n > rnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\n > x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... y[ i ] = rnorm();\n ... }\n > out = ttest( x, y )\n {\n rejected: false,\n pValue: ~0.191,\n statistic: ~1.315,\n ci: [ ~-0.196, ~0.964 ],\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.1916\n statistic: 1.3148\n df: 99\n 95% confidence interval: [-0.1955,0.9635]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose custom significance level:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ttest( arr, { 'alpha': 0.01 } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0474\n statistic: 2.8284\n df: 4\n 99% confidence interval: [-1.2556,5.2556]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'mu': 5 } )\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~3.758, ~6.242 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'alternative': 'less' } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is less than 0\n\n pValue: 0.9998\n statistic: 11.1803\n df: 4\n 95% confidence interval: [-Infinity,5.9534]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n > out = ttest( arr, { 'alternative': 'greater' } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is greater than 0\n\n pValue: 0.0002\n statistic: 11.1803\n df: 4\n 95% confidence interval: [4.0466,Infinity]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n See Also\n --------\n ttest2\n","ttest2":"\nttest2( x, y[, options] )\n Computes a two-sample Student's t test.\n\n By default, the function performs a two-sample t-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n options.variance: string (optional)\n String indicating if the test should be conducted under the assumption\n that the unknown variances of the normal distributions are `equal` or\n `unequal`. As a default choice, the function carries out the Welch test\n (using the Satterthwaite approximation for the degrees of freedom),\n which does not have the requirement that the variances of the underlying\n distributions are equal. If the equal variances assumption seems\n warranted, set the option to `equal`. Default: `unequal`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Student's sleep data:\n > var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\n > var y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\n > var out = ttest2( x, y )\n {\n rejected: false,\n pValue: ~0.079,\n statistic: ~-1.861,\n ci: [ ~-3.365, ~0.205 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 95% confidence interval: [-3.3655,0.2055]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ttest2( x, y, { 'alpha': 0.1 } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 90% confidence interval: [-3.0534,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 10% significance level\n\n // Perform one-sided tests:\n > out = ttest2( x, y, { 'alternative': 'less' } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.0397\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-Infinity,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n > out = ttest2( x, y, { 'alternative': 'greater' } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.9603\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-3.0534,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Run tests with equal variances assumption:\n > x = [ 2, 3, 1, 4 ];\n > y = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\n > out = ttest2( x, y, { 'variance': 'equal' } );\n > table = out.print()\n Two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.8848\n statistic: -0.1486\n df: 10\n 95% confidence interval: [-1.9996,1.7496]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 3.0 );\n ... }\n > y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 1.0, 3.0 );\n ... }\n > out = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n {\n rejected: false,\n pValue: ~0.642,\n statistic: ~-0.466,\n ci: [ ~-0.0455, ~1.646 ],\n // ...\n }\n\n See Also\n --------\n ttest\n","TWO_PI":"\nTWO_PI\n The mathematical constant `π` times `2`.\n\n Examples\n --------\n > TWO_PI\n 6.283185307179586\n\n See Also\n --------\n PI\n","typedarray":"\ntypedarray( [dtype] )\n Creates a typed array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray()\n \n > arr = typedarray( 'float32' )\n \n\n\ntypedarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = typedarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n Complex128Array, Complex64Array, Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","typedarray2json":"\ntypedarray2json( arr )\n Returns a JSON representation of a typed array.\n\n The following typed array types are supported:\n\n - Float64Array\n - Float32Array\n - Int32Array\n - Uint32Array\n - Int16Array\n - Uint16Array\n - Int8Array\n - Uint8Array\n - Uint8ClampedArray\n - Complex64Array\n - Complex128Array\n\n The returned JSON object has the following properties:\n\n - type: typed array type\n - data: typed array data as a generic array\n\n The implementation supports custom typed arrays and sets the `type` field to\n the closest known typed array type.\n\n Parameters\n ----------\n arr: TypedArray\n Typed array to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var arr = new Float64Array( 2 );\n > arr[ 0 ] = 5.0;\n > arr[ 1 ] = 3.0;\n > var json = typedarray2json( arr )\n { 'type': 'Float64Array', 'data': [ 5.0, 3.0 ] }\n\n See Also\n --------\n reviveTypedArray\n","typedarrayCtors":"\ntypedarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayCtors( 'float64' )\n \n > ctor = typedarrayCtors( 'float' )\n null\n\n See Also\n --------\n arrayCtors\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = typedarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, ndarrayDataTypes\n","typedarraypool":"\ntypedarraypool( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n Memory is **uninitialized**, which means that the contents of a returned\n typed array may contain sensitive contents.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool()\n []\n > arr = typedarraypool( 'float32' )\n []\n\n\ntypedarraypool( length[, dtype] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > arr = typedarraypool( 5, 'int32' )\n \n\n\ntypedarraypool( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n \n\n\ntypedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n \n\n\ntypedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []\n\n\ntypedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr )\n\n\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear()\n\n\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark\n\n\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes\n\n\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n See Also\n --------\n typedarray\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n typedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n typedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]typedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []typedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]","typedarraypool.free":"\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr )","typedarraypool.clear":"\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear()","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes","typedarraypool.factory":"\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n See Also\n --------\n typedarray","typemax":"\ntypemax( dtype )\n Returns the maximum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var m = typemax( 'int8' )\n 127\n > m = typemax( 'uint32' )\n 4294967295\n\n See Also\n --------\n realmax, typemin\n","typemin":"\ntypemin( dtype )\n Returns the minimum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var m = typemin( 'int8' )\n -128\n > m = typemin( 'uint32' )\n 0\n\n See Also\n --------\n realmin, typemax\n","typeOf":"\ntypeOf( value )\n Determines a value's type.\n\n The following values are not natively provided in older JavaScript engines:\n\n - Map\n - Set\n - WeakMap\n - WeakSet\n - Symbol\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n The value's type.\n\n Examples\n --------\n // Built-ins:\n > var t = typeOf( 'a' )\n 'string'\n > t = typeOf( 5 )\n 'number'\n > t = typeOf( NaN )\n 'number'\n > t = typeOf( true )\n 'boolean'\n > t = typeOf( false )\n 'boolean'\n > t = typeOf( null )\n 'null'\n > t = typeOf( undefined )\n 'undefined'\n > t = typeOf( [] )\n 'array'\n > t = typeOf( {} )\n 'object'\n > t = typeOf( function noop() {} )\n 'function'\n > t = typeOf( Symbol( 'beep' ) )\n 'symbol'\n > t = typeOf( /.+/ )\n 'regexp'\n > t = typeOf( new String( 'beep' ) )\n 'string'\n > t = typeOf( new Number( 5 ) )\n 'number'\n > t = typeOf( new Boolean( false ) )\n 'boolean'\n > t = typeOf( new Array() )\n 'array'\n > t = typeOf( new Object() )\n 'object'\n > t = typeOf( new Int8Array( 10 ) )\n 'int8array'\n > t = typeOf( new Uint8Array( 10 ) )\n 'uint8array'\n > t = typeOf( new Uint8ClampedArray( 10 ) )\n 'uint8clampedarray'\n > t = typeOf( new Int16Array( 10 ) )\n 'int16array'\n > t = typeOf( new Uint16Array( 10 ) )\n 'uint16array'\n > t = typeOf( new Int32Array( 10 ) )\n 'int32array'\n > t = typeOf( new Uint32Array( 10 ) )\n 'uint32array'\n > t = typeOf( new Float32Array( 10 ) )\n 'float32array'\n > t = typeOf( new Float64Array( 10 ) )\n 'float64array'\n > t = typeOf( new ArrayBuffer( 10 ) )\n 'arraybuffer'\n > t = typeOf( new Date() )\n 'date'\n > t = typeOf( new RegExp( '.+' ) )\n 'regexp'\n > t = typeOf( new Map() )\n 'map'\n > t = typeOf( new Set() )\n 'set'\n > t = typeOf( new WeakMap() )\n 'weakmap'\n > t = typeOf( new WeakSet() )\n 'weakset'\n > t = typeOf( new Error( 'beep' ) )\n 'error'\n > t = typeOf( new TypeError( 'beep' ) )\n 'typeerror'\n > t = typeOf( new SyntaxError( 'beep' ) )\n 'syntaxerror'\n > t = typeOf( new ReferenceError( 'beep' ) )\n 'referenceerror'\n > t = typeOf( new URIError( 'beep' ) )\n 'urierror'\n > t = typeOf( new RangeError( 'beep' ) )\n 'rangeerror'\n > t = typeOf( new EvalError( 'beep' ) )\n 'evalerror'\n > t = typeOf( Math )\n 'math'\n > t = typeOf( JSON )\n 'json'\n\n // Arguments object:\n > function beep() { return arguments; };\n > t = typeOf( beep() )\n 'arguments'\n\n // Node.js Buffer object:\n > t = typeOf( new Buffer( 10 ) )\n 'buffer'\n\n // Custom constructor:\n > function Person() { return this };\n > t = typeOf( new Person() )\n 'person'\n\n // Anonymous constructor:\n > var Foo = function () { return this; };\n > t = typeOf( new Foo() )\n '' || 'foo'\n\n See Also\n --------\n constructorName, nativeClass\n","UINT8_MAX":"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n\n The maximum unsigned 8-bit integer is given by `2^8 - 1`.\n\n Examples\n --------\n > UINT8_MAX\n 255\n\n See Also\n --------\n INT8_MAX\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n\n Examples\n --------\n > UINT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT8_NUM_BYTES, UINT16_NUM_BYTES, UINT32_NUM_BYTES\n","Uint8Array":"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array()\n \n\n\nUint8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'\n\n\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n \n\n\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5\n\n\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5\n\n\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray\n","Uint8Array.from":"\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint8Array.of":"\nUint8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1","Uint8Array.name":"\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n ","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray","Uint8ClampedArray":"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray()\n \n\n\nUint8ClampedArray( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8ClampedArray( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8ClampedArray( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'\n\n\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n \n\n\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5\n\n\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0\n\n\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5\n\n\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n ","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array","UINT16_MAX":"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n\n The maximum unsigned 16-bit integer is given by `2^16 - 1`.\n\n Examples\n --------\n > UINT16_MAX\n 65535\n\n See Also\n --------\n INT16_MAX\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n\n Examples\n --------\n > UINT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT16_NUM_BYTES, UINT32_NUM_BYTES, UINT8_NUM_BYTES\n","Uint16Array":"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array()\n \n\n\nUint16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Uint16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'\n\n\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n \n\n\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10\n\n\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5\n\n\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Uint16Array.from":"\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint16Array.of":"\nUint16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2","Uint16Array.name":"\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n ","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray","UINT32_MAX":"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n\n The maximum unsigned 32-bit integer is given by `2^32 - 1`.\n\n Examples\n --------\n > UINT32_MAX\n 4294967295\n\n See Also\n --------\n INT32_MAX\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n\n Examples\n --------\n > UINT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT32_NUM_BYTES, UINT16_NUM_BYTES, UINT8_NUM_BYTES\n","Uint32Array":"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array()\n \n\n\nUint32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Uint32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'\n\n\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n \n\n\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20\n\n\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5\n\n\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray\n","Uint32Array.from":"\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint32Array.of":"\nUint32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4","Uint32Array.name":"\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n ","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray","umask":"\numask( [mask,] [options] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n\n A mask is a set of bits, each of which restricts how its corresponding\n permission is set for newly created files.\n\n On POSIX platforms, each file has a set of attributes that control who can\n read, write, or execute that file. Upon creating a file, file permissions\n must be set to an initial setting. The process mask restricts those\n permission settings.\n\n If the mask contains a bit set to \"1\", the corresponding initial file\n permission is disabled. If the mask contains a bit set to \"0\", the\n corresponding permission is left to be determined by the requesting process\n and the system.\n\n The process mask is thus a filter that removes permissions as a file is\n created; i.e., each bit set to a \"1\" removes its corresponding permission.\n\n In octal representation, a mask is a four digit number, e.g., 0077,\n comprised as follows:\n\n - 0: special permissions (setuid, setgid, sticky bit)\n - 0: (u)ser/owner permissions\n - 7: (g)roup permissions\n - 7: (o)thers/non-group permissions\n\n Octal codes correspond to the following permissions:\n\n - 0: read, write, execute\n - 1: read, write\n - 2: read, execute\n - 3: read\n - 4: write, execute\n - 5: write\n - 6: execute\n - 7: no permissions\n\n If provided fewer than four digits, the mask is left-padded with zeros.\n\n Note, however, that only the last three digits (i.e., the file permissions\n digits) of the mask are actually used when the mask is applied.\n\n Permissions can be represented using the following symbolic form:\n\n u=rwx,g=rwx,o=rwx\n\n where\n\n - u: user permissions\n - g: group permissions\n - o: other/non-group permissions\n - r: read\n - w: write\n - x: execute\n\n When setting permissions using symbolic notation, the function accepts a\n mask expression of the form:\n\n []\n\n where \"classes\" may be a combination of\n\n - u: user\n - g: group\n - o: other/non-group\n - a: all\n\n \"symbols\" may be a combination of\n\n - r: read\n - w: write\n - x: execute\n - X: special execute\n - s: setuid/gid on execution\n - t: sticky\n\n and \"operator\" may be one of\n\n - `+`: enable\n - `-`: disable\n - `=`: enable specified and disable unspecified permissions\n\n For example,\n\n - `u-w`: disable user write permissions\n - `u+w`: enable user write permissions\n - `u=w`: enable user write permissions and disable user read and execute\n\n To specify multiple changes, provide a comma-separated list of mask\n expressions. For example,\n\n u+rwx,g-x,o=r\n\n would enable user read, write, and execute permissions, disable group\n execute permissions, enable other read permissions, and disable other\n write and execute permissions.\n\n The `a` class indicates \"all\", which is the same as specifying \"ugo\". This\n is the default class if a class is omitted when specifying permissions. For\n example, `+x` is equivalent to `a+x` which is equivalent to `ugo+x` which\n is equivalent to `u+x,g+x,o+x` and enables execution for all classes.\n\n Parameters\n ----------\n mask: integer|string (optional)\n Mask or mask expression. If the mask is a string, the mask is assumed to\n be in symbolic notation.\n\n options: Object (optional)\n Options.\n\n options.symbolic: boolean (optional)\n Boolean indicating whether to return the mask using symbolic notation.\n\n Returns\n -------\n mask: integer|string\n Process mask. If provided a mask, the returned value is the previous\n mask; otherwise, the returned value is the current process mask.\n\n Examples\n --------\n > var mask = umask()\n \n > mask = umask( { 'symbolic': true } )\n \n\n","uncapitalize":"\nuncapitalize( str )\n Lowercases the first character of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = uncapitalize( 'Beep' )\n 'beep'\n > out = uncapitalize( 'bOOp' )\n 'bOOp'\n\n See Also\n --------\n capitalize, lowercase\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj )\n Converts the first letter of each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'AA': 1, 'BB': 2 };\n > var out = uncapitalizeKeys( obj )\n { 'aA': 1, 'bB': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n","uncurry":"\nuncurry( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurry( addX );\n > var sum = fcn( 2, 3 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( x ) {\n ... return function add( y ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurry( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addX( x ) {\n ... this.x = x;\n ... return addY;\n ... };\n > function addY( y ) {\n ... return this.x + y;\n ... };\n > fcn = uncurry( addX, {} );\n > sum = fcn( 2, 3 )\n 5\n\n See Also\n --------\n curry, uncurryRight\n","uncurryRight":"\nuncurryRight( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Provided arguments are applied starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurryRight( addX );\n > var sum = fcn( 3, 2 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( y ) {\n ... return function add( x ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurryRight( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addY( y ) {\n ... this.y = y;\n ... return addX;\n ... };\n > function addX( x ) {\n ... return x + this.y;\n ... };\n > fcn = uncurryRight( addY, {} );\n > sum = fcn( 3, 2 )\n 5\n\n See Also\n --------\n curry, curryRight, uncurry\n","UNICODE_MAX":"\nUNICODE_MAX\n Maximum Unicode code point.\n\n Examples\n --------\n > UNICODE_MAX\n 1114111\n\n See Also\n --------\n UNICODE_MAX_BMP\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n\n Examples\n --------\n > UNICODE_MAX_BMP\n 65535\n\n See Also\n --------\n UNICODE_MAX\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data,] [options] )\n Returns a sparkline column chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeColumnChartSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data,] [options] )\n Returns a sparkline line chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: LineChart\n Line chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a line chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeLineChartSparkline( data );\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeSparkline":"\nUnicodeSparkline( [data,] [options] )\n Returns a Unicode sparkline instance.\n\n The following chart types are supported:\n\n - column: column chart (e.g., ▃▆▂▄▁▅▅).\n - line: line chart (e.g., ⡈⠑⠢⠔⠒⠒⠒).\n - tristate: tristate chart (e.g., ▄▀──▀▄▄▀).\n - up-down: up/down chart (e.g., ↓↑↑↑↑↓↓↑).\n - win-loss: win/loss chart (e.g., ┌╵└┴╵╷╷╵).\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.type: string (optional)\n Chart type. Default: 'column'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.type\n Chart type.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n > chart.type = 'line';\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data,] [options] )\n Returns a sparkline tristate chart instance.\n\n In a tristate chart, negative values are encoded as lower blocks, positive\n values are encoded as upper blocks, and values equal to zero are encoded as\n middle lines.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: TristateChart\n Tristate chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a tristate chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\n > var chart = new UnicodeTristateChartSparkline( data );\n > chart.render()\n '▄▀──▀▄▄▀'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data,] [options] )\n Returns a sparkline up/down chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ↑ |\n | -1 | ↓ |\n\n If provided any other value other than 1 or -1, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: UpDownChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1 or -1.\n\n chart.render()\n Renders an up/down chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\n > var chart = new UnicodeUpDownChartSparkline( data );\n > chart.render()\n '↓↑↑↑↑↓↓↑'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data,] [options] )\n Returns a sparkline win/loss chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ╵ |\n | -1 | ╷ |\n | 2 | └ |\n | -2 | ┌ |\n\n If a `2` or `-2` is preceded by a `2` or `-2`,\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 2 | ┴ |\n | -2 | ┬ |\n\n Based on the win/loss analogy,\n\n - 1: win away\n - 2: win at home\n - -1: loss away\n - -2: loss at home\n\n If provided any value other than 1, -1, 2, or -2, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: WinLossChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1, -1, 2, or -2.\n\n chart.render()\n Renders a win/loss chart sparkline.\n\n Examples\n --------\n > var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\n > var chart = new UnicodeWinLossChartSparkline( data );\n > chart.render()\n '┌╵└┴╵╷╷╵'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline\n","unlink":"\nunlink( path, clbk )\n Asynchronously removes a directory entry.\n\n If a provided path is a symbolic link, the function removes the symbolic\n link named by the path and does not affect any file or directory named by\n the contents of the symbolic link.\n\n Otherwise, the function removes the link named by the provided path and\n decrements the link count of the file referenced by the link.\n\n When a file's link count becomes 0 and no process has the file open, the\n space occupied by the file is freed and the file is no longer accessible.\n\n If one or more processes have the file open when the last link is removed,\n the link is removed before the function returns; however, the removal of\n file contents is postponed until all references to the file are closed.\n\n If the path refers to a socket, FIFO, or device, processes which have the\n object open may continue to use it.\n\n The path argument should *not* be a directory. To remove a directory, use\n rmdir().\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n clbk: Function\n Callback to invoke upon removing an entry.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > unlink( './beep/boop.txt', done );\n\n\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n See Also\n --------\n exists\n","unlink.sync":"\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n See Also\n --------\n exists","unshift":"\nunshift( collection, ...items )\n Adds one or more elements to the beginning of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = unshift( arr, 6.0, 7.0 )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = unshift( arr, 3.0, 4.0 )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = unshift( arr, 2.0, 3.0 )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n pop, push, shift\n","until":"\nuntil( predicate, fcn[, thisArg] )\n Invokes a function until a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > until( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, untilAsync, untilEach, whilst\n","untilAsync":"\nuntilAsync( predicate, fcn, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is falsy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > untilAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, until, whileAsync\n","untilEach":"\nuntilEach( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > untilEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEachRight, whileEach\n","untilEachRight":"\nuntilEachRight( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > untilEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n untilEach, whileEachRight\n","unzip":"\nunzip( arr[, idx] )\n Unzips a zipped array (i.e., a nested array of tuples).\n\n Parameters\n ----------\n arr: Array\n Zipped array.\n\n idx: Array (optional)\n Array of indices specifying which tuple elements to unzip.\n\n Returns\n -------\n out: Array\n Array of unzipped arrays.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > var out = unzip( arr )\n [ [ 1, 2 ], [ 'a', 'b' ], [ 3, 4 ] ]\n\n // Provide indices:\n > arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > out = unzip( arr, [ 0, 2 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n zip\n","uppercase":"\nuppercase( str )\n Converts a string to uppercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uppercase string.\n\n Examples\n --------\n > var out = uppercase( 'bEEp' )\n 'BEEP'\n\n See Also\n --------\n capitalize, lowercase\n","uppercaseKeys":"\nuppercaseKeys( obj )\n Converts each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'a': 1, 'b': 2 };\n > var out = uppercaseKeys( obj )\n { 'A': 1, 'B': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n\n Returns\n -------\n out: Array\n List of US state two-letter abbreviations.\n\n Examples\n --------\n > var list = US_STATES_ABBR()\n [ 'AL', 'AK', 'AZ', 'AR', ... ]\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n\n Returns\n -------\n out: Array\n List of US state capitals.\n\n Examples\n --------\n > var list = US_STATES_CAPITALS()\n [ 'Montgomery', 'Juneau', 'Phoenix', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS_NAMES, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n\n Returns\n -------\n out: Object\n An object mapping US state capitals to state names.\n\n Examples\n --------\n > var out = US_STATES_CAPITALS_NAMES()\n { 'Montgomery': 'Alabama', 'Juneau': 'Alaska', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n\n Returns\n -------\n out: Array\n List of US state names.\n\n Examples\n --------\n > var list = US_STATES_NAMES()\n [ 'Alabama', 'Alaska', 'Arizona', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS, US_STATES_CAPITALS_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n\n Returns\n -------\n out: Object\n An object mapping US state names to state capitals.\n\n Examples\n --------\n > var out = US_STATES_NAMES_CAPITALS()\n { 'Alabama': 'Montgomery', 'Alaska': 'Juneau', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n\n The following byte sequences are used to represent a character. The sequence\n depends on the code point:\n\n 0x00000000 - 0x0000007F:\n 0xxxxxxx\n\n 0x00000080 - 0x000007FF:\n 110xxxxx 10xxxxxx\n\n 0x00000800 - 0x0000FFFF:\n 1110xxxx 10xxxxxx 10xxxxxx\n\n 0x00010000 - 0x001FFFFF:\n 11110xxx 10xxxxxx 10xxxxxx 10xxxxxx\n\n The `x` bit positions correspond to code point bits.\n\n Only the shortest possible multi-byte sequence which can represent a code\n point is used.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: Array\n Array of integers.\n\n Examples\n --------\n > var str = '☃';\n > var out = utf16ToUTF8Array( str )\n [ 226, 152, 131 ]\n\n","vartest":"\nvartest( x, y[, options] )\n Computes a two-sample F-test for equal variances.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`.\n\n options.ratio: number (optional)\n Positive number denoting the ratio of the two population variances under\n the null hypothesis. Default: `1`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the ratio of variances.\n\n out.nullValue: number\n Assumed ratio of variances under H0.\n\n out.xvar: number\n Sample variance of `x`.\n\n out.yvar: number\n Sample variance of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.dfX: number\n Numerator degrees of freedom.\n\n out.dfY: number\n Denominator degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [ 610, 610, 550, 590, 565, 570 ];\n > var y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\n > var out = vartest( x, y )\n {\n rejected: false,\n pValue: ~0.399,\n statistic: ~1.976,\n ci: [ ~0.374, ~13.542 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n F test for comparing two variances\n\n Alternative hypothesis: True ratio in variances is not equal to 1\n\n pValue: 0.3992\n statistic: 1.976\n variance of x: 617.5 (df of x: 5)\n variance of y: 312.5 (df of y: 7)\n 95% confidence interval: [0.3739,13.5417]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n See Also\n --------\n bartlettTest\n","waterfall":"\nwaterfall( fcns, clbk[, thisArg] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n\n The last argument applied to each waterfall function is a callback. The\n callback should be invoked upon a series function completion. The first\n argument is reserved as an error argument (which can be `null`). Any results\n which should be passed to the next function in the series should be provided\n beginning with the second argument.\n\n If any function calls the provided callback with a truthy `error` argument,\n the waterfall suspends execution and immediately calls the completion\n callback for subsequent error handling.\n\n Execution is *not* guaranteed to be asynchronous. To ensure asynchrony, wrap\n the completion callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > waterfall( fcns, done );\n\n\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();\n\n","waterfall.factory":"\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();","whileAsync":"\nwhileAsync( predicate, fcn, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is truthy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > whileAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, untilAsync, whilst\n","whileEach":"\nwhileEach( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > whileEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEach, whileEachRight\n","whileEachRight":"\nwhileEachRight( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > whileEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n whileEach, untilEachRight\n","whilst":"\nwhilst( predicate, fcn[, thisArg] )\n Invokes a function while a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > whilst( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, until, whileAsync, whileEach\n","wilcoxon":"\nwilcoxon( x[, y][, options] )\n Computes a one-sample or paired Wilcoxon signed rank test.\n\n When no `y` is supplied, the function performs a one-sample Wilcoxon signed\n rank test for the null hypothesis that the data is drawn from a symmetric\n distribution around zero.\n\n When `y` is supplied, the function tests whether the\n differences `x - y` come from a symmetric distribution around zero.\n\n If `x` has less than fifty elements, an exact p-value is computed if there\n are no zero values or ties. Otherwise, a normal approximation is used.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array|TypedArray\n Data array.\n\n y: Array|TypedArray (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`), or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.correction: boolean (optional)\n Determines whether to apply continuity correction adjusting the Wilcoxon\n rank statistic by 0.5 towards the mean when using the normal\n approximation. Default: `true`.\n\n options.exact: boolean (optional)\n Determines whether to force use of the exact distribution instead of a\n normal approximation when there are more than fifty data points.\n Default: `false`.\n\n options.mu: number (optional)\n Hypothesized true location under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n options.zeroMethod: string (optional)\n Method governing how zero-differences are handled (`pratt`, `wilcox`, or\n `zsplit`). When set to `pratt`, differences of zero are used to\n calculate ranks but their ranks are then dropped. When set to `wilcox`,\n all zero-differences are discarded. When set to `zsplit`, differences of\n zero are used to rank and their ranks are then split between positive\n and negative ones. Default: `'wilcox'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.nullValue: number\n Assumed location parameter under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample test:\n > var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\n > var out = wilcoxon( x )\n {\n 'rejected': true,\n 'alpha': 0.05,\n 'pValue': 0.04125976562499978,\n 'statistic': 96\n // ...\n }\n\n // Paired test:\n > runif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\n > var x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = runif();\n ... y[ i ] = runif();\n ... }\n > out = wilcoxon( x, y )\n {\n 'rejected': false,\n 'alpha': 0.05,\n 'pValue': 0.21759090963694638,\n 'statistic': 2702.5,\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired Wilcoxon signed rank test\n\n Alternative hypothesis: Median of the difference `x - y` is not equal to 0\n\n pValue: 0.2176\n statistic: 2702.5\n\n Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n // Choose custom significance level:\n > out = wilcoxon( arr, { 'alpha': 0.01 });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is not equal to 0\n\n pValue: 0.0413\n statistic: 96\n\n Test Decision: Fail to reject null in favor of alternative at 1% significance level\n\n\n // Test for a median equal to ten:\n > out = wilcoxon( arr, { 'mu': 10 })\n {\n 'rejected': false,\n 'alpha': 0.05,\n 'pValue': 0.11169650413134602,\n 'statistic': 88.5,\n 'nullValue': 10,\n // ...\n }\n\n // Perform one-sided tests:\n > out = wilcoxon( arr, { 'alternative': 'less' });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is less than 0\n\n pValue: 0.9823\n statistic: 96\n\n Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n > out = wilcoxon( arr, { 'alternative': 'greater' });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is greater than 0\n\n pValue: 0.0206\n statistic: 96\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n See Also\n --------\n ttest, ztest\n","writableProperties":"\nwritableProperties( value )\n Returns an array of an object's own writable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own writable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = writableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n inheritedWritableProperties, writablePropertiesIn, properties\n","writablePropertiesIn":"\nwritablePropertiesIn( value )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited writable property names and\n symbols.\n\n Examples\n --------\n > var props = writablePropertiesIn( [] )\n\n See Also\n --------\n inheritedWritableProperties, writableProperties, propertiesIn\n","writablePropertyNames":"\nwritablePropertyNames( value )\n Returns an array of an object's own writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNames( obj )\n [ 'a' ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writableProperties, writablePropertyNamesIn, writablePropertySymbols, propertyNames\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value )\n Returns an array of an object's own and inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNamesIn( obj )\n e.g., [ 'a', ... ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertiesIn, writablePropertyNames, writablePropertySymbolsIn, propertyNamesIn\n","writablePropertySymbols":"\nwritablePropertySymbols( value )\n Returns an array of an object's own writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbols( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writableProperties, writablePropertyNames, writablePropertySymbolsIn, propertySymbols\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited writable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbolsIn( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertiesIn, writablePropertyNamesIn, writablePropertySymbols, propertySymbolsIn\n","writeFile":"\nwriteFile( file, data[, options], clbk )\n Asynchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon writing data to a file.\n\n Examples\n --------\n > function onWrite( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > writeFile( './beep/boop.txt', 'beep boop', onWrite );\n\n\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n See Also\n --------\n exists, readFile\n","writeFile.sync":"\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n See Also\n --------\n exists, readFile","zip":"\nzip( ...arr[, options] )\n Generates array tuples from input arrays.\n\n Parameters\n ----------\n arr: ...Array\n Input arrays to be zipped.\n\n options: Object (optional)\n Options.\n\n options.trunc: boolean (optional)\n Boolean indicating whether to truncate arrays longer than the shortest\n input array. Default: `true`.\n\n options.fill: any (optional)\n Fill value used for arrays of unequal length. Default: `null`.\n\n options.arrays: boolean (optional)\n Boolean indicating whether an input array should be interpreted as an\n array of arrays to be zipped. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n // Basic usage:\n > var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\n [ [ 1, 'a' ], [ 2, 'b' ] ]\n\n // Turn off truncation:\n > var opts = { 'trunc': false };\n > out = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n [ [ 1, 'a' ], [ 2, 'b' ], [ 3, null ] ]\n\n See Also\n --------\n unzip\n","ztest":"\nztest( x, sigma[, options] )\n Computes a one-sample z-test.\n\n The function performs a one-sample z-test for the null hypothesis that the\n data in array or typed array `x` is drawn from a normal distribution with\n mean zero and standard deviation `sigma`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n sigma: number\n Known standard deviation.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for mean.\n\n out.nullValue: number\n Assumed mean value under H0.\n\n out.sd: number\n Standard error.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test (`One-Sample z-test`).\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample z-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ztest( x, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.180,\n statistic: ~-1.34,\n ci: [ ~-0.66, ~0.124 ],\n ...\n }\n\n // Choose custom significance level and print output:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ztest( arr, 2.0, { 'alpha': 0.01 } );\n > table = out.print()\n One-sample z-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0253\n statistic: 2.2361\n 99% confidence interval: [-0.3039,4.3039]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'mu': 5 } )\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~4.123, ~5.877 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'alternative': 'less' } )\n {\n alpha: 0.05,\n rejected: false,\n pValue: 1,\n statistic: 11.180339887498949,\n ci: [ -Infinity, 5.735600904580115 ],\n // ...\n }\n > out = ztest( arr, 1.0, { 'alternative': 'greater' } )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 11.180339887498949,\n ci: [ 4.264399095419885, Infinity ],\n //...\n }\n\n See Also\n --------\n ztest2\n","ztest2":"\nztest2( x, y, sigmax, sigmay[, options] )\n Computes a two-sample z-test.\n\n By default, the function performs a two-sample z-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means and known\n standard deviations `sigmax` and `sigmay`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n sigmax: number\n Known standard deviation of first group.\n\n sigmay: number\n Known standard deviation of second group.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Drawn from Normal(0,2):\n > var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n // Drawn from Normal(1,2):\n > var y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\n > var out = ztest2( x, y, 2.0, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.398,\n statistic: ~-0.844\n ci: [ ~-2.508, ~0.988 ],\n alternative: 'two-sided',\n method: 'Two-sample z-test',\n nullValue: 0,\n xmean: ~0.573,\n ymean: ~1.328\n }\n\n // Print table output:\n > var table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 95% confidence interval: [-2.508,0.998]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 60% confidence interval: [-1.5078,-0.0022]\n\n Test Decision: Reject null in favor of alternative at 40% significance level\n\n // Perform one-sided tests:\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.1993\n statistic: -0.8441\n 95% confidence interval: [-Infinity,0.7162]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.8007\n statistic: -0.8441\n 95% confidence interval: [-2.2262,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 1.0 );\n ... }\n > y = new Array( 100 );\n ... for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 0.0, 2.0 );\n ... }\n > out = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n {\n rejected: false,\n pValue: ~0.35,\n statistic: ~-0.935\n ci: [ ~1.353, ~2.229 ],\n // ...\n }\n\n See Also\n --------\n ztest\n"} \ No newline at end of file diff --git a/lib/node_modules/@stdlib/repl/info/data/data.csv b/lib/node_modules/@stdlib/repl/info/data/data.csv index 1212b6beb8ea..9bf80ae45d25 100644 --- a/lib/node_modules/@stdlib/repl/info/data/data.csv +++ b/lib/node_modules/@stdlib/repl/info/data/data.csv @@ -2068,8 +2068,8 @@ base.strided.scusum,"\nbase.strided.scusum( N:integer, sum:number, x:Float32Arra base.strided.scusum.ndarray,"\nbase.strided.scusum.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n" base.strided.scusumkbn,"\nbase.strided.scusumkbn( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n" base.strided.scusumkbn.ndarray,"\nbase.strided.scusumkbn.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n" -base.strided.scusumkbn2,"\nbase.strided.scusumkbn2( N:integer, sum:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided \n array elements using a second-order iterative Kahan–Babuška algorithm.\n" -base.strided.scusumkbn2.ndarray,"\nbase.strided.scusumkbn2.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n" +base.strided.scusumkbn2,"\nbase.strided.scusumkbn2( N:integer, sum:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm.\n" +base.strided.scusumkbn2.ndarray,"\nbase.strided.scusumkbn2.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n" base.strided.scusumors,"\nbase.strided.scusumors( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n" base.strided.scusumors.ndarray,"\nbase.strided.scusumors.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n" base.strided.scusumpw,"\nbase.strided.scusumpw( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n" diff --git a/lib/node_modules/@stdlib/repl/info/data/data.json b/lib/node_modules/@stdlib/repl/info/data/data.json index afb0773f491d..e92481972f62 100644 --- a/lib/node_modules/@stdlib/repl/info/data/data.json +++ b/lib/node_modules/@stdlib/repl/info/data/data.json @@ -1 +1 @@ -{"abs":"\nabs( x:ndarray|ArrayLikeObject|number[, options:Object] )\n Computes the absolute value.\n","abs.assign":"\nabs.assign( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n Computes the absolute value and assigns results to a provided output array.\n","acartesianPower":"\nacartesianPower( x:ArrayLikeObject, n:integer )\n Returns the Cartesian power.\n","acartesianProduct":"\nacartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n Returns the Cartesian product.\n","acartesianSquare":"\nacartesianSquare( x:ArrayLikeObject )\n Returns the Cartesian square.\n","acronym":"\nacronym( str:string[, options:Object] )\n Generates an acronym for a given string.\n","aempty":"\naempty( length:integer[, dtype:string] )\n Creates an uninitialized array having a specified length.\n","aemptyLike":"\naemptyLike( x:TypedArray|Array[, dtype:string] )\n Creates an uninitialized array having the same length and data type as a\n provided input array.\n","AFINN_96":"\nAFINN_96()\n Returns a list of English words rated for valence.\n","AFINN_111":"\nAFINN_111()\n Returns a list of English words rated for valence.\n","afull":"\nafull( length:integer, value:any[, dtype:string] )\n Returns a filled array having a specified length.\n","afullLike":"\nafullLike( x:TypedArray|Array[, dtype:string] )\n Returns a filled array having the same length and data type as a provided\n input array.\n","alias2pkg":"\nalias2pkg( alias:string )\n Returns the package name associated with a provided alias.\n","alias2related":"\nalias2related( alias:string )\n Returns aliases related to a specified alias.\n","alias2standalone":"\nalias2standalone( alias:string )\n Returns the standalone package name associated with a provided alias.\n","aliases":"\naliases( [namespace:string] )\n Returns a list of standard library aliases.\n","allocUnsafe":"\nallocUnsafe( size:integer )\n Allocates a buffer having a specified number of bytes.\n","amskfilter":"\namskfilter( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n Returns a new array by applying a mask to a provided input array.\n","amskreject":"\namskreject( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n Returns a new array by applying a mask to a provided input array.\n","anans":"\nanans( length:integer[, dtype:string] )\n Returns an array filled with NaNs and having a specified length.\n","anansLike":"\nanansLike( x:TypedArray|Array[, dtype:string] )\n Returns an array filled with NaNs and having the same length and data type\n as a provided input array.\n","anova1":"\nanova1( x:Array, factor:Array[, options:Object] )\n Performs a one-way analysis of variance.\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n","any":"\nany( collection:Array|TypedArray|Object )\n Tests whether at least one element in a collection is truthy.\n","anyBy":"\nanyBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n","anyByAsync":"\nanyByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n","anyByAsync.factory":"\nanyByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n","anyByRight":"\nanyByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n","anyByRightAsync":"\nanyByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n","aones":"\naones( length:integer[, dtype:string] )\n Returns an array filled with ones and having a specified length.\n","aonesLike":"\naonesLike( x:TypedArray|Array[, dtype:string] )\n Returns an array filled with ones and having the same length and data type\n as a provided input array.\n","aoneTo":"\naoneTo( n:integer[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n","aoneToLike":"\naoneToLike( x:TypedArray|Array[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one and having the same length and data type as a provided\n input array.\n","APERY":"\nAPERY\n Apéry's constant.\n","append":"\nappend( collection1:Array|TypedArray|Object, \n collection2:Array|TypedArray|Object )\n Adds the elements of one collection to the end of another collection.\n","ARCH":"\nARCH\n Operating system CPU architecture for which the JavaScript runtime binary\n was compiled.\n","argumentFunction":"\nargumentFunction( idx:integer )\n Returns a function which always returns a specified argument.\n","ARGV":"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n","array":"\narray( [buffer:Array|TypedArray|Buffer|ndarray,] [options:Object] )\n Returns a multidimensional array.\n","array2buffer":"\narray2buffer( arr:Array )\n Allocates a buffer using an octet array.\n","array2fancy":"\narray2fancy( x:Array|TypedArray|Object[, options:Object] )\n Converts an array to an object supporting fancy indexing.\n","array2fancy.factory":"\narray2fancy.factory( [options:Object] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n","array2fancy.idx":"\narray2fancy.idx( x:Array|TypedArray|Object[, options:Object] )\n Wraps a provided array as an array index object.\n","array2iterator":"\narray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n","array2iteratorRight":"\narray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n","ArrayBuffer":"\nArrayBuffer( size:integer )\n Returns an array buffer having a specified number of bytes.\n","ArrayBuffer.length":"\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n","ArrayBuffer.isView":"\nArrayBuffer.isView( arr:any )\n Returns a boolean indicating if provided an array buffer view.\n","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n Copies the bytes of an array buffer to a new array buffer.\n","arraybuffer2buffer":"\narraybuffer2buffer( buf:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Allocates a buffer from an ArrayBuffer.\n","arrayCtors":"\narrayCtors( dtype:string )\n Returns an array constructor.\n","arrayDataType":"\narrayDataType( array:any )\n Returns the data type of an array.\n","arrayDataTypes":"\narrayDataTypes( [kind:string] )\n Returns a list of array data types.\n","ArrayIndex":"\nArrayIndex( x:Array|TypedArray|Object[, options:Object] )\n Wraps a provided array as an array index object.\n","ArrayIndex.free":"\nArrayIndex.free( id:string )\n Frees the instance associated with a provided identifier.\n","ArrayIndex.get":"\nArrayIndex.get( id:string )\n Returns the array associated with the instance having a provided identifier.\n","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n","arrayMinDataType":"\narrayMinDataType( value:any )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast and, for floating-point data types, can be downcast.\n","arrayNextDataType":"\narrayNextDataType( [dtype:string] )\n Returns the next larger array data type of the same kind.\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1:any, dtype2:any] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n","arraySafeCasts":"\narraySafeCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n","arraySameKindCasts":"\narraySameKindCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n","arrayShape":"\narrayShape( arr:ArrayLikeObject )\n Determines array dimensions.\n","arrayStream":"\narrayStream( src:ArrayLikeObject[, options:Object] )\n Creates a readable stream from an array-like object.\n","arrayStream.factory":"\narrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects.\n","arrayStream.objectMode":"\narrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n Returns an \"objectMode\" readable stream from an array-like object.\n","arrayview2iterator":"\narrayview2iterator( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of an array-like object\n view.\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n","aslice":"\naslice( x:ArrayLikeObject[, start:integer[, end:integer]] )\n Returns a shallow copy of a portion of an array.\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n Async iterator symbol.\n","atake":"\natake( x:Array|TypedArray|Object, indices:ArrayLikeObject[, \n options:Object] )\n Takes elements from an array.\n","azeros":"\nazeros( length:integer[, dtype:string] )\n Returns a zero-filled array having a specified length.\n","azerosLike":"\nazerosLike( x:TypedArray|Array[, dtype:string] )\n Returns a zero-filled array having the same length and data type as a\n provided input array.\n","azeroTo":"\nazeroTo( n:integer[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n","azeroToLike":"\nazeroToLike( x:TypedArray|Array[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero and having the same length and data type as a provided\n input array.\n","bartlettTest":"\nbartlettTest( ...x:Array[, options:Object] )\n Computes Bartlett’s test for equal variances.\n","base.abs":"\nbase.abs( x:number )\n Computes the absolute value of a double-precision floating-point number `x`.\n","base.abs2":"\nbase.abs2( x:number )\n Computes the squared absolute value of a double-precision floating-point\n `x`.\n","base.abs2f":"\nbase.abs2f( x:number )\n Computes the squared absolute value of a single-precision floating-point\n `x`.\n","base.absdiff":"\nbase.absdiff( x:number, y:number )\n Computes the absolute difference.\n","base.absf":"\nbase.absf( x:number )\n Computes the absolute value of a single-precision floating-point number `x`.\n","base.acos":"\nbase.acos( x:number )\n Compute the arccosine of a double-precision floating-point number.\n","base.acosh":"\nbase.acosh( x:number )\n Computes the hyperbolic arccosine of a double-precision floating-point\n number.\n","base.acot":"\nbase.acot( x:number )\n Computes the inverse cotangent of a double-precision floating-point number.\n","base.acoth":"\nbase.acoth( x:number )\n Computes the inverse hyperbolic cotangent of a double-precision floating-\n point number.\n","base.acovercos":"\nbase.acovercos( x:number )\n Computes the inverse coversed cosine.\n","base.acoversin":"\nbase.acoversin( x:number )\n Computes the inverse coversed sine.\n","base.acsc":"\nbase.acsc( x:number )\n Computes the arccosecant of a number.\n","base.acsch":"\nbase.acsch( x:number )\n Computes the hyperbolic arccosecant of a number.\n","base.add":"\nbase.add( x:number, y:number )\n Computes the sum of two double-precision floating-point numbers `x` and `y`.\n","base.add3":"\nbase.add3( x:number, y:number, z:number )\n Computes the sum of three double-precision floating-point numbers.\n","base.add4":"\nbase.add4( x:number, y:number, z:number, w:number )\n Computes the sum of four double-precision floating-point numbers.\n","base.add5":"\nbase.add5( x:number, y:number, z:number, w:number, u:number )\n Computes the sum of five double-precision floating-point numbers.\n","base.addf":"\nbase.addf( x:number, y:number )\n Computes the sum of two single-precision floating-point numbers `x` and `y`.\n","base.ahavercos":"\nbase.ahavercos( x:number )\n Computes the inverse half-value versed cosine.\n","base.ahaversin":"\nbase.ahaversin( x:number )\n Computes the inverse half-value versed sine.\n","base.asec":"\nbase.asec( x:number )\n Computes the inverse (arc) secant of a number.\n","base.asech":"\nbase.asech( x:number )\n Computes the hyperbolic arcsecant of a number.\n","base.asin":"\nbase.asin( x:number )\n Computes the arcsine of a double-precision floating-point number.\n","base.asinh":"\nbase.asinh( x:number )\n Computes the hyperbolic arcsine of a double-precision floating-point number.\n","base.atan":"\nbase.atan( x:number )\n Computes the arctangent of a double-precision floating-point number.\n","base.atan2":"\nbase.atan2( y:number, x:number )\n Computes the angle in the plane (in radians) between the positive x-axis and\n the ray from (0,0) to the point (x,y).\n","base.atanh":"\nbase.atanh( x:number )\n Computes the hyperbolic arctangent of a double-precision floating-point\n number.\n","base.avercos":"\nbase.avercos( x:number )\n Computes the inverse versed cosine.\n","base.aversin":"\nbase.aversin( x:number )\n Computes the inverse versed sine.\n","base.bernoulli":"\nbase.bernoulli( n:integer )\n Computes the nth Bernoulli number.\n","base.besselj0":"\nbase.besselj0( x:number )\n Computes the Bessel function of the first kind of order zero.\n","base.besselj1":"\nbase.besselj1( x:number )\n Computes the Bessel function of the first kind of order one.\n","base.bessely0":"\nbase.bessely0( x:number )\n Computes the Bessel function of the second kind of order zero.\n","base.bessely1":"\nbase.bessely1( x:number )\n Computes the Bessel function of the second kind of order one.\n","base.beta":"\nbase.beta( x:number, y:number )\n Evaluates the beta function.\n","base.betainc":"\nbase.betainc( x:number, a:number, b:number[, regularized:boolean[, \n upper:boolean]] )\n Computes the regularized incomplete beta function.\n","base.betaincinv":"\nbase.betaincinv( p:number, a:number, b:number[, upper:boolean] )\n Computes the inverse of the lower incomplete beta function.\n","base.betaln":"\nbase.betaln( a:number, b:number )\n Evaluates the natural logarithm of the beta function.\n","base.binet":"\nbase.binet( x:number )\n Evaluates Binet's formula extended to real numbers.\n","base.binomcoef":"\nbase.binomcoef( n:integer, k:integer )\n Computes the binomial coefficient of two integers.\n","base.binomcoefln":"\nbase.binomcoefln( n:integer, k:integer )\n Computes the natural logarithm of the binomial coefficient of two integers.\n","base.boxcox":"\nbase.boxcox( x:number, lambda:number )\n Computes a one-parameter Box-Cox transformation.\n","base.boxcox1p":"\nbase.boxcox1p( x:number, lambda:number )\n Computes a one-parameter Box-Cox transformation of 1+x.\n","base.boxcox1pinv":"\nbase.boxcox1pinv( y:number, lambda:number )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n","base.boxcoxinv":"\nbase.boxcoxinv( y:number, lambda:number )\n Computes the inverse of a one-parameter Box-Cox transformation.\n","base.cabs":"\nbase.cabs( z:Complex128 )\n Computes the absolute value of a double-precision complex floating-point\n number.\n","base.cabs2":"\nbase.cabs2( z:Complex128 )\n Computes the squared absolute value of a double-precision complex floating-\n point number.\n","base.cabs2f":"\nbase.cabs2f( z:Complex64 )\n Computes the squared absolute value of a single-precision complex floating-\n point number.\n","base.cabsf":"\nbase.cabsf( z:Complex64 )\n Computes the absolute value of a single-precision complex floating-point\n number.\n","base.cadd":"\nbase.cadd( z1:Complex128, z2:Complex128 )\n Adds two double-precision complex floating-point numbers.\n","base.caddf":"\nbase.caddf( z1:Complex64, z2:Complex64 )\n Adds two single-precision complex floating-point numbers.\n","base.cbrt":"\nbase.cbrt( x:number )\n Computes the cube root of a double-precision floating-point number.\n","base.cbrtf":"\nbase.cbrtf( x:number )\n Computes the cube root of a single-precision floating-point number.\n","base.cceil":"\nbase.cceil( z:Complex128 )\n Rounds a double-precision complex floating-point number toward positive\n infinity.\n","base.cceilf":"\nbase.cceilf( z:Complex64 )\n Rounds a single-precision complex floating-point number toward positive\n infinity.\n","base.cceiln":"\nbase.cceiln( z:Complex128, n:integer )\n Rounds each component of a double-precision complex number to the nearest\n multiple of `10^n` toward positive infinity.\n","base.ccis":"\nbase.ccis( z:Complex128 )\n Evaluates the cis function for a double-precision complex floating-point\n number.\n","base.cdiv":"\nbase.cdiv( z1:Complex128, z2:Complex128 )\n Divides two double-precision complex floating-point numbers.\n","base.ceil":"\nbase.ceil( x:number )\n Rounds a double-precision floating-point number toward positive infinity.\n","base.ceil2":"\nbase.ceil2( x:number )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n","base.ceil10":"\nbase.ceil10( x:number )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n","base.ceilb":"\nbase.ceilb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n","base.ceilf":"\nbase.ceilf( x:number )\n Rounds a single-precision floating-point number toward positive infinity.\n","base.ceiln":"\nbase.ceiln( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n","base.ceilsd":"\nbase.ceilsd( x:number, n:integer[, b:integer] )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n","base.cexp":"\nbase.cexp( z:Complex128 )\n Evaluates the exponential function for a double-precision complex floating-\n point number.\n","base.cflipsign":"\nbase.cflipsign( z:Complex128, y:number )\n Returns a double-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n","base.cflipsignf":"\nbase.cflipsignf( z:Complex64, y:number )\n Returns a single-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n","base.cfloor":"\nbase.cfloor( z:Complex128 )\n Rounds a double-precision complex floating-point number toward negative\n infinity.\n","base.cfloorn":"\nbase.cfloorn( z:Complex128, n:integer )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n` toward negative infinity.\n","base.cidentity":"\nbase.cidentity( z:Complex128 )\n Evaluates the identity function for a double-precision complex floating-\n point number.\n","base.cidentityf":"\nbase.cidentityf( z:Complex64 )\n Evaluates the identity function for a single-precision complex floating-\n point number.\n","base.cinv":"\nbase.cinv( z:Complex128 )\n Computes the inverse of a double-precision complex floating-point number.\n","base.clamp":"\nbase.clamp( v:number, min:number, max:number )\n Restricts a double-precision floating-point number to a specified range.\n","base.clampf":"\nbase.clampf( v:number, min:number, max:number )\n Restricts a single-precision floating-point number to a specified range.\n","base.cmul":"\nbase.cmul( z1:Complex128, z2:Complex128 )\n Multiplies two double-precision complex floating-point numbers.\n","base.cmulf":"\nbase.cmulf( z1:Complex64, z2:Complex64 )\n Multiplies two single-precision complex floating-point numbers.\n","base.cneg":"\nbase.cneg( z )\n Negates a double-precision complex floating-point number.\n","base.cnegf":"\nbase.cnegf( z )\n Negates a single-precision complex floating-point number.\n","base.continuedFraction":"\nbase.continuedFraction( generator:Function[, options:Object] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n","base.copysign":"\nbase.copysign( x:number, y:number )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n","base.copysignf":"\nbase.copysignf( x:number, y:number )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n","base.cos":"\nbase.cos( x:number )\n Computes the cosine of a number.\n","base.cosh":"\nbase.cosh( x:number )\n Computes the hyperbolic cosine of a double-precision floating-point number.\n","base.cosm1":"\nbase.cosm1( x:number )\n Computes the cosine of a number minus one.\n","base.cospi":"\nbase.cospi( x:number )\n Computes the value of `cos(πx)`.\n","base.cot":"\nbase.cot( x:number )\n Computes the cotangent of a number.\n","base.coth":"\nbase.coth( x:number )\n Computes the hyperbolic cotangent of a number.\n","base.covercos":"\nbase.covercos( x:number )\n Computes the coversed cosine.\n","base.coversin":"\nbase.coversin( x:number )\n Computes the coversed sine.\n","base.cphase":"\nbase.cphase( z:Complex128 )\n Computes the argument of a double-precision complex floating-point number\n in radians.\n","base.cpolar":"\nbase.cpolar( z:Complex128 )\n Returns the absolute value and phase of a double-precision complex\n floating-point number.\n","base.cpolar.assign":"\nbase.cpolar.assign( z:Complex128, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n","base.cround":"\nbase.cround( z:Complex128 )\n Rounds each component of a double-precision complex floating-point number\n to the nearest integer.\n","base.croundn":"\nbase.croundn( z:Complex128, n:integer )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n`.\n","base.csch":"\nbase.csch( x:number )\n Computes the hyperbolic cosecant of a number.\n","base.csignum":"\nbase.csignum( z:Complex128 )\n Evaluates the signum function of a double-precision complex floating-point\n number.\n","base.csub":"\nbase.csub( z1:Complex128, z2:Complex128 )\n Subtracts two double-precision complex floating-point numbers.\n","base.csubf":"\nbase.csubf( z1:Complex64, z2:Complex64 )\n Subtracts two single-precision complex floating-point numbers.\n","base.deg2rad":"\nbase.deg2rad( x:number )\n Converts an angle from degrees to radians.\n","base.deg2radf":"\nbase.deg2radf( x:number )\n Converts an angle from degrees to radians (single-precision).\n","base.digamma":"\nbase.digamma( x:number )\n Evaluates the digamma function.\n","base.diracDelta":"\nbase.diracDelta( x:number )\n Evaluates the Dirac delta function.\n","base.div":"\nbase.div( x:number, y:number )\n Divides two double-precision floating-point numbers `x` and `y`.\n","base.divf":"\nbase.divf( x:number, y:number )\n Divides two single-precision floating-point numbers `x` and `y`.\n","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a:number, b:number] )\n Returns an arcsine distribution object.\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a:number, b:number )\n Returns the differential entropy of an arcsine distribution (in nats).\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a:number, b:number )\n Returns the excess kurtosis of an arcsine distribution.\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x:number, a:number, b:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x:number, a:number, b:number )\n Evaluates the logarithm of the probability density function (PDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a:number, b:number )\n Returns the expected value of an arcsine distribution.\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a:number, b:number )\n Returns the median of an arcsine distribution.\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a:number, b:number )\n Returns the mode of an arcsine distribution.\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a:number, b:number )\n Returns the skewness of an arcsine distribution.\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a:number, b:number )\n Returns the standard deviation of an arcsine distribution.\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a:number, b:number )\n Returns the variance of an arcsine distribution.\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p:number] )\n Returns a Bernoulli distribution object.\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p` at a value `x`.\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p:number )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p:number )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p:number )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p:number )\n Returns the median of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t:number, p:number )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p:number )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x:number, p:number )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r:number, p:number )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p:number )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p:number )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p:number )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p:number )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α:number, β:number] )\n Returns a beta distribution object.\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α:number, β:number )\n Returns the differential entropy of a beta distribution.\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a beta distribution.\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n","base.dists.beta.mean":"\nbase.dists.beta.mean( α:number, β:number )\n Returns the expected value of a beta distribution.\n","base.dists.beta.median":"\nbase.dists.beta.median( α:number, β:number )\n Returns the median of a beta distribution.\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t:number, α:number, β:number )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n","base.dists.beta.mode":"\nbase.dists.beta.mode( α:number, β:number )\n Returns the mode of a beta distribution.\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α:number, β:number )\n Returns the skewness of a beta distribution.\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α:number, β:number )\n Returns the standard deviation of a beta distribution.\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α:number, β:number )\n Returns the variance of a beta distribution.\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α:number, β:number] )\n Returns a beta prime distribution object.\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a beta prime distribution.\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α:number, β:number )\n Returns the expected value of a beta prime distribution.\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α:number, β:number )\n Returns the mode of a beta prime distribution.\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α:number, β:number )\n Returns the skewness of a beta prime distribution.\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α:number, β:number )\n Returns the standard deviation of a beta prime distribution.\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α:number, β:number )\n Returns the variance of a beta prime distribution.\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n:integer, p:number] )\n Returns a binomial distribution object.\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x:number, n:integer, p:number )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n:integer, p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n:integer, p:number )\n Returns the entropy of a binomial distribution.\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n:integer, p:number )\n Returns the excess kurtosis of a binomial distribution.\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x:number, n:integer, p:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n:integer, p:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n:integer, p:number )\n Returns the expected value of a binomial distribution.\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n:integer, p:number )\n Returns the median of a binomial distribution.\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t:number, n:integer, p:number )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n:integer, p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n:integer, p:number )\n Returns the mode of a binomial distribution.\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x:number, n:integer, p:number )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n:integer, p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r:number, n:integer, p:number )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n:integer, p:number )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n:integer, p:number )\n Returns the skewness of a binomial distribution.\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n:integer, p:number )\n Returns the standard deviation of a binomial distribution.\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n:integer, p:number )\n Returns the variance of a binomial distribution.\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0:number, Ɣ:number] )\n Returns a Cauchy distribution object.\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x:number, x0:number, Ɣ:number )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0:number, Ɣ:number )\n Returns the differential entropy of a Cauchy distribution (in nats).\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x:number, x0:number, Ɣ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x:number, x0:number, Ɣ:number )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0:number, Ɣ:number )\n Returns the median of a Cauchy distribution.\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0:number, Ɣ:number )\n Returns the mode of a Cauchy distribution.\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x:number, x0:number, Ɣ:number )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p:number, x0:number, Ɣ:number )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x:number, k:number )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k:number] )\n Returns a chi distribution object.\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k:number )\n Returns the differential entropy of a chi distribution (in nats).\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k:number )\n Returns the excess kurtosis of a chi distribution.\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x:number, k:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.mean":"\nbase.dists.chi.mean( k:number )\n Returns the expected value of a chi distribution.\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k:number )\n Returns the mode of a chi distribution.\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x:number, k:number )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k:number )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p:number, k:number )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k:number )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k:number )\n Returns the skewness of a chi distribution.\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k:number )\n Returns the standard deviation of a chi distribution.\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k:number )\n Returns the variance of a chi distribution.\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x:number, k:number )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k:number] )\n Returns a chi-squared distribution object.\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k:number )\n Returns the differential entropy of a chi-squared distribution (in nats).\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k:number )\n Returns the excess kurtosis of a chi-squared distribution.\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x:number, k:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k:number )\n Returns the expected value of a chi-squared distribution.\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k:number )\n Returns the median of a chi-squared distribution.\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t:number, k:number )\n Evaluates the moment-generating function (MGF) for a chi-squared\n distribution with degrees of freedom `k` at a value `t`.\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k:number )\n Returns the mode of a chi-squared distribution.\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x:number, k:number )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k:number )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p:number, k:number )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k:number )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k:number )\n Returns the skewness of a chi-squared distribution.\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k:number )\n Returns the standard deviation of a chi-squared distribution.\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k:number )\n Returns the variance of a chi-squared distribution.\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x:number, μ:number, s:number )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ:number, s:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ:number, s:number] )\n Returns a raised cosine distribution object.\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ:number, s:number )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x:number, μ:number, s:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ:number, s:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ:number, s:number )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ:number, s:number )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t:number, μ:number, s:number )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ:number, s:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ:number, s:number )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x:number, μ:number, s:number )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ:number, s:number )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p:number, μ:number, s:number )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ:number, s:number )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ:number, s:number )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ:number, s:number )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ:number, s:number )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x:number, μ:number )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ:number] )\n Returns a degenerate distribution object.\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ:number )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x:number, μ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x:number, μ:number )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x:number, μ:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ:number )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ:number )\n Returns the median of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x:number, μ:number )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ:number )\n Returns the mode of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x:number, μ:number )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x:number, μ:number )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p:number, μ:number )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ:number )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ:number )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ:number )\n Returns the variance of a degenerate distribution with constant value `μ`.\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x:number, a:integer, b:integer )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a:integer, b:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a:integer, b:integer] )\n Returns a discrete uniform distribution object.\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a:integer, b:integer )\n Returns the excess kurtosis of a discrete uniform distribution.\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x:number, a:integer, b:integer )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a:integer, b:integer )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x:number, a:integer, b:integer )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a:integer, b:integer )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a:integer, b:integer )\n Returns the expected value of a discrete uniform distribution.\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a:integer, b:integer )\n Returns the median of a discrete uniform distribution.\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t:number, a:integer, b:integer )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a:integer, b:integer )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x:number, a:integer, b:integer )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a:integer, b:integer )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p:number, a:integer, b:integer )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a:integer, b:integer )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a:integer, b:integer )\n Returns the skewness of a discrete uniform distribution.\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a:integer, b:integer )\n Returns the standard deviation of a discrete uniform distribution.\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a:integer, b:integer )\n Returns the variance of a discrete uniform distribution.\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x:number, k:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k:number, λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k:integer, λ:number )\n Returns the differential entropy of an Erlang distribution (in nats).\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k:number, λ:number] )\n Returns an Erlang distribution object.\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k:integer, λ:number )\n Returns the excess kurtosis of an Erlang distribution.\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x:number, k:number, λ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k:number, λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k:integer, λ:number )\n Returns the expected value of an Erlang distribution.\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t:number, k:number, λ:number )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k:number, λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k:integer, λ:number )\n Returns the mode of an Erlang distribution.\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x:number, k:number, λ:number )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k:number, λ:number )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p:number, k:number, λ:number )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k:number, λ:number )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k:integer, λ:number )\n Returns the skewness of an Erlang distribution.\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k:integer, λ:number )\n Returns the standard deviation of an Erlang distribution.\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k:integer, λ:number )\n Returns the variance of an Erlang distribution.\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ:number )\n Returns the differential entropy of an exponential distribution.\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ:number] )\n Returns an exponential distribution object.\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ:number )\n Returns the excess kurtosis of an exponential distribution.\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x:number, λ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x:number, λ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ:number )\n Returns the expected value of an exponential distribution.\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ:number )\n Returns the median of an exponential distribution.\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t:number, λ:number )\n Evaluates the moment-generating function (MGF) for an exponential\n distribution with rate parameter `λ` at a value `t`.\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ:number )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ:number )\n Returns the mode of an exponential distribution.\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x:number, λ:number )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ:number )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p:number, λ:number )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ:number )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ:number )\n Returns the skewness of an exponential distribution.\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ:number )\n Returns the standard deviation of an exponential distribution.\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ:number )\n Returns the variance of an exponential distribution.\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x:number, d1:number, d2:number )\n Evaluates the cumulative distribution function (CDF) for an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1:number, d2:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n","base.dists.f.entropy":"\nbase.dists.f.entropy( d1:number, d2:number )\n Returns the differential entropy of an F distribution (in nats).\n","base.dists.f.F":"\nbase.dists.f.F( [d1:number, d2:number] )\n Returns an F distribution object.\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1:number, d2:number )\n Returns the excess kurtosis of an F distribution.\n","base.dists.f.mean":"\nbase.dists.f.mean( d1:number, d2:number )\n Returns the expected value of an F distribution.\n","base.dists.f.mode":"\nbase.dists.f.mode( d1:number, d2:number )\n Returns the mode of an F distribution.\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x:number, d1:number, d2:number )\n Evaluates the probability density function (PDF) for an F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1:number, d2:number )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n","base.dists.f.quantile":"\nbase.dists.f.quantile( p:number, d1:number, d2:number )\n Evaluates the quantile function for an F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1:number, d2:number )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n","base.dists.f.skewness":"\nbase.dists.f.skewness( d1:number, d2:number )\n Returns the skewness of an F distribution.\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1:number, d2:number )\n Returns the standard deviation of an F distribution.\n","base.dists.f.variance":"\nbase.dists.f.variance( d1:number, d2:number )\n Returns the variance of an F distribution.\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x:number, α:number, s:number, m:number )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α:number, s:number, m:number )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α:number, s:number, m:number] )\n Returns a Fréchet distribution object.\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α:number, s:number, m:number )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x:number, α:number, s:number, m:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x:number, α:number, s:number, m:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α:number, s:number, m:number )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α:number, s:number, m:number )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α:number, s:number, m:number )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x:number, α:number, s:number, m:number )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p:number, α:number, s:number, m:number )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α:number, s:number, m:number )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α:number, s:number, m:number )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α:number, s:number, m:number )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α:number, s:number, m:number )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α:number, β:number )\n Returns the differential entropy of a gamma distribution.\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α:number, β:number] )\n Returns a gamma distribution object.\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a gamma distribution.\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x:number, α:number, β:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x:number, α:number, β:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α:number, β:number )\n Returns the expected value of a gamma distribution.\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t:number, α:number, β:number )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α:number, β:number )\n Returns the mode of a gamma distribution.\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α:number, β:number )\n Returns the skewness of a gamma distribution.\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α:number, β:number )\n Returns the standard deviation of a gamma distribution.\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α:number, β:number )\n Returns the variance of a gamma distribution.\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p:number )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p:number] )\n Returns a geometric distribution object.\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p:number )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x:number, p:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x:number, p:number )\n Evaluates the logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p:number )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p:number )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p:number )\n Returns the median of a geometric distribution with success probability `p`.\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t:number, p:number )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p:number )\n Returns the mode of a geometric distribution with success probability `p`.\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x:number, p:number )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r:number, p:number )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p:number )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p:number )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p:number )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p:number )\n Returns the variance of a geometric distribution with success probability\n `p`.\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x:number, μ:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ:number, β:number )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ:number, β:number] )\n Returns a Gumbel distribution object.\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ:number, β:number )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x:number, μ:number, β:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ:number, β:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x:number, μ:number, β:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ:number, β:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ:number, β:number )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ:number, β:number )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t:number, μ:number, β:number )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ:number, β:number )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x:number, μ:number, β:number )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ:number, β:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p:number, μ:number, β:number )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ:number, β:number )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ:number, β:number )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ:number, β:number )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ:number, β:number )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x:number, N:integer, K:integer, n:integer )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N:integer, K:integer, n:integer] )\n Returns a hypergeometric distribution object.\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N:integer, K:integer, n:integer )\n Returns the excess kurtosis of a hypergeometric distribution.\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x:number, N:integer, K:integer, n:integer )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N:integer, K:integer, n:integer )\n Returns the expected value of a hypergeometric distribution.\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N:integer, K:integer, n:integer )\n Returns the mode of a hypergeometric distribution.\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x:number, N:integer, K:integer, n:integer )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p:number, N:integer, K:integer, n:integer )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N:integer, K:integer, n:integer )\n Returns the skewness of a hypergeometric distribution.\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N:integer, K:integer, n:integer )\n Returns the standard deviation of a hypergeometric distribution.\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N:integer, K:integer, n:integer )\n Returns the variance of a hypergeometric distribution.\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α:number, β:number )\n Returns the differential entropy of an inverse gamma distribution.\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α:number, β:number] )\n Returns an inverse gamma distribution object.\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α:number, β:number )\n Returns the excess kurtosis of an inverse gamma distribution.\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α:number, β:number )\n Returns the expected value of an inverse gamma distribution.\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α:number, β:number )\n Returns the mode of an inverse gamma distribution.\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α:number, β:number )\n Returns the skewness of an inverse gamma distribution.\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α:number, β:number )\n Returns the standard deviation of an inverse gamma distribution.\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α:number, β:number )\n Returns the variance of an inverse gamma distribution.\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a:number, b:number] )\n Returns a Kumaraswamy's double bounded distribution object.\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a:number, b:number )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a:number, b:number )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a:number, b:number )\n Returns the median of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a:number, b:number )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a:number, b:number )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a:number, b:number )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a:number, b:number )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x:number, μ:number, b:number )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ:number, b:number )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ:number, b:number )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ:number, b:number] )\n Returns a Laplace distribution object.\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x:number, μ:number, b:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x:number, μ:number, b:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ:number, b:number )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ:number, b:number )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t:number, μ:number, b:number )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ:number, b:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ:number, b:number )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x:number, μ:number, b:number )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ:number, b:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p:number, μ:number, b:number )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ:number, b:number )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ:number, b:number )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ:number, b:number )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ:number, b:number )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x:number, μ:number, c:number )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ:number, c:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ:number, c:number )\n Returns the entropy of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ:number, c:number] )\n Returns a Lévy distribution object.\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x:number, μ:number, c:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Lévy distribution with location parameter `μ` and scale parameter `c` at a\n value `x`.\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ:number, c:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x:number, μ:number, c:number )\n Evaluates the logarithm of the probability density function (PDF) for a Lévy\n distribution with location parameter `μ` and scale parameter `c` at a value\n `x`.\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ:number, c:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n","base.dists.levy.mean":"\nbase.dists.levy.mean( μ:number, c:number )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n","base.dists.levy.median":"\nbase.dists.levy.median( μ:number, c:number )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ:number, c:number )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x:number, μ:number, c:number )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ:number, c:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p:number, μ:number, c:number )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ:number, c:number )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ:number, c:number )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ:number, c:number )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x:number, μ:number, s:number )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ:number, s:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ:number, s:number )\n Returns the entropy of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ:number, s:number )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ:number, s:number] )\n Returns a logistic distribution object.\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ:number, s:number )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ:number, s:number )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t:number, μ:number, s:number )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ:number, s:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ:number, s:number )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x:number, μ:number, s:number )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ:number, s:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p:number, μ:number, s:number )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ:number, s:number )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ:number, s:number )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ:number, s:number )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ:number, s:number )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x:number, μ:number, σ:number )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ:number, σ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ:number, σ:number )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ:number, σ:number )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ:number, σ:number] )\n Returns a lognormal distribution object.\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a lognormal distribution with mean `μ` and standard deviation `σ`\n at a value `x`.\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ:number, σ:number )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ:number, σ:number )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ:number, σ:number )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x:number, μ:number, σ:number )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ:number, σ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p:number, μ:number, σ:number )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ:number, σ:number )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ:number, σ:number )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ:number, σ:number )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ:number, σ:number )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x:number, r:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r:number, p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r:integer, p:number )\n Returns the excess kurtosis of a negative binomial distribution.\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x:number, r:number, p:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r:number, p:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r:integer, p:number )\n Returns the expected value of a negative binomial distribution.\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x:number, r:number, p:number )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r:number, p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r:integer, p:number )\n Returns the mode of a negative binomial distribution.\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r:number, p:number] )\n Returns a negative binomial distribution object.\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x:number, r:number, p:number )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r:number, p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k:number, r:number, p:number )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r:number, p:number )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r:integer, p:number )\n Returns the skewness of a negative binomial distribution.\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r:integer, p:number )\n Returns the standard deviation of a negative binomial distribution.\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r:integer, p:number )\n Returns the variance of a negative binomial distribution.\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x:number, μ:number, σ:number )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ:number, σ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ:number, σ:number )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ:number, σ:number )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n a value `x`.\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.mean":"\nbase.dists.normal.mean( μ:number, σ:number )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.median":"\nbase.dists.normal.median( μ:number, σ:number )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x:number, μ:number, σ:number )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ:number, σ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.mode":"\nbase.dists.normal.mode( μ:number, σ:number )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ:number, σ:number] )\n Returns a normal distribution object.\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x:number, μ:number, σ:number )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ:number, σ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p:number, μ:number, σ:number )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ:number, σ:number )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ:number, σ:number )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ:number, σ:number )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ:number, σ:number )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α:number, β:number )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α:number, β:number )\n Returns the expected value of a Pareto (Type I) distribution.\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α:number, β:number )\n Returns the median of a Pareto (Type I) distribution.\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α:number, β:number )\n Returns the mode of a Pareto (Type I) distribution.\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α:number, β:number] )\n Returns a Pareto (Type I) distribution object.\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α:number, β:number )\n Returns the skewness of a Pareto (Type I) distribution.\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α:number, β:number )\n Returns the standard deviation of a Pareto (Type I) distribution.\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α:number, β:number )\n Returns the variance of a Pareto (Type I) distribution.\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ:number )\n Returns the entropy of a Poisson distribution.\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ:number )\n Returns the excess kurtosis of a Poisson distribution.\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x:number, λ:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ:number )\n Returns the expected value of a Poisson distribution.\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ:number )\n Returns the median of a Poisson distribution.\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x:number, λ:number )\n Evaluates the moment-generating function (MGF) for a Poisson distribution\n with mean parameter `λ` at a value `x`.\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ:number )\n Returns the mode of a Poisson distribution.\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x:number, λ:number )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ:number )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ:number] )\n Returns a Poisson distribution object.\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p:number, λ:number )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ:number )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ:number )\n Returns the skewness of a Poisson distribution.\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ:number )\n Returns the standard deviation of a Poisson distribution.\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ:number )\n Returns the variance of a Poisson distribution.\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x:number, sigma:number )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ:number )\n Returns the differential entropy of a Rayleigh distribution.\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ:number )\n Returns the excess kurtosis of a Rayleigh distribution.\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x:number, sigma:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x:number, sigma:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ:number )\n Returns the expected value of a Rayleigh distribution.\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ:number )\n Returns the median of a Rayleigh distribution.\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t:number, sigma:number )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ:number )\n Returns the mode of a Rayleigh distribution.\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x:number, sigma:number )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p:number, sigma:number )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma:number )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ:number] )\n Returns a Rayleigh distribution object.\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ:number )\n Returns the skewness of a Rayleigh distribution.\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ:number )\n Returns the standard deviation of a Rayleigh distribution.\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ:number )\n Returns the variance of a Rayleigh distribution.\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x:number, n:integer )\n Evaluates the cumulative distribution function (CDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x:number, n:integer )\n Evaluates the probability density function (PDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n:integer )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p:number, n:integer )\n Evaluates the quantile function for the Wilcoxon signed rank test statistic\n with `n` observations at a probability `p`.\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n:integer )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n","base.dists.t.cdf":"\nbase.dists.t.cdf( x:number, v:number )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.entropy":"\nbase.dists.t.entropy( v:number )\n Returns the differential entropy of a Student's t distribution.\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v:number )\n Returns the excess kurtosis of a Student's t distribution.\n","base.dists.t.mean":"\nbase.dists.t.mean( v:number )\n Returns the expected value of a Student's t distribution.\n","base.dists.t.median":"\nbase.dists.t.median( v:number )\n Returns the median of a Student's t distribution.\n","base.dists.t.mode":"\nbase.dists.t.mode( v:number )\n Returns the mode of a Student's t distribution.\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x:number, v:number )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.quantile":"\nbase.dists.t.quantile( p:number, v:number )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v:number )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n","base.dists.t.skewness":"\nbase.dists.t.skewness( v:number )\n Returns the skewness of a Student's t distribution.\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v:number )\n Returns the standard deviation of a Student's t distribution.\n","base.dists.t.T":"\nbase.dists.t.T( [v:number] )\n Returns a Student's t distribution object.\n","base.dists.t.variance":"\nbase.dists.t.variance( v:number )\n Returns the variance of a Student's t distribution.\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x:number, a:number, b:number, c:number )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a:number, b:number, c:number )\n Returns the differential entropy of a triangular distribution (in nats).\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a:number, b:number, c:number )\n Returns the excess kurtosis of a triangular distribution.\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x:number, a:number, b:number, c:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x:number, a:number, b:number, c:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a:number, b:number, c:number )\n Returns the expected value of a triangular distribution.\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a:number, b:number, c:number )\n Returns the median of a triangular distribution.\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t:number, a:number, b:number, c:number )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a:number, b:number, c:number )\n Returns the mode of a triangular distribution.\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x:number, a:number, b:number, c:number )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p:number, a:number, b:number, c:number )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a:number, b:number, c:number )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a:number, b:number, c:number )\n Returns the skewness of a triangular distribution.\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a:number, b:number, c:number )\n Returns the standard deviation of a triangular distribution.\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a:number, b:number, c:number] )\n Returns a triangular distribution object.\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a:number, b:number, c:number )\n Returns the variance of a triangular distribution.\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a:number, b:number )\n Returns the differential entropy of a uniform distribution.\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a:number, b:number )\n Returns the excess kurtosis of a uniform distribution.\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x:number, a:number, b:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x:number, a:number, b:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a:number, b:number )\n Returns the expected value of a uniform distribution.\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a:number, b:number )\n Returns the median of a uniform distribution.\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t:number, a:number, b:number )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a:number, b:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a:number, b:number )\n Returns the skewness of a uniform distribution.\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a:number, b:number )\n Returns the standard deviation of a uniform distribution.\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a:number, b:number] )\n Returns a uniform distribution object.\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a:number, b:number )\n Returns the variance of a uniform distribution.\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x:number, k:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k:number, λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k:number, λ:number )\n Returns the differential entropy of a Weibull distribution (in nats).\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k:number, λ:number )\n Returns the excess kurtosis of a Weibull distribution.\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x:number, k:number, λ:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k:number, λ:number)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x:number, k:number, λ:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k:number, λ:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k:number, λ:number )\n Returns the expected value of a Weibull distribution.\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k:number, λ:number )\n Returns the median of a Weibull distribution.\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x:number, k:number, λ:number )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k:number, λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k:number, λ:number )\n Returns the mode of a Weibull distribution.\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x:number, k:number, λ:number )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k:number, λ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p:number, k:number, λ:number )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k:number, λ:number )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k:number, λ:number )\n Returns the skewness of a Weibull distribution.\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k:number, λ:number )\n Returns the standard deviation of a Weibull distribution.\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k:number, λ:number )\n Returns the variance of a Weibull distribution.\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k:number, λ:number] )\n Returns a Weibull distribution object.\n","base.ellipe":"\nbase.ellipe( m:number )\n Computes the complete elliptic integral of the second kind.\n","base.ellipj":"\nbase.ellipj( u:number, m:number )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am.\n","base.ellipj.assign":"\nbase.ellipj.assign( u:number, m:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n","base.ellipj.sn":"\nbase.ellipj.sn( u:number, m:number )\n Computes the Jacobi elliptic function sn.\n","base.ellipj.cn":"\nbase.ellipj.cn( u:number, m:number )\n Computes the Jacobi elliptic functions cn.\n","base.ellipj.dn":"\nbase.ellipj.dn( u:number, m:number )\n Computes the Jacobi elliptic function dn.\n","base.ellipj.am":"\nbase.ellipj.am( u:number, m:number )\n Computes the Jacobi amplitude am.\n","base.ellipk":"\nbase.ellipk( m:number )\n Computes the complete elliptic integral of the first kind.\n","base.epsdiff":"\nbase.epsdiff( x:number, y:number[, scale:string|Function] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n","base.erf":"\nbase.erf( x:number )\n Evaluates the error function.\n","base.erfc":"\nbase.erfc( x:number )\n Evaluates the complementary error function.\n","base.erfcinv":"\nbase.erfcinv( x:number )\n Evaluates the inverse complementary error function.\n","base.erfcx":"\nbase.erfcx( x:number )\n Evaluates the scaled complementary error function.\n","base.erfinv":"\nbase.erfinv( x:number )\n Evaluates the inverse error function.\n","base.eta":"\nbase.eta( s:number )\n Evaluates the Dirichlet eta function as a function of a real variable `s`.\n","base.evalpoly":"\nbase.evalpoly( c:Array, x:number )\n Evaluates a polynomial.\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c:Array )\n Returns a function for evaluating a polynomial.\n","base.evalrational":"\nbase.evalrational( P:Array, Q:Array, x:number )\n Evaluates a rational function.\n","base.evalrational.factory":"\nbase.evalrational.factory( P:Array, Q:Array )\n Returns a function for evaluating a rational function.\n","base.exp":"\nbase.exp( x:number )\n Evaluates the natural exponential function.\n","base.exp2":"\nbase.exp2( x:number )\n Evaluates the base 2 exponential function.\n","base.exp10":"\nbase.exp10( x:number )\n Evaluates the base 10 exponential function.\n","base.expit":"\nbase.expit( x:number )\n Evaluates the standard logistic function.\n","base.expm1":"\nbase.expm1( x:number )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n","base.expm1rel":"\nbase.expm1rel( x:number )\n Relative error exponential.\n","base.exponent":"\nbase.exponent( x:number )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n","base.exponentf":"\nbase.exponentf( x:float )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n","base.factorial":"\nbase.factorial( x:number )\n Evaluates the factorial of `x`.\n","base.factorial2":"\nbase.factorial2( n:number )\n Evaluates the double factorial of `n`.\n","base.factorialln":"\nbase.factorialln( x:number )\n Evaluates the natural logarithm of the factorial of `x`.\n","base.fallingFactorial":"\nbase.fallingFactorial( x:number, n:integer )\n Computes the falling factorial of `x` and `n`.\n","base.fibonacci":"\nbase.fibonacci( n:integer )\n Computes the nth Fibonacci number.\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F:integer )\n Computes the Fibonacci number index.\n","base.fibpoly":"\nbase.fibpoly( n:integer, x:number )\n Evaluates a Fibonacci polynomial.\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n:integer )\n Returns a function for evaluating a Fibonacci polynomial.\n","base.firstCodePoint":"\nbase.firstCodePoint( str:string, n:integer )\n Returns the first `n` Unicode code points of a string.\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str:string, n:integer )\n Returns the first `n` UTF-16 code units of a string.\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str:string, n:integer )\n Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n","base.flipsign":"\nbase.flipsign( x:number, y:number )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n","base.flipsignf":"\nbase.flipsignf( x:number, y:number )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n","base.float32ToInt32":"\nbase.float32ToInt32( x:float )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n","base.float32ToUint32":"\nbase.float32ToUint32( x:float )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n","base.float64ToFloat32":"\nbase.float64ToFloat32( x:number )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n","base.float64ToInt32":"\nbase.float64ToInt32( x:number )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x:integer )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness).\n","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n","base.float64ToUint32":"\nbase.float64ToUint32( x:number )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n","base.floor":"\nbase.floor( x:number )\n Rounds a double-precision floating-point number toward negative infinity.\n","base.floor2":"\nbase.floor2( x:number )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n","base.floor10":"\nbase.floor10( x:number )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n","base.floorb":"\nbase.floorb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n","base.floorf":"\nbase.floorf( x:number )\n Rounds a single-precision floating-point number toward negative infinity.\n","base.floorn":"\nbase.floorn( x:number, n:integer )\n Rounds a double-precision floating-point number to the nearest multiple of\n `10^n` toward negative infinity.\n","base.floorsd":"\nbase.floorsd( x:number, n:integer[, b:integer] )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n","base.forEachChar":"\nbase.forEachChar( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each UTF-16 code unit in a string.\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each Unicode code point in a string.\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each grapheme cluster (i.e., user-perceived\n character) in a string.\n","base.fresnel":"\nbase.fresnel( x:number )\n Computes the Fresnel integrals S(x) and C(x).\n","base.fresnel.assign":"\nbase.fresnel.assign( x:number, out:Array, stride:integer, \n offset:integer )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n","base.fresnelc":"\nbase.fresnelc( x:number )\n Computes the Fresnel integral C(x).\n","base.fresnels":"\nbase.fresnels( x:number )\n Computes the Fresnel integral S(x).\n","base.frexp":"\nbase.frexp( x:number )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n","base.frexp.assign":"\nbase.frexp.assign( x:number, out:Array, stride:integer, offset:integer )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n","base.fromBinaryString":"\nbase.fromBinaryString( bstr:string )\n Creates a double-precision floating-point number from a literal bit\n representation.\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr:string )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr:string )\n Creates an unsigned 8-bit integer from a literal bit representation.\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr:string )\n Creates an unsigned 16-bit integer from a literal bit representation.\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr:string )\n Creates an unsigned 32-bit integer from a literal bit representation.\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Converts a signed 64-bit integer byte array to a double-precision floating-\n point number.\n","base.fromWordf":"\nbase.fromWordf( word:integer )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n","base.fromWords":"\nbase.fromWords( high:integer, low:integer )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.gamma":"\nbase.gamma( x:number )\n Evaluates the gamma function.\n","base.gamma1pm1":"\nbase.gamma1pm1( x:number )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z:number, delta:number )\n Computes the ratio of two gamma functions.\n","base.gammainc":"\nbase.gammainc( x:number, s:number[, regularized:boolean[, upper:boolean]] )\n Computes the regularized incomplete gamma function.\n","base.gammaincinv":"\nbase.gammaincinv( p:number, a:number[, upper:boolean] )\n Computes the inverse of the lower incomplete gamma function.\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x:number )\n Calculates the Lanczos sum for the approximation of the gamma function.\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x:number )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n","base.gammaln":"\nbase.gammaln( x:number )\n Evaluates the natural logarithm of the gamma function.\n","base.gcd":"\nbase.gcd( a:integer, b:integer )\n Computes the greatest common divisor (gcd).\n","base.getHighWord":"\nbase.getHighWord( x:number )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n","base.getLowWord":"\nbase.getLowWord( x:number )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n","base.hacovercos":"\nbase.hacovercos( x:number )\n Computes the half-value coversed cosine.\n","base.hacoversin":"\nbase.hacoversin( x:number )\n Computes the half-value coversed sine.\n","base.havercos":"\nbase.havercos( x:number )\n Computes the half-value versed cosine.\n","base.haversin":"\nbase.haversin( x:number )\n Computes the half-value versed sine.\n","base.heaviside":"\nbase.heaviside( x:number[, continuity:string] )\n Evaluates the Heaviside function.\n","base.hermitepoly":"\nbase.hermitepoly( n:integer, x:number )\n Evaluates a physicist's Hermite polynomial.\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n:integer )\n Returns a function for evaluating a physicist's Hermite polynomial.\n","base.hypot":"\nbase.hypot( x:number, y:number )\n Computes the hypotenuse avoiding overflow and underflow.\n","base.hypotf":"\nbase.hypotf( x:number, y:number )\n Computes the hypotenuse avoiding overflow and underflow (single-precision).\n","base.identity":"\nbase.identity( x:number )\n Evaluates the identity function for a double-precision floating-point number\n `x`.\n","base.identityf":"\nbase.identityf( x:number )\n Evaluates the identity function for a single-precision floating-point number\n `x`.\n","base.imul":"\nbase.imul( a:integer, b:integer )\n Performs C-like multiplication of two signed 32-bit integers.\n","base.imuldw":"\nbase.imuldw( a:integer, b:integer )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n","base.imuldw.assign":"\nbase.imuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n","base.int32ToUint32":"\nbase.int32ToUint32( x:integer )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n","base.inv":"\nbase.inv( x:number )\n Computes the multiplicative inverse of a double-precision floating-point\n number `x`.\n","base.invf":"\nbase.invf( x:number )\n Computes the multiplicative inverse of a single-precision floating-point\n number `x`.\n","base.isComposite":"\nbase.isComposite( x:number )\n Tests if a number is composite.\n","base.isCoprime":"\nbase.isCoprime( a:number, b:number )\n Tests if two numbers are coprime.\n","base.isEven":"\nbase.isEven( x:number )\n Tests if a finite numeric value is an even number.\n","base.isEvenInt32":"\nbase.isEvenInt32( x:integer )\n Tests if a 32-bit integer is even.\n","base.isFinite":"\nbase.isFinite( x:number )\n Tests if a double-precision floating-point numeric value is finite.\n","base.isFinitef":"\nbase.isFinitef( x:number )\n Tests if a single-precision floating-point numeric value is finite.\n","base.isInfinite":"\nbase.isInfinite( x:number )\n Tests if a double-precision floating-point numeric value is infinite.\n","base.isInfinitef":"\nbase.isInfinitef( x:number )\n Tests if a single-precision floating-point numeric value is infinite.\n","base.isInteger":"\nbase.isInteger( x:number )\n Tests if a finite double-precision floating-point number is an integer.\n","base.isnan":"\nbase.isnan( x:number )\n Tests if a double-precision floating-point numeric value is `NaN`.\n","base.isnanf":"\nbase.isnanf( x:number )\n Tests if a single-precision floating-point numeric value is `NaN`.\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x:number )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n","base.isNegativeZero":"\nbase.isNegativeZero( x:number )\n Tests if a double-precision floating-point numeric value is negative zero.\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x:number )\n Tests if a single-precision floating-point numeric value is negative zero.\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x:number )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x:number )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n","base.isOdd":"\nbase.isOdd( x:number )\n Tests if a finite numeric value is an odd number.\n","base.isOddInt32":"\nbase.isOddInt32( x:integer )\n Tests if a 32-bit integer is odd.\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x:number )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n","base.isPositiveZero":"\nbase.isPositiveZero( x:number )\n Tests if a double-precision floating-point numeric value is positive zero.\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x:number )\n Tests if a single-precision floating-point numeric value is positive zero.\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x:integer )\n Tests whether an unsigned integer is a power of 2.\n","base.isPrime":"\nbase.isPrime( x:number )\n Tests if a number is prime.\n","base.isProbability":"\nbase.isProbability( x:number )\n Tests if a double-precision floating-point number value is a probability.\n","base.isSafeInteger":"\nbase.isSafeInteger( x:number )\n Tests if a finite double-precision floating-point number is a safe integer.\n","base.kernelBetainc":"\nbase.kernelBetainc( x:number, a:number, b:number, regularized:boolean, \n upper:boolean )\n Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x:number, a:number, b:number, regularized:boolean, \n upper:boolean, out:Array|TypedArray|Object, stride:integer, offset:integer )\n Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a:number, b:number, p:number, q:number )\n Computes the inverse of the lower incomplete beta function.\n","base.kernelCos":"\nbase.kernelCos( x:number, y:number )\n Computes the cosine of a double-precision floating-point number on the\n interval [-π/4, π/4].\n","base.kernelSin":"\nbase.kernelSin( x:number, y:number )\n Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n","base.kernelTan":"\nbase.kernelTan( x:number, y:number, k:integer )\n Computes the tangent of a double-precision floating-point number on the\n interval [-π/4, π/4].\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i:number, j:number )\n Evaluates the Kronecker delta.\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i:number, j:number )\n Evaluates the Kronecker delta (single-precision).\n","base.labs":"\nbase.labs( x:integer )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n","base.lcm":"\nbase.lcm( a:integer, b:integer )\n Computes the least common multiple (lcm).\n","base.ldexp":"\nbase.ldexp( frac:number, exp:number )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n","base.ln":"\nbase.ln( x:number )\n Evaluates the natural logarithm of a double-precision floating-point number.\n","base.log":"\nbase.log( x:number, b:number )\n Computes the base `b` logarithm of `x`.\n","base.log1mexp":"\nbase.log1mexp( x:number )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n","base.log1p":"\nbase.log1p( x:number )\n Evaluates the natural logarithm of `1+x`.\n","base.log1pexp":"\nbase.log1pexp( x:number )\n Evaluates the natural logarithm of `1+exp(x)`.\n","base.log1pmx":"\nbase.log1pmx( x:number )\n Evaluates `ln(1+x) - x`.\n","base.log2":"\nbase.log2( x:number )\n Evaluates the binary logarithm (base two).\n","base.log10":"\nbase.log10( x:number )\n Evaluates the common logarithm (base 10).\n","base.logaddexp":"\nbase.logaddexp( x:number, y:number )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n","base.logit":"\nbase.logit( p:number )\n Evaluates the logit function.\n","base.lucas":"\nbase.lucas( n:integer )\n Computes the nth Lucas number.\n","base.lucaspoly":"\nbase.lucaspoly( n:integer, x:number )\n Evaluates a Lucas polynomial.\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n:integer )\n Returns a function for evaluating a Lucas polynomial.\n","base.max":"\nbase.max( x:number, y:number )\n Returns the maximum value.\n","base.maxabs":"\nbase.maxabs( x:number, y:number )\n Returns the maximum absolute value.\n","base.maxn":"\nbase.maxn( [x:number[, y:number[, ...args:number]]] )\n Returns the maximum value.\n","base.min":"\nbase.min( x:number, y:number )\n Returns the minimum value.\n","base.minabs":"\nbase.minabs( x:number, y:number )\n Returns the minimum absolute value.\n","base.minmax":"\nbase.minmax( x:number, y:number )\n Returns the minimum and maximum values.\n","base.minmax.assign":"\nbase.minmax.assign( x:number, y:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n","base.minmaxabs":"\nbase.minmaxabs( x:number, y:number )\n Returns the minimum and maximum absolute values.\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x:number, y:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Returns the minimum and maximum absolute values.\n","base.minn":"\nbase.minn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum value.\n","base.modf":"\nbase.modf( x:number )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n","base.modf.assign":"\nbase.modf.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n","base.mul":"\nbase.mul( x:number, y:number )\n Multiplies two double-precision floating-point numbers `x` and `y`.\n","base.mulf":"\nbase.mulf( x:number, y:number )\n Multiplies two single-precision floating-point numbers `x` and `y`.\n","base.ndarray":"\nbase.ndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string )\n Returns an ndarray.\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n Underlying data type.\n","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n Number of dimensions.\n","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n Array order.\n","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n Array shape.\n","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in an input ndarray and assigns results\n to elements in an output ndarray.\n","base.ndzeros":"\nbase.ndzeros( dtype:string, shape:ArrayLikeObject, order:string )\n Returns a zero-filled ndarray having a specified shape and data type.\n","base.ndzerosLike":"\nbase.ndzerosLike( x:ndarray )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n","base.negafibonacci":"\nbase.negafibonacci( n:integer )\n Computes the nth negaFibonacci number.\n","base.negalucas":"\nbase.negalucas( n:integer )\n Computes the nth negaLucas number.\n","base.nonfibonacci":"\nbase.nonfibonacci( n:integer )\n Computes the nth non-Fibonacci number.\n","base.normalize":"\nbase.normalize( x:number )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n","base.normalize.assign":"\nbase.normalize.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n","base.normalizef":"\nbase.normalizef( x:float )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n","base.normalizef.assign":"\nbase.normalizef.assign( x:float, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n assigns results to a provided output array.\n","base.normhermitepoly":"\nbase.normhermitepoly( n:integer, x:number )\n Evaluates a normalized Hermite polynomial.\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n:integer )\n Returns a function for evaluating a normalized Hermite polynomial.\n","base.pdiff":"\nbase.pdiff( x:number, y:number )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n","base.pdifff":"\nbase.pdifff( x:number, y:number )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n","base.polygamma":"\nbase.polygamma( n:integer, x:number )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n","base.pow":"\nbase.pow( b:number, x:number )\n Evaluates the exponential function `bˣ`.\n","base.powm1":"\nbase.powm1( b:number, x:number )\n Evaluates `bˣ - 1`.\n","base.rad2deg":"\nbase.rad2deg( x:number )\n Converts an angle from radians to degrees.\n","base.ramp":"\nbase.ramp( x:number )\n Evaluates the ramp function.\n","base.rampf":"\nbase.rampf( x:number )\n Evaluates the ramp function (single-precision).\n","base.random.arcsine":"\nbase.random.arcsine( a:number, b:number )\n Returns a pseudorandom number drawn from an arcsine distribution.\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n Generator name.\n","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n Length of generator seed.\n","base.random.arcsine.state":"\nbase.random.arcsine.state\n Generator state.\n","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n Length of generator state.\n","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.bernoulli":"\nbase.random.bernoulli( p:number )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n Generator name.\n","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n Length of generator seed.\n","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n Generator state.\n","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n Length of generator state.\n","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.beta":"\nbase.random.beta( α:number, β:number )\n Returns a pseudorandom number drawn from a beta distribution.\n","base.random.beta.factory":"\nbase.random.beta.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n","base.random.beta.NAME":"\nbase.random.beta.NAME\n Generator name.\n","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n","base.random.beta.seed":"\nbase.random.beta.seed\n Pseudorandom number generator seed.\n","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n Length of generator seed.\n","base.random.beta.state":"\nbase.random.beta.state\n Generator state.\n","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n Length of generator state.\n","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.betaprime":"\nbase.random.betaprime( α:number, β:number )\n Returns a pseudorandom number drawn from a beta prime distribution.\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n Generator name.\n","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n Length of generator seed.\n","base.random.betaprime.state":"\nbase.random.betaprime.state\n Generator state.\n","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n Length of generator state.\n","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.binomial":"\nbase.random.binomial( n:integer, p:number )\n Returns a pseudorandom number drawn from a binomial distribution.\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n:integer, p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n Generator name.\n","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n","base.random.binomial.seed":"\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n Length of generator seed.\n","base.random.binomial.state":"\nbase.random.binomial.state\n Generator state.\n","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n Length of generator state.\n","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n Size of generator state.\n","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.boxMuller":"\nbase.random.boxMuller()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n Generator name.\n","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n Length of generator seed.\n","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n Generator state.\n","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n Length of generator state.\n","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.cauchy":"\nbase.random.cauchy( x0:number, Ɣ:number )\n Returns a pseudorandom number drawn from a Cauchy distribution.\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0:number, Ɣ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n Generator name.\n","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n Length of generator seed.\n","base.random.cauchy.state":"\nbase.random.cauchy.state\n Generator state.\n","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n Length of generator state.\n","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.chi":"\nbase.random.chi( k:number )\n Returns a pseudorandom number drawn from a chi distribution.\n","base.random.chi.factory":"\nbase.random.chi.factory( [k:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n","base.random.chi.NAME":"\nbase.random.chi.NAME\n Generator name.\n","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n","base.random.chi.seed":"\nbase.random.chi.seed\n Pseudorandom number generator seed.\n","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n Length of generator seed.\n","base.random.chi.state":"\nbase.random.chi.state\n Generator state.\n","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n Length of generator state.\n","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.chisquare":"\nbase.random.chisquare( k:number )\n Returns a pseudorandom number drawn from a chi-square distribution.\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n Generator name.\n","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n Length of generator seed.\n","base.random.chisquare.state":"\nbase.random.chisquare.state\n Generator state.\n","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n Length of generator state.\n","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.cosine":"\nbase.random.cosine( μ:number, s:number )\n Returns a pseudorandom number drawn from a raised cosine distribution.\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ:number, s:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n Generator name.\n","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n","base.random.cosine.seed":"\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n Length of generator seed.\n","base.random.cosine.state":"\nbase.random.cosine.state\n Generator state.\n","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n Length of generator state.\n","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.discreteUniform":"\nbase.random.discreteUniform( a:integer, b:integer )\n Returns a pseudorandom number drawn from a discrete uniform distribution.\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a:integer, b:integer, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n Generator name.\n","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n Generator state.\n","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n Length of generator state.\n","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.erlang":"\nbase.random.erlang( k:integer, λ:number )\n Returns a pseudorandom number drawn from an Erlang distribution.\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k:integer, λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n Generator name.\n","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n","base.random.erlang.seed":"\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n Length of generator seed.\n","base.random.erlang.state":"\nbase.random.erlang.state\n Generator state.\n","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n Length of generator state.\n","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.exponential":"\nbase.random.exponential( λ:number )\n Returns a pseudorandom number drawn from an exponential distribution.\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n Generator name.\n","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n","base.random.exponential.seed":"\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n Length of generator seed.\n","base.random.exponential.state":"\nbase.random.exponential.state\n Generator state.\n","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n Length of generator state.\n","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.f":"\nbase.random.f( d1:number, d2:number )\n Returns a pseudorandom number drawn from an F distribution.\n","base.random.f.factory":"\nbase.random.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n","base.random.f.NAME":"\nbase.random.f.NAME\n Generator name.\n","base.random.f.PRNG":"\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n","base.random.f.seed":"\nbase.random.f.seed\n Pseudorandom number generator seed.\n","base.random.f.seedLength":"\nbase.random.f.seedLength\n Length of generator seed.\n","base.random.f.state":"\nbase.random.f.state\n Generator state.\n","base.random.f.stateLength":"\nbase.random.f.stateLength\n Length of generator state.\n","base.random.f.byteLength":"\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n","base.random.f.toJSON":"\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.frechet":"\nbase.random.frechet( α:number, s:number, m:number )\n Returns a pseudorandom number drawn from a Fréchet distribution.\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α:number, s:number, m:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n Generator name.\n","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n","base.random.frechet.seed":"\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n Length of generator seed.\n","base.random.frechet.state":"\nbase.random.frechet.state\n Generator state.\n","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n Length of generator state.\n","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.gamma":"\nbase.random.gamma( α:number, β:number )\n Returns a pseudorandom number drawn from a gamma distribution.\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n Generator name.\n","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n","base.random.gamma.seed":"\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n Length of generator seed.\n","base.random.gamma.state":"\nbase.random.gamma.state\n Generator state.\n","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n Length of generator state.\n","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n Size of generator state.\n","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.geometric":"\nbase.random.geometric( p:number )\n Returns a pseudorandom number drawn from a geometric distribution.\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n Generator name.\n","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n","base.random.geometric.seed":"\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n Length of generator seed.\n","base.random.geometric.state":"\nbase.random.geometric.state\n Generator state.\n","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n Length of generator state.\n","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.gumbel":"\nbase.random.gumbel( μ:number, β:number )\n Returns a pseudorandom number drawn from a Gumbel distribution.\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n Generator name.\n","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n Length of generator seed.\n","base.random.gumbel.state":"\nbase.random.gumbel.state\n Generator state.\n","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n Length of generator state.\n","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.hypergeometric":"\nbase.random.hypergeometric( N:integer, K:integer, n:integer )\n Returns a pseudorandom number drawn from a hypergeometric distribution.\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N:integer, K:integer, n:integer, ]\n [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n Generator name.\n","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n Generator state.\n","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n Length of generator state.\n","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n Generator name.\n","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n Generator state.\n","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.invgamma":"\nbase.random.invgamma( α:number, β:number )\n Returns a pseudorandom number drawn from an inverse gamma distribution.\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n Generator name.\n","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n Length of generator seed.\n","base.random.invgamma.state":"\nbase.random.invgamma.state\n Generator state.\n","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n Length of generator state.\n","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n Size of generator state.\n","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a:number, b:number )\n Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n distribution.\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n Generator name.\n","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n Generator state.\n","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.laplace":"\nbase.random.laplace( μ:number, b:number )\n Returns a pseudorandom number drawn from a Laplace distribution.\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n Generator name.\n","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n","base.random.laplace.seed":"\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n Length of generator seed.\n","base.random.laplace.state":"\nbase.random.laplace.state\n Generator state.\n","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n Length of generator state.\n","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.levy":"\nbase.random.levy( μ:number, c:number )\n Returns a pseudorandom number drawn from a Lévy distribution.\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ:number, c:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n","base.random.levy.NAME":"\nbase.random.levy.NAME\n Generator name.\n","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n","base.random.levy.seed":"\nbase.random.levy.seed\n Pseudorandom number generator seed.\n","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n Length of generator seed.\n","base.random.levy.state":"\nbase.random.levy.state\n Generator state.\n","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n Length of generator state.\n","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.logistic":"\nbase.random.logistic( μ:number, s:number )\n Returns a pseudorandom number drawn from a logistic distribution.\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ:number, s:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n Generator name.\n","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n","base.random.logistic.seed":"\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n Length of generator seed.\n","base.random.logistic.state":"\nbase.random.logistic.state\n Generator state.\n","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n Length of generator state.\n","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.lognormal":"\nbase.random.lognormal( μ:number, σ:number )\n Returns a pseudorandom number drawn from a lognormal distribution.\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n Generator name.\n","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n Length of generator seed.\n","base.random.lognormal.state":"\nbase.random.lognormal.state\n Generator state.\n","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n Length of generator state.\n","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstd":"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstd.factory":"\nbase.random.minstd.factory( [options:Object] )\n Returns a linear congruential pseudorandom number generator (LCG).\n","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n Generator name.\n","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n Minimum possible value.\n","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n Maximum possible value.\n","base.random.minstd.seed":"\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n Length of generator seed.\n","base.random.minstd.state":"\nbase.random.minstd.state\n Generator state.\n","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n Length of generator state.\n","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options:Object] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n Generator name.\n","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n Generator state.\n","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.mt19937":"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options:Object] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n Generator name.\n","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n Minimum possible value.\n","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n Maximum possible value.\n","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n Length of generator seed.\n","base.random.mt19937.state":"\nbase.random.mt19937.state\n Generator state.\n","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n Length of generator state.\n","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r:number, p:number )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n Generator name.\n","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n Generator state.\n","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.normal":"\nbase.random.normal( μ:number, σ:number )\n Returns a pseudorandom number drawn from a normal distribution.\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n","base.random.normal.NAME":"\nbase.random.normal.NAME\n Generator name.\n","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n","base.random.normal.seed":"\nbase.random.normal.seed\n Pseudorandom number generator seed.\n","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n Length of generator seed.\n","base.random.normal.state":"\nbase.random.normal.state\n Generator state.\n","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n Length of generator state.\n","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n Size of generator state.\n","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.pareto1":"\nbase.random.pareto1( α:number, β:number )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n Generator name.\n","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n Length of generator seed.\n","base.random.pareto1.state":"\nbase.random.pareto1.state\n Generator state.\n","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n Length of generator state.\n","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.poisson":"\nbase.random.poisson( λ:number )\n Returns a pseudorandom number drawn from a Poisson distribution.\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n Generator name.\n","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n","base.random.poisson.seed":"\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n Length of generator seed.\n","base.random.poisson.state":"\nbase.random.poisson.state\n Generator state.\n","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n Length of generator state.\n","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randi":"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n","base.random.randi.factory":"\nbase.random.randi.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n","base.random.randi.NAME":"\nbase.random.randi.NAME\n Generator name.\n","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n","base.random.randi.MIN":"\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n","base.random.randi.MAX":"\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n","base.random.randi.seed":"\nbase.random.randi.seed\n Pseudorandom number generator seed.\n","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n Length of generator seed.\n","base.random.randi.state":"\nbase.random.randi.state\n Generator state.\n","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n Length of generator state.\n","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randn":"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.randn.factory":"\nbase.random.randn.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.randn.NAME":"\nbase.random.randn.NAME\n Generator name.\n","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n","base.random.randn.seed":"\nbase.random.randn.seed\n Pseudorandom number generator seed.\n","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n Length of generator seed.\n","base.random.randn.state":"\nbase.random.randn.state\n Generator state.\n","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n Length of generator state.\n","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randu":"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n","base.random.randu.factory":"\nbase.random.randu.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n","base.random.randu.NAME":"\nbase.random.randu.NAME\n Generator name.\n","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n","base.random.randu.MIN":"\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n","base.random.randu.MAX":"\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n","base.random.randu.seed":"\nbase.random.randu.seed\n Pseudorandom number generator seed.\n","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n Length of generator seed.\n","base.random.randu.state":"\nbase.random.randu.state\n Generator state.\n","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n Length of generator state.\n","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.rayleigh":"\nbase.random.rayleigh( σ:number )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n Generator name.\n","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n Length of generator seed.\n","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n Generator state.\n","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n Length of generator state.\n","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.t":"\nbase.random.t( v:number )\n Returns a pseudorandom number drawn from a Student's t distribution.\n","base.random.t.factory":"\nbase.random.t.factory( [v:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n","base.random.t.NAME":"\nbase.random.t.NAME\n Generator name.\n","base.random.t.PRNG":"\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n","base.random.t.seed":"\nbase.random.t.seed\n Pseudorandom number generator seed.\n","base.random.t.seedLength":"\nbase.random.t.seedLength\n Length of generator seed.\n","base.random.t.state":"\nbase.random.t.state\n Generator state.\n","base.random.t.stateLength":"\nbase.random.t.stateLength\n Length of generator state.\n","base.random.t.byteLength":"\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n","base.random.t.toJSON":"\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.triangular":"\nbase.random.triangular( a:number, b:number, c:number )\n Returns a pseudorandom number drawn from a triangular distribution.\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n Generator name.\n","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n","base.random.triangular.seed":"\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n Length of generator seed.\n","base.random.triangular.state":"\nbase.random.triangular.state\n Generator state.\n","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n Length of generator state.\n","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.uniform":"\nbase.random.uniform( a:number, b:number )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n Generator name.\n","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n","base.random.uniform.seed":"\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n Length of generator seed.\n","base.random.uniform.state":"\nbase.random.uniform.state\n Generator state.\n","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n Length of generator state.\n","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.weibull":"\nbase.random.weibull( k:number, λ:number )\n Returns a pseudorandom number drawn from a Weibull distribution.\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k:number, λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n Generator name.\n","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n","base.random.weibull.seed":"\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n Length of generator seed.\n","base.random.weibull.state":"\nbase.random.weibull.state\n Generator state.\n","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n Length of generator state.\n","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.reldiff":"\nbase.reldiff( x:number, y:number[, scale:string|Function] )\n Computes the relative difference of two real numbers.\n","base.rempio2":"\nbase.rempio2( x:number, y:Array|TypedArray|Object )\n Computes `x - nπ/2 = r`.\n","base.risingFactorial":"\nbase.risingFactorial( x:number, n:integer )\n Computes the rising factorial of `x` and `n`.\n","base.rotl32":"\nbase.rotl32( x:integer, shift:integer )\n Performs a bitwise rotation to the left.\n","base.rotr32":"\nbase.rotr32( x:integer, shift:integer )\n Performs a bitwise rotation to the right.\n","base.round":"\nbase.round( x:number )\n Rounds a numeric value to the nearest integer.\n","base.round2":"\nbase.round2( x:number )\n Rounds a numeric value to the nearest power of two on a linear scale.\n","base.round10":"\nbase.round10( x:number )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n","base.roundb":"\nbase.roundb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n","base.roundn":"\nbase.roundn( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n`.\n","base.roundsd":"\nbase.roundsd( x:number, n:integer[, b:integer] )\n Rounds a numeric value to the nearest number with `n` significant figures.\n","base.rsqrt":"\nbase.rsqrt( x:number )\n Computes the reciprocal square root of a double-precision floating-point\n number.\n","base.rsqrtf":"\nbase.rsqrtf( x:number )\n Computes the reciprocal square root of a single-precision floating-point\n number.\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value:any, dtype:string, order:string )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n","base.setHighWord":"\nbase.setHighWord( x:number, high:integer )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n","base.setLowWord":"\nbase.setLowWord( x:number, low:integer )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n","base.sici":"\nbase.sici( x:number )\n Computes the sine and cosine integrals.\n","base.sici.assign":"\nbase.sici.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n","base.signbit":"\nbase.signbit( x:number )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.signbitf":"\nbase.signbitf( x:float )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.significandf":"\nbase.significandf( x:float )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n","base.signum":"\nbase.signum( x:number )\n Evaluates the signum function for a double-precision floating-point number.\n","base.signumf":"\nbase.signumf( x:number )\n Evaluates the signum function for a single-precision floating-point number.\n","base.sin":"\nbase.sin( x:number )\n Computes the sine of a number.\n","base.sinc":"\nbase.sinc( x:number )\n Computes the normalized cardinal sine of a number.\n","base.sincos":"\nbase.sincos( x:number )\n Simultaneously computes the sine and cosine of a number.\n\nbase.sincos( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Simultaneously computes the sine and cosine of a number and assigns\n results to a provided output array.\n","base.sincospi":"\nbase.sincospi( x:number )\n Simultaneously computes the sine and cosine of a number times π.\n","base.sincospi.assign":"\nbase.sincospi.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n","base.sinh":"\nbase.sinh( x:number )\n Computes the hyperbolic sine of a double-precision floating-point number.\n","base.sinpi":"\nbase.sinpi( x:number )\n Computes the value of `sin(πx)`.\n","base.spence":"\nbase.spence( x:number )\n Evaluates Spence’s function, which is also known as the dilogarithm.\n","base.sqrt":"\nbase.sqrt( x:number )\n Computes the principal square root of a double-precision floating-point\n number.\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x:number )\n Computes the principal square root of `1+x` minus one.\n","base.sqrtf":"\nbase.sqrtf( x:number )\n Computes the principal square root of a single-precision floating-point\n number.\n","base.sqrtpi":"\nbase.sqrtpi( x:number )\n Computes the principal square root of the product of π and a positive\n double-precision floating-point number.\n","base.strided.binary":"\nbase.strided.binary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike, dtypes3:ArrayLike[, options:Object] )\n Generates a list of binary interface signatures from strided array data\n types.\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table:Object, signatures:ArrayLike )\n Assigns callbacks to binary interfaces according to type promotion rules.\n","base.strided.ccopy":"\nbase.strided.ccopy( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector.\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector using alternative\n indexing semantics.\n","base.strided.cmap":"\nbase.strided.cmap( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer, fcn:Function )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array.\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n","base.strided.cswap":"\nbase.strided.cswap( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer )\n Interchanges two complex single-precision floating-point vectors.\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n Interchanges two complex single-precision floating-point vectors using\n alternative indexing semantics.\n","base.strided.cumax":"\nbase.strided.cumax( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative maximum of a strided array.\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative maximum absolute value of a strided array.\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n","base.strided.cumin":"\nbase.strided.cumin( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative minimum of a strided array.\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n","base.strided.cuminabs":"\nbase.strided.cuminabs( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative minimum absolute value of a strided array.\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n","base.strided.dabs":"\nbase.strided.dabs( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dabs2":"\nbase.strided.dabs2( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dapx":"\nbase.strided.dapx( N:integer, alpha:number, x:Float64Array, stride:integer )\n Adds a constant to each element in a double-precision floating-point strided\n array.\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Adds a constant to each element in a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dapxsum":"\nbase.strided.dapxsum( N:integer, alpha:number, x:Float64Array, stride:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum.\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N:integer, alpha:number, x:Float64Array, \n stride:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N:integer, alpha:number, x:Float64Array, \n stride:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N:integer, alpha:number, x:Float64Array, \n stride:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using ordinary recursive summation.\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N:integer, alpha:number, x:Float64Array, \n stride:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation.\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n","base.strided.dasum":"\nbase.strided.dasum( N:integer, x:Float64Array, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.dasumpw":"\nbase.strided.dasumpw( N:integer, x:Float64Array, stride:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation.\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n","base.strided.daxpy":"\nbase.strided.daxpy( N:integer, alpha:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n","base.strided.dcbrt":"\nbase.strided.dcbrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dceil":"\nbase.strided.dceil( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dcopy":"\nbase.strided.dcopy( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.dcumax":"\nbase.strided.dcumax( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements.\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements.\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.dcumin":"\nbase.strided.dcumin( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements.\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements.\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.dcusum":"\nbase.strided.dcusum( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements.\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N:integer, sum:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dcusumors":"\nbase.strided.dcusumors( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation.\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation.\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.ddot":"\nbase.strided.ddot( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the dot product of two double-precision floating-point vectors.\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n","base.strided.dfill":"\nbase.strided.dfill( N:integer, alpha:number, x:Float64Array, stride:integer )\n Fills a double-precision floating-point strided array with a specified\n scalar value.\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Fills a double-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n","base.strided.dfloor":"\nbase.strided.dfloor( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dinv":"\nbase.strided.dinv( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dmap":"\nbase.strided.dmap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array.\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.dmap2":"\nbase.strided.dmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, z:Float64Array, sz:integer, fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays and assigns results to a double-precision floating-point strided\n output array.\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n y:Float64Array, sy:integer, oy:integer, z:Float64Array, sz:integer, \n oz:integer, fcn:Function )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.dmax":"\nbase.strided.dmax( N:integer, x:Float64Array, stride:integer )\n Computes the maximum value of a double-precision floating-point strided\n array.\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N:integer, x:Float64Array, stride:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array.\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmaxabssorted":"\nbase.strided.dmaxabssorted( N:integer, x:Float64Array, stride:integer )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array.\n","base.strided.dmaxabssorted.ndarray":"\nbase.strided.dmaxabssorted.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dmaxsorted":"\nbase.strided.dmaxsorted( N:integer, x:Float64Array, stride:integer )\n Computes the maximum value of a sorted double-precision floating-point\n strided array.\n","base.strided.dmaxsorted.ndarray":"\nbase.strided.dmaxsorted.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmean":"\nbase.strided.dmean( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array.\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.dmeanli":"\nbase.strided.dmeanli( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n","base.strided.dmeanors":"\nbase.strided.dmeanors( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation.\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm.\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation.\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array.\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N:integer, c:number, x:Float64Array, \n strideX:integer, out:Float64Array, strideOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm.\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array.\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N:integer, x:Float64Array, stride:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmidrange":"\nbase.strided.dmidrange( N:integer, x:Float64Array, stride:integer )\n Computes the mid-range of a double-precision floating-point strided array.\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.dmin":"\nbase.strided.dmin( N:integer, x:Float64Array, stride:integer )\n Computes the minimum value of a double-precision floating-point strided\n array.\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dminabs":"\nbase.strided.dminabs( N:integer, x:Float64Array, stride:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array.\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dminsorted":"\nbase.strided.dminsorted( N:integer, x:Float64Array, stride:integer )\n Computes the minimum value of a sorted double-precision floating-point\n strided array.\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmskabs":"\nbase.strided.dmskabs( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y`.\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.dmskceil":"\nbase.strided.dmskceil( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskinv":"\nbase.strided.dmskinv( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmskmap":"\nbase.strided.dmskmap( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float64Array, sy:integer, \n oy:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, m:Uint8Array, sm:integer, z:Float64Array, sz:integer, \n fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, y:Float64Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n om:integer, z:Float64Array, sz:integer, oz:integer, fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.dmskmax":"\nbase.strided.dmskmax( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask.\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.dmskmin":"\nbase.strided.dmskmin( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask.\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.dmskramp":"\nbase.strided.dmskramp( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskrange":"\nbase.strided.dmskrange( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask.\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y`.\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.dnanasum":"\nbase.strided.dnanasum( N:integer, x:Float64Array, stride:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values.\n","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N:integer, x:Float64Array, stride:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation.\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n","base.strided.dnanmax":"\nbase.strided.dnanmax( N:integer, x:Float64Array, stride:integer )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N:integer, x:Float64Array, stride:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnanmean":"\nbase.strided.dnanmean( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation.\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, using Welford's algorithm and ignoring `NaN` values.\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.dnanmin":"\nbase.strided.dnanmin( N:integer, x:Float64Array, stride:integer )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N:integer, x:Float64Array, stride:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnannsum":"\nbase.strided.dnannsum( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.dnanrange":"\nbase.strided.dnanrange( N:integer, x:Float64Array, stride:integer )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values.\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values.\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n","base.strided.dnansum":"\nbase.strided.dnansum( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.dnansumors":"\nbase.strided.dnansumors( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values.\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n","base.strided.dnrm2":"\nbase.strided.dnrm2( N:integer, x:Float64Array, stride:integer )\n Computes the L2-norm of a double-precision floating-point vector.\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n","base.strided.dramp":"\nbase.strided.dramp( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.drange":"\nbase.strided.drange( N:integer, x:Float64Array, stride:integer )\n Computes the range of a double-precision floating-point strided array.\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n","base.strided.drev":"\nbase.strided.drev( N:integer, x:Float64Array, stride:integer )\n Reverses a double-precision floating-point strided array in-place.\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n","base.strided.drsqrt":"\nbase.strided.drsqrt( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N:integer, alpha:number, x:Float32Array, stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and returning an\n extended precision result.\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and returning an extended precision result.\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n","base.strided.dscal":"\nbase.strided.dscal( N:integer, alpha:number, x:Float64Array, stride:integer )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha`.\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n","base.strided.dsdot":"\nbase.strided.dsdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation and result.\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n","base.strided.dsem":"\nbase.strided.dsem( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array.\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dsemch":"\nbase.strided.dsemch( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm.\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n","base.strided.dsempn":"\nbase.strided.dsempn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm.\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n","base.strided.dsemtk":"\nbase.strided.dsemtk( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm.\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n","base.strided.dsemwd":"\nbase.strided.dsemwd( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm.\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.dsemyc":"\nbase.strided.dsemyc( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n","base.strided.dsmean":"\nbase.strided.dsmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and returning an extended precision\n result.\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n returning an extended precision result.\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and returning an extended precision result.\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and returning an\n extended precision result.\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and returning an\n extended precision result.\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using ordinary recursive summation with\n extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using a two-pass error correction algorithm\n with extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using Welford's algorithm with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N:integer, x:Float32Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.dsnansum":"\nbase.strided.dsnansum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation,\n and returning an extended precision result.\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n","base.strided.dsorthp":"\nbase.strided.dsorthp( N:integer, order:number, x:Float64Array, stride:integer )\n Sorts a double-precision floating-point strided array using heapsort.\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N:integer, order:number, x:Float64Array, \n stride:integer, offset:integer )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n","base.strided.dsortins":"\nbase.strided.dsortins( N:integer, order:number, x:Float64Array, stride:integer )\n Sorts a double-precision floating-point strided array using insertion sort.\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N:integer, order:number, x:Float64Array, \n stride:integer, offset:integer )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n","base.strided.dsortsh":"\nbase.strided.dsortsh( N:integer, order:number, x:Float64Array, stride:integer )\n Sorts a double-precision floating-point strided array using Shellsort.\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N:integer, order:number, x:Float64Array, \n stride:integer, offset:integer )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n","base.strided.dsqrt":"\nbase.strided.dsqrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dssum":"\nbase.strided.dssum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and returning an extended precision result.\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n","base.strided.dssumors":"\nbase.strided.dssumors( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and returning\n an extended precision result.\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n","base.strided.dssumpw":"\nbase.strided.dssumpw( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and returning an\n extended precision result.\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n","base.strided.dstdev":"\nbase.strided.dstdev( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array.\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dstdevch":"\nbase.strided.dstdevch( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm.\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n","base.strided.dsum":"\nbase.strided.dsum( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements.\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.dsumors":"\nbase.strided.dsumors( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation.\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dsumpw":"\nbase.strided.dsumpw( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation.\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.dsvariance":"\nbase.strided.dsvariance( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and returning an extended precision result.\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and returning an\n extended precision result.\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dswap":"\nbase.strided.dswap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Interchanges two double-precision floating-point vectors.\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n","base.strided.dtrunc":"\nbase.strided.dtrunc( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dvariance":"\nbase.strided.dvariance( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array.\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.dvariancech":"\nbase.strided.dvariancech( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm.\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm.\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm.\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm.\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.dvarm":"\nbase.strided.dvarm( N:integer, mean:number, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean.\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm.\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm.\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.gapx":"\nbase.strided.gapx( N:integer, alpha:number, x:Array|TypedArray, stride:integer )\n Adds a constant to each element in a strided array.\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each element in a strided array using alternative\n indexing semantics.\n","base.strided.gapxsum":"\nbase.strided.gapxsum( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Adds a constant to each strided array element and computes the sum.\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each strided array element and computes the sum using\n alternative indexing semantics.\n","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Adds a constant to each strided array element and computes the sum using an\n improved Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each strided array element and computes the sum using an\n improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Adds a constant to each strided array element and computes the sum using a\n second-order iterative Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each strided array element and computes the sum using a\n second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Adds a constant to each strided array element and computes the sum using\n ordinary recursive summation.\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each strided array element and computes the sum using\n ordinary recursive summation and alternative indexing semantics.\n","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Adds a constant to each strided array element and computes the sum using\n pairwise summation.\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each strided array element and computes the sum using\n pairwise summation and alternative indexing semantics.\n","base.strided.gasum":"\nbase.strided.gasum( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.gasumpw":"\nbase.strided.gasumpw( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation.\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.gaxpy":"\nbase.strided.gaxpy( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n","base.strided.gcopy":"\nbase.strided.gcopy( N:integer, x:ArrayLikeObject, strideX:integer, \n y:ArrayLikeObject, strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.gcusum":"\nbase.strided.gcusum( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements.\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm.\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm.\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumors":"\nbase.strided.gcusumors( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation.\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using pairwise\n summation.\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n","base.strided.gdot":"\nbase.strided.gdot( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the dot product of two vectors.\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n","base.strided.gfill":"\nbase.strided.gfill( N:integer, alpha:any, x:ArrayLikeObject, stride:integer )\n Fills a strided array with a specified scalar value.\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N:integer, alpha:any, x:ArrayLikeObject, \n stride:integer, offset:integer )\n Fills a strided array with a specified scalar value using alternative\n indexing semantics.\n","base.strided.gfillBy":"\nbase.strided.gfillBy( N:integer, x:ArrayLikeObject, stride:integer, \n clbk:Function[, thisArg:any] )\n Fills a strided array according to a provided callback function.\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N:integer, x:ArrayLikeObject, stride:integer, \n offset:integer, clbk:Function[, thisArg:any] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N:integer, x:Array|TypedArray, strideX:integer, \n out:Array|TypedArray, strideOut:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer, out:Array|TypedArray, strideOut:integer, \n offsetOut:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansum":"\nbase.strided.gnansum( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements, ignoring `NaN` values.\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm.\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N:integer, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.gnansumors":"\nbase.strided.gnansumors( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation.\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and\n pairwise summation.\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n","base.strided.gnrm2":"\nbase.strided.gnrm2( N:integer, x:Array|TypedArray, stride:integer )\n Computes the L2-norm of a vector.\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the L2-norm of a vector using alternative indexing semantics.\n","base.strided.grev":"\nbase.strided.grev( N:integer, x:ArrayLikeObject, stride:integer )\n Reverses a strided array in-place.\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N:integer, x:ArrayLikeObject, stride:integer, \n offset:integer )\n Reverses a strided array in-place using alternative indexing semantics.\n","base.strided.gscal":"\nbase.strided.gscal( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Multiplies a vector `x` by a constant `alpha`.\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort.\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort.\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort.\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n","base.strided.gsorthp":"\nbase.strided.gsorthp( N:integer, order:number, x:Array|TypedArray, \n stride:integer )\n Sorts a strided array using heapsort.\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N:integer, order:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Sorts a strided array using heapsort and alternative indexing semantics.\n","base.strided.gsortins":"\nbase.strided.gsortins( N:integer, order:number, x:Array|TypedArray, \n stride:integer )\n Sorts a strided array using insertion sort.\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N:integer, order:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n","base.strided.gsortsh":"\nbase.strided.gsortsh( N:integer, order:number, x:Array|TypedArray, \n stride:integer )\n Sorts a strided array using Shellsort.\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N:integer, order:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n","base.strided.gsum":"\nbase.strided.gsum( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements.\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm.\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm.\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gsumors":"\nbase.strided.gsumors( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements using ordinary recursive\n summation.\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n","base.strided.gsumpw":"\nbase.strided.gsumpw( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements using pairwise summation.\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n","base.strided.gswap":"\nbase.strided.gswap( N:integer, x:ArrayLikeObject, strideX:integer, \n y:ArrayLikeObject, strideY:integer )\n Interchanges vectors `x` and `y`.\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n","base.strided.mapBy":"\nbase.strided.mapBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, fcn:Function, clbk:Function[, \n thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, fcn:Function, \n clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.mapBy2":"\nbase.strided.mapBy2( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n fcn:Function, clbk:Function[, thisArg:any] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array.\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, fcn:Function, \n clbk:Function[, thisArg:any] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n","base.strided.max":"\nbase.strided.max( N:integer, x:Array|TypedArray, stride:integer )\n Computes the maximum value of a strided array.\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n","base.strided.maxabs":"\nbase.strided.maxabs( N:integer, x:Array|TypedArray, stride:integer )\n Computes the maximum absolute value of a strided array.\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n","base.strided.maxBy":"\nbase.strided.maxBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the maximum value of a strided array via a callback function.\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n","base.strided.maxsorted":"\nbase.strided.maxsorted( N:integer, x:Array|TypedArray, stride:integer )\n Computes the maximum value of a sorted strided array.\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.mean":"\nbase.strided.mean( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array.\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n","base.strided.meankbn":"\nbase.strided.meankbn( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm.\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n","base.strided.meankbn2":"\nbase.strided.meankbn2( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm.\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.meanors":"\nbase.strided.meanors( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation.\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n","base.strided.meanpn":"\nbase.strided.meanpn( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm.\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n","base.strided.meanpw":"\nbase.strided.meanpw( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using pairwise summation.\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n","base.strided.meanwd":"\nbase.strided.meanwd( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using Welford's algorithm.\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n","base.strided.mediansorted":"\nbase.strided.mediansorted( N:integer, x:Array|TypedArray, stride:integer )\n Computes the median value of a sorted strided array.\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N:integer, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.min":"\nbase.strided.min( N:integer, x:Array|TypedArray, stride:integer )\n Computes the minimum value of a strided array.\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n","base.strided.minabs":"\nbase.strided.minabs( N:integer, x:Array|TypedArray, stride:integer )\n Computes the minimum absolute value of a strided array.\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n","base.strided.minBy":"\nbase.strided.minBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the minimum value of a strided array via a callback function.\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n","base.strided.minsorted":"\nbase.strided.minsorted( N:integer, x:Array|TypedArray, stride:integer )\n Computes the minimum value of a sorted strided array.\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.mskmax":"\nbase.strided.mskmax( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the maximum value of a strided array according to a mask.\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskmin":"\nbase.strided.mskmin( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the minimum value of a strided array according to a mask.\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskrange":"\nbase.strided.mskrange( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the range of a strided array according to a mask.\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskunary":"\nbase.strided.mskunary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array and assigns results to elements in a\n strided output array.\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike[, options:Object] )\n Generates a list of masked unary interface signatures from strided array\n data types.\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table:Object, \n signatures:ArrayLike )\n Assigns callbacks to masked unary interfaces according to type promotion\n rules.\n","base.strided.nanmax":"\nbase.strided.nanmax( N:integer, x:Array|TypedArray, stride:integer )\n Computes the maximum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N:integer, x:Array|TypedArray, stride:integer )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values.\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the maximum value of a strided array via a callback function,\n ignoring `NaN` values.\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmean":"\nbase.strided.nanmean( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation.\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm.\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm.\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanmin":"\nbase.strided.nanmin( N:integer, x:Array|TypedArray, stride:integer )\n Computes the minimum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanminabs":"\nbase.strided.nanminabs( N:integer, x:Array|TypedArray, stride:integer )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values.\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanminBy":"\nbase.strided.nanminBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the minimum value of a strided array via a callback function,\n ignoring `NaN` values.\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the maximum value of a strided array according to a mask and\n ignoring `NaN` values.\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the minimum value of a strided array according to a mask and\n ignoring `NaN` values.\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the range of a strided array according to a mask and ignoring `NaN`\n values.\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanrange":"\nbase.strided.nanrange( N:integer, x:Array|TypedArray, stride:integer )\n Computes the range of a strided array, ignoring `NaN` values.\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values.\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n","base.strided.nanstdev":"\nbase.strided.nanstdev( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values.\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm.\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm.\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm.\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm.\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.nanvariance":"\nbase.strided.nanvariance( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values.\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm.\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm.\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm.\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm.\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n","base.strided.nullary":"\nbase.strided.nullary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a nullary callback and assigns results to elements in a strided\n output array.\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.quinary":"\nbase.strided.quinary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.range":"\nbase.strided.range( N:integer, x:Array|TypedArray, stride:integer )\n Computes the range of a strided array.\n","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the range of a strided array using alternative indexing semantics.\n","base.strided.rangeBy":"\nbase.strided.rangeBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function.\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n","base.strided.sabs":"\nbase.strided.sabs( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sabs2":"\nbase.strided.sabs2( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sapx":"\nbase.strided.sapx( N:integer, alpha:number, x:Float32Array, stride:integer )\n Adds a constant to each element in a single-precision floating-point strided\n array.\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each element in a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.sapxsum":"\nbase.strided.sapxsum( N:integer, alpha:number, x:Float32Array, stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum.\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation.\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation.\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n","base.strided.sasum":"\nbase.strided.sasum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.sasumpw":"\nbase.strided.sasumpw( N:integer, x:Float32Array, stride:integer )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation.\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n","base.strided.saxpy":"\nbase.strided.saxpy( N:integer, alpha:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n","base.strided.scbrt":"\nbase.strided.scbrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y`.\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.sceil":"\nbase.strided.sceil( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.scopy":"\nbase.strided.scopy( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.scumax":"\nbase.strided.scumax( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements.\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements.\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.scumin":"\nbase.strided.scumin( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements.\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.scuminabs":"\nbase.strided.scuminabs( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements.\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.scusum":"\nbase.strided.scusum( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements.\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N:integer, sum:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided \n array elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.scusumors":"\nbase.strided.scusumors( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n","base.strided.scusumpw":"\nbase.strided.scusumpw( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sdot":"\nbase.strided.sdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the dot product of two single-precision floating-point vectors.\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation.\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation.\n","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.sdsdot":"\nbase.strided.sdsdot( N:integer, scalar:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation.\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N:integer, scalar:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n","base.strided.sdsmean":"\nbase.strided.sdsmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation.\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation.\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation.\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation.\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation.\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation.\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.sdssum":"\nbase.strided.sdssum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation.\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation.\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n","base.strided.sfill":"\nbase.strided.sfill( N:integer, alpha:number, x:Float32Array, stride:integer )\n Fills a single-precision floating-point strided array with a specified\n scalar value.\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n","base.strided.sfloor":"\nbase.strided.sfloor( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sinv":"\nbase.strided.sinv( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.smap":"\nbase.strided.smap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array.\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.smap2":"\nbase.strided.smap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n sy:integer, z:Float32Array, sz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array.\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, \n y:Float32Array, sy:integer, oy:integer, z:Float32Array, sz:integer, \n oz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.smax":"\nbase.strided.smax( N:integer, x:Float32Array, stride:integer )\n Computes the maximum value of a single-precision floating-point strided\n array.\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.smaxabs":"\nbase.strided.smaxabs( N:integer, x:Float32Array, stride:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array.\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N:integer, x:Float32Array, stride:integer )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array.\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N:integer, x:Float32Array, stride:integer )\n Computes the maximum value of a sorted single-precision floating-point\n strided array.\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smean":"\nbase.strided.smean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array.\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.smeankbn":"\nbase.strided.smeankbn( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.smeanli":"\nbase.strided.smeanli( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n","base.strided.smeanors":"\nbase.strided.smeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation.\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.smeanpn":"\nbase.strided.smeanpn( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm.\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.smeanpw":"\nbase.strided.smeanpw( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation.\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n","base.strided.smeanwd":"\nbase.strided.smeanwd( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.smediansorted":"\nbase.strided.smediansorted( N:integer, x:Float32Array, stride:integer )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smidrange":"\nbase.strided.smidrange( N:integer, x:Float32Array, stride:integer )\n Computes the mid-range of a single-precision floating-point strided array.\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.smin":"\nbase.strided.smin( N:integer, x:Float32Array, stride:integer )\n Computes the minimum value of a single-precision floating-point strided\n array.\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.sminabs":"\nbase.strided.sminabs( N:integer, x:Float32Array, stride:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array.\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.sminsorted":"\nbase.strided.sminsorted( N:integer, x:Float32Array, stride:integer )\n Computes the minimum value of a sorted single-precision floating-point\n strided array.\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smskabs":"\nbase.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskabs2":"\nbase.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y`.\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.smskceil":"\nbase.strided.smskceil( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskfloor":"\nbase.strided.smskfloor( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskinv":"\nbase.strided.smskinv( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smskmap":"\nbase.strided.smskmap( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float32Array, sy:integer, \n oy:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.smskmap2":"\nbase.strided.smskmap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n sy:integer, m:Uint8Array, sm:integer, z:Float32Array, sz:integer, \n fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, y:Float32Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n om:integer, z:Float32Array, sz:integer, oz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.smskmax":"\nbase.strided.smskmax( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask.\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.smskmin":"\nbase.strided.smskmin( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask.\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.smskramp":"\nbase.strided.smskramp( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskrange":"\nbase.strided.smskrange( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask.\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y`.\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.snanmax":"\nbase.strided.snanmax( N:integer, x:Float32Array, stride:integer )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N:integer, x:Float32Array, stride:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanmean":"\nbase.strided.snanmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.snanmin":"\nbase.strided.snanmin( N:integer, x:Float32Array, stride:integer )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanminabs":"\nbase.strided.snanminabs( N:integer, x:Float32Array, stride:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanrange":"\nbase.strided.snanrange( N:integer, x:Float32Array, stride:integer )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values.\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanstdev":"\nbase.strided.snanstdev( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values.\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n","base.strided.snansum":"\nbase.strided.snansum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.snansumors":"\nbase.strided.snansumors( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.snansumpw":"\nbase.strided.snansumpw( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.snanvariance":"\nbase.strided.snanvariance( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values.\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n","base.strided.snrm2":"\nbase.strided.snrm2( N:integer, x:Float32Array, stride:integer )\n Computes the L2-norm of a single-precision floating-point vector.\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n","base.strided.sramp":"\nbase.strided.sramp( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.srange":"\nbase.strided.srange( N:integer, x:Float32Array, stride:integer )\n Computes the range of a single-precision floating-point strided array.\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n","base.strided.srev":"\nbase.strided.srev( N:integer, x:Float32Array, stride:integer )\n Reverses a single-precision floating-point strided array in-place.\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n","base.strided.srsqrt":"\nbase.strided.srsqrt( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sscal":"\nbase.strided.sscal( N:integer, alpha:number, x:Float32Array, stride:integer )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha`.\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n","base.strided.ssorthp":"\nbase.strided.ssorthp( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using heapsort.\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n","base.strided.ssortins":"\nbase.strided.ssortins( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using insertion sort.\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n","base.strided.ssortsh":"\nbase.strided.ssortsh( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using Shellsort.\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n","base.strided.ssqrt":"\nbase.strided.ssqrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sstdev":"\nbase.strided.sstdev( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array.\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.sstdevch":"\nbase.strided.sstdevch( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm.\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n","base.strided.ssum":"\nbase.strided.ssum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements.\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.ssumors":"\nbase.strided.ssumors( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation.\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.ssumpw":"\nbase.strided.ssumpw( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation.\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.sswap":"\nbase.strided.sswap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Interchanges two single-precision floating-point vectors.\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n","base.strided.stdev":"\nbase.strided.stdev( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array.\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n","base.strided.stdevch":"\nbase.strided.stdevch( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm.\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n","base.strided.stdevpn":"\nbase.strided.stdevpn( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using a two-pass\n algorithm.\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n","base.strided.stdevtk":"\nbase.strided.stdevtk( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm.\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n","base.strided.stdevwd":"\nbase.strided.stdevwd( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using Welford's\n algorithm.\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n","base.strided.stdevyc":"\nbase.strided.stdevyc( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer.\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n","base.strided.strunc":"\nbase.strided.strunc( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y`.\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.svariance":"\nbase.strided.svariance( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array.\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.svariancech":"\nbase.strided.svariancech( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm.\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.svariancepn":"\nbase.strided.svariancepn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm.\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.svariancetk":"\nbase.strided.svariancetk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm.\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.svariancewd":"\nbase.strided.svariancewd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm.\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.ternary":"\nbase.strided.ternary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.unary":"\nbase.strided.unary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array.\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function, clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function, clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike[, options:Object] )\n Generates a list of unary interface signatures from strided array data\n types.\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table:Object, signatures:ArrayLike )\n Assigns callbacks to unary interfaces according to type promotion rules.\n","base.strided.variance":"\nbase.strided.variance( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array.\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using alternative indexing\n semantics.\n","base.strided.variancech":"\nbase.strided.variancech( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm.\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n","base.strided.variancepn":"\nbase.strided.variancepn( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using a two-pass algorithm.\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n","base.strided.variancetk":"\nbase.strided.variancetk( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using a one-pass textbook\n algorithm.\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n","base.strided.variancewd":"\nbase.strided.variancewd( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using Welford's algorithm.\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n","base.strided.varianceyc":"\nbase.strided.varianceyc( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer.\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n","base.strided.zmap":"\nbase.strided.zmap( N:integer, x:Complex128Array, strideX:integer, \n y:Complex128Array, strideY:integer, fcn:Function )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array.\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N:integer, x:Complex128Array, strideX:integer, \n offsetX:integer, y:Complex128Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n","base.sub":"\nbase.sub( x:number, y:number )\n Subtracts two double-precision floating-point numbers `x` and `y`.\n","base.subf":"\nbase.subf( x:number, y:number )\n Subtracts two single-precision floating-point numbers `x` and `y`.\n","base.sumSeries":"\nbase.sumSeries( generator:Function[, options:Object] )\n Sum the elements of the series given by the supplied function.\n","base.tan":"\nbase.tan( x:number )\n Computes the tangent of a number.\n","base.tanh":"\nbase.tanh( x:number )\n Computes the hyperbolic tangent of a double-precision floating-point number.\n","base.toBinaryString":"\nbase.toBinaryString( x:number )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x:float )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x:integer )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x:integer )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x:integer )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n","base.toWordf":"\nbase.toWordf( x:float )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n","base.toWords":"\nbase.toWords( x:number )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.toWords.assign":"\nbase.toWords.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n","base.transpose":"\nbase.transpose( x:ndarray )\n Transposes a matrix (or a stack of matrices).\n","base.tribonacci":"\nbase.tribonacci( n:integer )\n Computes the nth Tribonacci number.\n","base.trigamma":"\nbase.trigamma( x:number )\n Evaluates the trigamma function.\n","base.trunc":"\nbase.trunc( x:number )\n Rounds a double-precision floating-point number toward zero.\n","base.trunc2":"\nbase.trunc2( x:number )\n Rounds a numeric value to the nearest power of two toward zero.\n","base.trunc10":"\nbase.trunc10( x:number )\n Rounds a numeric value to the nearest power of ten toward zero.\n","base.truncb":"\nbase.truncb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n","base.truncf":"\nbase.truncf( x:number )\n Rounds a single-precision floating-point number toward zero.\n","base.truncn":"\nbase.truncn( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n","base.truncsd":"\nbase.truncsd( x:number, n:integer[, b:integer] )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n","base.umul":"\nbase.umul( a:integer, b:integer )\n Performs C-like multiplication of two unsigned 32-bit integers.\n","base.umuldw":"\nbase.umuldw( a:integer, b:integer )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n","base.umuldw.assign":"\nbase.umuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x:integer )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n","base.vercos":"\nbase.vercos( x:number )\n Computes the versed cosine.\n","base.versin":"\nbase.versin( x:number )\n Computes the versed sine.\n","base.wrap":"\nbase.wrap( v:number, min:number, max:number )\n Wraps a value on the half-open interval `[min,max)`.\n","base.xlog1py":"\nbase.xlog1py( x:number, y:number )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n","base.xlogy":"\nbase.xlogy( x:number, y:number )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n","base.zeta":"\nbase.zeta( s:number )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and and other characteristics.\n","bifurcate":"\nbifurcate( collection:Array|TypedArray|Object, [options:Object,] \n filter:Array|TypedArray|Object )\n Splits values into two groups.\n","bifurcateBy":"\nbifurcateBy( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateByAsync":"\nbifurcateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which splits values into two groups according to an\n predicate function.\n","bifurcateIn":"\nbifurcateIn( obj:Object|Array|TypedArray, [options:Object,] predicate:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateOwn":"\nbifurcateOwn( obj:Object|Array|TypedArray, [options:Object,] \n predicate:Function )\n Splits values into two groups according to a predicate function.\n","BigInt":"\nBigInt( value:integer|string )\n Returns a BigInt.\n","binomialTest":"\nbinomialTest( x:(number|Array[, n:Array][, options:Object] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n","Boolean":"\nBoolean( value:any )\n Returns a boolean.\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n","broadcastArray":"\nbroadcastArray( x:ndarray, shape:ArrayLikeObject )\n Broadcasts an ndarray to a specified shape.\n","broadcastArrays":"\nbroadcastArrays( ...arrays:ndarray|ArrayLikeObject )\n Broadcasts ndarrays to a common shape.\n","Buffer":"\nBuffer\n\nBuffer( size:integer )\n Allocates a buffer having a specified number of bytes.\n\nBuffer( buffer:Buffer )\n Copies buffer data to a new Buffer instance.\n\nBuffer( array:Array )\n Allocates a buffer using an array of octets.\n\nBuffer( str:string[, encoding:string] )\n Allocates a buffer containing a provided string.\n","buffer2json":"\nbuffer2json( buffer:Buffer )\n Returns a JSON representation of a buffer.\n","BYTE_ORDER":"\nBYTE_ORDER\n Platform byte order.\n","camelcase":"\ncamelcase( str:string )\n Converts a string to camel case.\n","capitalize":"\ncapitalize( str:string )\n Capitalizes the first character in a string.\n","capitalizeKeys":"\ncapitalizeKeys( obj:Object )\n Converts the first letter of each object key to uppercase.\n","CATALAN":"\nCATALAN\n Catalan's constant.\n","CBRT_EPS":"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n Returns US birth data from 1969 to 1988, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n Returns US birth data from 1994 to 2003, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n the Center for Disease Control and Prevention's National Center for Health\n Statistics.\n","chdir":"\nchdir( path:string )\n Changes the current working directory.\n","chi2gof":"\nchi2gof( x:ndarray|Array|TypedArray, y:ndarray|Array|TypedArray|string[, \n ...args:number][, options:Object] )\n Performs a chi-square goodness-of-fit test.\n","chi2test":"\nchi2test( x:ndarray|Array[, options:Object] )\n Performs a chi-square independence test.\n","circarray2iterator":"\ncircarray2iterator( src:ArrayLikeObject[, options:Object][, mapFcn:Function[, \n thisArg:any]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n","circularArrayStream":"\ncircularArrayStream( src:ArrayLikeObject[, options:Object] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n","CircularBuffer":"\nCircularBuffer( buffer:integer|ArrayLike )\n Circular buffer constructor.\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n Clears a buffer.\n","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters:integer] )\n Returns an iterator for iterating over a circular buffer.\n","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value:any )\n Adds a value to a circular buffer.\n","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n","close":"\nclose( fd:integer, clbk:Function )\n Asynchronously closes a file descriptor, so that the file descriptor no\n longer refers to any file and may be reused.\n","close.sync":"\nclose.sync( fd:integer )\n Synchronously closes a file descriptor.\n","CMUDICT":"\nCMUDICT( [options:Object] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n","codePointAt":"\ncodePointAt( str:string, idx:integer[, backward:boolean] )\n Returns a Unicode code point from a string at a specified position.\n","commonKeys":"\ncommonKeys( obj1:any, obj2:any[, ...obj:any] )\n Returns the common own property names of two or more objects.\n","commonKeysIn":"\ncommonKeysIn( obj1:any, obj2:any[, ...obj:any] )\n Returns the common own and inherited property names of two or more objects.\n","complex":"\ncomplex( real:number, imag:number[, dtype:string] )\n Creates a complex number.\n","Complex64":"\nComplex64( real:number, imag:number )\n 64-bit complex number constructor.\n","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n Canonical single-precision complex floating-point NaN.\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n Single-precision complex floating-point zero.\n","Complex128":"\nComplex128( real:number, imag:number )\n 128-bit complex number constructor.\n","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n Canonical double-precision complex floating-point NaN.\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n Double-precision complex floating-point zero.\n","complexarray":"\ncomplexarray( [dtype:string] )\n Creates a complex typed array.\n\ncomplexarray( length:integer[, dtype:string] )\n Returns a complex number typed array having a specified length.\n\ncomplexarray( complexarray:ComplexArray[, dtype:string] )\n Creates a complex number typed array from another complex number typed\n array.\n\ncomplexarray( obj:Object[, dtype:string] )\n Creates a complex number typed array from an array-like object or iterable.\n\ncomplexarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a complex number typed array view of an ArrayBuffer.\n","complexarrayCtors":"\ncomplexarrayCtors( dtype:string )\n Returns a complex typed array constructor.\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n Returns a list of complex typed array data types.\n","complexCtors":"\ncomplexCtors( dtype:string )\n Returns a complex number constructor.\n","complexDataType":"\ncomplexDataType( value:any )\n Returns the data type of a complex number object.\n","complexDataTypes":"\ncomplexDataTypes()\n Returns a list of complex number data types.\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1:string, dtype2:string] )\n Returns the complex number data type with the smallest size and closest\n \"kind\" to which data types can be safely cast.\n","compose":"\ncompose( ...f:Function )\n Function composition.\n","composeAsync":"\ncomposeAsync( ...f:Function )\n Function composition.\n","configdir":"\nconfigdir( [p:string] )\n Returns a directory for user-specific configuration files.\n","conj":"\nconj( z:Complex128 )\n Returns the complex conjugate of a double-precision complex floating-point\n number.\n","conjf":"\nconjf( z:Complex64 )\n Returns the complex conjugate of a single-precision complex floating-point\n number.\n","constantcase":"\nconstantcase( str:string )\n Converts a string to constant case.\n","constantFunction":"\nconstantFunction( val:any )\n Creates a function which always returns the same value.\n","constantStream":"\nconstantStream( value:string|Buffer|Uint8Array|any[, options:Object] )\n Returns a readable stream which always streams the same value.\n","constantStream.factory":"\nconstantStream.factory( [value:string|Buffer|Uint8Array|any, ][options:Object] )\n Returns a function for creating readable streams which always stream the\n same value.\n","constantStream.objectMode":"\nconstantStream.objectMode( value:any[, options:Object] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n","constructorName":"\nconstructorName( val:any )\n Determines the name of a value's constructor.\n","contains":"\ncontains( val:ArrayLike, searchValue:any[, position:integer] )\n Tests if an array-like value contains a search value.\n","convertArray":"\nconvertArray( arr:ArrayLikeObject, dtype:string )\n Converts an input array to an array of a different data type.\n","convertArraySame":"\nconvertArraySame( x:ArrayLikeObject, y:Array|TypedArray )\n Converts an input array to the same data type as a second input array.\n","convertPath":"\nconvertPath( from:string, to:string )\n Converts between POSIX and Windows paths.\n","copy":"\ncopy( value:any[, level:integer] )\n Copy or deep clone a value to an arbitrary depth.\n","copyBuffer":"\ncopyBuffer( buffer:Buffer )\n Copies buffer data to a new Buffer instance.\n","countBy":"\ncountBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Groups values according to an indicator function and returns group counts.\n","countByAsync":"\ncountByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Groups values according to an indicator function and returns group counts.\n","countByAsync.factory":"\ncountByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n","currentYear":"\ncurrentYear()\n Returns the current year.\n","curry":"\ncurry( fcn:Function[, arity:integer][, thisArg:any] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n","curryRight":"\ncurryRight( fcn:Function[, arity:integer][, thisArg:any] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n","cwd":"\ncwd()\n Returns the current working directory.\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n Returns a list of familiar English words.\n","datasets":"\ndatasets( name:string[, options:Object] )\n Returns a dataset.\n","DataView":"\nDataView( buffer:ArrayBuffer|SharedArrayBuffer[, byteOffset:integer[, \n byteLength:integer]] )\n Returns a data view representing a provided array buffer.\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n Read-only property which returns the underyling array buffer.\n","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n","datespace":"\ndatespace( start:number, stop:number[, length:integer][ , options:Object] )\n Generates an array of linearly spaced dates.\n","dayOfQuarter":"\ndayOfQuarter( [month:string|integer|Date[, day:integer, year:integer]] )\n Returns the day of the quarter.\n","dayOfYear":"\ndayOfYear( [month:string|integer|Date[, day:integer, year:integer]] )\n Returns the day of the year.\n","daysInMonth":"\ndaysInMonth( [month:string|integer|Date[, year:integer]] )\n Returns the number of days in a month.\n","daysInYear":"\ndaysInYear( [value:integer|Date] )\n Returns the number of days in a year according to the Gregorian calendar.\n","ddot":"\nddot( x:ndarray, y:ndarray )\n Computes the dot product of two double-precision floating-point vectors.\n","debugSinkStream":"\ndebugSinkStream( [options:Object,] [clbk:Function] )\n Returns a writable stream for debugging stream pipelines.\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options:Object] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options:Object,] [clbk:Function] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n","debugStream":"\ndebugStream( [options:Object,] [clbk:Function] )\n Returns a transform stream for debugging stream pipelines.\n","debugStream.factory":"\ndebugStream.factory( [options:Object] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n","debugStream.objectMode":"\ndebugStream.objectMode( [options:Object,] [clbk:Function] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n","decorateAfter":"\ndecorateAfter( fcn:Function, arity:integer, after:Function[, thisArg:any] )\n Decorates a provided function such that the function's return value is\n provided as an argument to another function.\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn:Function, arity:integer, after:Function[, \n thisArg:any] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n","deepEqual":"\ndeepEqual( a:any, b:any )\n Tests for deep equality between two values.\n","deepGet":"\ndeepGet( obj:ObjectLike, path:string|Array[, options:Object] )\n Returns a nested property value.\n","deepGet.factory":"\ndeepGet.factory( path:string|Array[, options:Object] )\n Creates a reusable deep get function.\n","deepHasOwnProp":"\ndeepHasOwnProp( value:any, path:string|Array[, options:Object] )\n Returns a boolean indicating whether an object contains a nested key path.\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path:string|Array[, options:Object] )\n Returns a function which tests whether an object contains a nested key path.\n","deepHasProp":"\ndeepHasProp( value:any, path:string|Array[, options:Object] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n","deepHasProp.factory":"\ndeepHasProp.factory( path:string|Array[, options:Object] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n","deepPluck":"\ndeepPluck( arr:Array, path:string|Array[, options:Object] )\n Extracts a nested property value from each element of an object array.\n","deepSet":"\ndeepSet( obj:ObjectLike, path:string|Array, value:any[, options:Object] )\n Sets a nested property value.\n","deepSet.factory":"\ndeepSet.factory( path:string|Array[, options:Object] )\n Creates a reusable deep set function.\n","defineMemoizedProperty":"\ndefineMemoizedProperty( obj:Object, prop:string|symbol, descriptor:Object )\n Defines a memoized object property.\n","defineProperties":"\ndefineProperties( obj:Object, properties:Object )\n Defines (and/or modifies) object properties.\n","defineProperty":"\ndefineProperty( obj:Object, prop:string|symbol, descriptor:Object )\n Defines (or modifies) an object property.\n","dirname":"\ndirname( path:string )\n Returns a directory name.\n","dotcase":"\ndotcase( str:string )\n Converts a string to dot case.\n","DoublyLinkedList":"\nDoublyLinkedList()\n Doubly linked list constructor.\n","doUntil":"\ndoUntil( fcn:Function, predicate:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","doUntilAsync":"\ndoUntilAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","doUntilEach":"\ndoUntilEach( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n","doUntilEachRight":"\ndoUntilEachRight( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","doWhile":"\ndoWhile( fcn:Function, predicate:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","doWhileAsync":"\ndoWhileAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","doWhileEach":"\ndoWhileEach( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection.\n","doWhileEachRight":"\ndoWhileEachRight( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","dswap":"\ndswap( x:ndarray, y:ndarray )\n Interchanges two double-precision floating-point vectors.\n","E":"\nE\n Euler's number.\n","EMOJI":"\nEMOJI()\n Returns an emoji database.\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n Returns an object mapping emoji codes to pictographs.\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n Returns an object mapping emoji pictographs to codes.\n","emptyStream":"\nemptyStream( [options:Object] )\n Returns an \"empty\" readable stream.\n","emptyStream.factory":"\nemptyStream.factory( [options:Object] )\n Returns a function for creating empty readable streams.\n","emptyStream.objectMode":"\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n","endsWith":"\nendsWith( str:string, search:string[, len:integer] )\n Tests if a string ends with the characters of another string.\n","enumerableProperties":"\nenumerableProperties( value:any )\n Returns an array of an object's own enumerable property names and symbols.\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value:any )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value:any )\n Returns an array of an object's own enumerable symbol properties.\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n","ENV":"\nENV\n An object containing the user environment.\n","EPS":"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n","error2json":"\nerror2json( error:Error )\n Returns a JSON representation of an error object.\n","EULERGAMMA":"\nEULERGAMMA\n The Euler-Mascheroni constant.\n","every":"\nevery( collection:Array|TypedArray|Object )\n Tests whether all elements in a collection are truthy.\n","everyBy":"\neveryBy( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n","everyByAsync":"\neveryByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n","everyByAsync.factory":"\neveryByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n","everyByRight":"\neveryByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n","everyByRightAsync":"\neveryByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n","evil":"\nevil( str:string )\n Alias for `eval` global.\n","EXEC_PATH":"\nEXEC_PATH\n Absolute pathname of the executable which started the current Node.js\n process.\n","exists":"\nexists( path:string|Buffer, clbk:Function )\n Asynchronously tests whether a path exists on the filesystem.\n","exists.sync":"\nexists.sync( path:string|Buffer )\n Synchronously tests whether a path exists on the filesystem.\n","expandAcronyms":"\nexpandAcronyms( str:string )\n Expands acronyms in a string.\n","expandContractions":"\nexpandContractions( str:string )\n Expands all contractions to their formal equivalents.\n","extname":"\nextname( filename:string )\n Returns a filename extension.\n","FancyArray":"\nFancyArray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string[, options:Object] )\n Returns a FancyArray instance.\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","FancyArray.prototype.data":"\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n Underlying data type.\n","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","FancyArray.prototype.length":"\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n Number of dimensions.\n","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","FancyArray.prototype.order":"\nFancyArray.prototype.order\n Array order.\n","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n Array shape.\n","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n","fastmath.abs":"\nfastmath.abs( x:number )\n Computes an absolute value.\n","fastmath.acosh":"\nfastmath.acosh( x:number )\n Computes the hyperbolic arccosine of a number.\n","fastmath.ampbm":"\nfastmath.ampbm( x:number, y:number )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha:number, beta:number, [nonnegative:boolean[, \n ints:boolean]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n","fastmath.asinh":"\nfastmath.asinh( x:number )\n Computes the hyperbolic arcsine of a number.\n","fastmath.atanh":"\nfastmath.atanh( x:number )\n Computes the hyperbolic arctangent of a number.\n","fastmath.hypot":"\nfastmath.hypot( x:number, y:number )\n Computes the hypotenuse.\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x:uinteger )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n","fastmath.max":"\nfastmath.max( x:number, y:number )\n Returns the maximum value.\n","fastmath.min":"\nfastmath.min( x:number, y:number )\n Returns the minimum value.\n","fastmath.powint":"\nfastmath.powint( x:number, y:integer )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x:uinteger )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n","FIFO":"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n","filledarray":"\nfilledarray( [dtype:string] )\n Creates a filled array.\n\nfilledarray( value:any, length:integer[, dtype:string] )\n Returns a filled array having a specified length.\n\nfilledarray( value:any, array:ArrayLikeObject[, dtype:string] )\n Creates a filled array from another array (or array-like object).\n\nfilledarray( value:any, iterable:Iterable[, dtype:string] )\n Creates a filled array from an iterable.\n\nfilledarray( value:any, buffer:ArrayBuffer[, byteOffset:integer[, \n length:integer]][, dtype:string] )\n Returns a filled typed array view of an ArrayBuffer.\n","filledarrayBy":"\nfilledarrayBy( [dtype:string] )\n Creates a filled array.\n\nfilledarrayBy( length:integer[, dtype:string], clbk:Function[, thisArg:any] )\n Returns a filled array according to a provided callback function and having\n a specified length.\n\nfilledarrayBy( array:ArrayLikeObject[, dtype:string], clbk:Function[, \n thisArg:any] )\n Creates a filled array from another array (or array-like object) according\n to a provided callback function.\n\nfilledarrayBy( iterable:Iterable[, dtype:string], clbk:Function[, thisArg:any] )\n Creates a filled array from an iterable according to a provided callback\n function.\n\nfilledarrayBy( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string], clbk:Function[, thisArg:any] )\n Returns a filled typed array view of an ArrayBuffer according to a provided\n callback function.\n","filterArguments":"\nfilterArguments( fcn:Function, predicate:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n","find":"\nfind( arr:Array|TypedArray|string, [options:Object,] clbk:Function )\n Finds elements in an array-like object that satisfy a test condition.\n","firstChar":"\nfirstChar( str:string[, n:integer][, options:Object] )\n Returns the first character(s) of a string.\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n Returns FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n","flattenArray":"\nflattenArray( arr:ArrayLikeObject[, options:Object] )\n Flattens an array.\n","flattenArray.factory":"\nflattenArray.factory( dims:ArrayLike[, options:Object] )\n Returns a function for flattening arrays having specified dimensions.\n","flattenObject":"\nflattenObject( obj:ObjectLike[, options:Object] )\n Flattens an object.\n","flattenObject.factory":"\nflattenObject.factory( [options:Object] )\n Returns a function to flatten an object.\n","flignerTest":"\nflignerTest( ...x:Array[, options:Object] )\n Computes the Fligner-Killeen test for equal variances.\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n Platform float word order.\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n","FLOAT16_EPS":"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n","FLOAT16_MAX":"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n","FLOAT16_NINF":"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n","FLOAT16_PINF":"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n","FLOAT32_EPS":"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n","FLOAT32_MAX":"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n","FLOAT32_NAN":"\nFLOAT32_NAN\n Single-precision floating-point NaN.\n","FLOAT32_NINF":"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n","FLOAT32_PINF":"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n","Float32Array":"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\nFloat32Array( length:integer )\n Returns a typed array having a specified length.\n\nFloat32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nFloat32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nFloat32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Float32Array.from":"\nFloat32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Float32Array.of":"\nFloat32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float32Array.name":"\nFloat32Array.name\n Typed array constructor name.\n","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n","FLOAT64_MAX":"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n","Float64Array":"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\nFloat64Array( length:integer )\n Returns a typed array having a specified length.\n\nFloat64Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nFloat64Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nFloat64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Float64Array.from":"\nFloat64Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Float64Array.of":"\nFloat64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float64Array.name":"\nFloat64Array.name\n Typed array constructor name.\n","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","forEach":"\nforEach( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection.\n","forEachAsync":"\nforEachAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection.\n","forEachAsync.factory":"\nforEachAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection.\n","forEachChar":"\nforEachChar( str:string, [options:Object,] clbk:Function[, thisArg:any] )\n Invokes a function for each character in a string.\n","forEachRight":"\nforEachRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n","forEachRightAsync":"\nforEachRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n","forIn":"\nforIn( obj:Object, fcn:Function[, thisArg:any] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n","forOwn":"\nforOwn( obj:Object, fcn:Function[, thisArg:any] )\n Invokes a function for each own enumerable property of an object.\n","FOURTH_PI":"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n","fromCodePoint":"\nfromCodePoint( ...pt:integer )\n Creates a string from a sequence of Unicode code points.\n","Function":"\nFunction( [...argNames:any,] body:string )\n Returns a Function object.\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg:any, args:Array )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n","Function.prototype.call":"\nFunction.prototype.call( thisArg:any, ...args:any )\n Calls a function with a given `this` value and arguments provided\n individually.\n","Function.prototype.bind":"\nFunction.prototype.bind( thisArg:any, ...args:any )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n","Function.prototype.toString":"\nFunction.prototype.toString()\n Returns a string representation of the function.\n","Function.prototype.length":"\nFunction.prototype.length\n The number of arguments expected by the function.\n","Function.prototype.name":"\nFunction.prototype.name\n The name of the function.\n","Function.prototype.prototype":"\nFunction.prototype.prototype\n The prototype of the function.\n","function2string":"\nfunction2string( fcn:Function )\n Returns a string representing the source code of a provided function.\n","functionName":"\nfunctionName( fcn:Function )\n Returns the name of a function.\n","functionSequence":"\nfunctionSequence( ...fcn:Function )\n Returns a pipeline function.\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn:Function )\n Returns a pipeline function.\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n","gdot":"\ngdot( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n Computes the dot product of two vectors.\n","getegid":"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n","geteuid":"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n","getgid":"\ngetgid()\n Returns the numeric group identity of the calling process.\n","getGlobal":"\ngetGlobal( [codegen:boolean] )\n Returns the global object.\n","getPrototypeOf":"\ngetPrototypeOf( value:any )\n Returns the prototype of a provided object.\n","getuid":"\ngetuid()\n Returns the numeric user identity of the calling process.\n","GLAISHER":"\nGLAISHER\n Glaisher-Kinkelin constant.\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src:string[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over each grapheme cluster in a string.\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src:string[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over each grapheme\n cluster in a string.\n","group":"\ngroup( collection:Array|TypedArray|Object, [options:Object,] \n groups:Array|TypedArray|Object )\n Groups values as arrays associated with distinct keys.\n","groupBy":"\ngroupBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Groups values according to an indicator function.\n","groupByAsync":"\ngroupByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Groups values according to an indicator function.\n","groupByAsync.factory":"\ngroupByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which groups values according to an indicator function.\n","groupIn":"\ngroupIn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n Group values according to an indicator function.\n","groupOwn":"\ngroupOwn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n Group values according to an indicator function.\n","gswap":"\ngswap( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n Interchanges two vectors.\n","HALF_LN2":"\nHALF_LN2\n One half times the natural logarithm of `2`.\n","HALF_PI":"\nHALF_PI\n One half times the mathematical constant `π`.\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n Tests for native `BigInt64Array` support.\n","hasBigIntSupport":"\nhasBigIntSupport()\n Tests for native `BigInt` support.\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n Tests for native `BigUint64Array` support.\n","hasClassSupport":"\nhasClassSupport()\n Tests for native `class` support.\n","hasDataViewSupport":"\nhasDataViewSupport()\n Tests for native `DataView` support.\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n Tests for native function `name` support.\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n Tests whether an environment supports native generator functions.\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n Tests for `globalThis` support.\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n","hasMapSupport":"\nhasMapSupport()\n Tests for native `Map` support.\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n","hasOwnProp":"\nhasOwnProp( value:any, property:any )\n Tests if an object has a specified property.\n","hasProp":"\nhasProp( value:any, property:any )\n Tests if an object has a specified property, either own or inherited.\n","hasProxySupport":"\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n","hasSetSupport":"\nhasSetSupport()\n Tests for native `Set` support.\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n","hasSymbolSupport":"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n Tests for native `toStringTag` support.\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n Tests for native `Uint16Array` support.\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n Tests for native `Uint32Array` support.\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str:string, pos:integer )\n Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n","headercase":"\nheadercase( str:string )\n Converts a string to HTTP header case.\n","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n","homedir":"\nhomedir()\n Returns the current user's home directory.\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n Number of hours in a day.\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n Number of hours in a week.\n","hoursInMonth":"\nhoursInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of hours in a month.\n","hoursInYear":"\nhoursInYear( [value:integer|Date] )\n Returns the number of hours in a year according to the Gregorian calendar.\n","httpServer":"\nhttpServer( [options:Object,] [requestListener:Function] )\n Returns a function to create an HTTP server.\n","identity":"\nidentity( x:any )\n Identity function.\n","ifelse":"\nifelse( bool:boolean, x:any, y:any )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n","ifelseAsync":"\nifelseAsync( predicate:Function, x:any, y:any, done:Function )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n","ifthen":"\nifthen( bool:boolean, x:Function, y:Function )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n","ifthenAsync":"\nifthenAsync( predicate:Function, x:Function, y:Function, done:Function )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n","imag":"\nimag( z:Complex128 )\n Returns the imaginary component of a double-precision complex floating-point\n number.\n","imagf":"\nimagf( z:Complex64 )\n Returns the imaginary component of a single-precision complex floating-point\n number.\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium ostrowskianum*.\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n","incrapcorr":"\nincrapcorr( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n","incrBinaryClassification":"\nincrBinaryClassification( N:integer[, options:Object] )\n Returns an accumulator function which incrementally performs binary\n classification using stochastic gradient descent (SGD).\n","incrcount":"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n","incrcovariance":"\nincrcovariance( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n","incrcovmat":"\nincrcovmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n","incrcv":"\nincrcv( [mean:number] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n","increwmean":"\nincrewmean( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n","increwstdev":"\nincrewstdev( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n","increwvariance":"\nincrewvariance( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n","incrgmean":"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n","incrgrubbs":"\nincrgrubbs( [options:Object] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n","incrhmean":"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n","incrkmeans":"\nincrkmeans( k:integer|ndarray[, ndims:integer][, options:Object] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n","incrkurtosis":"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n","incrmaape":"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n","incrmae":"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n","incrmapcorr":"\nincrmapcorr( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n","incrmape":"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n","incrmax":"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n","incrmaxabs":"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n","incrmcovariance":"\nincrmcovariance( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n","incrmcv":"\nincrmcv( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n","incrmda":"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n","incrme":"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n","incrmean":"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n","incrmeanabs":"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n","incrmeanabs2":"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n","incrmeanstdev":"\nincrmeanstdev( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n","incrmeanvar":"\nincrmeanvar( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n","incrmgmean":"\nincrmgmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n","incrmgrubbs":"\nincrmgrubbs( W:integer[, options:Object] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n","incrmhmean":"\nincrmhmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n","incrmidrange":"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n","incrmin":"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n","incrminabs":"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n","incrminmax":"\nincrminmax( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n","incrminmaxabs":"\nincrminmaxabs( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n","incrmmaape":"\nincrmmaape( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n","incrmmae":"\nincrmmae( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n","incrmmape":"\nincrmmape( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n","incrmmax":"\nincrmmax( W:integer )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n","incrmmaxabs":"\nincrmmaxabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n","incrmmda":"\nincrmmda( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n","incrmme":"\nincrmme( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n","incrmmean":"\nincrmmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n","incrmmeanabs":"\nincrmmeanabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n","incrmmeanabs2":"\nincrmmeanabs2( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n","incrmmeanstdev":"\nincrmmeanstdev( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n","incrmmeanvar":"\nincrmmeanvar( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n","incrmmidrange":"\nincrmmidrange( W:integer )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n","incrmmin":"\nincrmmin( W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n","incrmminabs":"\nincrmminabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n","incrmminmax":"\nincrmminmax( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n","incrmminmaxabs":"\nincrmminmaxabs( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n","incrmmpe":"\nincrmmpe( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n","incrmmse":"\nincrmmse( W:integer )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n","incrmpcorr":"\nincrmpcorr( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n","incrmpcorr2":"\nincrmpcorr2( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n","incrmpcorrdist":"\nincrmpcorrdist( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n","incrmpe":"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n","incrmprod":"\nincrmprod( W:integer )\n Returns an accumulator function which incrementally computes a moving\n product.\n","incrmrange":"\nincrmrange( W:integer )\n Returns an accumulator function which incrementally computes a moving range.\n","incrmrmse":"\nincrmrmse( W:integer )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n","incrmrss":"\nincrmrss( W:integer )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n","incrmse":"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n","incrmstdev":"\nincrmstdev( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n","incrmsum":"\nincrmsum( W:integer )\n Returns an accumulator function which incrementally computes a moving sum.\n","incrmsumabs":"\nincrmsumabs( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n","incrmsumabs2":"\nincrmsumabs2( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n","incrmsummary":"\nincrmsummary( W:integer )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n","incrmsumprod":"\nincrmsumprod( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n","incrmvariance":"\nincrmvariance( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n","incrmvmr":"\nincrmvmr( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n","incrnancount":"\nincrnancount()\n Returns an accumulator function which incrementally updates a count,\n ignoring `NaN` values.\n","incrnansum":"\nincrnansum()\n Returns an accumulator function which incrementally computes a sum, ignoring\n `NaN` values.\n","incrnansumabs":"\nincrnansumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values, ignoring NaN values.\n","incrnansumabs2":"\nincrnansumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values, ignoring NaN values.\n","incrpcorr":"\nincrpcorr( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n","incrpcorr2":"\nincrpcorr2( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n","incrpcorrdist":"\nincrpcorrdist( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n","incrpcorrdistmat":"\nincrpcorrdistmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n","incrpcorrmat":"\nincrpcorrmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n","incrprod":"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n","incrrange":"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n","incrrmse":"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n","incrrss":"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n","incrskewness":"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n","incrspace":"\nincrspace( start:number, stop:number[, increment:number] )\n Generates a linearly spaced numeric array using a provided increment.\n","incrstdev":"\nincrstdev( [mean:number] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n","incrsum":"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n","incrsumabs":"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n","incrsumabs2":"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n","incrsummary":"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n","incrsumprod":"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n","incrvariance":"\nincrvariance( [mean:number] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n","incrvmr":"\nincrvmr( [mean:number] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n","incrwmean":"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n","ind2sub":"\nind2sub( shape:ArrayLike, idx:integer[, options:Object] )\n Converts a linear index to an array of subscripts.\n","ind2sub.assign":"\nind2sub.assign( shape:ArrayLike, idx:integer[, options:Object], \n out:Array|TypedArray|Object )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n","indexOf":"\nindexOf( arr:ArrayLike, searchElement:any[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","inherit":"\ninherit( ctor:Object|Function, superCtor:Object|Function )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable symbol properties.\n","inheritedKeys":"\ninheritedKeys( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable property names.\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable property names.\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n","inheritedProperties":"\ninheritedProperties( value:any[, level:integer] )\n Returns an array of an object's inherited property names and symbols.\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value:any, property:string|symbol[, \n level:integer] )\n Returns a property descriptor for an object's inherited property.\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value:any[, level:integer] )\n Returns an object's inherited property descriptors.\n","inheritedPropertyNames":"\ninheritedPropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited symbol properties.\n","inheritedWritableProperties":"\ninheritedWritableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited writable property names and\n symbols.\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited writable property names.\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited writable symbol properties.\n","inmap":"\ninmap( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n","inmapAsync":"\ninmapAsync( collection:Array|TypedArray|Object, [options:Object,] fcn:Function, \n done:Function )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n","inmapAsync.factory":"\ninmapAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n","inmapRight":"\ninmapRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n","inmapRightAsync":"\ninmapRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n","inspectSinkStream":"\ninspectSinkStream( [options:Object,] clbk:Function )\n Returns a writable stream for inspecting stream data.\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options:Object] )\n Returns a function for creating writable streams for inspecting stream data.\n","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options:Object,] clbk:Function )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n","inspectStream":"\ninspectStream( [options:Object,] clbk:Function )\n Returns a transform stream for inspecting stream data.\n","inspectStream.factory":"\ninspectStream.factory( [options:Object] )\n Returns a function for creating transform streams for inspecting stream\n data.\n","inspectStream.objectMode":"\ninspectStream.objectMode( [options:Object,] clbk:Function )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n","instanceOf":"\ninstanceOf( value:any, constructor:Function )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n","INT8_MAX":"\nINT8_MAX\n Maximum signed 8-bit integer.\n","INT8_MIN":"\nINT8_MIN\n Minimum signed 8-bit integer.\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n","Int8Array":"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\nInt8Array( length:integer )\n Returns a typed array having a specified length.\n\nInt8Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt8Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int8Array.from":"\nInt8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int8Array.of":"\nInt8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int8Array.name":"\nInt8Array.name\n Typed array constructor name.\n","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int8Array.prototype.length":"\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n Serializes an array as a string.\n","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","INT16_MAX":"\nINT16_MAX\n Maximum signed 16-bit integer.\n","INT16_MIN":"\nINT16_MIN\n Minimum signed 16-bit integer.\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n","Int16Array":"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\nInt16Array( length:integer )\n Returns a typed array having a specified length.\n\nInt16Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt16Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int16Array.from":"\nInt16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int16Array.of":"\nInt16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int16Array.name":"\nInt16Array.name\n Typed array constructor name.\n","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int16Array.prototype.length":"\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n Serializes an array as a string.\n","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","INT32_MAX":"\nINT32_MAX\n Maximum signed 32-bit integer.\n","INT32_MIN":"\nINT32_MIN\n Minimum signed 32-bit integer.\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n","Int32Array":"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\nInt32Array( length:integer )\n Returns a typed array having a specified length.\n\nInt32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int32Array.from":"\nInt32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int32Array.of":"\nInt32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int32Array.name":"\nInt32Array.name\n Typed array constructor name.\n","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int32Array.prototype.length":"\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n Serializes an array as a string.\n","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n","IS_BROWSER":"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n","IS_DARWIN":"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n","IS_ELECTRON":"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n","IS_NODE":"\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n","IS_WINDOWS":"\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n","isAbsolutePath":"\nisAbsolutePath( value:any )\n Tests if a value is an absolute path.\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value:any )\n Tests if a value is a POSIX absolute path.\n","isAbsolutePath.win32":"\nisAbsolutePath.win32( value:any )\n Tests if a value is a Windows absolute path.\n","isAccessorArray":"\nisAccessorArray( value:any )\n Tests if a value is an array-like object supporting the accessor (get/set)\n protocol.\n","isAccessorProperty":"\nisAccessorProperty( value:any, property:any )\n Tests if an object's own property has an accessor descriptor.\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property has an accessor descriptor.\n","isAlphagram":"\nisAlphagram( value:any )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n","isAlphaNumeric":"\nisAlphaNumeric( str:string )\n Tests whether a string contains only alphanumeric characters.\n","isAnagram":"\nisAnagram( str:string, value:any )\n Tests if a value is an anagram.\n","isArguments":"\nisArguments( value:any )\n Tests if a value is an arguments object.\n","isArray":"\nisArray( value:any )\n Tests if a value is an array.\n","isArrayArray":"\nisArrayArray( value:any )\n Tests if a value is an array of arrays.\n","isArrayBuffer":"\nisArrayBuffer( value:any )\n Tests if a value is an ArrayBuffer.\n","isArrayBufferView":"\nisArrayBufferView( value:any )\n Tests if a value is a `ArrayBuffer` view.\n","isArrayLength":"\nisArrayLength( value:any )\n Tests if a value is a valid array length.\n","isArrayLike":"\nisArrayLike( value:any )\n Tests if a value is array-like.\n","isArrayLikeObject":"\nisArrayLikeObject( value:any )\n Tests if a value is an array-like object.\n","isASCII":"\nisASCII( str:string )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n","isBetween":"\nisBetween( value:any, a:any, b:any[, left:string, right:string] )\n Tests if a value is between two values.\n","isBetweenArray":"\nisBetweenArray( value:any, a:any, b:any[, left:string, right:string] )\n Tests if a value is an array-like object where every element is between two\n values.\n","isBigInt":"\nisBigInt( value:any )\n Tests if a value is a BigInt.\n","isBigInt64Array":"\nisBigInt64Array( value:any )\n Tests if a value is a BigInt64Array.\n","isBigUint64Array":"\nisBigUint64Array( value:any )\n Tests if a value is a BigUint64Array.\n","isBinaryString":"\nisBinaryString( value:any )\n Tests if a value is a binary string.\n","isBlankString":"\nisBlankString( value:any )\n Tests if a value is a blank string (i.e., an empty string or a string\n consisting only of whitespace characters).\n","isBoolean":"\nisBoolean( value:any )\n Tests if a value is a boolean.\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value:any )\n Tests if a value is a boolean primitive.\n","isBoolean.isObject":"\nisBoolean.isObject( value:any )\n Tests if a value is a boolean object.\n","isBooleanArray":"\nisBooleanArray( value:any )\n Tests if a value is an array-like object of booleans.\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value:any )\n Tests if a value is an array-like object containing only boolean primitives.\n","isBooleanArray.objects":"\nisBooleanArray.objects( value:any )\n Tests if a value is an array-like object containing only Boolean objects.\n","isBoxedPrimitive":"\nisBoxedPrimitive( value:any )\n Tests if a value is a JavaScript boxed primitive.\n","isBuffer":"\nisBuffer( value:any )\n Tests if a value is a Buffer instance.\n","isCapitalized":"\nisCapitalized( value:any )\n Tests if a value is a string having an uppercase first character.\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value:any )\n Tests if a value is a matrix which is symmetric about its center.\n","isCircular":"\nisCircular( value:any )\n Tests if an object-like value contains a circular reference.\n","isCircularArray":"\nisCircularArray( value:any )\n Tests if a value is an array containing a circular reference.\n","isCircularPlainObject":"\nisCircularPlainObject( value:any )\n Tests if a value is a plain object containing a circular reference.\n","isClass":"\nisClass( value:any )\n Tests if a value is a class.\n","isCollection":"\nisCollection( value:any )\n Tests if a value is a collection.\n","isComplex":"\nisComplex( value:any )\n Tests if a value is a 64-bit or 128-bit complex number.\n","isComplex64":"\nisComplex64( value:any )\n Tests if a value is a 64-bit complex number.\n","isComplex64Array":"\nisComplex64Array( value:any )\n Tests if a value is a Complex64Array.\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing single-precision\n complex floating-point numbers.\n","isComplex64VectorLike":"\nisComplex64VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n","isComplex128":"\nisComplex128( value:any )\n Tests if a value is a 128-bit complex number.\n","isComplex128Array":"\nisComplex128Array( value:any )\n Tests if a value is a Complex128Array.\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing double-precision\n complex floating-point numbers.\n","isComplex128VectorLike":"\nisComplex128VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n","isComplexLike":"\nisComplexLike( value:any )\n Tests if a value is a complex number-like object.\n","isComplexTypedArray":"\nisComplexTypedArray( value:any )\n Tests if a value is a complex typed array.\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value:any )\n Tests if a value is complex-typed-array-like.\n","isComposite":"\nisComposite( value:any )\n Tests if a value is a composite number.\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value:any )\n Tests if a value is a number primitive which is a composite number.\n","isComposite.isObject":"\nisComposite.isObject( value:any )\n Tests if a value is a number object having a value which is a composite\n number.\n","isConfigurableProperty":"\nisConfigurableProperty( value:any, property:any )\n Tests if an object's own property is configurable.\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is configurable.\n","isCubeNumber":"\nisCubeNumber( value:any )\n Tests if a value is a cube number.\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a cube number.\n","isCubeNumber.isObject":"\nisCubeNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a cube number.\n","isDataProperty":"\nisDataProperty( value:any, property:any )\n Tests if an object's own property has a data descriptor.\n","isDataPropertyIn":"\nisDataPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property has a data descriptor.\n","isDataView":"\nisDataView( value:any )\n Tests if a value is a DataView.\n","isDateObject":"\nisDateObject( value:any )\n Tests if a value is a Date object.\n","isDateObjectArray":"\nisDateObjectArray( value:any )\n Tests if a value is an array-like object containing only Date objects.\n","isDigitString":"\nisDigitString( str:string )\n Tests whether a string contains only numeric digits.\n","isEmailAddress":"\nisEmailAddress( value:any )\n Tests if a value is an email address.\n","isEmptyArray":"\nisEmptyArray( value:any )\n Tests if a value is an empty array.\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value:any )\n Tests if a value is an empty array-like object.\n","isEmptyCollection":"\nisEmptyCollection( value:any )\n Tests if a value is an empty collection.\n","isEmptyObject":"\nisEmptyObject( value:any )\n Tests if a value is an empty object.\n","isEmptyString":"\nisEmptyString( value:any )\n Tests if a value is an empty string.\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value:any )\n Tests if a value is an empty string primitive.\n","isEmptyString.isObject":"\nisEmptyString.isObject( value:any )\n Tests if a value is an empty `String` object.\n","isEnumerableProperty":"\nisEnumerableProperty( value:any, property:any )\n Tests if an object's own property is enumerable.\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is enumerable.\n","isError":"\nisError( value:any )\n Tests if a value is an Error object.\n","isEvalError":"\nisEvalError( value:any )\n Tests if a value is an EvalError object.\n","isEven":"\nisEven( value:any )\n Tests if a value is an even number.\n","isEven.isPrimitive":"\nisEven.isPrimitive( value:any )\n Tests if a value is a number primitive that is an even number.\n","isEven.isObject":"\nisEven.isObject( value:any )\n Tests if a value is a number object that is an even number.\n","isFalsy":"\nisFalsy( value:any )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n","isFalsyArray":"\nisFalsyArray( value:any )\n Tests if a value is an array-like object containing only falsy values.\n","isFinite":"\nisFinite( value:any )\n Tests if a value is a finite number.\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a finite value.\n","isFinite.isObject":"\nisFinite.isObject( value:any )\n Tests if a value is a number object having a finite value.\n","isFiniteArray":"\nisFiniteArray( value:any )\n Tests if a value is an array-like object of finite numbers.\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n","isFiniteArray.objects":"\nisFiniteArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n","isFloat32Array":"\nisFloat32Array( value:any )\n Tests if a value is a Float32Array.\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing single-precision\n floating-point numbers.\n","isFloat32VectorLike":"\nisFloat32VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n","isFloat64Array":"\nisFloat64Array( value:any )\n Tests if a value is a Float64Array.\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing double-precision\n floating-point numbers.\n","isFloat64VectorLike":"\nisFloat64VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n","isFunction":"\nisFunction( value:any )\n Tests if a value is a function.\n","isFunctionArray":"\nisFunctionArray( value:any )\n Tests if a value is an array-like object containing only functions.\n","isGeneratorObject":"\nisGeneratorObject( value:any )\n Tests if a value is a generator object.\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value:any )\n Tests if a value is generator object-like.\n","isgzipBuffer":"\nisgzipBuffer( value:any )\n Tests if a value is a gzip buffer.\n","isHexString":"\nisHexString( str:string )\n Tests whether a string contains only hexadecimal digits.\n","isInfinite":"\nisInfinite( value:any )\n Tests if a value is an infinite number.\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value:any )\n Tests if a value is a number primitive having an infinite value.\n","isInfinite.isObject":"\nisInfinite.isObject( value:any )\n Tests if a value is a number object having an infinite value.\n","isInheritedProperty":"\nisInheritedProperty( value:any, property:any )\n Tests if an object has an inherited property.\n","isInt8Array":"\nisInt8Array( value:any )\n Tests if a value is an Int8Array.\n","isInt16Array":"\nisInt16Array( value:any )\n Tests if a value is an Int16Array.\n","isInt32Array":"\nisInt32Array( value:any )\n Tests if a value is an Int32Array.\n","isInteger":"\nisInteger( value:any )\n Tests if a value is an integer.\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having an integer value.\n","isInteger.isObject":"\nisInteger.isObject( value:any )\n Tests if a value is a number object having an integer value.\n","isIntegerArray":"\nisIntegerArray( value:any )\n Tests if a value is an array-like object of integer values.\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive integer\n values.\n","isIntegerArray.objects":"\nisIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n","isIterableLike":"\nisIterableLike( value:any )\n Tests if a value is iterable-like.\n","isIteratorLike":"\nisIteratorLike( value:any )\n Tests if a value is iterator-like.\n","isJSON":"\nisJSON( value:any )\n Tests if a value is a parseable JSON string.\n","isLeapYear":"\nisLeapYear( value:any )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n","isLocalhost":"\nisLocalhost( value:any )\n Tests whether a value is a localhost hostname.\n","isLowercase":"\nisLowercase( value:any )\n Tests if a value is a lowercase string.\n","isMatrixLike":"\nisMatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object.\n","isMethod":"\nisMethod( value:any, property:any )\n Tests if an object has a specified method name.\n","isMethodIn":"\nisMethodIn( value:any, property:any )\n Tests if an object has a specified method name, either own or inherited.\n","isMultiSlice":"\nisMultiSlice( value:any )\n Tests if a value is a MultiSlice object.\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value:any )\n Tests if a value is named typed tuple-like.\n","isnan":"\nisnan( value:any )\n Tests if a value is NaN.\n","isnan.isPrimitive":"\nisnan.isPrimitive( value:any )\n Tests if a value is a NaN number primitive.\n","isnan.isObject":"\nisnan.isObject( value:any )\n Tests if a value is a number object having a value of NaN.\n","isNaNArray":"\nisNaNArray( value:any )\n Tests if a value is an array-like object containing only NaN values.\n","isNaNArray.primitives":"\nisNaNArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n","isNaNArray.objects":"\nisNaNArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n","isNativeFunction":"\nisNativeFunction( value:any )\n Tests if a value is a native function.\n","isndarrayLike":"\nisndarrayLike( value:any )\n Tests if a value is ndarray-like.\n","isNegativeInteger":"\nisNegativeInteger( value:any )\n Tests if a value is a negative integer.\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a negative integer value.\n","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value:any )\n Tests if a value is a number object having a negative integer value.\n","isNegativeIntegerArray":"\nisNegativeIntegerArray( value:any )\n Tests if a value is an array-like object containing only negative integers.\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n","isNegativeNumber":"\nisNegativeNumber( value:any )\n Tests if a value is a negative number.\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a negative value.\n","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value:any )\n Tests if a value is a number object having a negative value.\n","isNegativeNumberArray":"\nisNegativeNumberArray( value:any )\n Tests if a value is an array-like object containing only negative numbers.\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n","isNegativeZero":"\nisNegativeZero( value:any )\n Tests if a value is negative zero.\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value:any )\n Tests if a value is a number primitive equal to negative zero.\n","isNegativeZero.isObject":"\nisNegativeZero.isObject( value:any )\n Tests if a value is a number object having a value equal to negative zero.\n","isNodeBuiltin":"\nisNodeBuiltin( str:string )\n Tests whether a string matches a Node.js built-in module name.\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value:any )\n Tests if a value is Node duplex stream-like.\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value:any )\n Tests if a value is Node readable stream-like.\n","isNodeREPL":"\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n","isNodeStreamLike":"\nisNodeStreamLike( value:any )\n Tests if a value is Node stream-like.\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value:any )\n Tests if a value is Node transform stream-like.\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value:any )\n Tests if a value is Node writable stream-like.\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value:any, property:any )\n Tests if an object's own property is non-configurable.\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is non-configurable.\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value:any, property:any )\n Tests if an object's own property is non-enumerable.\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is non-enumerable.\n","isNonNegativeFinite":"\nisNonNegativeFinite( value:any )\n Tests if a value is a nonnegative finite number.\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative finite value.\n","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value:any )\n Tests if a value is a number object having a nonnegative finite value.\n","isNonNegativeInteger":"\nisNonNegativeInteger( value:any )\n Tests if a value is a nonnegative integer.\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative integer value.\n","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value:any )\n Tests if a value is a number object having a nonnegative integer value.\n","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value:any )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n","isNonNegativeNumber":"\nisNonNegativeNumber( value:any )\n Tests if a value is a nonnegative number.\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative value.\n","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value:any )\n Tests if a value is a number object having a nonnegative value.\n","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value:any )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n","isNonPositiveInteger":"\nisNonPositiveInteger( value:any )\n Tests if a value is a nonpositive integer.\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive integer value.\n","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value:any )\n Tests if a value is a number object having a nonpositive integer value.\n","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value:any )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n","isNonPositiveNumber":"\nisNonPositiveNumber( value:any )\n Tests if a value is a nonpositive number.\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive value.\n","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value:any )\n Tests if a value is a number object having a nonpositive value.\n","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value:any )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value:any )\n Tests if a value is a non-symmetric matrix.\n","isNull":"\nisNull( value:any )\n Tests if a value is null.\n","isNullArray":"\nisNullArray( value:any )\n Tests if a value is an array-like object containing only null values.\n","isNumber":"\nisNumber( value:any )\n Tests if a value is a number.\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value:any )\n Tests if a value is a number primitive.\n","isNumber.isObject":"\nisNumber.isObject( value:any )\n Tests if a value is a `Number` object.\n","isNumberArray":"\nisNumberArray( value:any )\n Tests if a value is an array-like object containing only numbers.\n","isNumberArray.primitives":"\nisNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only number primitives.\n","isNumberArray.objects":"\nisNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only `Number` objects.\n","isNumericArray":"\nisNumericArray( value:any )\n Tests if a value is a numeric array.\n","isObject":"\nisObject( value:any )\n Tests if a value is an object; e.g., `{}`.\n","isObjectArray":"\nisObjectArray( value:any )\n Tests if a value is an array-like object containing only objects.\n","isObjectLike":"\nisObjectLike( value:any )\n Tests if a value is object-like.\n","isOdd":"\nisOdd( value:any )\n Tests if a value is an odd number.\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value:any )\n Tests if a value is a number primitive that is an odd number.\n","isOdd.isObject":"\nisOdd.isObject( value:any )\n Tests if a value is a number object that has an odd number value.\n","isoWeeksInYear":"\nisoWeeksInYear( [year:integer] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n","isPersymmetricMatrix":"\nisPersymmetricMatrix( value:any )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n","isPlainObject":"\nisPlainObject( value:any )\n Tests if a value is a plain object.\n","isPlainObjectArray":"\nisPlainObjectArray( value:any )\n Tests if a value is an array-like object containing only plain objects.\n","isPositiveInteger":"\nisPositiveInteger( value:any )\n Tests if a value is a positive integer.\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive integer value.\n","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value:any )\n Tests if a value is a number object having a positive integer value.\n","isPositiveIntegerArray":"\nisPositiveIntegerArray( value:any )\n Tests if a value is an array-like object containing only positive integers.\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n","isPositiveNumber":"\nisPositiveNumber( value:any )\n Tests if a value is a positive number.\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive value.\n","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value:any )\n Tests if a value is a number object having a positive value.\n","isPositiveNumberArray":"\nisPositiveNumberArray( value:any )\n Tests if a value is an array-like object containing only positive numbers.\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n","isPositiveZero":"\nisPositiveZero( value:any )\n Tests if a value is positive zero.\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value:any )\n Tests if a value is a number primitive equal to positive zero.\n","isPositiveZero.isObject":"\nisPositiveZero.isObject( value:any )\n Tests if a value is a number object having a value equal to positive zero.\n","isPrime":"\nisPrime( value:any )\n Tests if a value is a prime number.\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value:any )\n Tests if a value is a number primitive which is a prime number.\n","isPrime.isObject":"\nisPrime.isObject( value:any )\n Tests if a value is a number object having a value which is a prime number.\n","isPrimitive":"\nisPrimitive( value:any )\n Tests if a value is a JavaScript primitive.\n","isPrimitiveArray":"\nisPrimitiveArray( value:any )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n","isPRNGLike":"\nisPRNGLike( value:any )\n Tests if a value is PRNG-like.\n","isProbability":"\nisProbability( value:any )\n Tests if a value is a probability.\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value:any )\n Tests if a value is a number primitive which is a probability.\n","isProbability.isObject":"\nisProbability.isObject( value:any )\n Tests if a value is a number object having a value which is a probability.\n","isProbabilityArray":"\nisProbabilityArray( value:any )\n Tests if a value is an array-like object containing only probabilities.\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n","isProbabilityArray.objects":"\nisProbabilityArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n","isPropertyKey":"\nisPropertyKey( value:any )\n Tests whether a value is a property key.\n","isPrototypeOf":"\nisPrototypeOf( value:any, proto:Object|Function )\n Tests if an object's prototype chain contains a provided prototype.\n","isRangeError":"\nisRangeError( value:any )\n Tests if a value is a RangeError object.\n","isReadableProperty":"\nisReadableProperty( value:any, property:any )\n Tests if an object's own property is readable.\n","isReadablePropertyIn":"\nisReadablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is readable.\n","isReadOnlyProperty":"\nisReadOnlyProperty( value:any, property:any )\n Tests if an object's own property is read-only.\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is read-only.\n","isReadWriteProperty":"\nisReadWriteProperty( value:any, property:any )\n Tests if an object's own property is readable and writable.\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is readable and writable.\n","isReferenceError":"\nisReferenceError( value:any )\n Tests if a value is a ReferenceError object.\n","isRegExp":"\nisRegExp( value:any )\n Tests if a value is a regular expression.\n","isRegExpString":"\nisRegExpString( value:any )\n Tests if a value is a regular expression string.\n","isRelativePath":"\nisRelativePath( value:any )\n Tests if a value is a relative path.\n","isRelativePath.posix":"\nisRelativePath.posix( value:any )\n Tests if a value is a POSIX relative path.\n","isRelativePath.win32":"\nisRelativePath.win32( value:any )\n Tests if a value is a Windows relative path.\n","isSafeInteger":"\nisSafeInteger( value:any )\n Tests if a value is a safe integer.\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a safe integer value.\n","isSafeInteger.isObject":"\nisSafeInteger.isObject( value:any )\n Tests if a value is a `Number` object having a safe integer value.\n","isSafeIntegerArray":"\nisSafeIntegerArray( value:any )\n Tests if a value is an array-like object containing only safe integers.\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n","isSameArray":"\nisSameArray( v1:any, v2:any )\n Tests if two arguments are both generic arrays and have the same values.\n","isSameComplex64":"\nisSameComplex64( v1:any, v2:any )\n Tests if two arguments are both single-precision complex floating-point\n numbers and have the same value.\n","isSameComplex64Array":"\nisSameComplex64Array( v1:any, v2:any )\n Tests if two arguments are both Complex64Arrays and have the same values.\n","isSameComplex128":"\nisSameComplex128( v1:any, v2:any )\n Tests if two arguments are both double-precision complex floating-point\n numbers and have the same value.\n","isSameComplex128Array":"\nisSameComplex128Array( v1:any, v2:any )\n Tests if two arguments are both Complex128Arrays and have the same values.\n","isSameFloat32Array":"\nisSameFloat32Array( v1:any, v2:any )\n Tests if two arguments are both Float32Arrays and have the same values.\n","isSameFloat64Array":"\nisSameFloat64Array( v1:any, v2:any )\n Tests if two arguments are both Float64Arrays and have the same values.\n","isSameNativeClass":"\nisSameNativeClass( a:any, b:any )\n Tests if two arguments have the same native class.\n","isSameType":"\nisSameType( a:any, b:any )\n Tests if two arguments have the same type.\n","isSameValue":"\nisSameValue( a:any, b:any )\n Tests if two arguments are the same value.\n","isSameValueZero":"\nisSameValueZero( a:any, b:any )\n Tests if two arguments are the same value.\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value:any )\n Tests if a value is a SharedArrayBuffer.\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value:any )\n Tests if a value is a skew-centrosymmetric matrix.\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value:any )\n Tests if a value is a skew-persymmetric matrix.\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value:any )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n","isSlice":"\nisSlice( value:any )\n Tests if a value is a Slice object.\n","isSquareMatrix":"\nisSquareMatrix( value:any )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n","isSquareNumber":"\nisSquareNumber( value:any )\n Tests if a value is a square number.\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a square number.\n","isSquareNumber.isObject":"\nisSquareNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a square number.\n","isSquareTriangularNumber":"\nisSquareTriangularNumber( value:any )\n Tests if a value is a square triangular number.\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a square triangular number.\n","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a square\n triangular number.\n","isStrictEqual":"\nisStrictEqual( a:any, b:any )\n Tests if two arguments are strictly equal.\n","isString":"\nisString( value:any )\n Tests if a value is a string.\n","isString.isPrimitive":"\nisString.isPrimitive( value:any )\n Tests if a value is a string primitive.\n","isString.isObject":"\nisString.isObject( value:any )\n Tests if a value is a `String` object.\n","isStringArray":"\nisStringArray( value:any )\n Tests if a value is an array of strings.\n","isStringArray.primitives":"\nisStringArray.primitives( value:any )\n Tests if a value is an array containing only string primitives.\n","isStringArray.objects":"\nisStringArray.objects( value:any )\n Tests if a value is an array containing only `String` objects.\n","isSymbol":"\nisSymbol( value:any )\n Tests if a value is a symbol.\n","isSymbolArray":"\nisSymbolArray( value:any )\n Tests if a value is an array-like object containing only symbols.\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value:any )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n","isSymbolArray.objects":"\nisSymbolArray.objects( value:any )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n","isSymmetricMatrix":"\nisSymmetricMatrix( value:any )\n Tests if a value is a square matrix which equals its transpose.\n","isSyntaxError":"\nisSyntaxError( value:any )\n Tests if a value is a SyntaxError object.\n","isTriangularNumber":"\nisTriangularNumber( value:any )\n Tests if a value is a triangular number.\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a triangular number.\n","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a triangular\n number.\n","isTruthy":"\nisTruthy( value:any )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n","isTruthyArray":"\nisTruthyArray( value:any )\n Tests if a value is an array-like object containing only truthy values.\n","isTypedArray":"\nisTypedArray( value:any )\n Tests if a value is a typed array.\n","isTypedArrayLength":"\nisTypedArrayLength( value:any )\n Tests if a value is a valid typed array length.\n","isTypedArrayLike":"\nisTypedArrayLike( value:any )\n Tests if a value is typed-array-like.\n","isTypeError":"\nisTypeError( value:any )\n Tests if a value is a TypeError object.\n","isUint8Array":"\nisUint8Array( value:any )\n Tests if a value is a Uint8Array.\n","isUint8ClampedArray":"\nisUint8ClampedArray( value:any )\n Tests if a value is a Uint8ClampedArray.\n","isUint16Array":"\nisUint16Array( value:any )\n Tests if a value is a Uint16Array.\n","isUint32Array":"\nisUint32Array( value:any )\n Tests if a value is a Uint32Array.\n","isUNCPath":"\nisUNCPath( value:any )\n Tests if a value is a UNC path.\n","isUndefined":"\nisUndefined( value:any )\n Tests if a value is undefined.\n","isUndefinedOrNull":"\nisUndefinedOrNull( value:any )\n Tests if a value is undefined or null.\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value:any )\n Tests if a value is an array of probabilities that sum to one.\n","isUppercase":"\nisUppercase( value:any )\n Tests if a value is an uppercase string.\n","isURI":"\nisURI( value:any )\n Tests if a value is a URI.\n","isURIError":"\nisURIError( value:any )\n Tests if a value is a URIError object.\n","isVectorLike":"\nisVectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object.\n","isWhitespace":"\nisWhitespace( str:string )\n Tests whether a string contains only white space characters.\n","isWritableProperty":"\nisWritableProperty( value:any, property:any )\n Tests if an object's own property is writable.\n","isWritablePropertyIn":"\nisWritablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is writable.\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value:any, property:any )\n Tests if an object's own property is write-only.\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is write-only.\n","iterAbs":"\niterAbs( iterator:Object )\n Returns an iterator which iteratively computes the absolute value.\n","iterAbs2":"\niterAbs2( iterator:Object )\n Returns an iterator which iteratively computes the squared absolute value.\n","iterAcos":"\niterAcos( iterator:Object )\n Returns an iterator which iteratively computes the arccosine.\n","iterAcosh":"\niterAcosh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arccosine.\n","iterAcot":"\niterAcot( iterator:Object )\n Returns an iterator which iteratively computes the inverse cotangent.\n","iterAcoth":"\niterAcoth( iterator:Object )\n Returns an iterator which iteratively computes the inverse hyperbolic\n cotangent.\n","iterAcovercos":"\niterAcovercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse coversed cosine.\n","iterAcoversin":"\niterAcoversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse coversed sine.\n","iterAdd":"\niterAdd( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n","iterAdvance":"\niterAdvance( iterator:Object[, n:integer] )\n Advances an entire iterator.\n","iterAhavercos":"\niterAhavercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse half-value versed\n cosine.\n","iterAhaversin":"\niterAhaversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse half-value versed\n sine.\n","iterAny":"\niterAny( iterator:Object )\n Tests whether at least one iterated value is truthy.\n","iterAnyBy":"\niterAnyBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n","iterAsin":"\niterAsin( iterator:Object )\n Returns an iterator which iteratively computes the arcsine.\n","iterAsinh":"\niterAsinh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arcsine.\n","iterAtan":"\niterAtan( iterator:Object )\n Returns an iterator which iteratively computes the arctangent.\n","iterAtan2":"\niterAtan2( y:Object|number, x:Object|number )\n Returns an iterator which iteratively computes the angle in the plane (in\n radians) between the positive x-axis and the ray from (0,0) to the point\n (x,y).\n","iterAtanh":"\niterAtanh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arctangent.\n","iterator2array":"\niterator2array( iterator:Object[, out:ArrayLikeObject][, mapFcn:Function[, \n thisArg:any]] )\n Creates (or fills) an array from an iterator.\n","iterator2arrayview":"\niterator2arrayview( iterator:Object, dest:ArrayLikeObject[, begin:integer[, \n end:integer]][, mapFcn:Function[, thisArg:any]] )\n Fills an array-like object view with values returned from an iterator.\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator:Object, dest:ArrayLikeObject[, \n begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n","iteratorStream":"\niteratorStream( iterator:Object[, options:Object] )\n Creates a readable stream from an iterator.\n","iteratorStream.factory":"\niteratorStream.factory( [options:Object] )\n Returns a function for creating readable streams from iterators.\n","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator:Object[, options:Object] )\n Returns an \"objectMode\" readable stream from an iterator.\n","IteratorSymbol":"\nIteratorSymbol\n Iterator symbol.\n","iterAvercos":"\niterAvercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse versed cosine.\n","iterAversin":"\niterAversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse versed sine.\n","iterawgn":"\niterawgn( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n","iterawln":"\niterawln( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n","iterawun":"\niterawun( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options:Object] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n","iterBartlettPulse":"\niterBartlettPulse( [options:Object] )\n Returns an iterator which generates a Bartlett pulse waveform.\n","iterBesselj0":"\niterBesselj0( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order zero.\n","iterBesselj1":"\niterBesselj1( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order one.\n","iterBessely0":"\niterBessely0( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order zero.\n","iterBessely1":"\niterBessely1( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order one.\n","iterBeta":"\niterBeta( x:Object|number, y:Object|number )\n Returns an iterator which iteratively evaluates the beta function.\n","iterBetaln":"\niterBetaln( x:Object|number, y:Object|number )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n beta function.\n","iterBinet":"\niterBinet( iterator:Object )\n Returns an iterator which iteratively evaluates Binet's formula extended to\n real numbers.\n","iterCbrt":"\niterCbrt( iterator:Object )\n Returns an iterator which iteratively computes the cube root.\n","iterCeil":"\niterCeil( iterator:Object )\n Returns an iterator which rounds each iterated value toward positive\n infinity.\n","iterCeil2":"\niterCeil2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward positive infinity.\n","iterCeil10":"\niterCeil10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward positive infinity.\n","iterCompositesSeq":"\niterCompositesSeq( [options:Object] )\n Returns an iterator which generates a sequence of composite numbers.\n","iterConcat":"\niterConcat( iter0:Object, ...iterator:Object )\n Returns an iterator which iterates over the values of two or more iterators.\n","iterConstant":"\niterConstant( value:any[, options:Object] )\n Returns an iterator which always returns the same value.\n","iterContinuedFraction":"\niterContinuedFraction( iterator:Object[, options:Object] )\n Evaluates the terms of a continued fraction.\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x:number[, options:Object] )\n Returns an iterator which generates a list of all continued fraction terms\n which can be obtained given the precision of `x`.\n","iterCos":"\niterCos( iterator:Object )\n Returns an iterator which iteratively computes the cosine.\n","iterCosh":"\niterCosh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic cosine.\n","iterCosineWave":"\niterCosineWave( [options:Object] )\n Returns an iterator which generates a cosine wave.\n","iterCosm1":"\niterCosm1( iterator:Object )\n Returns an iterator which iteratively computes `cos(x) - 1`.\n","iterCospi":"\niterCospi( iterator:Object )\n Returns an iterator which computes the cosine of each iterated value times\n π.\n","iterCounter":"\niterCounter( iterator:Object )\n Returns an iterator which iteratively computes the number of iterated\n values.\n","iterCovercos":"\niterCovercos( iterator:Object )\n Returns an iterator which iteratively computes the coversed cosine.\n","iterCoversin":"\niterCoversin( iterator:Object )\n Returns an iterator which iteratively computes the coversed sine.\n","iterCubesSeq":"\niterCubesSeq( [options:Object] )\n Returns an iterator which generates a sequence of cubes.\n","itercugmean":"\nitercugmean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n","itercuhmean":"\nitercuhmean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n","itercumax":"\nitercumax( iterator:Object )\n Returns an iterator which iteratively computes a cumulative maximum value.\n","itercumaxabs":"\nitercumaxabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n","itercumean":"\nitercumean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n","itercumeanabs":"\nitercumeanabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n","itercumeanabs2":"\nitercumeanabs2( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n","itercumidrange":"\nitercumidrange( iterator:Object )\n Returns an iterator which iteratively computes a cumulative mid-range.\n","itercumin":"\nitercumin( iterator:Object )\n Returns an iterator which iteratively computes a cumulative minimum value.\n","itercuminabs":"\nitercuminabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n","itercuprod":"\nitercuprod( iterator:Object )\n Returns an iterator which iteratively computes a cumulative product.\n","itercurange":"\nitercurange( iterator:Object )\n Returns an iterator which iteratively computes a cumulative range.\n","itercusum":"\nitercusum( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum.\n","itercusumabs":"\nitercusumabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n","itercusumabs2":"\nitercusumabs2( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n","iterDatespace":"\niterDatespace( start:integer|string|Date, stop:integer|string|Date[, \n N:integer][, options:Object] )\n Returns an iterator which returns evenly spaced dates over a specified\n interval.\n","iterDedupe":"\niterDedupe( iterator:Object[, limit:integer] )\n Returns an iterator which removes consecutive duplicated values.\n","iterDedupeBy":"\niterDedupeBy( iterator:Object, [limit:integer,] fcn:Function )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n","iterDeg2rad":"\niterDeg2rad( iterator:Object )\n Returns an iterator which iteratively converts an angle from degrees to\n radians.\n","iterDigamma":"\niterDigamma( iterator:Object )\n Returns an iterator which iteratively evaluates the digamma function.\n","iterDiracComb":"\niterDiracComb( [options:Object] )\n Returns an iterator which generates a Dirac comb.\n","iterDiracDelta":"\niterDiracDelta( iterator:Object )\n Returns an iterator which iteratively evaluates the Dirac delta function.\n","iterDivide":"\niterDivide( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n","iterEllipe":"\niterEllipe( iterator:Object )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the second kind.\n","iterEllipk":"\niterEllipk( iterator:Object )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the first kind.\n","iterEmpty":"\niterEmpty()\n Returns an empty iterator.\n","iterErf":"\niterErf( iterator:Object )\n Returns an iterator which iteratively evaluates the error function.\n","iterErfc":"\niterErfc( iterator:Object )\n Returns an iterator which iteratively evaluates the complementary error\n function.\n","iterErfcinv":"\niterErfcinv( iterator:Object )\n Returns an iterator which iteratively evaluates the inverse complementary\n error function.\n","iterErfinv":"\niterErfinv( iterator:Object )\n Returns an iterator which iteratively evaluates the inverse error function.\n","iterEta":"\niterEta( iterator:Object )\n Returns an iterator which iteratively evaluates the Dirichlet eta function.\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved sequence of even\n integers.\n","iterEvery":"\niterEvery( iterator:Object )\n Tests whether all iterated values are truthy.\n","iterEveryBy":"\niterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n","iterExp":"\niterExp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural exponential\n function.\n","iterExp2":"\niterExp2( iterator:Object )\n Returns an iterator which iteratively evaluates the base `2` exponential\n function.\n","iterExp10":"\niterExp10( iterator:Object )\n Returns an iterator which iteratively evaluates the base `10` exponential\n function.\n","iterExpit":"\niterExpit( iterator:Object )\n Returns an iterator which iteratively evaluates the standard logistic\n function.\n","iterExpm1":"\niterExpm1( iterator:Object )\n Returns an iterator which iteratively computes `exp(x) - 1`.\n","iterExpm1rel":"\niterExpm1rel( iterator:Object )\n Returns an iterator which iteratively evaluates the relative error\n exponential.\n","iterFactorial":"\niterFactorial( iterator:Object )\n Returns an iterator which iteratively evaluates the factorial function.\n","iterFactorialln":"\niterFactorialln( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n factorial function.\n","iterFactorialsSeq":"\niterFactorialsSeq( [options:Object] )\n Returns an iterator which generates a sequence of factorials.\n","iterFibonacciSeq":"\niterFibonacciSeq( [options:Object] )\n Returns an iterator which generates a Fibonacci sequence.\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options:Object] )\n Returns an iterator which generates a sequence of fifth powers.\n","iterFill":"\niterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n","iterFilter":"\niterFilter( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n","iterFilterMap":"\niterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n","iterFirst":"\niterFirst( iterator:Object )\n Returns the first iterated value.\n","iterFlatTopPulse":"\niterFlatTopPulse( [options:Object] )\n Returns an iterator which generates a flat top pulse waveform.\n","iterFloor":"\niterFloor( iterator:Object )\n Returns an iterator which rounds each iterated value toward negative\n infinity.\n","iterFloor2":"\niterFloor2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward negative infinity.\n","iterFloor10":"\niterFloor10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward negative infinity.\n","iterFlow":"\niterFlow( methods:Object )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n","iterForEach":"\niterForEach( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options:Object] )\n Returns an iterator which generates a sequence of fourth powers.\n","iterFresnelc":"\niterFresnelc( iterator:Object )\n Returns an iterator which iteratively computes the Fresnel integral C(x).\n","iterFresnels":"\niterFresnels( iterator:Object )\n Returns an iterator which iteratively computes the Fresnel integral S(x).\n","iterGamma":"\niterGamma( iterator:Object )\n Returns an iterator which iteratively evaluates the gamma function.\n","iterGamma1pm1":"\niterGamma1pm1( iterator:Object )\n Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n cancellation errors for small `x`.\n","iterGammaln":"\niterGammaln( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n gamma function.\n","iterHacovercos":"\niterHacovercos( iterator:Object )\n Returns an iterator which iteratively computes the half-value coversed\n cosine.\n","iterHacoversin":"\niterHacoversin( iterator:Object )\n Returns an iterator which iteratively computes the half-value coversed sine.\n","iterHannPulse":"\niterHannPulse( [options:Object] )\n Returns an iterator which generates a Hann pulse waveform.\n","iterHavercos":"\niterHavercos( iterator:Object )\n Returns an iterator which iteratively computes the half-value versed cosine.\n","iterHaversin":"\niterHaversin( iterator:Object )\n Returns an iterator which iteratively computes the half-value versed sine.\n","iterHead":"\niterHead( iterator:Object, n:integer )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n","iterIncrspace":"\niterIncrspace( start:number, stop:number[, increment:number] )\n Returns an iterator which returns evenly spaced numbers according to a\n specified increment.\n","iterIntegersSeq":"\niterIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved integer sequence.\n","iterIntersection":"\niterIntersection( iter0:Object, ...iterator:Object )\n Returns an iterator which returns the intersection of two or more iterators.\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0:Object, ...iterator:Object, hashFcn:Function[, \n thisArg:any] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n","iterInv":"\niterInv( iterator:Object )\n Returns an iterator which iteratively computes the multiplicative inverse.\n","iterLanczosPulse":"\niterLanczosPulse( [options:Object] )\n Returns an iterator which generates a Lanczos pulse waveform.\n","iterLast":"\niterLast( iterator:Object )\n Consumes an entire iterator and returns the last iterated value.\n","iterLength":"\niterLength( iterator:Object )\n Consumes an entire iterator and returns the number of iterated values.\n","iterLinspace":"\niterLinspace( start:number, stop:number[, N:integer] )\n Returns an iterator which returns evenly spaced numbers over a specified\n interval.\n","iterLn":"\niterLn( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm.\n","iterLog":"\niterLog( x:Object|number, b:Object|number )\n Returns an iterator which iteratively computes the base `b` logarithm.\n","iterLog1mexp":"\niterLog1mexp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1-exp(-|x|)`.\n","iterLog1p":"\niterLog1p( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+x`.\n","iterLog1pexp":"\niterLog1pexp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+exp(x)`.\n","iterLog2":"\niterLog2( iterator:Object )\n Returns an iterator which iteratively evaluates the binary logarithm.\n","iterLog10":"\niterLog10( iterator:Object )\n Returns an iterator which iteratively evaluates the common logarithm\n (logarithm with base 10).\n","iterLogit":"\niterLogit( iterator:Object )\n Returns an iterator which iteratively evaluates the logit function.\n","iterLogspace":"\niterLogspace( start:number, stop:number[, N:integer][, options:Object] )\n Returns an iterator which returns evenly spaced numbers on a log scale.\n","iterLucasSeq":"\niterLucasSeq( [options:Object] )\n Returns an iterator which generates a Lucas sequence.\n","iterMap":"\niterMap( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which invokes a function for each iterated value.\n","iterMapN":"\niterMapN( iter0:Object, ...iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n","itermax":"\nitermax( iterator:Object )\n Computes the maximum value of all iterated values.\n","itermaxabs":"\nitermaxabs( iterator:Object )\n Computes the maximum absolute value of all iterated values.\n","itermean":"\nitermean( iterator:Object )\n Computes an arithmetic mean over all iterated values.\n","itermeanabs":"\nitermeanabs( iterator:Object )\n Computes an arithmetic mean of absolute values for all iterated values.\n","itermeanabs2":"\nitermeanabs2( iterator:Object )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n","itermidrange":"\nitermidrange( iterator:Object )\n Computes the mid-range of all iterated values.\n","itermin":"\nitermin( iterator:Object )\n Computes the minimum value of all iterated values.\n","iterminabs":"\niterminabs( iterator:Object )\n Computes the minimum absolute value of all iterated values.\n","itermmax":"\nitermmax( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving maximum value.\n","itermmaxabs":"\nitermmaxabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n","itermmean":"\nitermmean( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n","itermmeanabs":"\nitermmeanabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n","itermmeanabs2":"\nitermmeanabs2( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n","itermmidrange":"\nitermmidrange( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving mid-range.\n","itermmin":"\nitermmin( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving minimum value.\n","itermminabs":"\nitermminabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n","iterMod":"\niterMod( iter0:Object, ...iterator:Object )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n","itermprod":"\nitermprod( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving product.\n","itermrange":"\nitermrange( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving range.\n","itermsum":"\nitermsum( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum.\n","itermsumabs":"\nitermsumabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n","itermsumabs2":"\nitermsumabs2( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n","iterMultiply":"\niterMultiply( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options:Object] )\n Returns an iterator which generates a negaFibonacci sequence.\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options:Object] )\n Returns an iterator which generates a negaLucas sequence.\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of negative even integers.\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options:Object] )\n Returns an iterator which generates a negative integer sequence.\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of negative odd integers.\n","iterNone":"\niterNone( iterator:Object )\n Tests whether all iterated values are falsy.\n","iterNoneBy":"\niterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options:Object] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonnegative even integers.\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options:Object] )\n Returns an iterator which generates a nonnegative integer sequence.\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonpositive even integers.\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options:Object] )\n Returns an iterator which generates a nonpositive integer sequence.\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonsquares.\n","iterNth":"\niterNth( iterator:Object, n:integer )\n Returns the nth iterated value.\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved sequence of odd integers.\n","iterPeriodicSinc":"\niterPeriodicSinc( n:integer[, options:Object] )\n Returns an iterator which generates a periodic sinc waveform.\n","iterPipeline":"\niterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )\n Returns an iterator pipeline.\n","iterPop":"\niterPop( iterator:Object[, clbk:Function[, thisArg:any]] )\n Returns an iterator which skips the last value of a provided iterator.\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of positive even integers.\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options:Object] )\n Returns an iterator which generates a positive integer sequence.\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of positive odd integers.\n","iterPow":"\niterPow( base:Object|number, exponent:Object|number )\n Returns an iterator which iteratively evaluates the exponential function.\n","iterPrimesSeq":"\niterPrimesSeq( [options:Object] )\n Returns an iterator which generates a sequence of prime numbers.\n","iterprod":"\niterprod( iterator:Object )\n Computes the product of all iterated values.\n","iterPulse":"\niterPulse( [options:Object] )\n Returns an iterator which generates a pulse waveform.\n","iterPush":"\niterPush( iterator:Object, ...items:any )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n","iterRad2deg":"\niterRad2deg( iterator:Object )\n Returns an iterator which iteratively converts an angle from radians to\n degrees.\n","iterRamp":"\niterRamp( iterator:Object )\n Returns an iterator which iteratively evaluates the ramp function.\n","iterrange":"\niterrange( iterator:Object )\n Computes the range of all iterated values.\n","iterReject":"\niterReject( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n","iterReplicate":"\niterReplicate( iterator:Object, n:integer )\n Returns an iterator which replicates each iterated value `n` times.\n","iterReplicateBy":"\niterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n","iterRound":"\niterRound( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest integer.\n","iterRound2":"\niterRound2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two on a linear scale.\n","iterRound10":"\niterRound10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 on a linear scale.\n","iterRsqrt":"\niterRsqrt( iterator:Object )\n Returns an iterator which iteratively computes the reciprocal (inverse)\n square root.\n","iterSawtoothWave":"\niterSawtoothWave( [options:Object] )\n Returns an iterator which generates a sawtooth wave.\n","iterShift":"\niterShift( iterator:Object[, clbk:Function[, thisArg:any]] )\n Returns an iterator which skips the first value of a provided iterator.\n","iterSignum":"\niterSignum( iterator:Object )\n Returns an iterator which iteratively evaluates the signum function.\n","iterSin":"\niterSin( iterator:Object )\n Returns an iterator which iteratively computes the sine.\n","iterSinc":"\niterSinc( iterator:Object )\n Returns an iterator which iteratively computes the normalized cardinal sine.\n","iterSineWave":"\niterSineWave( [options:Object] )\n Returns an iterator which generates a sine wave.\n","iterSinh":"\niterSinh( iterator:Object )\n Returns an iterator which iteratively evaluates the hyperbolic sine.\n","iterSinpi":"\niterSinpi( iterator:Object )\n Returns an iterator which computes the sine of each iterated value times π.\n","iterSlice":"\niterSlice( iterator:Object[, begin:integer[, end:integer]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n","iterSome":"\niterSome( iterator:Object, n:number )\n Tests whether at least `n` iterated values are truthy.\n","iterSomeBy":"\niterSomeBy( iterator:Object, n:integer, predicate:Function[, thisArg:any ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n","iterSpence":"\niterSpence( iterator:Object )\n Returns an iterator which iteratively evaluates Spence's function.\n","iterSqrt":"\niterSqrt( iterator:Object )\n Returns an iterator which iteratively computes the principal square root.\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator:Object )\n Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n accurately for small `x`.\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options:Object] )\n Returns an iterator which generates a sequence of squared triangular\n numbers.\n","iterSquaresSeq":"\niterSquaresSeq( [options:Object] )\n Returns an iterator which generates a sequence of squares.\n","iterSquareWave":"\niterSquareWave( [options:Object] )\n Returns an iterator which generates a square wave.\n","iterstdev":"\niterstdev( iterator:Object[, mean:number] )\n Computes a correct sample standard deviation over all iterated values.\n","iterStep":"\niterStep( start:number, increment:number[, N:number] )\n Returns an iterator which returns a sequence of numbers according to a\n specified increment.\n","iterStrided":"\niterStrided( iterator:Object, stride:integer[, offset:integer[, \n eager:boolean]] )\n Returns an iterator which steps by a specified amount.\n","iterStridedBy":"\niterStridedBy( iterator:Object, fcn:Function[, offset:integer[, \n eager:boolean]][, thisArg:any] )\n Returns an iterator which steps according to a provided callback function.\n","iterSubtract":"\niterSubtract( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n","itersum":"\nitersum( iterator:Object )\n Computes the sum of all iterated values.\n","itersumabs":"\nitersumabs( iterator:Object )\n Computes the sum of absolute values for all iterated values.\n","itersumabs2":"\nitersumabs2( iterator:Object )\n Computes the sum of squared absolute values for all iterated values.\n","iterTan":"\niterTan( iterator:Object )\n Returns an iterator which iteratively evaluates the tangent.\n","iterTanh":"\niterTanh( iterator:Object )\n Returns an iterator which iteratively evaluates the hyperbolic tangent.\n","iterThunk":"\niterThunk( iterFcn:Function[, ...args:any] )\n Returns an iterator \"thunk\".\n","iterTriangleWave":"\niterTriangleWave( [options:Object] )\n Returns an iterator which generates a triangle wave.\n","iterTriangularSeq":"\niterTriangularSeq( [options:Object] )\n Returns an iterator which generates a sequence of triangular numbers.\n","iterTrigamma":"\niterTrigamma( iterator:Object )\n Returns an iterator which iteratively evaluates the trigamma function.\n","iterTrunc":"\niterTrunc( iterator:Object )\n Returns an iterator which rounds each iterated value toward zero.\n","iterTrunc2":"\niterTrunc2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward zero.\n","iterTrunc10":"\niterTrunc10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward zero.\n","iterUnion":"\niterUnion( iter0:Object, ...iterator:Object )\n Returns an iterator which returns the union of two or more iterators.\n","iterUnique":"\niterUnique( iterator:Object )\n Returns an iterator which returns unique values.\n","iterUniqueBy":"\niterUniqueBy( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which returns unique values according to a predicate\n function.\n","iterUniqueByHash":"\niterUniqueByHash( iterator:Object, hashFcn:Function[, thisArg:any] )\n Returns an iterator which returns unique values according to a hash\n function.\n","iterUnitspace":"\niterUnitspace( start:number[, stop:number] )\n Returns an iterator which returns numbers incremented by one.\n","iterUnshift":"\niterUnshift( iterator:Object, ...items:any )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n","itervariance":"\nitervariance( iterator:Object[, mean:number] )\n Computes an unbiased sample variance over all iterated values.\n","iterVercos":"\niterVercos( iterator:Object )\n Returns an iterator which iteratively computes the versed cosine.\n","iterVersin":"\niterVersin( iterator:Object )\n Returns an iterator which iteratively computes the versed sine.\n","iterZeta":"\niterZeta( iterator:Object )\n Returns an iterator which iteratively evaluates the Riemann zeta function.\n","joinStream":"\njoinStream( [options:Object] )\n Returns a transform stream which joins streamed data.\n","joinStream.factory":"\njoinStream.factory( [options:Object] )\n Returns a function for creating transform streams for joined streamed data.\n","joinStream.objectMode":"\njoinStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n","kde2d":"\nkde2d( x:Array, y:Array[, options:Object] )\n Two-dimensional kernel density estimation.\n","kebabcase":"\nkebabcase( str:string )\n Converts a string to kebab case.\n","keyBy":"\nkeyBy( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n","keyByRight":"\nkeyByRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n","keysIn":"\nkeysIn( obj:any )\n Returns an array of an object's own and inherited enumerable property\n names.\n","kruskalTest":"\nkruskalTest( ...x:Array[, options:Object] )\n Computes the Kruskal-Wallis test for equal medians.\n","kstest":"\nkstest( x:Array, y:Function|string[, ...params:number][, \n options:Object] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n","leveneTest":"\nleveneTest( x:Array[, ...y:Array[, options:Object]] )\n Computes Levene's test for equal variances.\n","LinkedList":"\nLinkedList()\n Linked list constructor.\n","linspace":"\nlinspace( start:number|ComplexLike, stop:number|ComplexLike, length:integer[, \n options:Object] )\n Generates a linearly spaced array over a specified interval.\n","linspace.assign":"\nlinspace.assign( start:number|ComplexLike, stop:number|ComplexLike, \n out:ArrayLikeObject[, options:Object] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n","LN_HALF":"\nLN_HALF\n Natural logarithm of `1/2`.\n","LN_PI":"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n","LN_TWO_PI":"\nLN_TWO_PI\n Natural logarithm of `2π`.\n","LN2":"\nLN2\n Natural logarithm of `2`.\n","LN10":"\nLN10\n Natural logarithm of `10`.\n","LOG2E":"\nLOG2E\n Base 2 logarithm of Euler's number.\n","LOG10E":"\nLOG10E\n Base 10 logarithm of Euler's number.\n","logspace":"\nlogspace( a:number, b:number[, length:integer] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n","lowercase":"\nlowercase( str:string )\n Converts a string to lowercase.\n","lowercaseKeys":"\nlowercaseKeys( obj:Object )\n Converts each object key to lowercase.\n","lowess":"\nlowess( x:Array, y:Array[, options:Object] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n","lpad":"\nlpad( str:string, len:integer[, pad:string] )\n Left pads a string such that the padded string has a length of at least\n `len`.\n","ltrim":"\nltrim( str:string )\n Trims whitespace from the beginning of a string.\n","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n","map":"\nmap( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array.\n","map.assign":"\nmap.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n","map2":"\nmap2( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n thisArg:any] )\n Applies a function to elements in two input arrays and assigns the results\n to a new array.\n","map2.assign":"\nmap2.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n","map2d":"\nmap2d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in an array of arrays and assigns\n the result to a nested element in a new array of arrays.\n","map2Right":"\nmap2Right( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n thisArg:any] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to a new array.\n","map2Right.assign":"\nmap2Right.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n","map3d":"\nmap3d( arr:ArrayLikeObject>, fcn:Function[, \n thisArg:any] )\n Applies a function to each nested element in a three-dimensional nested\n array and assigns the result to a nested element in a new three-dimensional\n nested array.\n","map4d":"\nmap4d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in a four-dimensional nested array\n and assigns the result to a nested element in a new four-dimensional nested\n array.\n","map5d":"\nmap5d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in a five-dimensional nested array\n and assigns the result to a nested element in a new five-dimensional nested\n array.\n","mapArguments":"\nmapArguments( fcn:Function, clbk:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function after\n transforming arguments according to a callback function.\n","mapFun":"\nmapFun( fcn:Function, n:integer[, thisArg:any] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n","mapFunAsync":"\nmapFunAsync( fcn:Function, n:integer, [options:Object,] done:Function )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n","mapKeys":"\nmapKeys( obj:Object, transform:Function )\n Maps keys from one object to a new object having the same values.\n","mapKeysAsync":"\nmapKeysAsync( obj:Object, [options:Object,] transform:Function, done:Function )\n Maps keys from one object to a new object having the same values.\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options:Object,] transform:Function )\n Returns a function which maps keys from one object to a new object having\n the same values.\n","mapReduce":"\nmapReduce( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n reducer:Function[, thisArg:any] )\n Performs a map-reduce operation for each element in an array and returns the\n accumulated result.\n","mapReduceRight":"\nmapReduceRight( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n reducer:Function[, thisArg:any] )\n Performs a map-reduce operation for each element in an array while iterating\n from right to left and returns the accumulated result.\n","mapRight":"\nmapRight( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array, iterating from right to left.\n","mapRight.assign":"\nmapRight.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n","mapValues":"\nmapValues( obj:Object, transform:Function )\n Maps values from one object to a new object having the same keys.\n","mapValuesAsync":"\nmapValuesAsync( obj:Object, [options:Object,] transform:Function, \n done:Function )\n Maps values from one object to a new object having the same keys.\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options:Object,] transform:Function )\n Returns a function which maps values from one object to a new object having\n the same keys.\n","maskArguments":"\nmaskArguments( fcn:Function, mask:ArrayLikeObject[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a specified mask.\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x:ndarray, shape:ArrayLikeObject )\n Broadcasts an ndarray to a specified shape if and only if the specified\n shape differs from the provided ndarray's shape.\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays:ndarray|ArrayLikeObject )\n Broadcasts ndarrays to a common shape.\n","memoize":"\nmemoize( fcn:Function[, hashFunction:Function] )\n Returns a memoized function.\n","merge":"\nmerge( target:Object, ...source:Object )\n Merges objects into a target object.\n","merge.factory":"\nmerge.factory( options:Object )\n Returns a function for merging and extending objects.\n","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n Number of milliseconds in a second.\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n Number of milliseconds in a week.\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options:Object] )\n Returns data for Charles Joseph Minard's cartographic depiction of\n Napoleon's Russian campaign of 1812.\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n Number of minutes in a day.\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n Number of minutes in a week.\n","minutesInMonth":"\nminutesInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of minutes in a month.\n","minutesInYear":"\nminutesInYear( [value:integer|Date] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n","MOBY_DICK":"\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n Number of months in a year.\n","moveProperty":"\nmoveProperty( source:Object, prop:string, target:Object )\n Moves a property from one object to another object.\n","MultiSlice":"\nMultiSlice( ...slice )\n Returns a multi-slice.\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n","namedtypedtuple":"\nnamedtypedtuple( fields:Array[, options:Object] )\n Returns a named typed tuple factory.\n","NAN":"\nNAN\n Double-precision floating-point NaN.\n","naryFunction":"\nnaryFunction( fcn:Function, arity:integer[, thisArg:any] )\n Returns a function that applies a specified number of arguments to a\n provided function.\n","nativeClass":"\nnativeClass( value:any )\n Returns a string value indicating a specification defined classification of\n an object.\n","ndarray":"\nndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string[, options:Object] )\n Returns an ndarray.\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","ndarray.prototype.data":"\nndarray.prototype.data\n Pointer to the underlying data buffer.\n","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n Underlying data type.\n","ndarray.prototype.flags":"\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","ndarray.prototype.length":"\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n Number of dimensions.\n","ndarray.prototype.offset":"\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","ndarray.prototype.order":"\nndarray.prototype.order\n Array order.\n","ndarray.prototype.shape":"\nndarray.prototype.shape\n Array shape.\n","ndarray.prototype.strides":"\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","ndarray.prototype.get":"\nndarray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","ndarray.prototype.iget":"\nndarray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","ndarray.prototype.set":"\nndarray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","ndarray.prototype.iset":"\nndarray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","ndarray.prototype.toString":"\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n","ndarray2array":"\nndarray2array( x:ndarray )\n Converts an ndarray to a generic array.\n","ndarrayCastingModes":"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x:ndarray )\n Returns the underlying data buffer of a provided ndarray.\n","ndarrayDataType":"\nndarrayDataType( x:ndarray )\n Returns the data type of a provided ndarray.\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind:string] )\n Returns a list of ndarray data types.\n","ndarrayDispatch":"\nndarrayDispatch( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns an ndarray function interface which performs multiple dispatch.\n","ndarrayFlag":"\nndarrayFlag( x:ndarray, name:string|symbol )\n Returns a specified flag for a provided ndarray.\n","ndarrayFlags":"\nndarrayFlags( x:ndarray )\n Returns the flags of a provided ndarray.\n","ndarrayIndexModes":"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n","ndarrayMinDataType":"\nndarrayMinDataType( value:any )\n Returns the minimum ndarray data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast and, for floating-point data types, can be downcast.\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype:any] )\n Returns the next larger ndarray data type of the same kind.\n","ndarrayOffset":"\nndarrayOffset( x:ndarray )\n Returns the index offset specifying the underlying buffer index of the first\n iterated ndarray element.\n","ndarrayOrder":"\nndarrayOrder( x:ndarray )\n Returns the layout order of a provided ndarray.\n","ndarrayOrders":"\nndarrayOrders()\n Returns a list of ndarray orders.\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1:any, dtype2:any] )\n Returns the ndarray data type with the smallest size and closest \"kind\" to\n which ndarray data types can be safely cast.\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same \"kind\".\n","ndarrayShape":"\nndarrayShape( x:ndarray )\n Returns the shape of a provided ndarray.\n","ndarrayStride":"\nndarrayStride( x:ndarray, dim:integer )\n Returns the stride along a specified dimension for a provided ndarray.\n","ndarrayStrides":"\nndarrayStrides( x:ndarray )\n Returns the strides of a provided ndarray.\n","ndat":"\nndat( x:ndarray[, ...indices:integer] )\n Returns an ndarray element.\n","ndempty":"\nndempty( shape:ArrayLikeObject|integer[, options:Object] )\n Returns an uninitialized ndarray having a specified shape and data type.\n","ndemptyLike":"\nndemptyLike( x:ndarray[, options:Object] )\n Returns an uninitialized ndarray having the same shape and data type as a\n provided input ndarray.\n","ndims":"\nndims( x:ndarray )\n Returns the number of ndarray dimensions.\n","nditerColumnEntries":"\nnditerColumnEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, column] pairs for each column in a\n matrix (or stack of matrices).\n","nditerColumns":"\nnditerColumns( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each column in a matrix (or stack of\n matrices).\n","nditerEntries":"\nnditerEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, value] pairs for each element in a\n provided ndarray.\n","nditerIndices":"\nnditerIndices( shape:Array[, options:Object] )\n Returns an iterator which returns indices for use indexing into an ndarray\n having a specified shape.\n","nditerMatrices":"\nnditerMatrices( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each matrix in a stack of matrices.\n","nditerMatrixEntries":"\nnditerMatrixEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, matrix] pairs for each matrix in a\n stack of matrices.\n","nditerRowEntries":"\nnditerRowEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, row] pairs for each row in a\n matrix (or stack of matrices).\n","nditerRows":"\nnditerRows( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each row in a matrix (or stack of\n matrices).\n","nditerValues":"\nnditerValues( x:ndarray[, options:Object] )\n Returns an iterator which returns individual elements from a provided\n ndarray.\n","ndslice":"\nndslice( x:ndarray, ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, \n options:Object] )\n Returns a read-only view of an input ndarray.\n","ndsliceAssign":"\nndsliceAssign( x:ndarray, y:ndarray, \n ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, options:Object] )\n Assigns element values from a broadcasted input ndarray to corresponding\n elements in an output ndarray view.\n","ndsliceDimension":"\nndsliceDimension( x:ndarray, dim:integer, slice:Slice|integer|null|undefined[, \n options:Object] )\n Returns a read-only view of an input ndarray when sliced along a specified\n dimension.\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x:ndarray, dim:integer, start:integer[, options:Object] )\n Returns a read-only shifted view of an input ndarray along a specified\n dimension.\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x:ndarray, dim:integer, stop:integer[, options:Object] )\n Returns a read-only truncated view of an input ndarray along a specified\n dimension.\n","ndsliceFrom":"\nndsliceFrom( x:ndarray, ...start:null|void|integer[, options:Object] )\n Returns a read-only shifted view of an input ndarray.\n","ndsliceTo":"\nndsliceTo( x:ndarray, ...stop:null|void|integer[, options:Object] )\n Returns a read-only truncated view of an input ndarray.\n","ndzeros":"\nndzeros( shape:ArrayLikeObject|integer[, options:Object] )\n Returns a zero-filled ndarray having a specified shape and data type.\n","ndzerosLike":"\nndzerosLike( x:ndarray[, options:Object] )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str:string[, fromIndex:integer] )\n Returns the next extended grapheme cluster break in a string after a\n specified position.\n","nextTick":"\nnextTick( clbk[, ...args] )\n Adds a callback to the \"next tick queue\".\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n","NINF":"\nNINF\n Double-precision floating-point negative infinity.\n","NODE_VERSION":"\nNODE_VERSION\n Node version.\n","none":"\nnone( collection:Array|TypedArray|Object )\n Tests whether all elements in a collection are falsy.\n","noneBy":"\nnoneBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n","noneByAsync":"\nnoneByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n","noneByAsync.factory":"\nnoneByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n","noneByRight":"\nnoneByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n","noneByRightAsync":"\nnoneByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n","nonEnumerableProperties":"\nnonEnumerableProperties( value:any )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value:any )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value:any )\n Returns an array of an object's own non-enumerable property names.\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value:any )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value:any )\n Returns an array of an object's own non-enumerable symbol properties.\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n","nonIndexKeys":"\nnonIndexKeys( obj:any )\n Returns an array of an object's own enumerable property names which are not\n integer indices.\n","noop":"\nnoop()\n A function which does nothing.\n","now":"\nnow()\n Returns the time in seconds since the epoch.\n","NUM_CPUS":"\nNUM_CPUS\n Number of CPUs.\n","num2words":"\nnum2words( value:integer[, options:Object] )\n Converts a number to a word representation.\n","Number":"\nNumber( value:number )\n Returns a Number object.\n","numel":"\nnumel( x:ndarray )\n Returns the number of elements in an ndarray.\n","numelDimension":"\nnumelDimension( x:ndarray, dim:integer )\n Returns the size (i.e., number of elements) of a specified dimension for a\n provided ndarray.\n","numGraphemeClusters":"\nnumGraphemeClusters( str:string )\n Returns the number of grapheme clusters in a string.\n","Object":"\nObject( value:any )\n Returns an object.\n","Object.assign":"\nObject.assign( target:Object, ...sources:Object )\n Assigns enumerable and own properties from source objects to a target\n object.\n","Object.create":"\nObject.create( prototype:Object, properties:Object )\n Creates a new object with a specified prototype object and properties.\n","Object.defineProperties":"\nObject.defineProperties( obj:Object, properties:Object )\n Defines properties for an object.\n","Object.defineProperty":"\nObject.defineProperty( obj:Object, key:string, descriptor:Object )\n Defines a property for an object.\n","Object.entries":"\nObject.entries( obj:Object )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n","Object.freeze":"\nObject.freeze( obj:Object )\n Freezes an object.\n","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj:Object, key:string )\n Returns an object's own property descriptor.\n","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj:Object )\n Returns an object's own property descriptors.\n","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj:Object )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj:Object )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj:Object )\n Returns an object's prototype.\n","Object.hasOwn":"\nObject.hasOwn( obj:Object, p:string )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n","Object.is":"\nObject.is( value1:any, value2:any )\n Returns a boolean indicating whether two values are the same value.\n","Object.isExtensible":"\nObject.isExtensible( obj:Object )\n Returns a boolean indicating whether an object is extensible.\n","Object.isFrozen":"\nObject.isFrozen( obj:Object )\n Returns a boolean indicating whether an object is frozen.\n","Object.isSealed":"\nObject.isSealed( obj:Object )\n Returns a boolean indicating whether an object is sealed.\n","Object.keys":"\nObject.keys( obj:Object )\n Returns an array of an object's own enumerable string-keyed property\n names.\n","Object.preventExtensions":"\nObject.preventExtensions( obj:Object )\n Prevents the addition of new properties to an object.\n","Object.seal":"\nObject.seal( obj:Object )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj:Object, proto:Object )\n Sets an object's prototype.\n","Object.values":"\nObject.values( obj:Object )\n Returns an array of an object's own enumerable property values.\n","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n","Object.prototype.toString":"\nObject.prototype.toString()\n Returns a string representing the object.\n","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p:string )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj:Object )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p:string )\n Returns a boolean indicating whether an object's property is enumerable.\n","Object.prototype.constructor":"\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n","objectEntries":"\nobjectEntries( obj:ObjectLike )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n","objectEntriesIn":"\nobjectEntriesIn( obj:ObjectLike )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n","objectFromEntries":"\nobjectFromEntries( entries:Array )\n Creates an object from an array of key-value pairs.\n","objectInverse":"\nobjectInverse( obj:ObjectLike[, options:Object] )\n Inverts an object, such that keys become values and values become keys.\n","objectInverseBy":"\nobjectInverseBy( obj:ObjectLike, [options:Object,] transform:Function )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n","objectKeys":"\nobjectKeys( value:any )\n Returns an array of an object's own enumerable property names.\n","objectValues":"\nobjectValues( obj:ObjectLike )\n Returns an array of an object's own enumerable property values.\n","objectValuesIn":"\nobjectValuesIn( obj:ObjectLike )\n Returns an array of an object's own and inherited enumerable property\n values.\n","omit":"\nomit( obj:Object, keys:string|Array )\n Returns a partial object copy excluding specified keys.\n","omitBy":"\nomitBy( obj:Object, predicate:Function )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n","open":"\nopen( path:string|Buffer[, flags:string|number[, mode:integer]], clbk:Function )\n Asynchronously opens a file.\n","open.sync":"\nopen.sync( path:string|Buffer[, flags:string|number[, mode:integer]] )\n Synchronously opens a file.\n","openURL":"\nopenURL( url:string )\n Opens a URL in a user's default browser.\n","ordinalize":"\nordinalize( value:string|integer[, options:Object] )\n Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n","pad":"\npad( str:string, len:integer[, options:Object] )\n Pads a `string` such that the padded `string` has length `len`.\n","padjust":"\npadjust( pvals:Array, method:string[, comparisons:integer] )\n Adjusts supplied p-values for multiple comparisons via a specified method.\n","papply":"\npapply( fcn:Function, ...args:any )\n Returns a function of smaller arity by partially applying arguments.\n","papplyRight":"\npapplyRight( fcn:Function, ...args:any )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n","parallel":"\nparallel( files:Array, [options:Object,] clbk:Function )\n Executes scripts in parallel.\n","parseJSON":"\nparseJSON( str:string[, reviver:Function] )\n Attempts to parse a string as JSON.\n","pascalcase":"\npascalcase( str:string )\n Converts a string to Pascal case.\n","PATH_DELIMITER":"\nPATH_DELIMITER\n Platform-specific path delimiter.\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n","PATH_SEP":"\nPATH_SEP\n Platform-specific path segment separator.\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n POSIX path segment separator.\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n Windows path segment separator.\n","pcorrtest":"\npcorrtest( x:Array, y:Array[, options:Object] )\n Computes a Pearson product-moment correlation test between paired samples.\n","percentEncode":"\npercentEncode( str:string )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","PHI":"\nPHI\n Golden ratio.\n","PI":"\nPI\n The mathematical constant `π`.\n","PI_SQUARED":"\nPI_SQUARED\n Square of the mathematical constant `π`.\n","pick":"\npick( obj:Object, keys:string|Array )\n Returns a partial object copy containing only specified keys.\n","pickArguments":"\npickArguments( fcn:Function, indices:Array[, thisArg:any] )\n Returns a function that applies specified arguments to a provided function.\n","pickBy":"\npickBy( obj:Object, predicate:Function )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n","PINF":"\nPINF\n Double-precision floating-point positive infinity.\n","pkg2alias":"\npkg2alias( pkg:string )\n Returns the alias associated with a specified package name.\n","pkg2related":"\npkg2related( pkg:string )\n Returns package names related to a specified package name.\n","pkg2standalone":"\npkg2standalone( pkg:string )\n Returns the standalone package name associated with a provided internal\n package name.\n","PLATFORM":"\nPLATFORM\n Platform on which the current process is running.\n","plot":"\nplot( [x:Array|Array, y:Array|Array,] [options:Object] )\n Returns a plot instance for creating 2-dimensional plots.\n","Plot":"\nPlot( [x:Array|Array, y:Array|Array,] [options:Object] )\n Returns a plot instance for creating 2-dimensional plots.\n","pluck":"\npluck( arr:Array, prop:string[, options:Object] )\n Extracts a property value from each element of an object array.\n","pop":"\npop( collection:Array|TypedArray|Object )\n Removes and returns the last element of a collection.\n","porterStemmer":"\nporterStemmer( word:string )\n Extracts the stem of a given word.\n","prepend":"\nprepend( collection1:Array|TypedArray|Object, \n collection2:Array|TypedArray|Object )\n Adds the elements of one collection to the beginning of another collection.\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str:string[, fromIndex:integer] )\n Returns the previous extended grapheme cluster break in a string before a\n specified position.\n","PRIMES_100K":"\nPRIMES_100K()\n Returns an array containing the first 100,000 prime numbers.\n","properties":"\nproperties( value:any )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n","propertiesIn":"\npropertiesIn( value:any )\n Returns an array of an object's own and inherited property names and\n symbols.\n","propertyDescriptor":"\npropertyDescriptor( value:any, property:string|symbol )\n Returns a property descriptor for an object's own property.\n","propertyDescriptorIn":"\npropertyDescriptorIn( value:any, property:string|symbol )\n Returns a property descriptor for an object's own or inherited property.\n","propertyDescriptors":"\npropertyDescriptors( value:any )\n Returns an object's own property descriptors.\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value:any )\n Returns an object's own and inherited property descriptors.\n","propertyNames":"\npropertyNames( value:any )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n","propertyNamesIn":"\npropertyNamesIn( value:any )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n","propertySymbols":"\npropertySymbols( value:any )\n Returns an array of an object's own symbol properties.\n","propertySymbolsIn":"\npropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited symbol properties.\n","Proxy":"\nProxy( target:Object, handlers:Object )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n","Proxy.revocable":"\nProxy.revocable( target:Object, handlers:Object )\n Returns a revocable proxy object.\n","push":"\npush( collection:Array|TypedArray|Object, ...items:any )\n Adds one or more elements to the end of a collection.\n","quarterOfYear":"\nquarterOfYear( [month:integer|string|Date] )\n Returns the quarter of the year.\n","random.array.arcsine":"\nrandom.array.arcsine( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an arcsine\n distribution.\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n Length of generator seed.\n","random.array.arcsine.state":"\nrandom.array.arcsine.state\n Generator state.\n","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n Length of generator state.\n","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n","random.array.bernoulli":"\nrandom.array.bernoulli( len:integer, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n Generator state.\n","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n Length of generator state.\n","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n","random.array.beta":"\nrandom.array.beta( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a beta\n distribution.\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n","random.array.beta.seed":"\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n Length of generator seed.\n","random.array.beta.state":"\nrandom.array.beta.state\n Generator state.\n","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n Length of generator state.\n","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n","random.array.betaprime":"\nrandom.array.betaprime( len:integer, alpha:number, beta:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a beta prime\n distribution.\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n Length of generator seed.\n","random.array.betaprime.state":"\nrandom.array.betaprime.state\n Generator state.\n","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n Length of generator state.\n","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n","random.array.binomial":"\nrandom.array.binomial( len:integer, n:number, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a binomial\n distribution.\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n:number, p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n:number, p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n","random.array.binomial.seed":"\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n Length of generator seed.\n","random.array.binomial.state":"\nrandom.array.binomial.state\n Generator state.\n","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n Length of generator state.\n","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n","random.array.cauchy":"\nrandom.array.cauchy( len:integer, x0:number, gamma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Cauchy\n distribution.\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0:number, gamma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0:number, gamma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n Length of generator seed.\n","random.array.cauchy.state":"\nrandom.array.cauchy.state\n Generator state.\n","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n Length of generator state.\n","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n","random.array.chi":"\nrandom.array.chi( len:integer, k:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a chi\n distribution.\n","random.array.chi.assign":"\nrandom.array.chi.assign( k:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n","random.array.chi.factory":"\nrandom.array.chi.factory( [k:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n","random.array.chi.seed":"\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n Length of generator seed.\n","random.array.chi.state":"\nrandom.array.chi.state\n Generator state.\n","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n Length of generator state.\n","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n","random.array.chisquare":"\nrandom.array.chisquare( len:integer, k:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a chi-square\n distribution.\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n Length of generator seed.\n","random.array.chisquare.state":"\nrandom.array.chisquare.state\n Generator state.\n","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n Length of generator state.\n","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n","random.array.cosine":"\nrandom.array.cosine( len:integer, mu:number, s:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a raised cosine\n distribution.\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu:number, s:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu:number, s:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n","random.array.cosine.seed":"\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n Length of generator seed.\n","random.array.cosine.state":"\nrandom.array.cosine.state\n Generator state.\n","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n Length of generator state.\n","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n","random.array.discreteUniform":"\nrandom.array.discreteUniform( len:integer, a:number, b:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a discrete\n uniform distribution.\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a:number, b:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n Generator state.\n","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n","random.array.erlang":"\nrandom.array.erlang( len:integer, k:number, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an Erlang\n distribution.\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k:number, lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k:number, lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n","random.array.erlang.seed":"\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n Length of generator seed.\n","random.array.erlang.state":"\nrandom.array.erlang.state\n Generator state.\n","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n Length of generator state.\n","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n","random.array.exponential":"\nrandom.array.exponential( len:integer, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an exponential\n distribution.\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n","random.array.exponential.seed":"\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n Length of generator seed.\n","random.array.exponential.state":"\nrandom.array.exponential.state\n Generator state.\n","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n Length of generator state.\n","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n","random.array.f":"\nrandom.array.f( len:integer, d1:number, d2:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an F\n distribution.\n","random.array.f.assign":"\nrandom.array.f.assign( d1:number, d2:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n","random.array.f.factory":"\nrandom.array.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n","random.array.f.PRNG":"\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n","random.array.f.seed":"\nrandom.array.f.seed\n Pseudorandom number generator seed.\n","random.array.f.seedLength":"\nrandom.array.f.seedLength\n Length of generator seed.\n","random.array.f.state":"\nrandom.array.f.state\n Generator state.\n","random.array.f.stateLength":"\nrandom.array.f.stateLength\n Length of generator state.\n","random.array.f.byteLength":"\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n","random.array.frechet":"\nrandom.array.frechet( len:integer, alpha:number, s:number, m:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha:number, s:number, m:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha:number, s:number, m:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n","random.array.frechet.seed":"\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n Length of generator seed.\n","random.array.frechet.state":"\nrandom.array.frechet.state\n Generator state.\n","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n Length of generator state.\n","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n","random.array.gamma":"\nrandom.array.gamma( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a gamma\n distribution.\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n","random.array.gamma.seed":"\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n Length of generator seed.\n","random.array.gamma.state":"\nrandom.array.gamma.state\n Generator state.\n","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n Length of generator state.\n","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n","random.array.geometric":"\nrandom.array.geometric( len:integer, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a geometric\n distribution.\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n","random.array.geometric.seed":"\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n Length of generator seed.\n","random.array.geometric.state":"\nrandom.array.geometric.state\n Generator state.\n","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n Length of generator state.\n","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n","random.array.gumbel":"\nrandom.array.gumbel( len:integer, mu:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Gumbel\n distribution.\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n Length of generator seed.\n","random.array.gumbel.state":"\nrandom.array.gumbel.state\n Generator state.\n","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n Length of generator state.\n","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n","random.array.hypergeometric":"\nrandom.array.hypergeometric( len:integer, N:number, K:number, n:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a hypergeometric\n distribution.\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N:number, K:number, n:number, \n out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N:number, K:number, n:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n Generator state.\n","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n","random.array.invgamma":"\nrandom.array.invgamma( len:integer, alpha:number, beta:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n Length of generator seed.\n","random.array.invgamma.state":"\nrandom.array.invgamma.state\n Generator state.\n","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n Length of generator state.\n","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n double bounded distribution.\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n Generator state.\n","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n","random.array.laplace":"\nrandom.array.laplace( len:integer, mu:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n","random.array.laplace.seed":"\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n Length of generator seed.\n","random.array.laplace.state":"\nrandom.array.laplace.state\n Generator state.\n","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n Length of generator state.\n","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n","random.array.levy":"\nrandom.array.levy( len:integer, mu:number, c:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Lévy\n distribution.\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu:number, c:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n","random.array.levy.factory":"\nrandom.array.levy.factory( [mu:number, c:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n","random.array.levy.seed":"\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n Length of generator seed.\n","random.array.levy.state":"\nrandom.array.levy.state\n Generator state.\n","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n Length of generator state.\n","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n","random.array.logistic":"\nrandom.array.logistic( len:integer, mu:number, s:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a logistic\n distribution.\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu:number, s:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu:number, s:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n","random.array.logistic.seed":"\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n Length of generator seed.\n","random.array.logistic.state":"\nrandom.array.logistic.state\n Generator state.\n","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n Length of generator state.\n","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n","random.array.lognormal":"\nrandom.array.lognormal( len:integer, mu:number, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a lognormal\n distribution.\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu:number, sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu:number, sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n Length of generator seed.\n","random.array.lognormal.state":"\nrandom.array.lognormal.state\n Generator state.\n","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n Length of generator state.\n","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n","random.array.minstd":"\nrandom.array.minstd( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n","random.array.minstd.seed":"\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n Length of generator seed.\n","random.array.minstd.state":"\nrandom.array.minstd.state\n Generator state.\n","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n Length of generator state.\n","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n Generator state.\n","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n","random.array.mt19937":"\nrandom.array.mt19937( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[0, 4294967295]`.\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n Length of generator seed.\n","random.array.mt19937.state":"\nrandom.array.mt19937.state\n Generator state.\n","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n Length of generator state.\n","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len:integer, r:number, p:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a negative\n binomial distribution.\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r:number, p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n Generator state.\n","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n","random.array.normal":"\nrandom.array.normal( len:integer, mu:number, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a normal\n distribution.\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu:number, sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n","random.array.normal.factory":"\nrandom.array.normal.factory( [mu:number, sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n","random.array.normal.seed":"\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n Length of generator seed.\n","random.array.normal.state":"\nrandom.array.normal.state\n Generator state.\n","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n Length of generator state.\n","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n","random.array.pareto1":"\nrandom.array.pareto1( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n I) distribution.\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n Length of generator seed.\n","random.array.pareto1.state":"\nrandom.array.pareto1.state\n Generator state.\n","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n Length of generator state.\n","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n","random.array.poisson":"\nrandom.array.poisson( len:integer, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Poisson\n distribution.\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n","random.array.poisson.seed":"\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n Length of generator seed.\n","random.array.poisson.state":"\nrandom.array.poisson.state\n Generator state.\n","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n Length of generator state.\n","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n","random.array.randu":"\nrandom.array.randu( len:integer[, options:Object] )\n Returns an array containing uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options:Object] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n","random.array.randu.seed":"\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n Length of generator seed.\n","random.array.randu.state":"\nrandom.array.randu.state\n Generator state.\n","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n Length of generator state.\n","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n","random.array.rayleigh":"\nrandom.array.rayleigh( len:integer, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n Generator state.\n","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n Length of generator state.\n","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n","random.array.t":"\nrandom.array.t( len:integer, v:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Student's t\n distribution.\n","random.array.t.assign":"\nrandom.array.t.assign( v:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n","random.array.t.factory":"\nrandom.array.t.factory( [v:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n","random.array.t.PRNG":"\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n","random.array.t.seed":"\nrandom.array.t.seed\n Pseudorandom number generator seed.\n","random.array.t.seedLength":"\nrandom.array.t.seedLength\n Length of generator seed.\n","random.array.t.state":"\nrandom.array.t.state\n Generator state.\n","random.array.t.stateLength":"\nrandom.array.t.stateLength\n Length of generator state.\n","random.array.t.byteLength":"\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n","random.array.triangular":"\nrandom.array.triangular( len:integer, a:number, b:number, c:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a triangular\n distribution.\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a:number, b:number, c:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n","random.array.triangular.seed":"\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n Length of generator seed.\n","random.array.triangular.state":"\nrandom.array.triangular.state\n Generator state.\n","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n Length of generator state.\n","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n","random.array.uniform":"\nrandom.array.uniform( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a continuous\n uniform distribution.\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n","random.array.uniform.seed":"\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n Length of generator seed.\n","random.array.uniform.state":"\nrandom.array.uniform.state\n Generator state.\n","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n Length of generator state.\n","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n","random.array.weibull":"\nrandom.array.weibull( len:integer, k:number, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Weibull\n distribution.\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k:number, lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k:number, lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n","random.array.weibull.seed":"\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n Length of generator seed.\n","random.array.weibull.state":"\nrandom.array.weibull.state\n Generator state.\n","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n Length of generator state.\n","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n","random.iterators.arcsine":"\nrandom.iterators.arcsine( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n","random.iterators.beta":"\nrandom.iterators.beta( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n","random.iterators.binomial":"\nrandom.iterators.binomial( n:integer, p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0:number, Ɣ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n","random.iterators.chi":"\nrandom.iterators.chi( k:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ:number, s:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a:integer, b:integer[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n","random.iterators.erlang":"\nrandom.iterators.erlang( k:integer, λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n","random.iterators.f":"\nrandom.iterators.f( d1:number, d2:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n","random.iterators.frechet":"\nrandom.iterators.frechet( α:number, s:number, m:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.iterators.gamma":"\nrandom.iterators.gamma( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n","random.iterators.geometric":"\nrandom.iterators.geometric( p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n","random.iterators.levy":"\nrandom.iterators.levy( μ:number, c:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ:number, s:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ:number, σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r:number, p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n","random.iterators.normal":"\nrandom.iterators.normal( μ:number, σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n","random.iterators.randi":"\nrandom.iterators.randi( [options:Object] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n","random.iterators.randn":"\nrandom.iterators.randn( [options:Object] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n","random.iterators.randu":"\nrandom.iterators.randu( [options:Object] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n","random.iterators.t":"\nrandom.iterators.t( v:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n","random.iterators.triangular":"\nrandom.iterators.triangular( a:number, b:number, c:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n","random.iterators.uniform":"\nrandom.iterators.uniform( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n","random.iterators.weibull":"\nrandom.iterators.weibull( k:number, λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n","random.streams.arcsine":"\nrandom.streams.arcsine( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n","random.streams.bernoulli":"\nrandom.streams.bernoulli( p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n","random.streams.beta":"\nrandom.streams.beta( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n","random.streams.betaprime":"\nrandom.streams.betaprime( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n","random.streams.binomial":"\nrandom.streams.binomial( n:integer, p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n:integer, p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n:integer, p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n","random.streams.cauchy":"\nrandom.streams.cauchy( x0:number, γ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0:number, γ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0:number, γ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n","random.streams.chi":"\nrandom.streams.chi( k:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n","random.streams.chisquare":"\nrandom.streams.chisquare( k:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n","random.streams.cosine":"\nrandom.streams.cosine( μ:number, s:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ:number, s:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ:number, s:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a:integer, b:integer[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a:integer, b:integer, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a:integer, b:integer[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n","random.streams.erlang":"\nrandom.streams.erlang( k:integer, λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k:number, λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k:number, λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n","random.streams.exponential":"\nrandom.streams.exponential( λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n","random.streams.f":"\nrandom.streams.f( d1:number, d2:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1:number, d2:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n","random.streams.frechet":"\nrandom.streams.frechet( α:number, s:number, m:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Fréchet distribution.\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α:number, s:number, m:number,]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α:number, s:number, m:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n","random.streams.gamma":"\nrandom.streams.gamma( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n","random.streams.geometric":"\nrandom.streams.geometric( p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n","random.streams.gumbel":"\nrandom.streams.gumbel( μ:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N:integer, K:integer, n:integer,]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n","random.streams.invgamma":"\nrandom.streams.invgamma( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.laplace":"\nrandom.streams.laplace( μ:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n","random.streams.levy":"\nrandom.streams.levy( μ:number, c:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ:number, c:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ:number, c:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n","random.streams.logistic":"\nrandom.streams.logistic( μ:number, s:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ:number, s:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ:number, s:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n","random.streams.lognormal":"\nrandom.streams.lognormal( μ:number, σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ:number, σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n","random.streams.minstd":"\nrandom.streams.minstd( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n","random.streams.mt19937":"\nrandom.streams.mt19937( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r:number, p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r:number, p:number, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r:integer, p:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n","random.streams.normal":"\nrandom.streams.normal( μ:number, σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ:number, σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n","random.streams.pareto1":"\nrandom.streams.pareto1( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n","random.streams.poisson":"\nrandom.streams.poisson( λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n","random.streams.randi":"\nrandom.streams.randi( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n","random.streams.randn":"\nrandom.streams.randn( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n","random.streams.randu":"\nrandom.streams.randu( [options:Object] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n","random.streams.t":"\nrandom.streams.t( v:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n","random.streams.triangular":"\nrandom.streams.triangular( a:number, b:number, c:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n triangular distribution.\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a:number, b:number, c:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n","random.streams.uniform":"\nrandom.streams.uniform( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n","random.streams.weibull":"\nrandom.streams.weibull( k:number, λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k:number, λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k:number, λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n","random.strided.arcsine":"\nrandom.strided.arcsine( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution.\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n","random.strided.bernoulli":"\nrandom.strided.bernoulli( N:integer, p:ArrayLikeObject, sp:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n Generator state.\n","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n","random.strided.beta":"\nrandom.strided.beta( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution.\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n","random.strided.betaprime":"\nrandom.strided.betaprime( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution.\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n","random.strided.chi":"\nrandom.strided.chi( N:integer, k:ArrayLikeObject, sk:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution.\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n","random.strided.chi.seed":"\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n Length of generator seed.\n","random.strided.chi.state":"\nrandom.strided.chi.state\n Generator state.\n","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n Length of generator state.\n","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n","random.strided.chisquare":"\nrandom.strided.chisquare( N:integer, k:ArrayLikeObject, sk:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution.\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n Generator state.\n","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n Length of generator state.\n","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n","random.strided.cosine":"\nrandom.strided.cosine( N:integer, mu:ArrayLikeObject, sm:integer, \n s:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution.\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, s:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution.\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N:integer, a:ArrayLikeObject, \n sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n","random.strided.exponential":"\nrandom.strided.exponential( N:integer, lambda:ArrayLikeObject, sl:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution.\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N:integer, lambda:ArrayLikeObject, \n sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n Length of generator seed.\n","random.strided.exponential.state":"\nrandom.strided.exponential.state\n Generator state.\n","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n Length of generator state.\n","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n","random.strided.gamma":"\nrandom.strided.gamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution.\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n","random.strided.geometric":"\nrandom.strided.geometric( N:integer, p:ArrayLikeObject, sp:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution.\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n Length of generator seed.\n","random.strided.geometric.state":"\nrandom.strided.geometric.state\n Generator state.\n","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n Length of generator state.\n","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n","random.strided.invgamma":"\nrandom.strided.invgamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n","random.strided.lognormal":"\nrandom.strided.lognormal( N:integer, mu:ArrayLikeObject, sm:integer, \n sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution.\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n","random.strided.minstd":"\nrandom.strided.minstd( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N:integer, out:ArrayLikeObject, \n so:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.mt19937":"\nrandom.strided.mt19937( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive).\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.normal":"\nrandom.strided.normal( N:integer, mu:ArrayLikeObject, sm:integer, \n sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution.\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n","random.strided.poisson":"\nrandom.strided.poisson( N:integer, lambda:ArrayLikeObject, sl:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution.\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, \n ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n Length of generator seed.\n","random.strided.poisson.state":"\nrandom.strided.poisson.state\n Generator state.\n","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n Length of generator state.\n","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n","random.strided.randu":"\nrandom.strided.randu( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n","random.strided.rayleigh":"\nrandom.strided.rayleigh( N:integer, sigma:ArrayLikeObject, ss:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N:integer, sigma:ArrayLikeObject, ss:integer, \n os:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n Generator state.\n","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n","random.strided.t":"\nrandom.strided.t( N:integer, v:ArrayLikeObject, sv:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution.\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N:integer, v:ArrayLikeObject, sv:integer, ov:integer, \n out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n","random.strided.t.factory":"\nrandom.strided.t.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n","random.strided.t.seed":"\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n Length of generator seed.\n","random.strided.t.state":"\nrandom.strided.t.state\n Generator state.\n","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n Length of generator state.\n","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n","random.strided.uniform":"\nrandom.strided.uniform( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution.\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n","ranks":"\nranks( arr:Array[, options:Object] )\n Computes the sample ranks for the values of an array-like object.\n","readDir":"\nreadDir( path:string|Buffer, clbk:Function )\n Asynchronously reads the contents of a directory.\n","readDir.sync":"\nreadDir.sync( path:string|Buffer )\n Synchronously reads the contents of a directory.\n","readFile":"\nreadFile( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n Asynchronously reads the entire contents of a file.\n","readFile.sync":"\nreadFile.sync( file:string|Buffer|integer[, options:Object|string] )\n Synchronously reads the entire contents of a file.\n","readFileList":"\nreadFileList( filepaths:Array[, options:Object|string], clbk:Function )\n Asynchronously reads the entire contents of each file in a file list.\n","readFileList.sync":"\nreadFileList.sync( filepaths:Array[, options:Object|string] )\n Synchronously reads the entire contents of each file in a file list.\n","readJSON":"\nreadJSON( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n Asynchronously reads a file as JSON.\n","readJSON.sync":"\nreadJSON.sync( file:string|Buffer|integer[, options:Object|string] )\n Synchronously reads a file as JSON.\n","readWASM":"\nreadWASM( file:string|Buffer|integer[, options:Object], clbk:Function )\n Asynchronously reads a file as WebAssembly.\n","readWASM.sync":"\nreadWASM.sync( file:string|Buffer|integer[, options:Object] )\n Synchronously reads a file as WebAssembly.\n","real":"\nreal( z:Complex128 )\n Returns the real component of a double-precision complex floating-point\n number.\n","realarray":"\nrealarray( [dtype:string] )\n Creates a typed array.\n\nrealarray( length:integer[, dtype:string] )\n Returns a typed array having a specified length.\n\nrealarray( typedarray:TypedArray[, dtype:string] )\n Creates a typed array from another typed array.\n\nrealarray( obj:Object[, dtype:string] )\n Creates a typed array from an array-like object or iterable.\n\nrealarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a typed array view of an ArrayBuffer.\n","realarrayCtors":"\nrealarrayCtors( dtype:string )\n Returns a typed array constructor.\n","realarrayDataTypes":"\nrealarrayDataTypes()\n Returns a list of typed array real-valued data types.\n","realf":"\nrealf( z:Complex64 )\n Returns the real component of a single-precision complex floating-point\n number.\n","realmax":"\nrealmax( dtype:string )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n","realmin":"\nrealmin( dtype:string )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n","reBasename":"\nreBasename( [platform:string] )\n Returns a regular expression to capture the last part of a path.\n","reBasename.REGEXP":"\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n","reBasenamePosix":"\nreBasenamePosix()\n Returns a regular expression to capture the last part of a POSIX path.\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n","reBasenameWindows":"\nreBasenameWindows()\n Returns a regular expression to capture the last part of a Windows path.\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n","reColorHexadecimal":"\nreColorHexadecimal( [mode:string] )\n Returns a regular expression to match a hexadecimal color.\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n","reDecimalNumber":"\nreDecimalNumber( [options:Object] )\n Returns a regular expression to match a decimal number.\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n","reDirname":"\nreDirname( [platform:string] )\n Returns a regular expression to capture a path dirname.\n","reDirname.REGEXP":"\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n","reDirnamePosix":"\nreDirnamePosix()\n Returns a regular expression to capture a POSIX path dirname.\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n","reDirnameWindows":"\nreDirnameWindows()\n Returns a regular expression to capture a Windows path dirname.\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n","reduce":"\nreduce( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n thisArg:any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","reduce2d":"\nreduce2d( arr:ArrayLikeObject, initial:ArrayLikeObject, \n reducer:Function[, thisArg:any] )\n Reduces the number of dimensions by one of a two-dimensional nested array by\n applying a function against an accumulator and each element along the\n innermost dimension and returning the accumulation results as a one-\n dimensional array.\n","reduceAsync":"\nreduceAsync( collection:Array|TypedArray|Object, initial:any, [options:Object,] \n reducer:Function, done:Function )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n","reduceAsync.factory":"\nreduceAsync.factory( [options:Object,] fcn:Function )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n","reduceRight":"\nreduceRight( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n thisArg:any] )\n Applies a function against an accumulator and each element in an array while\n iterating from right to left and returns the accumulated result.\n","reduceRightAsync":"\nreduceRightAsync( collection:Array|TypedArray|Object, initial:any, \n [options:Object,] reducer:Function, done:Function )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n","reEOL":"\nreEOL( [options:Object] )\n Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP":"\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n","reExtendedLengthPath":"\nreExtendedLengthPath()\n Returns a regular expression to test if a string is an extended-length path.\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n","reExtname":"\nreExtname( [platform:string] )\n Returns a regular expression to capture a filename extension.\n","reExtname.REGEXP":"\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n","reExtnamePosix":"\nreExtnamePosix\n Returns a regular expression to capture a POSIX filename extension.\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n","reExtnameWindows":"\nreExtnameWindows\n Returns a regular expression to capture a Windows filename extension.\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n","reFilename":"\nreFilename( [platform:string] )\n Regular expression to split a filename.\n","reFilename.REGEXP":"\nreFilename.REGEXP\n Regular expression to split a filename.\n","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n","reFilenamePosix":"\nreFilenamePosix()\n Returns a regular expression to split a POSIX filename.\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n","reFilenameWindows":"\nreFilenameWindows()\n Returns a regular expression to split a Windows filename.\n","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n","reFromString":"\nreFromString( str:string )\n Parses a regular expression string and returns a new regular expression.\n","reFunctionName":"\nreFunctionName()\n Return a regular expression to capture a function name.\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n","regexp2json":"\nregexp2json( re:RegExp )\n Returns a JSON representation of a regular expression.\n","reim":"\nreim( z:Complex128 )\n Returns the real and imaginary components of a double-precision complex\n floating-point number.\n","reimf":"\nreimf( z:Complex64 )\n Returns the real and imaginary components of a single-precision complex\n floating-point number.\n","rejectArguments":"\nrejectArguments( fcn:Function, predicate:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n","removeFirst":"\nremoveFirst( str:string[, n:integer][, options:Object] )\n Removes the first character(s) of a `string`.\n","removeLast":"\nremoveLast( str:string[, n:integer][, options:Object] )\n Removes the last character(s) of a `string`.\n","removePunctuation":"\nremovePunctuation( str:string )\n Removes punctuation characters from a `string`.\n","removeUTF8BOM":"\nremoveUTF8BOM( str:string )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n","removeWords":"\nremoveWords( str:string, words:Array[, ignoreCase:boolean] )\n Removes all occurrences of the given words from a `string`.\n","rename":"\nrename( oldPath:string|Buffer, newPath:string|Buffer, clbk:Function )\n Asynchronously renames a file.\n","rename.sync":"\nrename.sync( oldPath:string|Buffer, newPath:string|Buffer )\n Synchronously renames a file.\n","reNativeFunction":"\nreNativeFunction()\n Returns a regular expression to match a native function.\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n","reorderArguments":"\nreorderArguments( fcn:Function, indices:Array[, thisArg:any] )\n Returns a function that invokes a provided function with reordered\n arguments.\n","repeat":"\nrepeat( str:string, n:integer )\n Repeats a string `n` times and returns the concatenated result.\n","replace":"\nreplace( str:string, search:string|RegExp, newval:string|Function )\n Replaces search occurrences with a replacement string.\n","reRegExp":"\nreRegExp()\n Returns a regular expression to parse a regular expression string.\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n","rescape":"\nrescape( str:string )\n Escapes a regular expression string.\n","reSemVer":"\nreSemVer()\n Returns a regular expression to match a semantic version string.\n","reSemVer.REGEXP":"\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n","resolveParentPath":"\nresolveParentPath( path:string[, options:Object], clbk:Function )\n Asynchronously resolves a path by walking parent directories.\n","resolveParentPath.sync":"\nresolveParentPath.sync( path:string[, options:Object] )\n Synchronously resolves a path by walking parent directories.\n","resolveParentPathBy":"\nresolveParentPathBy( path:string[, options:Object], predicate:Function, \n clbk:Function )\n Asynchronously resolves a path according to a predicate function by walking\n parent directories.\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path:string[, options:Object], predicate:Function )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n","reUncPath":"\nreUncPath()\n Return a regular expression to parse a UNC path.\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n Returns a regular expression to match a UTF-16 surrogate pair.\n","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n Returns a regular expression to match an unpaired UTF-16 surrogate.\n","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n","reverseArguments":"\nreverseArguments( fcn:Function[, thisArg:any] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n","reverseString":"\nreverseString( str:string[, options:Object] )\n Reverses a string.\n","reviveBasePRNG":"\nreviveBasePRNG( key:string, value:any )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n","reviveBuffer":"\nreviveBuffer( key:string, value:any )\n Revives a JSON-serialized Buffer.\n","reviveComplex":"\nreviveComplex( key:string, value:any )\n Revives a JSON-serialized complex number.\n","reviveComplex64":"\nreviveComplex64( key:string, value:any )\n Revives a JSON-serialized 64-bit complex number.\n","reviveComplex128":"\nreviveComplex128( key:string, value:any )\n Revives a JSON-serialized 128-bit complex number.\n","reviveError":"\nreviveError( key:string, value:any )\n Revives a JSON-serialized error object.\n","reviveRegExp":"\nreviveRegExp( key:string, value:any )\n Revives a JSON-serialized regular expression.\n","reviveTypedArray":"\nreviveTypedArray( key:string, value:any )\n Revives a JSON-serialized typed array.\n","reWhitespace":"\nreWhitespace( [options:Object] )\n Returns a regular expression to match a white space character.\n","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n","rpad":"\nrpad( str:string, len:integer[, pad:string] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n","rtrim":"\nrtrim( str:string )\n Trims whitespace from the end of a string.\n","safeintmax":"\nsafeintmax( dtype:string )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n","safeintmin":"\nsafeintmin( dtype:string )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n","sample":"\nsample( x:ArrayLike[, options:Object] )\n Samples elements from an array-like object.\n","sample.factory":"\nsample.factory( [pool:ArrayLike, ][options:Object] )\n Returns a function to sample elements from an array-like object.\n","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n","scalar2array":"\nscalar2array( value:any[, dtype:string] )\n Returns a single-element array containing a provided scalar value.\n","scalar2ndarray":"\nscalar2ndarray( value:any[, options:Object] )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n","sdot":"\nsdot( x:ndarray, y:ndarray )\n Computes the dot product of two single-precision floating-point vectors.\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n Number of seconds in a day.\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n Number of seconds in a week.\n","secondsInMonth":"\nsecondsInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of seconds in a month.\n","secondsInYear":"\nsecondsInYear( [value:integer|Date] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n","seq2slice":"\nseq2slice( str:string, len:integer, strict:boolean )\n Converts a subsequence string to a Slice object.\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a configurable read-only property.\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj:Object, prop:string|symbol, \n getter:Function )\n Defines a configurable read-only accessor.\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj:Object, prop:string|symbol, \n getter:Function, setter:Function )\n Defines a configurable property having read-write accessors.\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n setter:Function )\n Defines a configurable write-only accessor.\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n Defines a configurable memoized read-only object property.\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n Defines a memoized read-only object property.\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj:Object, prop:string|symbol, value:any )\n Defines a non-enumerable property.\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a non-enumerable read-only property.\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj:Object, prop:string|symbol, \n getter:Function )\n Defines a non-enumerable read-only accessor.\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj:Object, prop:string|symbol, \n getter:Function, setter:Function )\n Defines a non-enumerable property having read-write accessors.\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n setter:Function )\n Defines a non-enumerable write-only accessor.\n","setReadOnly":"\nsetReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a read-only property.\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function )\n Defines a read-only accessor.\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj:Object, prop:string|symbol, getter:Function, \n setter:Function )\n Defines a property having read-write accessors.\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj:Object, prop:string|symbol, setter:Function )\n Defines a write-only accessor.\n","SharedArrayBuffer":"\nSharedArrayBuffer( size:integer )\n Returns a shared array buffer having a specified number of bytes.\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n","shift":"\nshift( collection:Array|TypedArray|Object )\n Removes and returns the first element of a collection.\n","shuffle":"\nshuffle( arr:ArrayLike[, options:Object] )\n Shuffles elements of an array-like object.\n","shuffle.factory":"\nshuffle.factory( [options:Object] )\n Returns a function to shuffle elements of array-like objects.\n","sizeOf":"\nsizeOf( dtype:string )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n","Slice":"\nSlice( [stop:integer|null|undefined] )\n Returns a Slice.\n\nSlice( start:integer|null|undefined, stop:integer|null|undefined[, \n step:integer|null|undefined] )\n Returns a Slice.\n","Slice.prototype.start":"\nSlice.prototype.start\n Read-only property returning the starting slice index.\n","Slice.prototype.stop":"\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n","Slice.prototype.step":"\nSlice.prototype.step\n Read-only property returning the index increment.\n","Slice.prototype.toString":"\nSlice.prototype.toString()\n Serializes a Slice as a string.\n","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n","snakecase":"\nsnakecase( str:string )\n Converts a string to snake case.\n","some":"\nsome( collection:Array|TypedArray|Object, n:number )\n Tests whether at least `n` elements in a collection are truthy.\n","someBy":"\nsomeBy( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n thisArg:any ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n","someByAsync":"\nsomeByAsync( collection:Array|TypedArray|Object, n:number, [options:Object,] \n predicate:Function, done:Function )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n","someByAsync.factory":"\nsomeByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n","someByRight":"\nsomeByRight( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n thisArg:any ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n","someByRightAsync":"\nsomeByRightAsync( collection:Array|TypedArray|Object, n:number, \n [options:Object,] predicate:Function, done:Function )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n","SOTU":"\nSOTU( [options:Object] )\n Returns State of the Union (SOTU) addresses.\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n","SparklineBase":"\nSparklineBase( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a Sparkline instance.\n","sparsearray2iterator":"\nsparsearray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, \n thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n","splitStream":"\nsplitStream( [options:Object] )\n Returns a transform stream which splits streamed data.\n","splitStream.factory":"\nsplitStream.factory( [options:Object] )\n Returns a function for creating transform streams for splitting streamed\n data.\n","splitStream.objectMode":"\nsplitStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n","SQRT_EPS":"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n","SQRT_HALF":"\nSQRT_HALF\n Square root of `1/2`.\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n","SQRT_PHI":"\nSQRT_PHI\n Square root of the golden ratio.\n","SQRT_PI":"\nSQRT_PI\n Square root of the mathematical constant `π`.\n","SQRT_THREE":"\nSQRT_THREE\n Square root of `3`.\n","SQRT_TWO":"\nSQRT_TWO\n Square root of `2`.\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n Returns US birth data from 2000 to 2014, as provided by the Social Security\n Administration.\n","sswap":"\nsswap( x:ndarray, y:ndarray )\n Interchanges two single-precision floating-point vectors.\n","Stack":"\nStack()\n Stack constructor.\n","standalone2pkg":"\nstandalone2pkg( pkg:string )\n Returns the internal package name associated with a provided standalone\n package name.\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n Returns a string array containing two or three letter abbreviations for each\n card in a standard 52-card deck.\n","startcase":"\nstartcase( str:string )\n Capitalizes the first letter of each word in an input string.\n","startsWith":"\nstartsWith( str:string, search:string[, position:integer] )\n Tests if a string starts with the characters of another string.\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n Returns a list of English stop words.\n","strided.abs":"\nstrided.abs( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n offsetY:integer )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.abs2":"\nstrided.abs2( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.abs2By":"\nstrided.abs2By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n","strided.absBy":"\nstrided.absBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y`.\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n","strided.add":"\nstrided.add( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.add.ndarray":"\nstrided.add.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.cbrt":"\nstrided.cbrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y`.\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n","strided.ceil":"\nstrided.ceil( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y`.\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.deg2rad":"\nstrided.deg2rad( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y`.\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.dataTypes":"\nstrided.dataTypes()\n Returns a list of strided array data types.\n","strided.dispatch":"\nstrided.dispatch( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns a strided array function interface which performs multiple dispatch.\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns a strided array function interface which accepts a callback function\n and performs multiple dispatch.\n","strided.floor":"\nstrided.floor( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y`.\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.inv":"\nstrided.inv( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n offsetY:integer )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.mul":"\nstrided.mul( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.ramp":"\nstrided.ramp( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.rsqrt":"\nstrided.rsqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.sqrt":"\nstrided.sqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.sub":"\nstrided.sub( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.trunc":"\nstrided.trunc( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y`.\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n","stridedarray2iterator":"\nstridedarray2iterator( N:integer, src:ArrayLikeObject, stride:integer, \n offset:integer[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n","stridedArrayStream":"\nstridedArrayStream( N:integer, buffer:ArrayLikeObject, stride:integer, \n offset:integer[, options:Object] )\n Creates a readable stream from a strided array-like object.\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects.\n","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N:integer, buffer:ArrayLikeObject, \n stride:integer, offset:integer[, options:Object] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n","string2buffer":"\nstring2buffer( str:string[, encoding:string] )\n Allocates a buffer containing a provided string.\n","sub2ind":"\nsub2ind( shape:ArrayLike, ...subscript:integer[, options:Object] )\n Converts subscripts to a linear index.\n","substringAfter":"\nsubstringAfter( str:string, search:string[, fromIndex:integer] )\n Returns the part of a string after a specified substring.\n","substringAfterLast":"\nsubstringAfterLast( str:string, search:string[, fromIndex:integer] )\n Returns the part of a string after the last occurrence of a specified\n substring.\n","substringBefore":"\nsubstringBefore( str:string, search:string )\n Returns the part of a string before a specified substring.\n","substringBeforeLast":"\nsubstringBeforeLast( str:string, search:string )\n Returns the part of a string before the last occurrence of a specified\n substring.\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n","Symbol":"\nSymbol( [description:string] )\n Returns a symbol.\n","tabulate":"\ntabulate( collection:Array|TypedArray|Object )\n Generates a frequency table.\n","tabulateBy":"\ntabulateBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Generates a frequency table according to an indicator function.\n","tabulateByAsync":"\ntabulateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Generates a frequency table according to an indicator function.\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which generates a frequency table according to an\n indicator function.\n","thunk":"\nthunk( fcn:Function[, ...args:any] )\n Returns a thunk.\n","tic":"\ntic()\n Returns a high-resolution time.\n","timeit":"\ntimeit( code:string, [options:Object,] clbk:Function )\n Times a snippet.\n","tmpdir":"\ntmpdir()\n Returns the directory for storing temporary files.\n","toc":"\ntoc( time:Array )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n","tokenize":"\ntokenize( str:string[, keepWhitespace:boolean] )\n Tokenizes a string.\n","transformStream":"\ntransformStream( [options:Object] )\n Returns a transform stream.\n","transformStream.factory":"\ntransformStream.factory( [options:Object] )\n Returns a function for creating transform streams.\n","transformStream.objectMode":"\ntransformStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream.\n","transformStream.ctor":"\ntransformStream.ctor( [options:Object] )\n Returns a custom transform stream constructor.\n","trim":"\ntrim( str:string )\n Trims whitespace from the beginning and end of a `string`.\n","truncate":"\ntruncate( str:string, len:integer[, ending:string] )\n Truncates a string to a specified length.\n","truncateMiddle":"\ntruncateMiddle( str:string, len:integer[, seq:string] )\n Truncates a string in the middle to a specified length.\n","trycatch":"\ntrycatch( x:Function, y:any )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n","trycatchAsync":"\ntrycatchAsync( x:Function, y:any, done:Function )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n","tryFunction":"\ntryFunction( fcn:Function[, thisArg:any] )\n Wraps a function in a try/catch block.\n","tryRequire":"\ntryRequire( id:string )\n Wraps `require` in a `try/catch` block.\n","trythen":"\ntrythen( x:Function, y:Function )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n","trythenAsync":"\ntrythenAsync( x:Function, y:Function, done:Function )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n","ttest":"\nttest( x:Array[, y:Array][, options:Object] )\n Computes a one-sample or paired Student's t test.\n","ttest2":"\nttest2( x:Array, y:Array[, options:Object] )\n Computes a two-sample Student's t test.\n","TWO_PI":"\nTWO_PI\n The mathematical constant `π` times `2`.\n","typedarray":"\ntypedarray( [dtype:string] )\n Creates a typed array.\n\ntypedarray( length:integer[, dtype:string] )\n Returns a typed array having a specified length.\n\ntypedarray( typedarray:TypedArray[, dtype:string] )\n Creates a typed array from another typed array.\n\ntypedarray( obj:Object[, dtype:string] )\n Creates a typed array from an array-like object or iterable.\n\ntypedarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a typed array view of an ArrayBuffer.\n","typedarray2json":"\ntypedarray2json( arr:TypedArray )\n Returns a JSON representation of a typed array.\n","typedarrayCtors":"\ntypedarrayCtors( dtype:string )\n Returns a typed array constructor.\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n","typedarraypool":"\ntypedarraypool( [dtype:string] )\n Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool( length:integer[, dtype:string] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\ntypedarraypool( typedarray:TypedArray[, dtype:string] )\n Creates a pooled typed array from another typed array.\n\ntypedarraypool( obj:Object[, dtype:string] )\n Creates a pooled typed array from an array-like object.\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype:string] )\n Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool.malloc( length:integer[, dtype:string] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\ntypedarraypool.malloc( typedarray:TypedArray[, dtype:string] )\n Creates a pooled typed array from another typed array.\n\ntypedarraypool.malloc( obj:Object[, dtype:string] )\n Creates a pooled typed array from an array-like object.\n","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype:string] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\ntypedarraypool.calloc( length:integer[, dtype:string] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n","typedarraypool.free":"\ntypedarraypool.free( buf:TypedArray|ArrayBuffer )\n Frees a typed array or typed array buffer for use in a future allocation.\n","typedarraypool.clear":"\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n","typedarraypool.factory":"\ntypedarraypool.factory( [options:Object] )\n Creates a typed array pool.\n","typemax":"\ntypemax( dtype:string )\n Returns the maximum value of a specified numeric type.\n","typemin":"\ntypemin( dtype:string )\n Returns the minimum value of a specified numeric type.\n","typeOf":"\ntypeOf( value:any )\n Determines a value's type.\n","UINT8_MAX":"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n","Uint8Array":"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\nUint8Array( length:integer )\n Returns a typed array having a specified length.\n\nUint8Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint8Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint8Array.from":"\nUint8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint8Array.of":"\nUint8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8Array.name":"\nUint8Array.name\n Typed array constructor name.\n","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n Serializes an array as a string.\n","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Uint8ClampedArray":"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\nUint8ClampedArray( length:integer )\n Returns a typed array having a specified length.\n\nUint8ClampedArray( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint8ClampedArray( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint8ClampedArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n Typed array constructor name.\n","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement:number[, \n fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement:number[, \n fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n","UINT16_MAX":"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n","Uint16Array":"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\nUint16Array( length:integer )\n Returns a typed array having a specified length.\n\nUint16Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint16Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint16Array.from":"\nUint16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint16Array.of":"\nUint16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint16Array.name":"\nUint16Array.name\n Typed array constructor name.\n","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n Serializes an array as a string.\n","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","UINT32_MAX":"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n","Uint32Array":"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\nUint32Array( length:integer )\n Returns a typed array having a specified length.\n\nUint32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint32Array.from":"\nUint32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint32Array.of":"\nUint32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint32Array.name":"\nUint32Array.name\n Typed array constructor name.\n","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n Serializes an array as a string.\n","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","umask":"\numask( [mask:integer|string,] [options:Object] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n","uncapitalize":"\nuncapitalize( str:string )\n Lowercases the first character of a string.\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj:Object )\n Converts the first letter of each object key to lowercase.\n","uncurry":"\nuncurry( fcn:Function[, arity:integer, ][thisArg:any] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n","uncurryRight":"\nuncurryRight( fcn:Function[, arity:integer, ][thisArg:any] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n","UNICODE_MAX":"\nUNICODE_MAX\n Maximum Unicode code point.\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline column chart instance.\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline line chart instance.\n","UnicodeSparkline":"\nUnicodeSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a Unicode sparkline instance.\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline tristate chart instance.\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline up/down chart instance.\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline win/loss chart instance.\n","unlink":"\nunlink( path:string|Buffer|integer, clbk:Function )\n Asynchronously removes a directory entry.\n","unlink.sync":"\nunlink.sync( path:string|Buffer|integer )\n Synchronously removes a directory entry.\n","unshift":"\nunshift( collection:Array|TypedArray|Object, ...items:any )\n Adds one or more elements to the beginning of a collection.\n","until":"\nuntil( predicate:Function, fcn:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","untilAsync":"\nuntilAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","untilEach":"\nuntilEach( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n","untilEachRight":"\nuntilEachRight( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","unzip":"\nunzip( arr:Array[, idx:Array] )\n Unzips a zipped array (i.e., a nested array of tuples).\n","uppercase":"\nuppercase( str:string )\n Converts a string to uppercase.\n","uppercaseKeys":"\nuppercaseKeys( obj:Object )\n Converts each object key to uppercase.\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str:string )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n","vartest":"\nvartest( x:Array, y:Array[, options:Object] )\n Computes a two-sample F-test for equal variances.\n","waterfall":"\nwaterfall( fcns:Array, clbk:Function[, thisArg:any] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n","waterfall.factory":"\nwaterfall.factory( fcns:Array, clbk:Function[, thisArg:any] )\n Returns a reusable waterfall function.\n","whileAsync":"\nwhileAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","whileEach":"\nwhileEach( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection.\n","whileEachRight":"\nwhileEachRight( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","whilst":"\nwhilst( predicate:Function, fcn:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","wilcoxon":"\nwilcoxon( x:Array|TypedArray[, y:Array|TypedArray][, options:Object] )\n Computes a one-sample or paired Wilcoxon signed rank test.\n","writableProperties":"\nwritableProperties( value:any )\n Returns an array of an object's own writable property names and symbols.\n","writablePropertiesIn":"\nwritablePropertiesIn( value:any )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n","writablePropertyNames":"\nwritablePropertyNames( value:any )\n Returns an array of an object's own writable property names.\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value:any )\n Returns an array of an object's own and inherited writable property names.\n","writablePropertySymbols":"\nwritablePropertySymbols( value:any )\n Returns an array of an object's own writable symbol properties.\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited writable symbol\n properties.\n","writeFile":"\nwriteFile( file:string|Buffer|integer, data:string|Buffer[, \n options:Object|string], clbk:Function )\n Asynchronously writes data to a file.\n","writeFile.sync":"\nwriteFile.sync( file:string|Buffer|integer, data:string|Buffer[, \n options:Object|string] )\n Synchronously writes data to a file.\n","zip":"\nzip( ...arr:Array[, options:Object] )\n Generates array tuples from input arrays.\n","ztest":"\nztest( x:Array, sigma:number[, options:Object] )\n Computes a one-sample z-test.\n","ztest2":"\nztest2( x:Array, y:Array, sigmax:number, sigmay:number[, \n options:Object] )\n Computes a two-sample z-test.\n"} \ No newline at end of file +{"abs":"\nabs( x:ndarray|ArrayLikeObject|number[, options:Object] )\n Computes the absolute value.\n","abs.assign":"\nabs.assign( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n Computes the absolute value and assigns results to a provided output array.\n","acartesianPower":"\nacartesianPower( x:ArrayLikeObject, n:integer )\n Returns the Cartesian power.\n","acartesianProduct":"\nacartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n Returns the Cartesian product.\n","acartesianSquare":"\nacartesianSquare( x:ArrayLikeObject )\n Returns the Cartesian square.\n","acronym":"\nacronym( str:string[, options:Object] )\n Generates an acronym for a given string.\n","aempty":"\naempty( length:integer[, dtype:string] )\n Creates an uninitialized array having a specified length.\n","aemptyLike":"\naemptyLike( x:TypedArray|Array[, dtype:string] )\n Creates an uninitialized array having the same length and data type as a\n provided input array.\n","AFINN_96":"\nAFINN_96()\n Returns a list of English words rated for valence.\n","AFINN_111":"\nAFINN_111()\n Returns a list of English words rated for valence.\n","afull":"\nafull( length:integer, value:any[, dtype:string] )\n Returns a filled array having a specified length.\n","afullLike":"\nafullLike( x:TypedArray|Array[, dtype:string] )\n Returns a filled array having the same length and data type as a provided\n input array.\n","alias2pkg":"\nalias2pkg( alias:string )\n Returns the package name associated with a provided alias.\n","alias2related":"\nalias2related( alias:string )\n Returns aliases related to a specified alias.\n","alias2standalone":"\nalias2standalone( alias:string )\n Returns the standalone package name associated with a provided alias.\n","aliases":"\naliases( [namespace:string] )\n Returns a list of standard library aliases.\n","allocUnsafe":"\nallocUnsafe( size:integer )\n Allocates a buffer having a specified number of bytes.\n","amskfilter":"\namskfilter( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n Returns a new array by applying a mask to a provided input array.\n","amskreject":"\namskreject( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n Returns a new array by applying a mask to a provided input array.\n","anans":"\nanans( length:integer[, dtype:string] )\n Returns an array filled with NaNs and having a specified length.\n","anansLike":"\nanansLike( x:TypedArray|Array[, dtype:string] )\n Returns an array filled with NaNs and having the same length and data type\n as a provided input array.\n","anova1":"\nanova1( x:Array, factor:Array[, options:Object] )\n Performs a one-way analysis of variance.\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n","any":"\nany( collection:Array|TypedArray|Object )\n Tests whether at least one element in a collection is truthy.\n","anyBy":"\nanyBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n","anyByAsync":"\nanyByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n","anyByAsync.factory":"\nanyByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n","anyByRight":"\nanyByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n","anyByRightAsync":"\nanyByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n","aones":"\naones( length:integer[, dtype:string] )\n Returns an array filled with ones and having a specified length.\n","aonesLike":"\naonesLike( x:TypedArray|Array[, dtype:string] )\n Returns an array filled with ones and having the same length and data type\n as a provided input array.\n","aoneTo":"\naoneTo( n:integer[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n","aoneToLike":"\naoneToLike( x:TypedArray|Array[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one and having the same length and data type as a provided\n input array.\n","APERY":"\nAPERY\n Apéry's constant.\n","append":"\nappend( collection1:Array|TypedArray|Object, \n collection2:Array|TypedArray|Object )\n Adds the elements of one collection to the end of another collection.\n","ARCH":"\nARCH\n Operating system CPU architecture for which the JavaScript runtime binary\n was compiled.\n","argumentFunction":"\nargumentFunction( idx:integer )\n Returns a function which always returns a specified argument.\n","ARGV":"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n","array":"\narray( [buffer:Array|TypedArray|Buffer|ndarray,] [options:Object] )\n Returns a multidimensional array.\n","array2buffer":"\narray2buffer( arr:Array )\n Allocates a buffer using an octet array.\n","array2fancy":"\narray2fancy( x:Array|TypedArray|Object[, options:Object] )\n Converts an array to an object supporting fancy indexing.\n","array2fancy.factory":"\narray2fancy.factory( [options:Object] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n","array2fancy.idx":"\narray2fancy.idx( x:Array|TypedArray|Object[, options:Object] )\n Wraps a provided array as an array index object.\n","array2iterator":"\narray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n","array2iteratorRight":"\narray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n","ArrayBuffer":"\nArrayBuffer( size:integer )\n Returns an array buffer having a specified number of bytes.\n","ArrayBuffer.length":"\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n","ArrayBuffer.isView":"\nArrayBuffer.isView( arr:any )\n Returns a boolean indicating if provided an array buffer view.\n","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n Copies the bytes of an array buffer to a new array buffer.\n","arraybuffer2buffer":"\narraybuffer2buffer( buf:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Allocates a buffer from an ArrayBuffer.\n","arrayCtors":"\narrayCtors( dtype:string )\n Returns an array constructor.\n","arrayDataType":"\narrayDataType( array:any )\n Returns the data type of an array.\n","arrayDataTypes":"\narrayDataTypes( [kind:string] )\n Returns a list of array data types.\n","ArrayIndex":"\nArrayIndex( x:Array|TypedArray|Object[, options:Object] )\n Wraps a provided array as an array index object.\n","ArrayIndex.free":"\nArrayIndex.free( id:string )\n Frees the instance associated with a provided identifier.\n","ArrayIndex.get":"\nArrayIndex.get( id:string )\n Returns the array associated with the instance having a provided identifier.\n","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n","arrayMinDataType":"\narrayMinDataType( value:any )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast and, for floating-point data types, can be downcast.\n","arrayNextDataType":"\narrayNextDataType( [dtype:string] )\n Returns the next larger array data type of the same kind.\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1:any, dtype2:any] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n","arraySafeCasts":"\narraySafeCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n","arraySameKindCasts":"\narraySameKindCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n","arrayShape":"\narrayShape( arr:ArrayLikeObject )\n Determines array dimensions.\n","arrayStream":"\narrayStream( src:ArrayLikeObject[, options:Object] )\n Creates a readable stream from an array-like object.\n","arrayStream.factory":"\narrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects.\n","arrayStream.objectMode":"\narrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n Returns an \"objectMode\" readable stream from an array-like object.\n","arrayview2iterator":"\narrayview2iterator( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of an array-like object\n view.\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n","aslice":"\naslice( x:ArrayLikeObject[, start:integer[, end:integer]] )\n Returns a shallow copy of a portion of an array.\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n Async iterator symbol.\n","atake":"\natake( x:Array|TypedArray|Object, indices:ArrayLikeObject[, \n options:Object] )\n Takes elements from an array.\n","azeros":"\nazeros( length:integer[, dtype:string] )\n Returns a zero-filled array having a specified length.\n","azerosLike":"\nazerosLike( x:TypedArray|Array[, dtype:string] )\n Returns a zero-filled array having the same length and data type as a\n provided input array.\n","azeroTo":"\nazeroTo( n:integer[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n","azeroToLike":"\nazeroToLike( x:TypedArray|Array[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero and having the same length and data type as a provided\n input array.\n","bartlettTest":"\nbartlettTest( ...x:Array[, options:Object] )\n Computes Bartlett’s test for equal variances.\n","base.abs":"\nbase.abs( x:number )\n Computes the absolute value of a double-precision floating-point number `x`.\n","base.abs2":"\nbase.abs2( x:number )\n Computes the squared absolute value of a double-precision floating-point\n `x`.\n","base.abs2f":"\nbase.abs2f( x:number )\n Computes the squared absolute value of a single-precision floating-point\n `x`.\n","base.absdiff":"\nbase.absdiff( x:number, y:number )\n Computes the absolute difference.\n","base.absf":"\nbase.absf( x:number )\n Computes the absolute value of a single-precision floating-point number `x`.\n","base.acos":"\nbase.acos( x:number )\n Compute the arccosine of a double-precision floating-point number.\n","base.acosh":"\nbase.acosh( x:number )\n Computes the hyperbolic arccosine of a double-precision floating-point\n number.\n","base.acot":"\nbase.acot( x:number )\n Computes the inverse cotangent of a double-precision floating-point number.\n","base.acoth":"\nbase.acoth( x:number )\n Computes the inverse hyperbolic cotangent of a double-precision floating-\n point number.\n","base.acovercos":"\nbase.acovercos( x:number )\n Computes the inverse coversed cosine.\n","base.acoversin":"\nbase.acoversin( x:number )\n Computes the inverse coversed sine.\n","base.acsc":"\nbase.acsc( x:number )\n Computes the arccosecant of a number.\n","base.acsch":"\nbase.acsch( x:number )\n Computes the hyperbolic arccosecant of a number.\n","base.add":"\nbase.add( x:number, y:number )\n Computes the sum of two double-precision floating-point numbers `x` and `y`.\n","base.add3":"\nbase.add3( x:number, y:number, z:number )\n Computes the sum of three double-precision floating-point numbers.\n","base.add4":"\nbase.add4( x:number, y:number, z:number, w:number )\n Computes the sum of four double-precision floating-point numbers.\n","base.add5":"\nbase.add5( x:number, y:number, z:number, w:number, u:number )\n Computes the sum of five double-precision floating-point numbers.\n","base.addf":"\nbase.addf( x:number, y:number )\n Computes the sum of two single-precision floating-point numbers `x` and `y`.\n","base.ahavercos":"\nbase.ahavercos( x:number )\n Computes the inverse half-value versed cosine.\n","base.ahaversin":"\nbase.ahaversin( x:number )\n Computes the inverse half-value versed sine.\n","base.asec":"\nbase.asec( x:number )\n Computes the inverse (arc) secant of a number.\n","base.asech":"\nbase.asech( x:number )\n Computes the hyperbolic arcsecant of a number.\n","base.asin":"\nbase.asin( x:number )\n Computes the arcsine of a double-precision floating-point number.\n","base.asinh":"\nbase.asinh( x:number )\n Computes the hyperbolic arcsine of a double-precision floating-point number.\n","base.atan":"\nbase.atan( x:number )\n Computes the arctangent of a double-precision floating-point number.\n","base.atan2":"\nbase.atan2( y:number, x:number )\n Computes the angle in the plane (in radians) between the positive x-axis and\n the ray from (0,0) to the point (x,y).\n","base.atanh":"\nbase.atanh( x:number )\n Computes the hyperbolic arctangent of a double-precision floating-point\n number.\n","base.avercos":"\nbase.avercos( x:number )\n Computes the inverse versed cosine.\n","base.aversin":"\nbase.aversin( x:number )\n Computes the inverse versed sine.\n","base.bernoulli":"\nbase.bernoulli( n:integer )\n Computes the nth Bernoulli number.\n","base.besselj0":"\nbase.besselj0( x:number )\n Computes the Bessel function of the first kind of order zero.\n","base.besselj1":"\nbase.besselj1( x:number )\n Computes the Bessel function of the first kind of order one.\n","base.bessely0":"\nbase.bessely0( x:number )\n Computes the Bessel function of the second kind of order zero.\n","base.bessely1":"\nbase.bessely1( x:number )\n Computes the Bessel function of the second kind of order one.\n","base.beta":"\nbase.beta( x:number, y:number )\n Evaluates the beta function.\n","base.betainc":"\nbase.betainc( x:number, a:number, b:number[, regularized:boolean[, \n upper:boolean]] )\n Computes the regularized incomplete beta function.\n","base.betaincinv":"\nbase.betaincinv( p:number, a:number, b:number[, upper:boolean] )\n Computes the inverse of the lower incomplete beta function.\n","base.betaln":"\nbase.betaln( a:number, b:number )\n Evaluates the natural logarithm of the beta function.\n","base.binet":"\nbase.binet( x:number )\n Evaluates Binet's formula extended to real numbers.\n","base.binomcoef":"\nbase.binomcoef( n:integer, k:integer )\n Computes the binomial coefficient of two integers.\n","base.binomcoefln":"\nbase.binomcoefln( n:integer, k:integer )\n Computes the natural logarithm of the binomial coefficient of two integers.\n","base.boxcox":"\nbase.boxcox( x:number, lambda:number )\n Computes a one-parameter Box-Cox transformation.\n","base.boxcox1p":"\nbase.boxcox1p( x:number, lambda:number )\n Computes a one-parameter Box-Cox transformation of 1+x.\n","base.boxcox1pinv":"\nbase.boxcox1pinv( y:number, lambda:number )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n","base.boxcoxinv":"\nbase.boxcoxinv( y:number, lambda:number )\n Computes the inverse of a one-parameter Box-Cox transformation.\n","base.cabs":"\nbase.cabs( z:Complex128 )\n Computes the absolute value of a double-precision complex floating-point\n number.\n","base.cabs2":"\nbase.cabs2( z:Complex128 )\n Computes the squared absolute value of a double-precision complex floating-\n point number.\n","base.cabs2f":"\nbase.cabs2f( z:Complex64 )\n Computes the squared absolute value of a single-precision complex floating-\n point number.\n","base.cabsf":"\nbase.cabsf( z:Complex64 )\n Computes the absolute value of a single-precision complex floating-point\n number.\n","base.cadd":"\nbase.cadd( z1:Complex128, z2:Complex128 )\n Adds two double-precision complex floating-point numbers.\n","base.caddf":"\nbase.caddf( z1:Complex64, z2:Complex64 )\n Adds two single-precision complex floating-point numbers.\n","base.cbrt":"\nbase.cbrt( x:number )\n Computes the cube root of a double-precision floating-point number.\n","base.cbrtf":"\nbase.cbrtf( x:number )\n Computes the cube root of a single-precision floating-point number.\n","base.cceil":"\nbase.cceil( z:Complex128 )\n Rounds a double-precision complex floating-point number toward positive\n infinity.\n","base.cceilf":"\nbase.cceilf( z:Complex64 )\n Rounds a single-precision complex floating-point number toward positive\n infinity.\n","base.cceiln":"\nbase.cceiln( z:Complex128, n:integer )\n Rounds each component of a double-precision complex number to the nearest\n multiple of `10^n` toward positive infinity.\n","base.ccis":"\nbase.ccis( z:Complex128 )\n Evaluates the cis function for a double-precision complex floating-point\n number.\n","base.cdiv":"\nbase.cdiv( z1:Complex128, z2:Complex128 )\n Divides two double-precision complex floating-point numbers.\n","base.ceil":"\nbase.ceil( x:number )\n Rounds a double-precision floating-point number toward positive infinity.\n","base.ceil2":"\nbase.ceil2( x:number )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n","base.ceil10":"\nbase.ceil10( x:number )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n","base.ceilb":"\nbase.ceilb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n","base.ceilf":"\nbase.ceilf( x:number )\n Rounds a single-precision floating-point number toward positive infinity.\n","base.ceiln":"\nbase.ceiln( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n","base.ceilsd":"\nbase.ceilsd( x:number, n:integer[, b:integer] )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n","base.cexp":"\nbase.cexp( z:Complex128 )\n Evaluates the exponential function for a double-precision complex floating-\n point number.\n","base.cflipsign":"\nbase.cflipsign( z:Complex128, y:number )\n Returns a double-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n","base.cflipsignf":"\nbase.cflipsignf( z:Complex64, y:number )\n Returns a single-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n","base.cfloor":"\nbase.cfloor( z:Complex128 )\n Rounds a double-precision complex floating-point number toward negative\n infinity.\n","base.cfloorn":"\nbase.cfloorn( z:Complex128, n:integer )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n` toward negative infinity.\n","base.cidentity":"\nbase.cidentity( z:Complex128 )\n Evaluates the identity function for a double-precision complex floating-\n point number.\n","base.cidentityf":"\nbase.cidentityf( z:Complex64 )\n Evaluates the identity function for a single-precision complex floating-\n point number.\n","base.cinv":"\nbase.cinv( z:Complex128 )\n Computes the inverse of a double-precision complex floating-point number.\n","base.clamp":"\nbase.clamp( v:number, min:number, max:number )\n Restricts a double-precision floating-point number to a specified range.\n","base.clampf":"\nbase.clampf( v:number, min:number, max:number )\n Restricts a single-precision floating-point number to a specified range.\n","base.cmul":"\nbase.cmul( z1:Complex128, z2:Complex128 )\n Multiplies two double-precision complex floating-point numbers.\n","base.cmulf":"\nbase.cmulf( z1:Complex64, z2:Complex64 )\n Multiplies two single-precision complex floating-point numbers.\n","base.cneg":"\nbase.cneg( z )\n Negates a double-precision complex floating-point number.\n","base.cnegf":"\nbase.cnegf( z )\n Negates a single-precision complex floating-point number.\n","base.continuedFraction":"\nbase.continuedFraction( generator:Function[, options:Object] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n","base.copysign":"\nbase.copysign( x:number, y:number )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n","base.copysignf":"\nbase.copysignf( x:number, y:number )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n","base.cos":"\nbase.cos( x:number )\n Computes the cosine of a number.\n","base.cosh":"\nbase.cosh( x:number )\n Computes the hyperbolic cosine of a double-precision floating-point number.\n","base.cosm1":"\nbase.cosm1( x:number )\n Computes the cosine of a number minus one.\n","base.cospi":"\nbase.cospi( x:number )\n Computes the value of `cos(πx)`.\n","base.cot":"\nbase.cot( x:number )\n Computes the cotangent of a number.\n","base.coth":"\nbase.coth( x:number )\n Computes the hyperbolic cotangent of a number.\n","base.covercos":"\nbase.covercos( x:number )\n Computes the coversed cosine.\n","base.coversin":"\nbase.coversin( x:number )\n Computes the coversed sine.\n","base.cphase":"\nbase.cphase( z:Complex128 )\n Computes the argument of a double-precision complex floating-point number\n in radians.\n","base.cpolar":"\nbase.cpolar( z:Complex128 )\n Returns the absolute value and phase of a double-precision complex\n floating-point number.\n","base.cpolar.assign":"\nbase.cpolar.assign( z:Complex128, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n","base.cround":"\nbase.cround( z:Complex128 )\n Rounds each component of a double-precision complex floating-point number\n to the nearest integer.\n","base.croundn":"\nbase.croundn( z:Complex128, n:integer )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n`.\n","base.csch":"\nbase.csch( x:number )\n Computes the hyperbolic cosecant of a number.\n","base.csignum":"\nbase.csignum( z:Complex128 )\n Evaluates the signum function of a double-precision complex floating-point\n number.\n","base.csub":"\nbase.csub( z1:Complex128, z2:Complex128 )\n Subtracts two double-precision complex floating-point numbers.\n","base.csubf":"\nbase.csubf( z1:Complex64, z2:Complex64 )\n Subtracts two single-precision complex floating-point numbers.\n","base.deg2rad":"\nbase.deg2rad( x:number )\n Converts an angle from degrees to radians.\n","base.deg2radf":"\nbase.deg2radf( x:number )\n Converts an angle from degrees to radians (single-precision).\n","base.digamma":"\nbase.digamma( x:number )\n Evaluates the digamma function.\n","base.diracDelta":"\nbase.diracDelta( x:number )\n Evaluates the Dirac delta function.\n","base.div":"\nbase.div( x:number, y:number )\n Divides two double-precision floating-point numbers `x` and `y`.\n","base.divf":"\nbase.divf( x:number, y:number )\n Divides two single-precision floating-point numbers `x` and `y`.\n","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a:number, b:number] )\n Returns an arcsine distribution object.\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a:number, b:number )\n Returns the differential entropy of an arcsine distribution (in nats).\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a:number, b:number )\n Returns the excess kurtosis of an arcsine distribution.\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x:number, a:number, b:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x:number, a:number, b:number )\n Evaluates the logarithm of the probability density function (PDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a:number, b:number )\n Returns the expected value of an arcsine distribution.\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a:number, b:number )\n Returns the median of an arcsine distribution.\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a:number, b:number )\n Returns the mode of an arcsine distribution.\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a:number, b:number )\n Returns the skewness of an arcsine distribution.\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a:number, b:number )\n Returns the standard deviation of an arcsine distribution.\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a:number, b:number )\n Returns the variance of an arcsine distribution.\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p:number] )\n Returns a Bernoulli distribution object.\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p` at a value `x`.\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p:number )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p:number )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p:number )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p:number )\n Returns the median of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t:number, p:number )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p:number )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x:number, p:number )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r:number, p:number )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p:number )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p:number )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p:number )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p:number )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α:number, β:number] )\n Returns a beta distribution object.\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α:number, β:number )\n Returns the differential entropy of a beta distribution.\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a beta distribution.\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n","base.dists.beta.mean":"\nbase.dists.beta.mean( α:number, β:number )\n Returns the expected value of a beta distribution.\n","base.dists.beta.median":"\nbase.dists.beta.median( α:number, β:number )\n Returns the median of a beta distribution.\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t:number, α:number, β:number )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n","base.dists.beta.mode":"\nbase.dists.beta.mode( α:number, β:number )\n Returns the mode of a beta distribution.\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α:number, β:number )\n Returns the skewness of a beta distribution.\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α:number, β:number )\n Returns the standard deviation of a beta distribution.\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α:number, β:number )\n Returns the variance of a beta distribution.\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α:number, β:number] )\n Returns a beta prime distribution object.\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a beta prime distribution.\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α:number, β:number )\n Returns the expected value of a beta prime distribution.\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α:number, β:number )\n Returns the mode of a beta prime distribution.\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α:number, β:number )\n Returns the skewness of a beta prime distribution.\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α:number, β:number )\n Returns the standard deviation of a beta prime distribution.\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α:number, β:number )\n Returns the variance of a beta prime distribution.\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n:integer, p:number] )\n Returns a binomial distribution object.\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x:number, n:integer, p:number )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n:integer, p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n:integer, p:number )\n Returns the entropy of a binomial distribution.\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n:integer, p:number )\n Returns the excess kurtosis of a binomial distribution.\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x:number, n:integer, p:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n:integer, p:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n:integer, p:number )\n Returns the expected value of a binomial distribution.\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n:integer, p:number )\n Returns the median of a binomial distribution.\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t:number, n:integer, p:number )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n:integer, p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n:integer, p:number )\n Returns the mode of a binomial distribution.\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x:number, n:integer, p:number )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n:integer, p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r:number, n:integer, p:number )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n:integer, p:number )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n:integer, p:number )\n Returns the skewness of a binomial distribution.\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n:integer, p:number )\n Returns the standard deviation of a binomial distribution.\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n:integer, p:number )\n Returns the variance of a binomial distribution.\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0:number, Ɣ:number] )\n Returns a Cauchy distribution object.\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x:number, x0:number, Ɣ:number )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0:number, Ɣ:number )\n Returns the differential entropy of a Cauchy distribution (in nats).\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x:number, x0:number, Ɣ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x:number, x0:number, Ɣ:number )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0:number, Ɣ:number )\n Returns the median of a Cauchy distribution.\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0:number, Ɣ:number )\n Returns the mode of a Cauchy distribution.\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x:number, x0:number, Ɣ:number )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p:number, x0:number, Ɣ:number )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x:number, k:number )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k:number] )\n Returns a chi distribution object.\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k:number )\n Returns the differential entropy of a chi distribution (in nats).\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k:number )\n Returns the excess kurtosis of a chi distribution.\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x:number, k:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.mean":"\nbase.dists.chi.mean( k:number )\n Returns the expected value of a chi distribution.\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k:number )\n Returns the mode of a chi distribution.\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x:number, k:number )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k:number )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p:number, k:number )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k:number )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k:number )\n Returns the skewness of a chi distribution.\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k:number )\n Returns the standard deviation of a chi distribution.\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k:number )\n Returns the variance of a chi distribution.\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x:number, k:number )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k:number] )\n Returns a chi-squared distribution object.\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k:number )\n Returns the differential entropy of a chi-squared distribution (in nats).\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k:number )\n Returns the excess kurtosis of a chi-squared distribution.\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x:number, k:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k:number )\n Returns the expected value of a chi-squared distribution.\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k:number )\n Returns the median of a chi-squared distribution.\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t:number, k:number )\n Evaluates the moment-generating function (MGF) for a chi-squared\n distribution with degrees of freedom `k` at a value `t`.\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k:number )\n Returns the mode of a chi-squared distribution.\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x:number, k:number )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k:number )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p:number, k:number )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k:number )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k:number )\n Returns the skewness of a chi-squared distribution.\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k:number )\n Returns the standard deviation of a chi-squared distribution.\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k:number )\n Returns the variance of a chi-squared distribution.\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x:number, μ:number, s:number )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ:number, s:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ:number, s:number] )\n Returns a raised cosine distribution object.\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ:number, s:number )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x:number, μ:number, s:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ:number, s:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ:number, s:number )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ:number, s:number )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t:number, μ:number, s:number )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ:number, s:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ:number, s:number )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x:number, μ:number, s:number )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ:number, s:number )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p:number, μ:number, s:number )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ:number, s:number )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ:number, s:number )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ:number, s:number )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ:number, s:number )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x:number, μ:number )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ:number] )\n Returns a degenerate distribution object.\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ:number )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x:number, μ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x:number, μ:number )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x:number, μ:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ:number )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ:number )\n Returns the median of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x:number, μ:number )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ:number )\n Returns the mode of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x:number, μ:number )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x:number, μ:number )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p:number, μ:number )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ:number )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ:number )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ:number )\n Returns the variance of a degenerate distribution with constant value `μ`.\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x:number, a:integer, b:integer )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a:integer, b:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a:integer, b:integer] )\n Returns a discrete uniform distribution object.\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a:integer, b:integer )\n Returns the excess kurtosis of a discrete uniform distribution.\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x:number, a:integer, b:integer )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a:integer, b:integer )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x:number, a:integer, b:integer )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a:integer, b:integer )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a:integer, b:integer )\n Returns the expected value of a discrete uniform distribution.\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a:integer, b:integer )\n Returns the median of a discrete uniform distribution.\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t:number, a:integer, b:integer )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a:integer, b:integer )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x:number, a:integer, b:integer )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a:integer, b:integer )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p:number, a:integer, b:integer )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a:integer, b:integer )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a:integer, b:integer )\n Returns the skewness of a discrete uniform distribution.\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a:integer, b:integer )\n Returns the standard deviation of a discrete uniform distribution.\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a:integer, b:integer )\n Returns the variance of a discrete uniform distribution.\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x:number, k:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k:number, λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k:integer, λ:number )\n Returns the differential entropy of an Erlang distribution (in nats).\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k:number, λ:number] )\n Returns an Erlang distribution object.\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k:integer, λ:number )\n Returns the excess kurtosis of an Erlang distribution.\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x:number, k:number, λ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k:number, λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k:integer, λ:number )\n Returns the expected value of an Erlang distribution.\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t:number, k:number, λ:number )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k:number, λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k:integer, λ:number )\n Returns the mode of an Erlang distribution.\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x:number, k:number, λ:number )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k:number, λ:number )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p:number, k:number, λ:number )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k:number, λ:number )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k:integer, λ:number )\n Returns the skewness of an Erlang distribution.\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k:integer, λ:number )\n Returns the standard deviation of an Erlang distribution.\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k:integer, λ:number )\n Returns the variance of an Erlang distribution.\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ:number )\n Returns the differential entropy of an exponential distribution.\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ:number] )\n Returns an exponential distribution object.\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ:number )\n Returns the excess kurtosis of an exponential distribution.\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x:number, λ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x:number, λ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ:number )\n Returns the expected value of an exponential distribution.\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ:number )\n Returns the median of an exponential distribution.\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t:number, λ:number )\n Evaluates the moment-generating function (MGF) for an exponential\n distribution with rate parameter `λ` at a value `t`.\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ:number )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ:number )\n Returns the mode of an exponential distribution.\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x:number, λ:number )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ:number )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p:number, λ:number )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ:number )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ:number )\n Returns the skewness of an exponential distribution.\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ:number )\n Returns the standard deviation of an exponential distribution.\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ:number )\n Returns the variance of an exponential distribution.\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x:number, d1:number, d2:number )\n Evaluates the cumulative distribution function (CDF) for an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1:number, d2:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n","base.dists.f.entropy":"\nbase.dists.f.entropy( d1:number, d2:number )\n Returns the differential entropy of an F distribution (in nats).\n","base.dists.f.F":"\nbase.dists.f.F( [d1:number, d2:number] )\n Returns an F distribution object.\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1:number, d2:number )\n Returns the excess kurtosis of an F distribution.\n","base.dists.f.mean":"\nbase.dists.f.mean( d1:number, d2:number )\n Returns the expected value of an F distribution.\n","base.dists.f.mode":"\nbase.dists.f.mode( d1:number, d2:number )\n Returns the mode of an F distribution.\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x:number, d1:number, d2:number )\n Evaluates the probability density function (PDF) for an F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1:number, d2:number )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n","base.dists.f.quantile":"\nbase.dists.f.quantile( p:number, d1:number, d2:number )\n Evaluates the quantile function for an F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1:number, d2:number )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n","base.dists.f.skewness":"\nbase.dists.f.skewness( d1:number, d2:number )\n Returns the skewness of an F distribution.\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1:number, d2:number )\n Returns the standard deviation of an F distribution.\n","base.dists.f.variance":"\nbase.dists.f.variance( d1:number, d2:number )\n Returns the variance of an F distribution.\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x:number, α:number, s:number, m:number )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α:number, s:number, m:number )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α:number, s:number, m:number] )\n Returns a Fréchet distribution object.\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α:number, s:number, m:number )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x:number, α:number, s:number, m:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x:number, α:number, s:number, m:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α:number, s:number, m:number )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α:number, s:number, m:number )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α:number, s:number, m:number )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x:number, α:number, s:number, m:number )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p:number, α:number, s:number, m:number )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α:number, s:number, m:number )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α:number, s:number, m:number )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α:number, s:number, m:number )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α:number, s:number, m:number )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α:number, β:number )\n Returns the differential entropy of a gamma distribution.\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α:number, β:number] )\n Returns a gamma distribution object.\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a gamma distribution.\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x:number, α:number, β:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x:number, α:number, β:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α:number, β:number )\n Returns the expected value of a gamma distribution.\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t:number, α:number, β:number )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α:number, β:number )\n Returns the mode of a gamma distribution.\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α:number, β:number )\n Returns the skewness of a gamma distribution.\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α:number, β:number )\n Returns the standard deviation of a gamma distribution.\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α:number, β:number )\n Returns the variance of a gamma distribution.\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p:number )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p:number] )\n Returns a geometric distribution object.\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p:number )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x:number, p:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x:number, p:number )\n Evaluates the logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p:number )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p:number )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p:number )\n Returns the median of a geometric distribution with success probability `p`.\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t:number, p:number )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p:number )\n Returns the mode of a geometric distribution with success probability `p`.\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x:number, p:number )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r:number, p:number )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p:number )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p:number )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p:number )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p:number )\n Returns the variance of a geometric distribution with success probability\n `p`.\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x:number, μ:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ:number, β:number )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ:number, β:number] )\n Returns a Gumbel distribution object.\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ:number, β:number )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x:number, μ:number, β:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ:number, β:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x:number, μ:number, β:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ:number, β:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ:number, β:number )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ:number, β:number )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t:number, μ:number, β:number )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ:number, β:number )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x:number, μ:number, β:number )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ:number, β:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p:number, μ:number, β:number )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ:number, β:number )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ:number, β:number )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ:number, β:number )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ:number, β:number )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x:number, N:integer, K:integer, n:integer )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N:integer, K:integer, n:integer] )\n Returns a hypergeometric distribution object.\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N:integer, K:integer, n:integer )\n Returns the excess kurtosis of a hypergeometric distribution.\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x:number, N:integer, K:integer, n:integer )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N:integer, K:integer, n:integer )\n Returns the expected value of a hypergeometric distribution.\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N:integer, K:integer, n:integer )\n Returns the mode of a hypergeometric distribution.\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x:number, N:integer, K:integer, n:integer )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p:number, N:integer, K:integer, n:integer )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N:integer, K:integer, n:integer )\n Returns the skewness of a hypergeometric distribution.\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N:integer, K:integer, n:integer )\n Returns the standard deviation of a hypergeometric distribution.\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N:integer, K:integer, n:integer )\n Returns the variance of a hypergeometric distribution.\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α:number, β:number )\n Returns the differential entropy of an inverse gamma distribution.\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α:number, β:number] )\n Returns an inverse gamma distribution object.\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α:number, β:number )\n Returns the excess kurtosis of an inverse gamma distribution.\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α:number, β:number )\n Returns the expected value of an inverse gamma distribution.\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α:number, β:number )\n Returns the mode of an inverse gamma distribution.\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α:number, β:number )\n Returns the skewness of an inverse gamma distribution.\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α:number, β:number )\n Returns the standard deviation of an inverse gamma distribution.\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α:number, β:number )\n Returns the variance of an inverse gamma distribution.\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a:number, b:number] )\n Returns a Kumaraswamy's double bounded distribution object.\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a:number, b:number )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a:number, b:number )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a:number, b:number )\n Returns the median of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a:number, b:number )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a:number, b:number )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a:number, b:number )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a:number, b:number )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x:number, μ:number, b:number )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ:number, b:number )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ:number, b:number )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ:number, b:number] )\n Returns a Laplace distribution object.\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x:number, μ:number, b:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x:number, μ:number, b:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ:number, b:number )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ:number, b:number )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t:number, μ:number, b:number )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ:number, b:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ:number, b:number )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x:number, μ:number, b:number )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ:number, b:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p:number, μ:number, b:number )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ:number, b:number )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ:number, b:number )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ:number, b:number )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ:number, b:number )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x:number, μ:number, c:number )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ:number, c:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ:number, c:number )\n Returns the entropy of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ:number, c:number] )\n Returns a Lévy distribution object.\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x:number, μ:number, c:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Lévy distribution with location parameter `μ` and scale parameter `c` at a\n value `x`.\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ:number, c:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x:number, μ:number, c:number )\n Evaluates the logarithm of the probability density function (PDF) for a Lévy\n distribution with location parameter `μ` and scale parameter `c` at a value\n `x`.\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ:number, c:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n","base.dists.levy.mean":"\nbase.dists.levy.mean( μ:number, c:number )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n","base.dists.levy.median":"\nbase.dists.levy.median( μ:number, c:number )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ:number, c:number )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x:number, μ:number, c:number )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ:number, c:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p:number, μ:number, c:number )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ:number, c:number )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ:number, c:number )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ:number, c:number )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x:number, μ:number, s:number )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ:number, s:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ:number, s:number )\n Returns the entropy of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ:number, s:number )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ:number, s:number] )\n Returns a logistic distribution object.\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ:number, s:number )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ:number, s:number )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t:number, μ:number, s:number )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ:number, s:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ:number, s:number )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x:number, μ:number, s:number )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ:number, s:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p:number, μ:number, s:number )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ:number, s:number )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ:number, s:number )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ:number, s:number )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ:number, s:number )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x:number, μ:number, σ:number )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ:number, σ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ:number, σ:number )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ:number, σ:number )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ:number, σ:number] )\n Returns a lognormal distribution object.\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a lognormal distribution with mean `μ` and standard deviation `σ`\n at a value `x`.\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ:number, σ:number )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ:number, σ:number )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ:number, σ:number )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x:number, μ:number, σ:number )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ:number, σ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p:number, μ:number, σ:number )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ:number, σ:number )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ:number, σ:number )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ:number, σ:number )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ:number, σ:number )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x:number, r:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r:number, p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r:integer, p:number )\n Returns the excess kurtosis of a negative binomial distribution.\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x:number, r:number, p:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r:number, p:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r:integer, p:number )\n Returns the expected value of a negative binomial distribution.\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x:number, r:number, p:number )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r:number, p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r:integer, p:number )\n Returns the mode of a negative binomial distribution.\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r:number, p:number] )\n Returns a negative binomial distribution object.\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x:number, r:number, p:number )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r:number, p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k:number, r:number, p:number )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r:number, p:number )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r:integer, p:number )\n Returns the skewness of a negative binomial distribution.\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r:integer, p:number )\n Returns the standard deviation of a negative binomial distribution.\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r:integer, p:number )\n Returns the variance of a negative binomial distribution.\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x:number, μ:number, σ:number )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ:number, σ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ:number, σ:number )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ:number, σ:number )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n a value `x`.\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.mean":"\nbase.dists.normal.mean( μ:number, σ:number )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.median":"\nbase.dists.normal.median( μ:number, σ:number )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x:number, μ:number, σ:number )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ:number, σ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.mode":"\nbase.dists.normal.mode( μ:number, σ:number )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ:number, σ:number] )\n Returns a normal distribution object.\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x:number, μ:number, σ:number )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ:number, σ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p:number, μ:number, σ:number )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ:number, σ:number )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ:number, σ:number )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ:number, σ:number )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ:number, σ:number )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α:number, β:number )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α:number, β:number )\n Returns the expected value of a Pareto (Type I) distribution.\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α:number, β:number )\n Returns the median of a Pareto (Type I) distribution.\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α:number, β:number )\n Returns the mode of a Pareto (Type I) distribution.\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α:number, β:number] )\n Returns a Pareto (Type I) distribution object.\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α:number, β:number )\n Returns the skewness of a Pareto (Type I) distribution.\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α:number, β:number )\n Returns the standard deviation of a Pareto (Type I) distribution.\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α:number, β:number )\n Returns the variance of a Pareto (Type I) distribution.\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ:number )\n Returns the entropy of a Poisson distribution.\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ:number )\n Returns the excess kurtosis of a Poisson distribution.\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x:number, λ:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ:number )\n Returns the expected value of a Poisson distribution.\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ:number )\n Returns the median of a Poisson distribution.\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x:number, λ:number )\n Evaluates the moment-generating function (MGF) for a Poisson distribution\n with mean parameter `λ` at a value `x`.\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ:number )\n Returns the mode of a Poisson distribution.\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x:number, λ:number )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ:number )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ:number] )\n Returns a Poisson distribution object.\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p:number, λ:number )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ:number )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ:number )\n Returns the skewness of a Poisson distribution.\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ:number )\n Returns the standard deviation of a Poisson distribution.\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ:number )\n Returns the variance of a Poisson distribution.\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x:number, sigma:number )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ:number )\n Returns the differential entropy of a Rayleigh distribution.\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ:number )\n Returns the excess kurtosis of a Rayleigh distribution.\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x:number, sigma:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x:number, sigma:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ:number )\n Returns the expected value of a Rayleigh distribution.\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ:number )\n Returns the median of a Rayleigh distribution.\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t:number, sigma:number )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ:number )\n Returns the mode of a Rayleigh distribution.\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x:number, sigma:number )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p:number, sigma:number )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma:number )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ:number] )\n Returns a Rayleigh distribution object.\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ:number )\n Returns the skewness of a Rayleigh distribution.\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ:number )\n Returns the standard deviation of a Rayleigh distribution.\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ:number )\n Returns the variance of a Rayleigh distribution.\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x:number, n:integer )\n Evaluates the cumulative distribution function (CDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x:number, n:integer )\n Evaluates the probability density function (PDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n:integer )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p:number, n:integer )\n Evaluates the quantile function for the Wilcoxon signed rank test statistic\n with `n` observations at a probability `p`.\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n:integer )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n","base.dists.t.cdf":"\nbase.dists.t.cdf( x:number, v:number )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.entropy":"\nbase.dists.t.entropy( v:number )\n Returns the differential entropy of a Student's t distribution.\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v:number )\n Returns the excess kurtosis of a Student's t distribution.\n","base.dists.t.mean":"\nbase.dists.t.mean( v:number )\n Returns the expected value of a Student's t distribution.\n","base.dists.t.median":"\nbase.dists.t.median( v:number )\n Returns the median of a Student's t distribution.\n","base.dists.t.mode":"\nbase.dists.t.mode( v:number )\n Returns the mode of a Student's t distribution.\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x:number, v:number )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.quantile":"\nbase.dists.t.quantile( p:number, v:number )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v:number )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n","base.dists.t.skewness":"\nbase.dists.t.skewness( v:number )\n Returns the skewness of a Student's t distribution.\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v:number )\n Returns the standard deviation of a Student's t distribution.\n","base.dists.t.T":"\nbase.dists.t.T( [v:number] )\n Returns a Student's t distribution object.\n","base.dists.t.variance":"\nbase.dists.t.variance( v:number )\n Returns the variance of a Student's t distribution.\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x:number, a:number, b:number, c:number )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a:number, b:number, c:number )\n Returns the differential entropy of a triangular distribution (in nats).\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a:number, b:number, c:number )\n Returns the excess kurtosis of a triangular distribution.\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x:number, a:number, b:number, c:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x:number, a:number, b:number, c:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a:number, b:number, c:number )\n Returns the expected value of a triangular distribution.\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a:number, b:number, c:number )\n Returns the median of a triangular distribution.\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t:number, a:number, b:number, c:number )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a:number, b:number, c:number )\n Returns the mode of a triangular distribution.\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x:number, a:number, b:number, c:number )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p:number, a:number, b:number, c:number )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a:number, b:number, c:number )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a:number, b:number, c:number )\n Returns the skewness of a triangular distribution.\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a:number, b:number, c:number )\n Returns the standard deviation of a triangular distribution.\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a:number, b:number, c:number] )\n Returns a triangular distribution object.\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a:number, b:number, c:number )\n Returns the variance of a triangular distribution.\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a:number, b:number )\n Returns the differential entropy of a uniform distribution.\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a:number, b:number )\n Returns the excess kurtosis of a uniform distribution.\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x:number, a:number, b:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x:number, a:number, b:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a:number, b:number )\n Returns the expected value of a uniform distribution.\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a:number, b:number )\n Returns the median of a uniform distribution.\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t:number, a:number, b:number )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a:number, b:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a:number, b:number )\n Returns the skewness of a uniform distribution.\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a:number, b:number )\n Returns the standard deviation of a uniform distribution.\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a:number, b:number] )\n Returns a uniform distribution object.\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a:number, b:number )\n Returns the variance of a uniform distribution.\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x:number, k:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k:number, λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k:number, λ:number )\n Returns the differential entropy of a Weibull distribution (in nats).\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k:number, λ:number )\n Returns the excess kurtosis of a Weibull distribution.\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x:number, k:number, λ:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k:number, λ:number)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x:number, k:number, λ:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k:number, λ:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k:number, λ:number )\n Returns the expected value of a Weibull distribution.\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k:number, λ:number )\n Returns the median of a Weibull distribution.\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x:number, k:number, λ:number )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k:number, λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k:number, λ:number )\n Returns the mode of a Weibull distribution.\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x:number, k:number, λ:number )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k:number, λ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p:number, k:number, λ:number )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k:number, λ:number )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k:number, λ:number )\n Returns the skewness of a Weibull distribution.\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k:number, λ:number )\n Returns the standard deviation of a Weibull distribution.\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k:number, λ:number )\n Returns the variance of a Weibull distribution.\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k:number, λ:number] )\n Returns a Weibull distribution object.\n","base.ellipe":"\nbase.ellipe( m:number )\n Computes the complete elliptic integral of the second kind.\n","base.ellipj":"\nbase.ellipj( u:number, m:number )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am.\n","base.ellipj.assign":"\nbase.ellipj.assign( u:number, m:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n","base.ellipj.sn":"\nbase.ellipj.sn( u:number, m:number )\n Computes the Jacobi elliptic function sn.\n","base.ellipj.cn":"\nbase.ellipj.cn( u:number, m:number )\n Computes the Jacobi elliptic functions cn.\n","base.ellipj.dn":"\nbase.ellipj.dn( u:number, m:number )\n Computes the Jacobi elliptic function dn.\n","base.ellipj.am":"\nbase.ellipj.am( u:number, m:number )\n Computes the Jacobi amplitude am.\n","base.ellipk":"\nbase.ellipk( m:number )\n Computes the complete elliptic integral of the first kind.\n","base.epsdiff":"\nbase.epsdiff( x:number, y:number[, scale:string|Function] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n","base.erf":"\nbase.erf( x:number )\n Evaluates the error function.\n","base.erfc":"\nbase.erfc( x:number )\n Evaluates the complementary error function.\n","base.erfcinv":"\nbase.erfcinv( x:number )\n Evaluates the inverse complementary error function.\n","base.erfcx":"\nbase.erfcx( x:number )\n Evaluates the scaled complementary error function.\n","base.erfinv":"\nbase.erfinv( x:number )\n Evaluates the inverse error function.\n","base.eta":"\nbase.eta( s:number )\n Evaluates the Dirichlet eta function as a function of a real variable `s`.\n","base.evalpoly":"\nbase.evalpoly( c:Array, x:number )\n Evaluates a polynomial.\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c:Array )\n Returns a function for evaluating a polynomial.\n","base.evalrational":"\nbase.evalrational( P:Array, Q:Array, x:number )\n Evaluates a rational function.\n","base.evalrational.factory":"\nbase.evalrational.factory( P:Array, Q:Array )\n Returns a function for evaluating a rational function.\n","base.exp":"\nbase.exp( x:number )\n Evaluates the natural exponential function.\n","base.exp2":"\nbase.exp2( x:number )\n Evaluates the base 2 exponential function.\n","base.exp10":"\nbase.exp10( x:number )\n Evaluates the base 10 exponential function.\n","base.expit":"\nbase.expit( x:number )\n Evaluates the standard logistic function.\n","base.expm1":"\nbase.expm1( x:number )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n","base.expm1rel":"\nbase.expm1rel( x:number )\n Relative error exponential.\n","base.exponent":"\nbase.exponent( x:number )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n","base.exponentf":"\nbase.exponentf( x:float )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n","base.factorial":"\nbase.factorial( x:number )\n Evaluates the factorial of `x`.\n","base.factorial2":"\nbase.factorial2( n:number )\n Evaluates the double factorial of `n`.\n","base.factorialln":"\nbase.factorialln( x:number )\n Evaluates the natural logarithm of the factorial of `x`.\n","base.fallingFactorial":"\nbase.fallingFactorial( x:number, n:integer )\n Computes the falling factorial of `x` and `n`.\n","base.fibonacci":"\nbase.fibonacci( n:integer )\n Computes the nth Fibonacci number.\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F:integer )\n Computes the Fibonacci number index.\n","base.fibpoly":"\nbase.fibpoly( n:integer, x:number )\n Evaluates a Fibonacci polynomial.\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n:integer )\n Returns a function for evaluating a Fibonacci polynomial.\n","base.firstCodePoint":"\nbase.firstCodePoint( str:string, n:integer )\n Returns the first `n` Unicode code points of a string.\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str:string, n:integer )\n Returns the first `n` UTF-16 code units of a string.\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str:string, n:integer )\n Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n","base.flipsign":"\nbase.flipsign( x:number, y:number )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n","base.flipsignf":"\nbase.flipsignf( x:number, y:number )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n","base.float32ToInt32":"\nbase.float32ToInt32( x:float )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n","base.float32ToUint32":"\nbase.float32ToUint32( x:float )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n","base.float64ToFloat32":"\nbase.float64ToFloat32( x:number )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n","base.float64ToInt32":"\nbase.float64ToInt32( x:number )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x:integer )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness).\n","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n","base.float64ToUint32":"\nbase.float64ToUint32( x:number )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n","base.floor":"\nbase.floor( x:number )\n Rounds a double-precision floating-point number toward negative infinity.\n","base.floor2":"\nbase.floor2( x:number )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n","base.floor10":"\nbase.floor10( x:number )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n","base.floorb":"\nbase.floorb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n","base.floorf":"\nbase.floorf( x:number )\n Rounds a single-precision floating-point number toward negative infinity.\n","base.floorn":"\nbase.floorn( x:number, n:integer )\n Rounds a double-precision floating-point number to the nearest multiple of\n `10^n` toward negative infinity.\n","base.floorsd":"\nbase.floorsd( x:number, n:integer[, b:integer] )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n","base.forEachChar":"\nbase.forEachChar( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each UTF-16 code unit in a string.\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each Unicode code point in a string.\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each grapheme cluster (i.e., user-perceived\n character) in a string.\n","base.fresnel":"\nbase.fresnel( x:number )\n Computes the Fresnel integrals S(x) and C(x).\n","base.fresnel.assign":"\nbase.fresnel.assign( x:number, out:Array, stride:integer, \n offset:integer )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n","base.fresnelc":"\nbase.fresnelc( x:number )\n Computes the Fresnel integral C(x).\n","base.fresnels":"\nbase.fresnels( x:number )\n Computes the Fresnel integral S(x).\n","base.frexp":"\nbase.frexp( x:number )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n","base.frexp.assign":"\nbase.frexp.assign( x:number, out:Array, stride:integer, offset:integer )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n","base.fromBinaryString":"\nbase.fromBinaryString( bstr:string )\n Creates a double-precision floating-point number from a literal bit\n representation.\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr:string )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr:string )\n Creates an unsigned 8-bit integer from a literal bit representation.\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr:string )\n Creates an unsigned 16-bit integer from a literal bit representation.\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr:string )\n Creates an unsigned 32-bit integer from a literal bit representation.\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Converts a signed 64-bit integer byte array to a double-precision floating-\n point number.\n","base.fromWordf":"\nbase.fromWordf( word:integer )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n","base.fromWords":"\nbase.fromWords( high:integer, low:integer )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.gamma":"\nbase.gamma( x:number )\n Evaluates the gamma function.\n","base.gamma1pm1":"\nbase.gamma1pm1( x:number )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z:number, delta:number )\n Computes the ratio of two gamma functions.\n","base.gammainc":"\nbase.gammainc( x:number, s:number[, regularized:boolean[, upper:boolean]] )\n Computes the regularized incomplete gamma function.\n","base.gammaincinv":"\nbase.gammaincinv( p:number, a:number[, upper:boolean] )\n Computes the inverse of the lower incomplete gamma function.\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x:number )\n Calculates the Lanczos sum for the approximation of the gamma function.\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x:number )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n","base.gammaln":"\nbase.gammaln( x:number )\n Evaluates the natural logarithm of the gamma function.\n","base.gcd":"\nbase.gcd( a:integer, b:integer )\n Computes the greatest common divisor (gcd).\n","base.getHighWord":"\nbase.getHighWord( x:number )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n","base.getLowWord":"\nbase.getLowWord( x:number )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n","base.hacovercos":"\nbase.hacovercos( x:number )\n Computes the half-value coversed cosine.\n","base.hacoversin":"\nbase.hacoversin( x:number )\n Computes the half-value coversed sine.\n","base.havercos":"\nbase.havercos( x:number )\n Computes the half-value versed cosine.\n","base.haversin":"\nbase.haversin( x:number )\n Computes the half-value versed sine.\n","base.heaviside":"\nbase.heaviside( x:number[, continuity:string] )\n Evaluates the Heaviside function.\n","base.hermitepoly":"\nbase.hermitepoly( n:integer, x:number )\n Evaluates a physicist's Hermite polynomial.\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n:integer )\n Returns a function for evaluating a physicist's Hermite polynomial.\n","base.hypot":"\nbase.hypot( x:number, y:number )\n Computes the hypotenuse avoiding overflow and underflow.\n","base.hypotf":"\nbase.hypotf( x:number, y:number )\n Computes the hypotenuse avoiding overflow and underflow (single-precision).\n","base.identity":"\nbase.identity( x:number )\n Evaluates the identity function for a double-precision floating-point number\n `x`.\n","base.identityf":"\nbase.identityf( x:number )\n Evaluates the identity function for a single-precision floating-point number\n `x`.\n","base.imul":"\nbase.imul( a:integer, b:integer )\n Performs C-like multiplication of two signed 32-bit integers.\n","base.imuldw":"\nbase.imuldw( a:integer, b:integer )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n","base.imuldw.assign":"\nbase.imuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n","base.int32ToUint32":"\nbase.int32ToUint32( x:integer )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n","base.inv":"\nbase.inv( x:number )\n Computes the multiplicative inverse of a double-precision floating-point\n number `x`.\n","base.invf":"\nbase.invf( x:number )\n Computes the multiplicative inverse of a single-precision floating-point\n number `x`.\n","base.isComposite":"\nbase.isComposite( x:number )\n Tests if a number is composite.\n","base.isCoprime":"\nbase.isCoprime( a:number, b:number )\n Tests if two numbers are coprime.\n","base.isEven":"\nbase.isEven( x:number )\n Tests if a finite numeric value is an even number.\n","base.isEvenInt32":"\nbase.isEvenInt32( x:integer )\n Tests if a 32-bit integer is even.\n","base.isFinite":"\nbase.isFinite( x:number )\n Tests if a double-precision floating-point numeric value is finite.\n","base.isFinitef":"\nbase.isFinitef( x:number )\n Tests if a single-precision floating-point numeric value is finite.\n","base.isInfinite":"\nbase.isInfinite( x:number )\n Tests if a double-precision floating-point numeric value is infinite.\n","base.isInfinitef":"\nbase.isInfinitef( x:number )\n Tests if a single-precision floating-point numeric value is infinite.\n","base.isInteger":"\nbase.isInteger( x:number )\n Tests if a finite double-precision floating-point number is an integer.\n","base.isnan":"\nbase.isnan( x:number )\n Tests if a double-precision floating-point numeric value is `NaN`.\n","base.isnanf":"\nbase.isnanf( x:number )\n Tests if a single-precision floating-point numeric value is `NaN`.\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x:number )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n","base.isNegativeZero":"\nbase.isNegativeZero( x:number )\n Tests if a double-precision floating-point numeric value is negative zero.\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x:number )\n Tests if a single-precision floating-point numeric value is negative zero.\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x:number )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x:number )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n","base.isOdd":"\nbase.isOdd( x:number )\n Tests if a finite numeric value is an odd number.\n","base.isOddInt32":"\nbase.isOddInt32( x:integer )\n Tests if a 32-bit integer is odd.\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x:number )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n","base.isPositiveZero":"\nbase.isPositiveZero( x:number )\n Tests if a double-precision floating-point numeric value is positive zero.\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x:number )\n Tests if a single-precision floating-point numeric value is positive zero.\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x:integer )\n Tests whether an unsigned integer is a power of 2.\n","base.isPrime":"\nbase.isPrime( x:number )\n Tests if a number is prime.\n","base.isProbability":"\nbase.isProbability( x:number )\n Tests if a double-precision floating-point number value is a probability.\n","base.isSafeInteger":"\nbase.isSafeInteger( x:number )\n Tests if a finite double-precision floating-point number is a safe integer.\n","base.kernelBetainc":"\nbase.kernelBetainc( x:number, a:number, b:number, regularized:boolean, \n upper:boolean )\n Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x:number, a:number, b:number, regularized:boolean, \n upper:boolean, out:Array|TypedArray|Object, stride:integer, offset:integer )\n Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a:number, b:number, p:number, q:number )\n Computes the inverse of the lower incomplete beta function.\n","base.kernelCos":"\nbase.kernelCos( x:number, y:number )\n Computes the cosine of a double-precision floating-point number on the\n interval [-π/4, π/4].\n","base.kernelSin":"\nbase.kernelSin( x:number, y:number )\n Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n","base.kernelTan":"\nbase.kernelTan( x:number, y:number, k:integer )\n Computes the tangent of a double-precision floating-point number on the\n interval [-π/4, π/4].\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i:number, j:number )\n Evaluates the Kronecker delta.\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i:number, j:number )\n Evaluates the Kronecker delta (single-precision).\n","base.labs":"\nbase.labs( x:integer )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n","base.lcm":"\nbase.lcm( a:integer, b:integer )\n Computes the least common multiple (lcm).\n","base.ldexp":"\nbase.ldexp( frac:number, exp:number )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n","base.ln":"\nbase.ln( x:number )\n Evaluates the natural logarithm of a double-precision floating-point number.\n","base.log":"\nbase.log( x:number, b:number )\n Computes the base `b` logarithm of `x`.\n","base.log1mexp":"\nbase.log1mexp( x:number )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n","base.log1p":"\nbase.log1p( x:number )\n Evaluates the natural logarithm of `1+x`.\n","base.log1pexp":"\nbase.log1pexp( x:number )\n Evaluates the natural logarithm of `1+exp(x)`.\n","base.log1pmx":"\nbase.log1pmx( x:number )\n Evaluates `ln(1+x) - x`.\n","base.log2":"\nbase.log2( x:number )\n Evaluates the binary logarithm (base two).\n","base.log10":"\nbase.log10( x:number )\n Evaluates the common logarithm (base 10).\n","base.logaddexp":"\nbase.logaddexp( x:number, y:number )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n","base.logit":"\nbase.logit( p:number )\n Evaluates the logit function.\n","base.lucas":"\nbase.lucas( n:integer )\n Computes the nth Lucas number.\n","base.lucaspoly":"\nbase.lucaspoly( n:integer, x:number )\n Evaluates a Lucas polynomial.\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n:integer )\n Returns a function for evaluating a Lucas polynomial.\n","base.max":"\nbase.max( x:number, y:number )\n Returns the maximum value.\n","base.maxabs":"\nbase.maxabs( x:number, y:number )\n Returns the maximum absolute value.\n","base.maxn":"\nbase.maxn( [x:number[, y:number[, ...args:number]]] )\n Returns the maximum value.\n","base.min":"\nbase.min( x:number, y:number )\n Returns the minimum value.\n","base.minabs":"\nbase.minabs( x:number, y:number )\n Returns the minimum absolute value.\n","base.minmax":"\nbase.minmax( x:number, y:number )\n Returns the minimum and maximum values.\n","base.minmax.assign":"\nbase.minmax.assign( x:number, y:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n","base.minmaxabs":"\nbase.minmaxabs( x:number, y:number )\n Returns the minimum and maximum absolute values.\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x:number, y:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Returns the minimum and maximum absolute values.\n","base.minn":"\nbase.minn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum value.\n","base.modf":"\nbase.modf( x:number )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n","base.modf.assign":"\nbase.modf.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n","base.mul":"\nbase.mul( x:number, y:number )\n Multiplies two double-precision floating-point numbers `x` and `y`.\n","base.mulf":"\nbase.mulf( x:number, y:number )\n Multiplies two single-precision floating-point numbers `x` and `y`.\n","base.ndarray":"\nbase.ndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string )\n Returns an ndarray.\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n Underlying data type.\n","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n Number of dimensions.\n","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n Array order.\n","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n Array shape.\n","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in an input ndarray and assigns results\n to elements in an output ndarray.\n","base.ndzeros":"\nbase.ndzeros( dtype:string, shape:ArrayLikeObject, order:string )\n Returns a zero-filled ndarray having a specified shape and data type.\n","base.ndzerosLike":"\nbase.ndzerosLike( x:ndarray )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n","base.negafibonacci":"\nbase.negafibonacci( n:integer )\n Computes the nth negaFibonacci number.\n","base.negalucas":"\nbase.negalucas( n:integer )\n Computes the nth negaLucas number.\n","base.nonfibonacci":"\nbase.nonfibonacci( n:integer )\n Computes the nth non-Fibonacci number.\n","base.normalize":"\nbase.normalize( x:number )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n","base.normalize.assign":"\nbase.normalize.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n","base.normalizef":"\nbase.normalizef( x:float )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n","base.normalizef.assign":"\nbase.normalizef.assign( x:float, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n assigns results to a provided output array.\n","base.normhermitepoly":"\nbase.normhermitepoly( n:integer, x:number )\n Evaluates a normalized Hermite polynomial.\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n:integer )\n Returns a function for evaluating a normalized Hermite polynomial.\n","base.pdiff":"\nbase.pdiff( x:number, y:number )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n","base.pdifff":"\nbase.pdifff( x:number, y:number )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n","base.polygamma":"\nbase.polygamma( n:integer, x:number )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n","base.pow":"\nbase.pow( b:number, x:number )\n Evaluates the exponential function `bˣ`.\n","base.powm1":"\nbase.powm1( b:number, x:number )\n Evaluates `bˣ - 1`.\n","base.rad2deg":"\nbase.rad2deg( x:number )\n Converts an angle from radians to degrees.\n","base.ramp":"\nbase.ramp( x:number )\n Evaluates the ramp function.\n","base.rampf":"\nbase.rampf( x:number )\n Evaluates the ramp function (single-precision).\n","base.random.arcsine":"\nbase.random.arcsine( a:number, b:number )\n Returns a pseudorandom number drawn from an arcsine distribution.\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n Generator name.\n","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n Length of generator seed.\n","base.random.arcsine.state":"\nbase.random.arcsine.state\n Generator state.\n","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n Length of generator state.\n","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.bernoulli":"\nbase.random.bernoulli( p:number )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n Generator name.\n","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n Length of generator seed.\n","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n Generator state.\n","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n Length of generator state.\n","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.beta":"\nbase.random.beta( α:number, β:number )\n Returns a pseudorandom number drawn from a beta distribution.\n","base.random.beta.factory":"\nbase.random.beta.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n","base.random.beta.NAME":"\nbase.random.beta.NAME\n Generator name.\n","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n","base.random.beta.seed":"\nbase.random.beta.seed\n Pseudorandom number generator seed.\n","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n Length of generator seed.\n","base.random.beta.state":"\nbase.random.beta.state\n Generator state.\n","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n Length of generator state.\n","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.betaprime":"\nbase.random.betaprime( α:number, β:number )\n Returns a pseudorandom number drawn from a beta prime distribution.\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n Generator name.\n","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n Length of generator seed.\n","base.random.betaprime.state":"\nbase.random.betaprime.state\n Generator state.\n","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n Length of generator state.\n","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.binomial":"\nbase.random.binomial( n:integer, p:number )\n Returns a pseudorandom number drawn from a binomial distribution.\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n:integer, p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n Generator name.\n","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n","base.random.binomial.seed":"\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n Length of generator seed.\n","base.random.binomial.state":"\nbase.random.binomial.state\n Generator state.\n","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n Length of generator state.\n","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n Size of generator state.\n","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.boxMuller":"\nbase.random.boxMuller()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n Generator name.\n","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n Length of generator seed.\n","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n Generator state.\n","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n Length of generator state.\n","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.cauchy":"\nbase.random.cauchy( x0:number, Ɣ:number )\n Returns a pseudorandom number drawn from a Cauchy distribution.\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0:number, Ɣ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n Generator name.\n","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n Length of generator seed.\n","base.random.cauchy.state":"\nbase.random.cauchy.state\n Generator state.\n","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n Length of generator state.\n","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.chi":"\nbase.random.chi( k:number )\n Returns a pseudorandom number drawn from a chi distribution.\n","base.random.chi.factory":"\nbase.random.chi.factory( [k:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n","base.random.chi.NAME":"\nbase.random.chi.NAME\n Generator name.\n","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n","base.random.chi.seed":"\nbase.random.chi.seed\n Pseudorandom number generator seed.\n","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n Length of generator seed.\n","base.random.chi.state":"\nbase.random.chi.state\n Generator state.\n","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n Length of generator state.\n","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.chisquare":"\nbase.random.chisquare( k:number )\n Returns a pseudorandom number drawn from a chi-square distribution.\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n Generator name.\n","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n Length of generator seed.\n","base.random.chisquare.state":"\nbase.random.chisquare.state\n Generator state.\n","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n Length of generator state.\n","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.cosine":"\nbase.random.cosine( μ:number, s:number )\n Returns a pseudorandom number drawn from a raised cosine distribution.\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ:number, s:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n Generator name.\n","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n","base.random.cosine.seed":"\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n Length of generator seed.\n","base.random.cosine.state":"\nbase.random.cosine.state\n Generator state.\n","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n Length of generator state.\n","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.discreteUniform":"\nbase.random.discreteUniform( a:integer, b:integer )\n Returns a pseudorandom number drawn from a discrete uniform distribution.\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a:integer, b:integer, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n Generator name.\n","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n Generator state.\n","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n Length of generator state.\n","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.erlang":"\nbase.random.erlang( k:integer, λ:number )\n Returns a pseudorandom number drawn from an Erlang distribution.\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k:integer, λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n Generator name.\n","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n","base.random.erlang.seed":"\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n Length of generator seed.\n","base.random.erlang.state":"\nbase.random.erlang.state\n Generator state.\n","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n Length of generator state.\n","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.exponential":"\nbase.random.exponential( λ:number )\n Returns a pseudorandom number drawn from an exponential distribution.\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n Generator name.\n","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n","base.random.exponential.seed":"\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n Length of generator seed.\n","base.random.exponential.state":"\nbase.random.exponential.state\n Generator state.\n","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n Length of generator state.\n","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.f":"\nbase.random.f( d1:number, d2:number )\n Returns a pseudorandom number drawn from an F distribution.\n","base.random.f.factory":"\nbase.random.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n","base.random.f.NAME":"\nbase.random.f.NAME\n Generator name.\n","base.random.f.PRNG":"\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n","base.random.f.seed":"\nbase.random.f.seed\n Pseudorandom number generator seed.\n","base.random.f.seedLength":"\nbase.random.f.seedLength\n Length of generator seed.\n","base.random.f.state":"\nbase.random.f.state\n Generator state.\n","base.random.f.stateLength":"\nbase.random.f.stateLength\n Length of generator state.\n","base.random.f.byteLength":"\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n","base.random.f.toJSON":"\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.frechet":"\nbase.random.frechet( α:number, s:number, m:number )\n Returns a pseudorandom number drawn from a Fréchet distribution.\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α:number, s:number, m:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n Generator name.\n","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n","base.random.frechet.seed":"\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n Length of generator seed.\n","base.random.frechet.state":"\nbase.random.frechet.state\n Generator state.\n","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n Length of generator state.\n","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.gamma":"\nbase.random.gamma( α:number, β:number )\n Returns a pseudorandom number drawn from a gamma distribution.\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n Generator name.\n","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n","base.random.gamma.seed":"\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n Length of generator seed.\n","base.random.gamma.state":"\nbase.random.gamma.state\n Generator state.\n","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n Length of generator state.\n","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n Size of generator state.\n","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.geometric":"\nbase.random.geometric( p:number )\n Returns a pseudorandom number drawn from a geometric distribution.\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n Generator name.\n","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n","base.random.geometric.seed":"\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n Length of generator seed.\n","base.random.geometric.state":"\nbase.random.geometric.state\n Generator state.\n","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n Length of generator state.\n","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.gumbel":"\nbase.random.gumbel( μ:number, β:number )\n Returns a pseudorandom number drawn from a Gumbel distribution.\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n Generator name.\n","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n Length of generator seed.\n","base.random.gumbel.state":"\nbase.random.gumbel.state\n Generator state.\n","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n Length of generator state.\n","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.hypergeometric":"\nbase.random.hypergeometric( N:integer, K:integer, n:integer )\n Returns a pseudorandom number drawn from a hypergeometric distribution.\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N:integer, K:integer, n:integer, ]\n [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n Generator name.\n","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n Generator state.\n","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n Length of generator state.\n","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n Generator name.\n","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n Generator state.\n","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.invgamma":"\nbase.random.invgamma( α:number, β:number )\n Returns a pseudorandom number drawn from an inverse gamma distribution.\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n Generator name.\n","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n Length of generator seed.\n","base.random.invgamma.state":"\nbase.random.invgamma.state\n Generator state.\n","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n Length of generator state.\n","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n Size of generator state.\n","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a:number, b:number )\n Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n distribution.\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n Generator name.\n","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n Generator state.\n","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.laplace":"\nbase.random.laplace( μ:number, b:number )\n Returns a pseudorandom number drawn from a Laplace distribution.\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n Generator name.\n","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n","base.random.laplace.seed":"\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n Length of generator seed.\n","base.random.laplace.state":"\nbase.random.laplace.state\n Generator state.\n","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n Length of generator state.\n","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.levy":"\nbase.random.levy( μ:number, c:number )\n Returns a pseudorandom number drawn from a Lévy distribution.\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ:number, c:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n","base.random.levy.NAME":"\nbase.random.levy.NAME\n Generator name.\n","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n","base.random.levy.seed":"\nbase.random.levy.seed\n Pseudorandom number generator seed.\n","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n Length of generator seed.\n","base.random.levy.state":"\nbase.random.levy.state\n Generator state.\n","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n Length of generator state.\n","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.logistic":"\nbase.random.logistic( μ:number, s:number )\n Returns a pseudorandom number drawn from a logistic distribution.\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ:number, s:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n Generator name.\n","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n","base.random.logistic.seed":"\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n Length of generator seed.\n","base.random.logistic.state":"\nbase.random.logistic.state\n Generator state.\n","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n Length of generator state.\n","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.lognormal":"\nbase.random.lognormal( μ:number, σ:number )\n Returns a pseudorandom number drawn from a lognormal distribution.\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n Generator name.\n","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n Length of generator seed.\n","base.random.lognormal.state":"\nbase.random.lognormal.state\n Generator state.\n","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n Length of generator state.\n","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstd":"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstd.factory":"\nbase.random.minstd.factory( [options:Object] )\n Returns a linear congruential pseudorandom number generator (LCG).\n","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n Generator name.\n","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n Minimum possible value.\n","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n Maximum possible value.\n","base.random.minstd.seed":"\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n Length of generator seed.\n","base.random.minstd.state":"\nbase.random.minstd.state\n Generator state.\n","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n Length of generator state.\n","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options:Object] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n Generator name.\n","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n Generator state.\n","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.mt19937":"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options:Object] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n Generator name.\n","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n Minimum possible value.\n","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n Maximum possible value.\n","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n Length of generator seed.\n","base.random.mt19937.state":"\nbase.random.mt19937.state\n Generator state.\n","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n Length of generator state.\n","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r:number, p:number )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n Generator name.\n","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n Generator state.\n","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.normal":"\nbase.random.normal( μ:number, σ:number )\n Returns a pseudorandom number drawn from a normal distribution.\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n","base.random.normal.NAME":"\nbase.random.normal.NAME\n Generator name.\n","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n","base.random.normal.seed":"\nbase.random.normal.seed\n Pseudorandom number generator seed.\n","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n Length of generator seed.\n","base.random.normal.state":"\nbase.random.normal.state\n Generator state.\n","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n Length of generator state.\n","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n Size of generator state.\n","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.pareto1":"\nbase.random.pareto1( α:number, β:number )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n Generator name.\n","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n Length of generator seed.\n","base.random.pareto1.state":"\nbase.random.pareto1.state\n Generator state.\n","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n Length of generator state.\n","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.poisson":"\nbase.random.poisson( λ:number )\n Returns a pseudorandom number drawn from a Poisson distribution.\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n Generator name.\n","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n","base.random.poisson.seed":"\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n Length of generator seed.\n","base.random.poisson.state":"\nbase.random.poisson.state\n Generator state.\n","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n Length of generator state.\n","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randi":"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n","base.random.randi.factory":"\nbase.random.randi.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n","base.random.randi.NAME":"\nbase.random.randi.NAME\n Generator name.\n","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n","base.random.randi.MIN":"\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n","base.random.randi.MAX":"\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n","base.random.randi.seed":"\nbase.random.randi.seed\n Pseudorandom number generator seed.\n","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n Length of generator seed.\n","base.random.randi.state":"\nbase.random.randi.state\n Generator state.\n","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n Length of generator state.\n","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randn":"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.randn.factory":"\nbase.random.randn.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.randn.NAME":"\nbase.random.randn.NAME\n Generator name.\n","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n","base.random.randn.seed":"\nbase.random.randn.seed\n Pseudorandom number generator seed.\n","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n Length of generator seed.\n","base.random.randn.state":"\nbase.random.randn.state\n Generator state.\n","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n Length of generator state.\n","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randu":"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n","base.random.randu.factory":"\nbase.random.randu.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n","base.random.randu.NAME":"\nbase.random.randu.NAME\n Generator name.\n","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n","base.random.randu.MIN":"\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n","base.random.randu.MAX":"\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n","base.random.randu.seed":"\nbase.random.randu.seed\n Pseudorandom number generator seed.\n","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n Length of generator seed.\n","base.random.randu.state":"\nbase.random.randu.state\n Generator state.\n","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n Length of generator state.\n","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.rayleigh":"\nbase.random.rayleigh( σ:number )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n Generator name.\n","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n Length of generator seed.\n","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n Generator state.\n","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n Length of generator state.\n","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.t":"\nbase.random.t( v:number )\n Returns a pseudorandom number drawn from a Student's t distribution.\n","base.random.t.factory":"\nbase.random.t.factory( [v:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n","base.random.t.NAME":"\nbase.random.t.NAME\n Generator name.\n","base.random.t.PRNG":"\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n","base.random.t.seed":"\nbase.random.t.seed\n Pseudorandom number generator seed.\n","base.random.t.seedLength":"\nbase.random.t.seedLength\n Length of generator seed.\n","base.random.t.state":"\nbase.random.t.state\n Generator state.\n","base.random.t.stateLength":"\nbase.random.t.stateLength\n Length of generator state.\n","base.random.t.byteLength":"\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n","base.random.t.toJSON":"\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.triangular":"\nbase.random.triangular( a:number, b:number, c:number )\n Returns a pseudorandom number drawn from a triangular distribution.\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n Generator name.\n","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n","base.random.triangular.seed":"\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n Length of generator seed.\n","base.random.triangular.state":"\nbase.random.triangular.state\n Generator state.\n","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n Length of generator state.\n","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.uniform":"\nbase.random.uniform( a:number, b:number )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n Generator name.\n","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n","base.random.uniform.seed":"\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n Length of generator seed.\n","base.random.uniform.state":"\nbase.random.uniform.state\n Generator state.\n","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n Length of generator state.\n","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.weibull":"\nbase.random.weibull( k:number, λ:number )\n Returns a pseudorandom number drawn from a Weibull distribution.\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k:number, λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n Generator name.\n","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n","base.random.weibull.seed":"\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n Length of generator seed.\n","base.random.weibull.state":"\nbase.random.weibull.state\n Generator state.\n","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n Length of generator state.\n","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.reldiff":"\nbase.reldiff( x:number, y:number[, scale:string|Function] )\n Computes the relative difference of two real numbers.\n","base.rempio2":"\nbase.rempio2( x:number, y:Array|TypedArray|Object )\n Computes `x - nπ/2 = r`.\n","base.risingFactorial":"\nbase.risingFactorial( x:number, n:integer )\n Computes the rising factorial of `x` and `n`.\n","base.rotl32":"\nbase.rotl32( x:integer, shift:integer )\n Performs a bitwise rotation to the left.\n","base.rotr32":"\nbase.rotr32( x:integer, shift:integer )\n Performs a bitwise rotation to the right.\n","base.round":"\nbase.round( x:number )\n Rounds a numeric value to the nearest integer.\n","base.round2":"\nbase.round2( x:number )\n Rounds a numeric value to the nearest power of two on a linear scale.\n","base.round10":"\nbase.round10( x:number )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n","base.roundb":"\nbase.roundb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n","base.roundn":"\nbase.roundn( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n`.\n","base.roundsd":"\nbase.roundsd( x:number, n:integer[, b:integer] )\n Rounds a numeric value to the nearest number with `n` significant figures.\n","base.rsqrt":"\nbase.rsqrt( x:number )\n Computes the reciprocal square root of a double-precision floating-point\n number.\n","base.rsqrtf":"\nbase.rsqrtf( x:number )\n Computes the reciprocal square root of a single-precision floating-point\n number.\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value:any, dtype:string, order:string )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n","base.setHighWord":"\nbase.setHighWord( x:number, high:integer )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n","base.setLowWord":"\nbase.setLowWord( x:number, low:integer )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n","base.sici":"\nbase.sici( x:number )\n Computes the sine and cosine integrals.\n","base.sici.assign":"\nbase.sici.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n","base.signbit":"\nbase.signbit( x:number )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.signbitf":"\nbase.signbitf( x:float )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.significandf":"\nbase.significandf( x:float )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n","base.signum":"\nbase.signum( x:number )\n Evaluates the signum function for a double-precision floating-point number.\n","base.signumf":"\nbase.signumf( x:number )\n Evaluates the signum function for a single-precision floating-point number.\n","base.sin":"\nbase.sin( x:number )\n Computes the sine of a number.\n","base.sinc":"\nbase.sinc( x:number )\n Computes the normalized cardinal sine of a number.\n","base.sincos":"\nbase.sincos( x:number )\n Simultaneously computes the sine and cosine of a number.\n\nbase.sincos( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Simultaneously computes the sine and cosine of a number and assigns\n results to a provided output array.\n","base.sincospi":"\nbase.sincospi( x:number )\n Simultaneously computes the sine and cosine of a number times π.\n","base.sincospi.assign":"\nbase.sincospi.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n","base.sinh":"\nbase.sinh( x:number )\n Computes the hyperbolic sine of a double-precision floating-point number.\n","base.sinpi":"\nbase.sinpi( x:number )\n Computes the value of `sin(πx)`.\n","base.spence":"\nbase.spence( x:number )\n Evaluates Spence’s function, which is also known as the dilogarithm.\n","base.sqrt":"\nbase.sqrt( x:number )\n Computes the principal square root of a double-precision floating-point\n number.\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x:number )\n Computes the principal square root of `1+x` minus one.\n","base.sqrtf":"\nbase.sqrtf( x:number )\n Computes the principal square root of a single-precision floating-point\n number.\n","base.sqrtpi":"\nbase.sqrtpi( x:number )\n Computes the principal square root of the product of π and a positive\n double-precision floating-point number.\n","base.strided.binary":"\nbase.strided.binary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike, dtypes3:ArrayLike[, options:Object] )\n Generates a list of binary interface signatures from strided array data\n types.\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table:Object, signatures:ArrayLike )\n Assigns callbacks to binary interfaces according to type promotion rules.\n","base.strided.ccopy":"\nbase.strided.ccopy( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector.\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector using alternative\n indexing semantics.\n","base.strided.cmap":"\nbase.strided.cmap( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer, fcn:Function )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array.\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n","base.strided.cswap":"\nbase.strided.cswap( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer )\n Interchanges two complex single-precision floating-point vectors.\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n Interchanges two complex single-precision floating-point vectors using\n alternative indexing semantics.\n","base.strided.cumax":"\nbase.strided.cumax( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative maximum of a strided array.\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative maximum absolute value of a strided array.\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n","base.strided.cumin":"\nbase.strided.cumin( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative minimum of a strided array.\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n","base.strided.cuminabs":"\nbase.strided.cuminabs( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative minimum absolute value of a strided array.\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n","base.strided.dabs":"\nbase.strided.dabs( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dabs2":"\nbase.strided.dabs2( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dapx":"\nbase.strided.dapx( N:integer, alpha:number, x:Float64Array, stride:integer )\n Adds a constant to each element in a double-precision floating-point strided\n array.\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Adds a constant to each element in a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dapxsum":"\nbase.strided.dapxsum( N:integer, alpha:number, x:Float64Array, stride:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum.\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N:integer, alpha:number, x:Float64Array, \n stride:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N:integer, alpha:number, x:Float64Array, \n stride:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N:integer, alpha:number, x:Float64Array, \n stride:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using ordinary recursive summation.\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N:integer, alpha:number, x:Float64Array, \n stride:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation.\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n","base.strided.dasum":"\nbase.strided.dasum( N:integer, x:Float64Array, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.dasumpw":"\nbase.strided.dasumpw( N:integer, x:Float64Array, stride:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation.\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n","base.strided.daxpy":"\nbase.strided.daxpy( N:integer, alpha:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n","base.strided.dcbrt":"\nbase.strided.dcbrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dceil":"\nbase.strided.dceil( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dcopy":"\nbase.strided.dcopy( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.dcumax":"\nbase.strided.dcumax( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements.\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements.\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.dcumin":"\nbase.strided.dcumin( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements.\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements.\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.dcusum":"\nbase.strided.dcusum( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements.\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N:integer, sum:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dcusumors":"\nbase.strided.dcusumors( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation.\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation.\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.ddot":"\nbase.strided.ddot( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the dot product of two double-precision floating-point vectors.\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n","base.strided.dfill":"\nbase.strided.dfill( N:integer, alpha:number, x:Float64Array, stride:integer )\n Fills a double-precision floating-point strided array with a specified\n scalar value.\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Fills a double-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n","base.strided.dfloor":"\nbase.strided.dfloor( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dinv":"\nbase.strided.dinv( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dmap":"\nbase.strided.dmap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array.\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.dmap2":"\nbase.strided.dmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, z:Float64Array, sz:integer, fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays and assigns results to a double-precision floating-point strided\n output array.\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n y:Float64Array, sy:integer, oy:integer, z:Float64Array, sz:integer, \n oz:integer, fcn:Function )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.dmax":"\nbase.strided.dmax( N:integer, x:Float64Array, stride:integer )\n Computes the maximum value of a double-precision floating-point strided\n array.\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N:integer, x:Float64Array, stride:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array.\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmaxabssorted":"\nbase.strided.dmaxabssorted( N:integer, x:Float64Array, stride:integer )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array.\n","base.strided.dmaxabssorted.ndarray":"\nbase.strided.dmaxabssorted.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dmaxsorted":"\nbase.strided.dmaxsorted( N:integer, x:Float64Array, stride:integer )\n Computes the maximum value of a sorted double-precision floating-point\n strided array.\n","base.strided.dmaxsorted.ndarray":"\nbase.strided.dmaxsorted.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmean":"\nbase.strided.dmean( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array.\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.dmeanli":"\nbase.strided.dmeanli( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n","base.strided.dmeanors":"\nbase.strided.dmeanors( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation.\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm.\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation.\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array.\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N:integer, c:number, x:Float64Array, \n strideX:integer, out:Float64Array, strideOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm.\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array.\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N:integer, x:Float64Array, stride:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmidrange":"\nbase.strided.dmidrange( N:integer, x:Float64Array, stride:integer )\n Computes the mid-range of a double-precision floating-point strided array.\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.dmin":"\nbase.strided.dmin( N:integer, x:Float64Array, stride:integer )\n Computes the minimum value of a double-precision floating-point strided\n array.\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dminabs":"\nbase.strided.dminabs( N:integer, x:Float64Array, stride:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array.\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dminsorted":"\nbase.strided.dminsorted( N:integer, x:Float64Array, stride:integer )\n Computes the minimum value of a sorted double-precision floating-point\n strided array.\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmskabs":"\nbase.strided.dmskabs( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y`.\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.dmskceil":"\nbase.strided.dmskceil( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskinv":"\nbase.strided.dmskinv( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmskmap":"\nbase.strided.dmskmap( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float64Array, sy:integer, \n oy:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, m:Uint8Array, sm:integer, z:Float64Array, sz:integer, \n fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, y:Float64Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n om:integer, z:Float64Array, sz:integer, oz:integer, fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.dmskmax":"\nbase.strided.dmskmax( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask.\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.dmskmin":"\nbase.strided.dmskmin( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask.\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.dmskramp":"\nbase.strided.dmskramp( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskrange":"\nbase.strided.dmskrange( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask.\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y`.\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.dnanasum":"\nbase.strided.dnanasum( N:integer, x:Float64Array, stride:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values.\n","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N:integer, x:Float64Array, stride:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation.\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n","base.strided.dnanmax":"\nbase.strided.dnanmax( N:integer, x:Float64Array, stride:integer )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N:integer, x:Float64Array, stride:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnanmean":"\nbase.strided.dnanmean( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation.\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, using Welford's algorithm and ignoring `NaN` values.\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.dnanmin":"\nbase.strided.dnanmin( N:integer, x:Float64Array, stride:integer )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N:integer, x:Float64Array, stride:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnannsum":"\nbase.strided.dnannsum( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.dnanrange":"\nbase.strided.dnanrange( N:integer, x:Float64Array, stride:integer )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values.\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values.\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n","base.strided.dnansum":"\nbase.strided.dnansum( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.dnansumors":"\nbase.strided.dnansumors( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values.\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n","base.strided.dnrm2":"\nbase.strided.dnrm2( N:integer, x:Float64Array, stride:integer )\n Computes the L2-norm of a double-precision floating-point vector.\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n","base.strided.dramp":"\nbase.strided.dramp( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.drange":"\nbase.strided.drange( N:integer, x:Float64Array, stride:integer )\n Computes the range of a double-precision floating-point strided array.\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n","base.strided.drev":"\nbase.strided.drev( N:integer, x:Float64Array, stride:integer )\n Reverses a double-precision floating-point strided array in-place.\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n","base.strided.drsqrt":"\nbase.strided.drsqrt( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N:integer, alpha:number, x:Float32Array, stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and returning an\n extended precision result.\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and returning an extended precision result.\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n","base.strided.dscal":"\nbase.strided.dscal( N:integer, alpha:number, x:Float64Array, stride:integer )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha`.\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n","base.strided.dsdot":"\nbase.strided.dsdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation and result.\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n","base.strided.dsem":"\nbase.strided.dsem( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array.\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dsemch":"\nbase.strided.dsemch( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm.\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n","base.strided.dsempn":"\nbase.strided.dsempn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm.\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n","base.strided.dsemtk":"\nbase.strided.dsemtk( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm.\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n","base.strided.dsemwd":"\nbase.strided.dsemwd( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm.\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.dsemyc":"\nbase.strided.dsemyc( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n","base.strided.dsmean":"\nbase.strided.dsmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and returning an extended precision\n result.\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n returning an extended precision result.\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and returning an extended precision result.\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and returning an\n extended precision result.\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and returning an\n extended precision result.\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using ordinary recursive summation with\n extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using a two-pass error correction algorithm\n with extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using Welford's algorithm with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N:integer, x:Float32Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.dsnansum":"\nbase.strided.dsnansum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation,\n and returning an extended precision result.\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n","base.strided.dsorthp":"\nbase.strided.dsorthp( N:integer, order:number, x:Float64Array, stride:integer )\n Sorts a double-precision floating-point strided array using heapsort.\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N:integer, order:number, x:Float64Array, \n stride:integer, offset:integer )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n","base.strided.dsortins":"\nbase.strided.dsortins( N:integer, order:number, x:Float64Array, stride:integer )\n Sorts a double-precision floating-point strided array using insertion sort.\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N:integer, order:number, x:Float64Array, \n stride:integer, offset:integer )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n","base.strided.dsortsh":"\nbase.strided.dsortsh( N:integer, order:number, x:Float64Array, stride:integer )\n Sorts a double-precision floating-point strided array using Shellsort.\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N:integer, order:number, x:Float64Array, \n stride:integer, offset:integer )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n","base.strided.dsqrt":"\nbase.strided.dsqrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dssum":"\nbase.strided.dssum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and returning an extended precision result.\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n","base.strided.dssumors":"\nbase.strided.dssumors( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and returning\n an extended precision result.\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n","base.strided.dssumpw":"\nbase.strided.dssumpw( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and returning an\n extended precision result.\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n","base.strided.dstdev":"\nbase.strided.dstdev( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array.\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dstdevch":"\nbase.strided.dstdevch( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm.\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n","base.strided.dsum":"\nbase.strided.dsum( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements.\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.dsumors":"\nbase.strided.dsumors( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation.\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dsumpw":"\nbase.strided.dsumpw( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation.\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.dsvariance":"\nbase.strided.dsvariance( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and returning an extended precision result.\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and returning an\n extended precision result.\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dswap":"\nbase.strided.dswap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Interchanges two double-precision floating-point vectors.\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n","base.strided.dtrunc":"\nbase.strided.dtrunc( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dvariance":"\nbase.strided.dvariance( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array.\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.dvariancech":"\nbase.strided.dvariancech( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm.\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm.\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm.\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm.\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.dvarm":"\nbase.strided.dvarm( N:integer, mean:number, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean.\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm.\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm.\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.gapx":"\nbase.strided.gapx( N:integer, alpha:number, x:Array|TypedArray, stride:integer )\n Adds a constant to each element in a strided array.\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each element in a strided array using alternative\n indexing semantics.\n","base.strided.gapxsum":"\nbase.strided.gapxsum( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Adds a constant to each strided array element and computes the sum.\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each strided array element and computes the sum using\n alternative indexing semantics.\n","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Adds a constant to each strided array element and computes the sum using an\n improved Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each strided array element and computes the sum using an\n improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Adds a constant to each strided array element and computes the sum using a\n second-order iterative Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each strided array element and computes the sum using a\n second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Adds a constant to each strided array element and computes the sum using\n ordinary recursive summation.\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each strided array element and computes the sum using\n ordinary recursive summation and alternative indexing semantics.\n","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Adds a constant to each strided array element and computes the sum using\n pairwise summation.\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each strided array element and computes the sum using\n pairwise summation and alternative indexing semantics.\n","base.strided.gasum":"\nbase.strided.gasum( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.gasumpw":"\nbase.strided.gasumpw( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation.\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.gaxpy":"\nbase.strided.gaxpy( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n","base.strided.gcopy":"\nbase.strided.gcopy( N:integer, x:ArrayLikeObject, strideX:integer, \n y:ArrayLikeObject, strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.gcusum":"\nbase.strided.gcusum( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements.\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm.\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm.\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumors":"\nbase.strided.gcusumors( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation.\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using pairwise\n summation.\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n","base.strided.gdot":"\nbase.strided.gdot( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the dot product of two vectors.\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n","base.strided.gfill":"\nbase.strided.gfill( N:integer, alpha:any, x:ArrayLikeObject, stride:integer )\n Fills a strided array with a specified scalar value.\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N:integer, alpha:any, x:ArrayLikeObject, \n stride:integer, offset:integer )\n Fills a strided array with a specified scalar value using alternative\n indexing semantics.\n","base.strided.gfillBy":"\nbase.strided.gfillBy( N:integer, x:ArrayLikeObject, stride:integer, \n clbk:Function[, thisArg:any] )\n Fills a strided array according to a provided callback function.\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N:integer, x:ArrayLikeObject, stride:integer, \n offset:integer, clbk:Function[, thisArg:any] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N:integer, x:Array|TypedArray, strideX:integer, \n out:Array|TypedArray, strideOut:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer, out:Array|TypedArray, strideOut:integer, \n offsetOut:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansum":"\nbase.strided.gnansum( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements, ignoring `NaN` values.\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm.\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N:integer, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.gnansumors":"\nbase.strided.gnansumors( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation.\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and\n pairwise summation.\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n","base.strided.gnrm2":"\nbase.strided.gnrm2( N:integer, x:Array|TypedArray, stride:integer )\n Computes the L2-norm of a vector.\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the L2-norm of a vector using alternative indexing semantics.\n","base.strided.grev":"\nbase.strided.grev( N:integer, x:ArrayLikeObject, stride:integer )\n Reverses a strided array in-place.\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N:integer, x:ArrayLikeObject, stride:integer, \n offset:integer )\n Reverses a strided array in-place using alternative indexing semantics.\n","base.strided.gscal":"\nbase.strided.gscal( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Multiplies a vector `x` by a constant `alpha`.\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort.\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort.\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort.\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n","base.strided.gsorthp":"\nbase.strided.gsorthp( N:integer, order:number, x:Array|TypedArray, \n stride:integer )\n Sorts a strided array using heapsort.\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N:integer, order:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Sorts a strided array using heapsort and alternative indexing semantics.\n","base.strided.gsortins":"\nbase.strided.gsortins( N:integer, order:number, x:Array|TypedArray, \n stride:integer )\n Sorts a strided array using insertion sort.\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N:integer, order:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n","base.strided.gsortsh":"\nbase.strided.gsortsh( N:integer, order:number, x:Array|TypedArray, \n stride:integer )\n Sorts a strided array using Shellsort.\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N:integer, order:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n","base.strided.gsum":"\nbase.strided.gsum( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements.\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm.\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm.\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gsumors":"\nbase.strided.gsumors( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements using ordinary recursive\n summation.\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n","base.strided.gsumpw":"\nbase.strided.gsumpw( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements using pairwise summation.\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n","base.strided.gswap":"\nbase.strided.gswap( N:integer, x:ArrayLikeObject, strideX:integer, \n y:ArrayLikeObject, strideY:integer )\n Interchanges vectors `x` and `y`.\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n","base.strided.mapBy":"\nbase.strided.mapBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, fcn:Function, clbk:Function[, \n thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, fcn:Function, \n clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.mapBy2":"\nbase.strided.mapBy2( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n fcn:Function, clbk:Function[, thisArg:any] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array.\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, fcn:Function, \n clbk:Function[, thisArg:any] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n","base.strided.max":"\nbase.strided.max( N:integer, x:Array|TypedArray, stride:integer )\n Computes the maximum value of a strided array.\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n","base.strided.maxabs":"\nbase.strided.maxabs( N:integer, x:Array|TypedArray, stride:integer )\n Computes the maximum absolute value of a strided array.\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n","base.strided.maxBy":"\nbase.strided.maxBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the maximum value of a strided array via a callback function.\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n","base.strided.maxsorted":"\nbase.strided.maxsorted( N:integer, x:Array|TypedArray, stride:integer )\n Computes the maximum value of a sorted strided array.\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.mean":"\nbase.strided.mean( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array.\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n","base.strided.meankbn":"\nbase.strided.meankbn( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm.\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n","base.strided.meankbn2":"\nbase.strided.meankbn2( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm.\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.meanors":"\nbase.strided.meanors( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation.\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n","base.strided.meanpn":"\nbase.strided.meanpn( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm.\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n","base.strided.meanpw":"\nbase.strided.meanpw( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using pairwise summation.\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n","base.strided.meanwd":"\nbase.strided.meanwd( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using Welford's algorithm.\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n","base.strided.mediansorted":"\nbase.strided.mediansorted( N:integer, x:Array|TypedArray, stride:integer )\n Computes the median value of a sorted strided array.\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N:integer, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.min":"\nbase.strided.min( N:integer, x:Array|TypedArray, stride:integer )\n Computes the minimum value of a strided array.\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n","base.strided.minabs":"\nbase.strided.minabs( N:integer, x:Array|TypedArray, stride:integer )\n Computes the minimum absolute value of a strided array.\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n","base.strided.minBy":"\nbase.strided.minBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the minimum value of a strided array via a callback function.\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n","base.strided.minsorted":"\nbase.strided.minsorted( N:integer, x:Array|TypedArray, stride:integer )\n Computes the minimum value of a sorted strided array.\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.mskmax":"\nbase.strided.mskmax( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the maximum value of a strided array according to a mask.\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskmin":"\nbase.strided.mskmin( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the minimum value of a strided array according to a mask.\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskrange":"\nbase.strided.mskrange( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the range of a strided array according to a mask.\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskunary":"\nbase.strided.mskunary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array and assigns results to elements in a\n strided output array.\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike[, options:Object] )\n Generates a list of masked unary interface signatures from strided array\n data types.\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table:Object, \n signatures:ArrayLike )\n Assigns callbacks to masked unary interfaces according to type promotion\n rules.\n","base.strided.nanmax":"\nbase.strided.nanmax( N:integer, x:Array|TypedArray, stride:integer )\n Computes the maximum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N:integer, x:Array|TypedArray, stride:integer )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values.\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the maximum value of a strided array via a callback function,\n ignoring `NaN` values.\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmean":"\nbase.strided.nanmean( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation.\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm.\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm.\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanmin":"\nbase.strided.nanmin( N:integer, x:Array|TypedArray, stride:integer )\n Computes the minimum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanminabs":"\nbase.strided.nanminabs( N:integer, x:Array|TypedArray, stride:integer )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values.\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanminBy":"\nbase.strided.nanminBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the minimum value of a strided array via a callback function,\n ignoring `NaN` values.\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the maximum value of a strided array according to a mask and\n ignoring `NaN` values.\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the minimum value of a strided array according to a mask and\n ignoring `NaN` values.\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the range of a strided array according to a mask and ignoring `NaN`\n values.\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanrange":"\nbase.strided.nanrange( N:integer, x:Array|TypedArray, stride:integer )\n Computes the range of a strided array, ignoring `NaN` values.\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values.\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n","base.strided.nanstdev":"\nbase.strided.nanstdev( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values.\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm.\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm.\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm.\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm.\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.nanvariance":"\nbase.strided.nanvariance( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values.\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm.\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm.\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm.\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm.\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n","base.strided.nullary":"\nbase.strided.nullary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a nullary callback and assigns results to elements in a strided\n output array.\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.quinary":"\nbase.strided.quinary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.range":"\nbase.strided.range( N:integer, x:Array|TypedArray, stride:integer )\n Computes the range of a strided array.\n","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the range of a strided array using alternative indexing semantics.\n","base.strided.rangeBy":"\nbase.strided.rangeBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function.\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n","base.strided.sabs":"\nbase.strided.sabs( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sabs2":"\nbase.strided.sabs2( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sapx":"\nbase.strided.sapx( N:integer, alpha:number, x:Float32Array, stride:integer )\n Adds a constant to each element in a single-precision floating-point strided\n array.\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each element in a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.sapxsum":"\nbase.strided.sapxsum( N:integer, alpha:number, x:Float32Array, stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum.\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation.\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation.\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n","base.strided.sasum":"\nbase.strided.sasum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.sasumpw":"\nbase.strided.sasumpw( N:integer, x:Float32Array, stride:integer )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation.\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n","base.strided.saxpy":"\nbase.strided.saxpy( N:integer, alpha:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n","base.strided.scbrt":"\nbase.strided.scbrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y`.\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.sceil":"\nbase.strided.sceil( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.scopy":"\nbase.strided.scopy( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.scumax":"\nbase.strided.scumax( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements.\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements.\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.scumin":"\nbase.strided.scumin( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements.\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.scuminabs":"\nbase.strided.scuminabs( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements.\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.scusum":"\nbase.strided.scusum( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements.\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N:integer, sum:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.scusumors":"\nbase.strided.scusumors( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n","base.strided.scusumpw":"\nbase.strided.scusumpw( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sdot":"\nbase.strided.sdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the dot product of two single-precision floating-point vectors.\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation.\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation.\n","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.sdsdot":"\nbase.strided.sdsdot( N:integer, scalar:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation.\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N:integer, scalar:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n","base.strided.sdsmean":"\nbase.strided.sdsmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation.\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation.\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation.\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation.\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation.\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation.\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.sdssum":"\nbase.strided.sdssum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation.\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation.\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n","base.strided.sfill":"\nbase.strided.sfill( N:integer, alpha:number, x:Float32Array, stride:integer )\n Fills a single-precision floating-point strided array with a specified\n scalar value.\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n","base.strided.sfloor":"\nbase.strided.sfloor( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sinv":"\nbase.strided.sinv( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.smap":"\nbase.strided.smap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array.\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.smap2":"\nbase.strided.smap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n sy:integer, z:Float32Array, sz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array.\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, \n y:Float32Array, sy:integer, oy:integer, z:Float32Array, sz:integer, \n oz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.smax":"\nbase.strided.smax( N:integer, x:Float32Array, stride:integer )\n Computes the maximum value of a single-precision floating-point strided\n array.\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.smaxabs":"\nbase.strided.smaxabs( N:integer, x:Float32Array, stride:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array.\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N:integer, x:Float32Array, stride:integer )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array.\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N:integer, x:Float32Array, stride:integer )\n Computes the maximum value of a sorted single-precision floating-point\n strided array.\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smean":"\nbase.strided.smean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array.\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.smeankbn":"\nbase.strided.smeankbn( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.smeanli":"\nbase.strided.smeanli( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n","base.strided.smeanors":"\nbase.strided.smeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation.\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.smeanpn":"\nbase.strided.smeanpn( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm.\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.smeanpw":"\nbase.strided.smeanpw( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation.\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n","base.strided.smeanwd":"\nbase.strided.smeanwd( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.smediansorted":"\nbase.strided.smediansorted( N:integer, x:Float32Array, stride:integer )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smidrange":"\nbase.strided.smidrange( N:integer, x:Float32Array, stride:integer )\n Computes the mid-range of a single-precision floating-point strided array.\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.smin":"\nbase.strided.smin( N:integer, x:Float32Array, stride:integer )\n Computes the minimum value of a single-precision floating-point strided\n array.\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.sminabs":"\nbase.strided.sminabs( N:integer, x:Float32Array, stride:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array.\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.sminsorted":"\nbase.strided.sminsorted( N:integer, x:Float32Array, stride:integer )\n Computes the minimum value of a sorted single-precision floating-point\n strided array.\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smskabs":"\nbase.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskabs2":"\nbase.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y`.\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.smskceil":"\nbase.strided.smskceil( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskfloor":"\nbase.strided.smskfloor( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskinv":"\nbase.strided.smskinv( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smskmap":"\nbase.strided.smskmap( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float32Array, sy:integer, \n oy:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.smskmap2":"\nbase.strided.smskmap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n sy:integer, m:Uint8Array, sm:integer, z:Float32Array, sz:integer, \n fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, y:Float32Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n om:integer, z:Float32Array, sz:integer, oz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.smskmax":"\nbase.strided.smskmax( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask.\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.smskmin":"\nbase.strided.smskmin( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask.\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.smskramp":"\nbase.strided.smskramp( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskrange":"\nbase.strided.smskrange( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask.\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y`.\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.snanmax":"\nbase.strided.snanmax( N:integer, x:Float32Array, stride:integer )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N:integer, x:Float32Array, stride:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanmean":"\nbase.strided.snanmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.snanmin":"\nbase.strided.snanmin( N:integer, x:Float32Array, stride:integer )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanminabs":"\nbase.strided.snanminabs( N:integer, x:Float32Array, stride:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanrange":"\nbase.strided.snanrange( N:integer, x:Float32Array, stride:integer )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values.\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanstdev":"\nbase.strided.snanstdev( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values.\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n","base.strided.snansum":"\nbase.strided.snansum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.snansumors":"\nbase.strided.snansumors( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.snansumpw":"\nbase.strided.snansumpw( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.snanvariance":"\nbase.strided.snanvariance( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values.\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n","base.strided.snrm2":"\nbase.strided.snrm2( N:integer, x:Float32Array, stride:integer )\n Computes the L2-norm of a single-precision floating-point vector.\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n","base.strided.sramp":"\nbase.strided.sramp( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.srange":"\nbase.strided.srange( N:integer, x:Float32Array, stride:integer )\n Computes the range of a single-precision floating-point strided array.\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n","base.strided.srev":"\nbase.strided.srev( N:integer, x:Float32Array, stride:integer )\n Reverses a single-precision floating-point strided array in-place.\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n","base.strided.srsqrt":"\nbase.strided.srsqrt( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sscal":"\nbase.strided.sscal( N:integer, alpha:number, x:Float32Array, stride:integer )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha`.\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n","base.strided.ssorthp":"\nbase.strided.ssorthp( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using heapsort.\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n","base.strided.ssortins":"\nbase.strided.ssortins( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using insertion sort.\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n","base.strided.ssortsh":"\nbase.strided.ssortsh( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using Shellsort.\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n","base.strided.ssqrt":"\nbase.strided.ssqrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sstdev":"\nbase.strided.sstdev( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array.\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.sstdevch":"\nbase.strided.sstdevch( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm.\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n","base.strided.ssum":"\nbase.strided.ssum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements.\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.ssumors":"\nbase.strided.ssumors( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation.\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.ssumpw":"\nbase.strided.ssumpw( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation.\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.sswap":"\nbase.strided.sswap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Interchanges two single-precision floating-point vectors.\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n","base.strided.stdev":"\nbase.strided.stdev( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array.\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n","base.strided.stdevch":"\nbase.strided.stdevch( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm.\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n","base.strided.stdevpn":"\nbase.strided.stdevpn( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using a two-pass\n algorithm.\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n","base.strided.stdevtk":"\nbase.strided.stdevtk( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm.\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n","base.strided.stdevwd":"\nbase.strided.stdevwd( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using Welford's\n algorithm.\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n","base.strided.stdevyc":"\nbase.strided.stdevyc( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer.\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n","base.strided.strunc":"\nbase.strided.strunc( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y`.\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.svariance":"\nbase.strided.svariance( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array.\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.svariancech":"\nbase.strided.svariancech( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm.\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.svariancepn":"\nbase.strided.svariancepn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm.\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.svariancetk":"\nbase.strided.svariancetk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm.\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.svariancewd":"\nbase.strided.svariancewd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm.\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.ternary":"\nbase.strided.ternary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.unary":"\nbase.strided.unary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array.\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function, clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function, clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike[, options:Object] )\n Generates a list of unary interface signatures from strided array data\n types.\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table:Object, signatures:ArrayLike )\n Assigns callbacks to unary interfaces according to type promotion rules.\n","base.strided.variance":"\nbase.strided.variance( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array.\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using alternative indexing\n semantics.\n","base.strided.variancech":"\nbase.strided.variancech( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm.\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n","base.strided.variancepn":"\nbase.strided.variancepn( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using a two-pass algorithm.\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n","base.strided.variancetk":"\nbase.strided.variancetk( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using a one-pass textbook\n algorithm.\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n","base.strided.variancewd":"\nbase.strided.variancewd( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using Welford's algorithm.\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n","base.strided.varianceyc":"\nbase.strided.varianceyc( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer.\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n","base.strided.zmap":"\nbase.strided.zmap( N:integer, x:Complex128Array, strideX:integer, \n y:Complex128Array, strideY:integer, fcn:Function )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array.\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N:integer, x:Complex128Array, strideX:integer, \n offsetX:integer, y:Complex128Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n","base.sub":"\nbase.sub( x:number, y:number )\n Subtracts two double-precision floating-point numbers `x` and `y`.\n","base.subf":"\nbase.subf( x:number, y:number )\n Subtracts two single-precision floating-point numbers `x` and `y`.\n","base.sumSeries":"\nbase.sumSeries( generator:Function[, options:Object] )\n Sum the elements of the series given by the supplied function.\n","base.tan":"\nbase.tan( x:number )\n Computes the tangent of a number.\n","base.tanh":"\nbase.tanh( x:number )\n Computes the hyperbolic tangent of a double-precision floating-point number.\n","base.toBinaryString":"\nbase.toBinaryString( x:number )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x:float )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x:integer )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x:integer )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x:integer )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n","base.toWordf":"\nbase.toWordf( x:float )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n","base.toWords":"\nbase.toWords( x:number )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.toWords.assign":"\nbase.toWords.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n","base.transpose":"\nbase.transpose( x:ndarray )\n Transposes a matrix (or a stack of matrices).\n","base.tribonacci":"\nbase.tribonacci( n:integer )\n Computes the nth Tribonacci number.\n","base.trigamma":"\nbase.trigamma( x:number )\n Evaluates the trigamma function.\n","base.trunc":"\nbase.trunc( x:number )\n Rounds a double-precision floating-point number toward zero.\n","base.trunc2":"\nbase.trunc2( x:number )\n Rounds a numeric value to the nearest power of two toward zero.\n","base.trunc10":"\nbase.trunc10( x:number )\n Rounds a numeric value to the nearest power of ten toward zero.\n","base.truncb":"\nbase.truncb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n","base.truncf":"\nbase.truncf( x:number )\n Rounds a single-precision floating-point number toward zero.\n","base.truncn":"\nbase.truncn( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n","base.truncsd":"\nbase.truncsd( x:number, n:integer[, b:integer] )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n","base.umul":"\nbase.umul( a:integer, b:integer )\n Performs C-like multiplication of two unsigned 32-bit integers.\n","base.umuldw":"\nbase.umuldw( a:integer, b:integer )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n","base.umuldw.assign":"\nbase.umuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x:integer )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n","base.vercos":"\nbase.vercos( x:number )\n Computes the versed cosine.\n","base.versin":"\nbase.versin( x:number )\n Computes the versed sine.\n","base.wrap":"\nbase.wrap( v:number, min:number, max:number )\n Wraps a value on the half-open interval `[min,max)`.\n","base.xlog1py":"\nbase.xlog1py( x:number, y:number )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n","base.xlogy":"\nbase.xlogy( x:number, y:number )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n","base.zeta":"\nbase.zeta( s:number )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and and other characteristics.\n","bifurcate":"\nbifurcate( collection:Array|TypedArray|Object, [options:Object,] \n filter:Array|TypedArray|Object )\n Splits values into two groups.\n","bifurcateBy":"\nbifurcateBy( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateByAsync":"\nbifurcateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which splits values into two groups according to an\n predicate function.\n","bifurcateIn":"\nbifurcateIn( obj:Object|Array|TypedArray, [options:Object,] predicate:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateOwn":"\nbifurcateOwn( obj:Object|Array|TypedArray, [options:Object,] \n predicate:Function )\n Splits values into two groups according to a predicate function.\n","BigInt":"\nBigInt( value:integer|string )\n Returns a BigInt.\n","binomialTest":"\nbinomialTest( x:(number|Array[, n:Array][, options:Object] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n","Boolean":"\nBoolean( value:any )\n Returns a boolean.\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n","broadcastArray":"\nbroadcastArray( x:ndarray, shape:ArrayLikeObject )\n Broadcasts an ndarray to a specified shape.\n","broadcastArrays":"\nbroadcastArrays( ...arrays:ndarray|ArrayLikeObject )\n Broadcasts ndarrays to a common shape.\n","Buffer":"\nBuffer\n\nBuffer( size:integer )\n Allocates a buffer having a specified number of bytes.\n\nBuffer( buffer:Buffer )\n Copies buffer data to a new Buffer instance.\n\nBuffer( array:Array )\n Allocates a buffer using an array of octets.\n\nBuffer( str:string[, encoding:string] )\n Allocates a buffer containing a provided string.\n","buffer2json":"\nbuffer2json( buffer:Buffer )\n Returns a JSON representation of a buffer.\n","BYTE_ORDER":"\nBYTE_ORDER\n Platform byte order.\n","camelcase":"\ncamelcase( str:string )\n Converts a string to camel case.\n","capitalize":"\ncapitalize( str:string )\n Capitalizes the first character in a string.\n","capitalizeKeys":"\ncapitalizeKeys( obj:Object )\n Converts the first letter of each object key to uppercase.\n","CATALAN":"\nCATALAN\n Catalan's constant.\n","CBRT_EPS":"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n Returns US birth data from 1969 to 1988, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n Returns US birth data from 1994 to 2003, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n the Center for Disease Control and Prevention's National Center for Health\n Statistics.\n","chdir":"\nchdir( path:string )\n Changes the current working directory.\n","chi2gof":"\nchi2gof( x:ndarray|Array|TypedArray, y:ndarray|Array|TypedArray|string[, \n ...args:number][, options:Object] )\n Performs a chi-square goodness-of-fit test.\n","chi2test":"\nchi2test( x:ndarray|Array[, options:Object] )\n Performs a chi-square independence test.\n","circarray2iterator":"\ncircarray2iterator( src:ArrayLikeObject[, options:Object][, mapFcn:Function[, \n thisArg:any]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n","circularArrayStream":"\ncircularArrayStream( src:ArrayLikeObject[, options:Object] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n","CircularBuffer":"\nCircularBuffer( buffer:integer|ArrayLike )\n Circular buffer constructor.\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n Clears a buffer.\n","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters:integer] )\n Returns an iterator for iterating over a circular buffer.\n","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value:any )\n Adds a value to a circular buffer.\n","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n","close":"\nclose( fd:integer, clbk:Function )\n Asynchronously closes a file descriptor, so that the file descriptor no\n longer refers to any file and may be reused.\n","close.sync":"\nclose.sync( fd:integer )\n Synchronously closes a file descriptor.\n","CMUDICT":"\nCMUDICT( [options:Object] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n","codePointAt":"\ncodePointAt( str:string, idx:integer[, backward:boolean] )\n Returns a Unicode code point from a string at a specified position.\n","commonKeys":"\ncommonKeys( obj1:any, obj2:any[, ...obj:any] )\n Returns the common own property names of two or more objects.\n","commonKeysIn":"\ncommonKeysIn( obj1:any, obj2:any[, ...obj:any] )\n Returns the common own and inherited property names of two or more objects.\n","complex":"\ncomplex( real:number, imag:number[, dtype:string] )\n Creates a complex number.\n","Complex64":"\nComplex64( real:number, imag:number )\n 64-bit complex number constructor.\n","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n Canonical single-precision complex floating-point NaN.\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n Single-precision complex floating-point zero.\n","Complex128":"\nComplex128( real:number, imag:number )\n 128-bit complex number constructor.\n","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n Canonical double-precision complex floating-point NaN.\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n Double-precision complex floating-point zero.\n","complexarray":"\ncomplexarray( [dtype:string] )\n Creates a complex typed array.\n\ncomplexarray( length:integer[, dtype:string] )\n Returns a complex number typed array having a specified length.\n\ncomplexarray( complexarray:ComplexArray[, dtype:string] )\n Creates a complex number typed array from another complex number typed\n array.\n\ncomplexarray( obj:Object[, dtype:string] )\n Creates a complex number typed array from an array-like object or iterable.\n\ncomplexarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a complex number typed array view of an ArrayBuffer.\n","complexarrayCtors":"\ncomplexarrayCtors( dtype:string )\n Returns a complex typed array constructor.\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n Returns a list of complex typed array data types.\n","complexCtors":"\ncomplexCtors( dtype:string )\n Returns a complex number constructor.\n","complexDataType":"\ncomplexDataType( value:any )\n Returns the data type of a complex number object.\n","complexDataTypes":"\ncomplexDataTypes()\n Returns a list of complex number data types.\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1:string, dtype2:string] )\n Returns the complex number data type with the smallest size and closest\n \"kind\" to which data types can be safely cast.\n","compose":"\ncompose( ...f:Function )\n Function composition.\n","composeAsync":"\ncomposeAsync( ...f:Function )\n Function composition.\n","configdir":"\nconfigdir( [p:string] )\n Returns a directory for user-specific configuration files.\n","conj":"\nconj( z:Complex128 )\n Returns the complex conjugate of a double-precision complex floating-point\n number.\n","conjf":"\nconjf( z:Complex64 )\n Returns the complex conjugate of a single-precision complex floating-point\n number.\n","constantcase":"\nconstantcase( str:string )\n Converts a string to constant case.\n","constantFunction":"\nconstantFunction( val:any )\n Creates a function which always returns the same value.\n","constantStream":"\nconstantStream( value:string|Buffer|Uint8Array|any[, options:Object] )\n Returns a readable stream which always streams the same value.\n","constantStream.factory":"\nconstantStream.factory( [value:string|Buffer|Uint8Array|any, ][options:Object] )\n Returns a function for creating readable streams which always stream the\n same value.\n","constantStream.objectMode":"\nconstantStream.objectMode( value:any[, options:Object] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n","constructorName":"\nconstructorName( val:any )\n Determines the name of a value's constructor.\n","contains":"\ncontains( val:ArrayLike, searchValue:any[, position:integer] )\n Tests if an array-like value contains a search value.\n","convertArray":"\nconvertArray( arr:ArrayLikeObject, dtype:string )\n Converts an input array to an array of a different data type.\n","convertArraySame":"\nconvertArraySame( x:ArrayLikeObject, y:Array|TypedArray )\n Converts an input array to the same data type as a second input array.\n","convertPath":"\nconvertPath( from:string, to:string )\n Converts between POSIX and Windows paths.\n","copy":"\ncopy( value:any[, level:integer] )\n Copy or deep clone a value to an arbitrary depth.\n","copyBuffer":"\ncopyBuffer( buffer:Buffer )\n Copies buffer data to a new Buffer instance.\n","countBy":"\ncountBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Groups values according to an indicator function and returns group counts.\n","countByAsync":"\ncountByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Groups values according to an indicator function and returns group counts.\n","countByAsync.factory":"\ncountByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n","currentYear":"\ncurrentYear()\n Returns the current year.\n","curry":"\ncurry( fcn:Function[, arity:integer][, thisArg:any] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n","curryRight":"\ncurryRight( fcn:Function[, arity:integer][, thisArg:any] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n","cwd":"\ncwd()\n Returns the current working directory.\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n Returns a list of familiar English words.\n","datasets":"\ndatasets( name:string[, options:Object] )\n Returns a dataset.\n","DataView":"\nDataView( buffer:ArrayBuffer|SharedArrayBuffer[, byteOffset:integer[, \n byteLength:integer]] )\n Returns a data view representing a provided array buffer.\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n Read-only property which returns the underyling array buffer.\n","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n","datespace":"\ndatespace( start:number, stop:number[, length:integer][ , options:Object] )\n Generates an array of linearly spaced dates.\n","dayOfQuarter":"\ndayOfQuarter( [month:string|integer|Date[, day:integer, year:integer]] )\n Returns the day of the quarter.\n","dayOfYear":"\ndayOfYear( [month:string|integer|Date[, day:integer, year:integer]] )\n Returns the day of the year.\n","daysInMonth":"\ndaysInMonth( [month:string|integer|Date[, year:integer]] )\n Returns the number of days in a month.\n","daysInYear":"\ndaysInYear( [value:integer|Date] )\n Returns the number of days in a year according to the Gregorian calendar.\n","ddot":"\nddot( x:ndarray, y:ndarray )\n Computes the dot product of two double-precision floating-point vectors.\n","debugSinkStream":"\ndebugSinkStream( [options:Object,] [clbk:Function] )\n Returns a writable stream for debugging stream pipelines.\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options:Object] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options:Object,] [clbk:Function] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n","debugStream":"\ndebugStream( [options:Object,] [clbk:Function] )\n Returns a transform stream for debugging stream pipelines.\n","debugStream.factory":"\ndebugStream.factory( [options:Object] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n","debugStream.objectMode":"\ndebugStream.objectMode( [options:Object,] [clbk:Function] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n","decorateAfter":"\ndecorateAfter( fcn:Function, arity:integer, after:Function[, thisArg:any] )\n Decorates a provided function such that the function's return value is\n provided as an argument to another function.\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn:Function, arity:integer, after:Function[, \n thisArg:any] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n","deepEqual":"\ndeepEqual( a:any, b:any )\n Tests for deep equality between two values.\n","deepGet":"\ndeepGet( obj:ObjectLike, path:string|Array[, options:Object] )\n Returns a nested property value.\n","deepGet.factory":"\ndeepGet.factory( path:string|Array[, options:Object] )\n Creates a reusable deep get function.\n","deepHasOwnProp":"\ndeepHasOwnProp( value:any, path:string|Array[, options:Object] )\n Returns a boolean indicating whether an object contains a nested key path.\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path:string|Array[, options:Object] )\n Returns a function which tests whether an object contains a nested key path.\n","deepHasProp":"\ndeepHasProp( value:any, path:string|Array[, options:Object] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n","deepHasProp.factory":"\ndeepHasProp.factory( path:string|Array[, options:Object] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n","deepPluck":"\ndeepPluck( arr:Array, path:string|Array[, options:Object] )\n Extracts a nested property value from each element of an object array.\n","deepSet":"\ndeepSet( obj:ObjectLike, path:string|Array, value:any[, options:Object] )\n Sets a nested property value.\n","deepSet.factory":"\ndeepSet.factory( path:string|Array[, options:Object] )\n Creates a reusable deep set function.\n","defineMemoizedProperty":"\ndefineMemoizedProperty( obj:Object, prop:string|symbol, descriptor:Object )\n Defines a memoized object property.\n","defineProperties":"\ndefineProperties( obj:Object, properties:Object )\n Defines (and/or modifies) object properties.\n","defineProperty":"\ndefineProperty( obj:Object, prop:string|symbol, descriptor:Object )\n Defines (or modifies) an object property.\n","dirname":"\ndirname( path:string )\n Returns a directory name.\n","dotcase":"\ndotcase( str:string )\n Converts a string to dot case.\n","DoublyLinkedList":"\nDoublyLinkedList()\n Doubly linked list constructor.\n","doUntil":"\ndoUntil( fcn:Function, predicate:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","doUntilAsync":"\ndoUntilAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","doUntilEach":"\ndoUntilEach( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n","doUntilEachRight":"\ndoUntilEachRight( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","doWhile":"\ndoWhile( fcn:Function, predicate:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","doWhileAsync":"\ndoWhileAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","doWhileEach":"\ndoWhileEach( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection.\n","doWhileEachRight":"\ndoWhileEachRight( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","dswap":"\ndswap( x:ndarray, y:ndarray )\n Interchanges two double-precision floating-point vectors.\n","E":"\nE\n Euler's number.\n","EMOJI":"\nEMOJI()\n Returns an emoji database.\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n Returns an object mapping emoji codes to pictographs.\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n Returns an object mapping emoji pictographs to codes.\n","emptyStream":"\nemptyStream( [options:Object] )\n Returns an \"empty\" readable stream.\n","emptyStream.factory":"\nemptyStream.factory( [options:Object] )\n Returns a function for creating empty readable streams.\n","emptyStream.objectMode":"\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n","endsWith":"\nendsWith( str:string, search:string[, len:integer] )\n Tests if a string ends with the characters of another string.\n","enumerableProperties":"\nenumerableProperties( value:any )\n Returns an array of an object's own enumerable property names and symbols.\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value:any )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value:any )\n Returns an array of an object's own enumerable symbol properties.\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n","ENV":"\nENV\n An object containing the user environment.\n","EPS":"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n","error2json":"\nerror2json( error:Error )\n Returns a JSON representation of an error object.\n","EULERGAMMA":"\nEULERGAMMA\n The Euler-Mascheroni constant.\n","every":"\nevery( collection:Array|TypedArray|Object )\n Tests whether all elements in a collection are truthy.\n","everyBy":"\neveryBy( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n","everyByAsync":"\neveryByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n","everyByAsync.factory":"\neveryByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n","everyByRight":"\neveryByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n","everyByRightAsync":"\neveryByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n","evil":"\nevil( str:string )\n Alias for `eval` global.\n","EXEC_PATH":"\nEXEC_PATH\n Absolute pathname of the executable which started the current Node.js\n process.\n","exists":"\nexists( path:string|Buffer, clbk:Function )\n Asynchronously tests whether a path exists on the filesystem.\n","exists.sync":"\nexists.sync( path:string|Buffer )\n Synchronously tests whether a path exists on the filesystem.\n","expandAcronyms":"\nexpandAcronyms( str:string )\n Expands acronyms in a string.\n","expandContractions":"\nexpandContractions( str:string )\n Expands all contractions to their formal equivalents.\n","extname":"\nextname( filename:string )\n Returns a filename extension.\n","FancyArray":"\nFancyArray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string[, options:Object] )\n Returns a FancyArray instance.\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","FancyArray.prototype.data":"\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n Underlying data type.\n","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","FancyArray.prototype.length":"\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n Number of dimensions.\n","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","FancyArray.prototype.order":"\nFancyArray.prototype.order\n Array order.\n","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n Array shape.\n","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n","fastmath.abs":"\nfastmath.abs( x:number )\n Computes an absolute value.\n","fastmath.acosh":"\nfastmath.acosh( x:number )\n Computes the hyperbolic arccosine of a number.\n","fastmath.ampbm":"\nfastmath.ampbm( x:number, y:number )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha:number, beta:number, [nonnegative:boolean[, \n ints:boolean]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n","fastmath.asinh":"\nfastmath.asinh( x:number )\n Computes the hyperbolic arcsine of a number.\n","fastmath.atanh":"\nfastmath.atanh( x:number )\n Computes the hyperbolic arctangent of a number.\n","fastmath.hypot":"\nfastmath.hypot( x:number, y:number )\n Computes the hypotenuse.\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x:uinteger )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n","fastmath.max":"\nfastmath.max( x:number, y:number )\n Returns the maximum value.\n","fastmath.min":"\nfastmath.min( x:number, y:number )\n Returns the minimum value.\n","fastmath.powint":"\nfastmath.powint( x:number, y:integer )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x:uinteger )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n","FIFO":"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n","filledarray":"\nfilledarray( [dtype:string] )\n Creates a filled array.\n\nfilledarray( value:any, length:integer[, dtype:string] )\n Returns a filled array having a specified length.\n\nfilledarray( value:any, array:ArrayLikeObject[, dtype:string] )\n Creates a filled array from another array (or array-like object).\n\nfilledarray( value:any, iterable:Iterable[, dtype:string] )\n Creates a filled array from an iterable.\n\nfilledarray( value:any, buffer:ArrayBuffer[, byteOffset:integer[, \n length:integer]][, dtype:string] )\n Returns a filled typed array view of an ArrayBuffer.\n","filledarrayBy":"\nfilledarrayBy( [dtype:string] )\n Creates a filled array.\n\nfilledarrayBy( length:integer[, dtype:string], clbk:Function[, thisArg:any] )\n Returns a filled array according to a provided callback function and having\n a specified length.\n\nfilledarrayBy( array:ArrayLikeObject[, dtype:string], clbk:Function[, \n thisArg:any] )\n Creates a filled array from another array (or array-like object) according\n to a provided callback function.\n\nfilledarrayBy( iterable:Iterable[, dtype:string], clbk:Function[, thisArg:any] )\n Creates a filled array from an iterable according to a provided callback\n function.\n\nfilledarrayBy( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string], clbk:Function[, thisArg:any] )\n Returns a filled typed array view of an ArrayBuffer according to a provided\n callback function.\n","filterArguments":"\nfilterArguments( fcn:Function, predicate:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n","find":"\nfind( arr:Array|TypedArray|string, [options:Object,] clbk:Function )\n Finds elements in an array-like object that satisfy a test condition.\n","firstChar":"\nfirstChar( str:string[, n:integer][, options:Object] )\n Returns the first character(s) of a string.\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n Returns FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n","flattenArray":"\nflattenArray( arr:ArrayLikeObject[, options:Object] )\n Flattens an array.\n","flattenArray.factory":"\nflattenArray.factory( dims:ArrayLike[, options:Object] )\n Returns a function for flattening arrays having specified dimensions.\n","flattenObject":"\nflattenObject( obj:ObjectLike[, options:Object] )\n Flattens an object.\n","flattenObject.factory":"\nflattenObject.factory( [options:Object] )\n Returns a function to flatten an object.\n","flignerTest":"\nflignerTest( ...x:Array[, options:Object] )\n Computes the Fligner-Killeen test for equal variances.\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n Platform float word order.\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n","FLOAT16_EPS":"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n","FLOAT16_MAX":"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n","FLOAT16_NINF":"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n","FLOAT16_PINF":"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n","FLOAT32_EPS":"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n","FLOAT32_MAX":"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n","FLOAT32_NAN":"\nFLOAT32_NAN\n Single-precision floating-point NaN.\n","FLOAT32_NINF":"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n","FLOAT32_PINF":"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n","Float32Array":"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\nFloat32Array( length:integer )\n Returns a typed array having a specified length.\n\nFloat32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nFloat32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nFloat32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Float32Array.from":"\nFloat32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Float32Array.of":"\nFloat32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float32Array.name":"\nFloat32Array.name\n Typed array constructor name.\n","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n","FLOAT64_MAX":"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n","Float64Array":"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\nFloat64Array( length:integer )\n Returns a typed array having a specified length.\n\nFloat64Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nFloat64Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nFloat64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Float64Array.from":"\nFloat64Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Float64Array.of":"\nFloat64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float64Array.name":"\nFloat64Array.name\n Typed array constructor name.\n","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","forEach":"\nforEach( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection.\n","forEachAsync":"\nforEachAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection.\n","forEachAsync.factory":"\nforEachAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection.\n","forEachChar":"\nforEachChar( str:string, [options:Object,] clbk:Function[, thisArg:any] )\n Invokes a function for each character in a string.\n","forEachRight":"\nforEachRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n","forEachRightAsync":"\nforEachRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n","forIn":"\nforIn( obj:Object, fcn:Function[, thisArg:any] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n","forOwn":"\nforOwn( obj:Object, fcn:Function[, thisArg:any] )\n Invokes a function for each own enumerable property of an object.\n","FOURTH_PI":"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n","fromCodePoint":"\nfromCodePoint( ...pt:integer )\n Creates a string from a sequence of Unicode code points.\n","Function":"\nFunction( [...argNames:any,] body:string )\n Returns a Function object.\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg:any, args:Array )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n","Function.prototype.call":"\nFunction.prototype.call( thisArg:any, ...args:any )\n Calls a function with a given `this` value and arguments provided\n individually.\n","Function.prototype.bind":"\nFunction.prototype.bind( thisArg:any, ...args:any )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n","Function.prototype.toString":"\nFunction.prototype.toString()\n Returns a string representation of the function.\n","Function.prototype.length":"\nFunction.prototype.length\n The number of arguments expected by the function.\n","Function.prototype.name":"\nFunction.prototype.name\n The name of the function.\n","Function.prototype.prototype":"\nFunction.prototype.prototype\n The prototype of the function.\n","function2string":"\nfunction2string( fcn:Function )\n Returns a string representing the source code of a provided function.\n","functionName":"\nfunctionName( fcn:Function )\n Returns the name of a function.\n","functionSequence":"\nfunctionSequence( ...fcn:Function )\n Returns a pipeline function.\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn:Function )\n Returns a pipeline function.\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n","gdot":"\ngdot( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n Computes the dot product of two vectors.\n","getegid":"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n","geteuid":"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n","getgid":"\ngetgid()\n Returns the numeric group identity of the calling process.\n","getGlobal":"\ngetGlobal( [codegen:boolean] )\n Returns the global object.\n","getPrototypeOf":"\ngetPrototypeOf( value:any )\n Returns the prototype of a provided object.\n","getuid":"\ngetuid()\n Returns the numeric user identity of the calling process.\n","GLAISHER":"\nGLAISHER\n Glaisher-Kinkelin constant.\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src:string[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over each grapheme cluster in a string.\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src:string[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over each grapheme\n cluster in a string.\n","group":"\ngroup( collection:Array|TypedArray|Object, [options:Object,] \n groups:Array|TypedArray|Object )\n Groups values as arrays associated with distinct keys.\n","groupBy":"\ngroupBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Groups values according to an indicator function.\n","groupByAsync":"\ngroupByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Groups values according to an indicator function.\n","groupByAsync.factory":"\ngroupByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which groups values according to an indicator function.\n","groupIn":"\ngroupIn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n Group values according to an indicator function.\n","groupOwn":"\ngroupOwn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n Group values according to an indicator function.\n","gswap":"\ngswap( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n Interchanges two vectors.\n","HALF_LN2":"\nHALF_LN2\n One half times the natural logarithm of `2`.\n","HALF_PI":"\nHALF_PI\n One half times the mathematical constant `π`.\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n Tests for native `BigInt64Array` support.\n","hasBigIntSupport":"\nhasBigIntSupport()\n Tests for native `BigInt` support.\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n Tests for native `BigUint64Array` support.\n","hasClassSupport":"\nhasClassSupport()\n Tests for native `class` support.\n","hasDataViewSupport":"\nhasDataViewSupport()\n Tests for native `DataView` support.\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n Tests for native function `name` support.\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n Tests whether an environment supports native generator functions.\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n Tests for `globalThis` support.\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n","hasMapSupport":"\nhasMapSupport()\n Tests for native `Map` support.\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n","hasOwnProp":"\nhasOwnProp( value:any, property:any )\n Tests if an object has a specified property.\n","hasProp":"\nhasProp( value:any, property:any )\n Tests if an object has a specified property, either own or inherited.\n","hasProxySupport":"\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n","hasSetSupport":"\nhasSetSupport()\n Tests for native `Set` support.\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n","hasSymbolSupport":"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n Tests for native `toStringTag` support.\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n Tests for native `Uint16Array` support.\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n Tests for native `Uint32Array` support.\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str:string, pos:integer )\n Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n","headercase":"\nheadercase( str:string )\n Converts a string to HTTP header case.\n","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n","homedir":"\nhomedir()\n Returns the current user's home directory.\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n Number of hours in a day.\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n Number of hours in a week.\n","hoursInMonth":"\nhoursInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of hours in a month.\n","hoursInYear":"\nhoursInYear( [value:integer|Date] )\n Returns the number of hours in a year according to the Gregorian calendar.\n","httpServer":"\nhttpServer( [options:Object,] [requestListener:Function] )\n Returns a function to create an HTTP server.\n","identity":"\nidentity( x:any )\n Identity function.\n","ifelse":"\nifelse( bool:boolean, x:any, y:any )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n","ifelseAsync":"\nifelseAsync( predicate:Function, x:any, y:any, done:Function )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n","ifthen":"\nifthen( bool:boolean, x:Function, y:Function )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n","ifthenAsync":"\nifthenAsync( predicate:Function, x:Function, y:Function, done:Function )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n","imag":"\nimag( z:Complex128 )\n Returns the imaginary component of a double-precision complex floating-point\n number.\n","imagf":"\nimagf( z:Complex64 )\n Returns the imaginary component of a single-precision complex floating-point\n number.\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium ostrowskianum*.\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n","incrapcorr":"\nincrapcorr( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n","incrBinaryClassification":"\nincrBinaryClassification( N:integer[, options:Object] )\n Returns an accumulator function which incrementally performs binary\n classification using stochastic gradient descent (SGD).\n","incrcount":"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n","incrcovariance":"\nincrcovariance( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n","incrcovmat":"\nincrcovmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n","incrcv":"\nincrcv( [mean:number] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n","increwmean":"\nincrewmean( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n","increwstdev":"\nincrewstdev( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n","increwvariance":"\nincrewvariance( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n","incrgmean":"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n","incrgrubbs":"\nincrgrubbs( [options:Object] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n","incrhmean":"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n","incrkmeans":"\nincrkmeans( k:integer|ndarray[, ndims:integer][, options:Object] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n","incrkurtosis":"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n","incrmaape":"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n","incrmae":"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n","incrmapcorr":"\nincrmapcorr( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n","incrmape":"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n","incrmax":"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n","incrmaxabs":"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n","incrmcovariance":"\nincrmcovariance( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n","incrmcv":"\nincrmcv( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n","incrmda":"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n","incrme":"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n","incrmean":"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n","incrmeanabs":"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n","incrmeanabs2":"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n","incrmeanstdev":"\nincrmeanstdev( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n","incrmeanvar":"\nincrmeanvar( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n","incrmgmean":"\nincrmgmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n","incrmgrubbs":"\nincrmgrubbs( W:integer[, options:Object] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n","incrmhmean":"\nincrmhmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n","incrmidrange":"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n","incrmin":"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n","incrminabs":"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n","incrminmax":"\nincrminmax( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n","incrminmaxabs":"\nincrminmaxabs( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n","incrmmaape":"\nincrmmaape( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n","incrmmae":"\nincrmmae( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n","incrmmape":"\nincrmmape( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n","incrmmax":"\nincrmmax( W:integer )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n","incrmmaxabs":"\nincrmmaxabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n","incrmmda":"\nincrmmda( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n","incrmme":"\nincrmme( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n","incrmmean":"\nincrmmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n","incrmmeanabs":"\nincrmmeanabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n","incrmmeanabs2":"\nincrmmeanabs2( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n","incrmmeanstdev":"\nincrmmeanstdev( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n","incrmmeanvar":"\nincrmmeanvar( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n","incrmmidrange":"\nincrmmidrange( W:integer )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n","incrmmin":"\nincrmmin( W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n","incrmminabs":"\nincrmminabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n","incrmminmax":"\nincrmminmax( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n","incrmminmaxabs":"\nincrmminmaxabs( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n","incrmmpe":"\nincrmmpe( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n","incrmmse":"\nincrmmse( W:integer )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n","incrmpcorr":"\nincrmpcorr( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n","incrmpcorr2":"\nincrmpcorr2( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n","incrmpcorrdist":"\nincrmpcorrdist( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n","incrmpe":"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n","incrmprod":"\nincrmprod( W:integer )\n Returns an accumulator function which incrementally computes a moving\n product.\n","incrmrange":"\nincrmrange( W:integer )\n Returns an accumulator function which incrementally computes a moving range.\n","incrmrmse":"\nincrmrmse( W:integer )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n","incrmrss":"\nincrmrss( W:integer )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n","incrmse":"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n","incrmstdev":"\nincrmstdev( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n","incrmsum":"\nincrmsum( W:integer )\n Returns an accumulator function which incrementally computes a moving sum.\n","incrmsumabs":"\nincrmsumabs( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n","incrmsumabs2":"\nincrmsumabs2( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n","incrmsummary":"\nincrmsummary( W:integer )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n","incrmsumprod":"\nincrmsumprod( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n","incrmvariance":"\nincrmvariance( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n","incrmvmr":"\nincrmvmr( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n","incrnancount":"\nincrnancount()\n Returns an accumulator function which incrementally updates a count,\n ignoring `NaN` values.\n","incrnansum":"\nincrnansum()\n Returns an accumulator function which incrementally computes a sum, ignoring\n `NaN` values.\n","incrnansumabs":"\nincrnansumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values, ignoring NaN values.\n","incrnansumabs2":"\nincrnansumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values, ignoring NaN values.\n","incrpcorr":"\nincrpcorr( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n","incrpcorr2":"\nincrpcorr2( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n","incrpcorrdist":"\nincrpcorrdist( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n","incrpcorrdistmat":"\nincrpcorrdistmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n","incrpcorrmat":"\nincrpcorrmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n","incrprod":"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n","incrrange":"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n","incrrmse":"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n","incrrss":"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n","incrskewness":"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n","incrspace":"\nincrspace( start:number, stop:number[, increment:number] )\n Generates a linearly spaced numeric array using a provided increment.\n","incrstdev":"\nincrstdev( [mean:number] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n","incrsum":"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n","incrsumabs":"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n","incrsumabs2":"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n","incrsummary":"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n","incrsumprod":"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n","incrvariance":"\nincrvariance( [mean:number] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n","incrvmr":"\nincrvmr( [mean:number] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n","incrwmean":"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n","ind2sub":"\nind2sub( shape:ArrayLike, idx:integer[, options:Object] )\n Converts a linear index to an array of subscripts.\n","ind2sub.assign":"\nind2sub.assign( shape:ArrayLike, idx:integer[, options:Object], \n out:Array|TypedArray|Object )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n","indexOf":"\nindexOf( arr:ArrayLike, searchElement:any[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","inherit":"\ninherit( ctor:Object|Function, superCtor:Object|Function )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable symbol properties.\n","inheritedKeys":"\ninheritedKeys( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable property names.\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable property names.\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n","inheritedProperties":"\ninheritedProperties( value:any[, level:integer] )\n Returns an array of an object's inherited property names and symbols.\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value:any, property:string|symbol[, \n level:integer] )\n Returns a property descriptor for an object's inherited property.\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value:any[, level:integer] )\n Returns an object's inherited property descriptors.\n","inheritedPropertyNames":"\ninheritedPropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited symbol properties.\n","inheritedWritableProperties":"\ninheritedWritableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited writable property names and\n symbols.\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited writable property names.\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited writable symbol properties.\n","inmap":"\ninmap( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n","inmapAsync":"\ninmapAsync( collection:Array|TypedArray|Object, [options:Object,] fcn:Function, \n done:Function )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n","inmapAsync.factory":"\ninmapAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n","inmapRight":"\ninmapRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n","inmapRightAsync":"\ninmapRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n","inspectSinkStream":"\ninspectSinkStream( [options:Object,] clbk:Function )\n Returns a writable stream for inspecting stream data.\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options:Object] )\n Returns a function for creating writable streams for inspecting stream data.\n","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options:Object,] clbk:Function )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n","inspectStream":"\ninspectStream( [options:Object,] clbk:Function )\n Returns a transform stream for inspecting stream data.\n","inspectStream.factory":"\ninspectStream.factory( [options:Object] )\n Returns a function for creating transform streams for inspecting stream\n data.\n","inspectStream.objectMode":"\ninspectStream.objectMode( [options:Object,] clbk:Function )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n","instanceOf":"\ninstanceOf( value:any, constructor:Function )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n","INT8_MAX":"\nINT8_MAX\n Maximum signed 8-bit integer.\n","INT8_MIN":"\nINT8_MIN\n Minimum signed 8-bit integer.\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n","Int8Array":"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\nInt8Array( length:integer )\n Returns a typed array having a specified length.\n\nInt8Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt8Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int8Array.from":"\nInt8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int8Array.of":"\nInt8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int8Array.name":"\nInt8Array.name\n Typed array constructor name.\n","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int8Array.prototype.length":"\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n Serializes an array as a string.\n","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","INT16_MAX":"\nINT16_MAX\n Maximum signed 16-bit integer.\n","INT16_MIN":"\nINT16_MIN\n Minimum signed 16-bit integer.\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n","Int16Array":"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\nInt16Array( length:integer )\n Returns a typed array having a specified length.\n\nInt16Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt16Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int16Array.from":"\nInt16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int16Array.of":"\nInt16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int16Array.name":"\nInt16Array.name\n Typed array constructor name.\n","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int16Array.prototype.length":"\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n Serializes an array as a string.\n","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","INT32_MAX":"\nINT32_MAX\n Maximum signed 32-bit integer.\n","INT32_MIN":"\nINT32_MIN\n Minimum signed 32-bit integer.\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n","Int32Array":"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\nInt32Array( length:integer )\n Returns a typed array having a specified length.\n\nInt32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int32Array.from":"\nInt32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int32Array.of":"\nInt32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int32Array.name":"\nInt32Array.name\n Typed array constructor name.\n","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int32Array.prototype.length":"\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n Serializes an array as a string.\n","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n","IS_BROWSER":"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n","IS_DARWIN":"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n","IS_ELECTRON":"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n","IS_NODE":"\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n","IS_WINDOWS":"\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n","isAbsolutePath":"\nisAbsolutePath( value:any )\n Tests if a value is an absolute path.\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value:any )\n Tests if a value is a POSIX absolute path.\n","isAbsolutePath.win32":"\nisAbsolutePath.win32( value:any )\n Tests if a value is a Windows absolute path.\n","isAccessorArray":"\nisAccessorArray( value:any )\n Tests if a value is an array-like object supporting the accessor (get/set)\n protocol.\n","isAccessorProperty":"\nisAccessorProperty( value:any, property:any )\n Tests if an object's own property has an accessor descriptor.\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property has an accessor descriptor.\n","isAlphagram":"\nisAlphagram( value:any )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n","isAlphaNumeric":"\nisAlphaNumeric( str:string )\n Tests whether a string contains only alphanumeric characters.\n","isAnagram":"\nisAnagram( str:string, value:any )\n Tests if a value is an anagram.\n","isArguments":"\nisArguments( value:any )\n Tests if a value is an arguments object.\n","isArray":"\nisArray( value:any )\n Tests if a value is an array.\n","isArrayArray":"\nisArrayArray( value:any )\n Tests if a value is an array of arrays.\n","isArrayBuffer":"\nisArrayBuffer( value:any )\n Tests if a value is an ArrayBuffer.\n","isArrayBufferView":"\nisArrayBufferView( value:any )\n Tests if a value is a `ArrayBuffer` view.\n","isArrayLength":"\nisArrayLength( value:any )\n Tests if a value is a valid array length.\n","isArrayLike":"\nisArrayLike( value:any )\n Tests if a value is array-like.\n","isArrayLikeObject":"\nisArrayLikeObject( value:any )\n Tests if a value is an array-like object.\n","isASCII":"\nisASCII( str:string )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n","isBetween":"\nisBetween( value:any, a:any, b:any[, left:string, right:string] )\n Tests if a value is between two values.\n","isBetweenArray":"\nisBetweenArray( value:any, a:any, b:any[, left:string, right:string] )\n Tests if a value is an array-like object where every element is between two\n values.\n","isBigInt":"\nisBigInt( value:any )\n Tests if a value is a BigInt.\n","isBigInt64Array":"\nisBigInt64Array( value:any )\n Tests if a value is a BigInt64Array.\n","isBigUint64Array":"\nisBigUint64Array( value:any )\n Tests if a value is a BigUint64Array.\n","isBinaryString":"\nisBinaryString( value:any )\n Tests if a value is a binary string.\n","isBlankString":"\nisBlankString( value:any )\n Tests if a value is a blank string (i.e., an empty string or a string\n consisting only of whitespace characters).\n","isBoolean":"\nisBoolean( value:any )\n Tests if a value is a boolean.\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value:any )\n Tests if a value is a boolean primitive.\n","isBoolean.isObject":"\nisBoolean.isObject( value:any )\n Tests if a value is a boolean object.\n","isBooleanArray":"\nisBooleanArray( value:any )\n Tests if a value is an array-like object of booleans.\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value:any )\n Tests if a value is an array-like object containing only boolean primitives.\n","isBooleanArray.objects":"\nisBooleanArray.objects( value:any )\n Tests if a value is an array-like object containing only Boolean objects.\n","isBoxedPrimitive":"\nisBoxedPrimitive( value:any )\n Tests if a value is a JavaScript boxed primitive.\n","isBuffer":"\nisBuffer( value:any )\n Tests if a value is a Buffer instance.\n","isCapitalized":"\nisCapitalized( value:any )\n Tests if a value is a string having an uppercase first character.\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value:any )\n Tests if a value is a matrix which is symmetric about its center.\n","isCircular":"\nisCircular( value:any )\n Tests if an object-like value contains a circular reference.\n","isCircularArray":"\nisCircularArray( value:any )\n Tests if a value is an array containing a circular reference.\n","isCircularPlainObject":"\nisCircularPlainObject( value:any )\n Tests if a value is a plain object containing a circular reference.\n","isClass":"\nisClass( value:any )\n Tests if a value is a class.\n","isCollection":"\nisCollection( value:any )\n Tests if a value is a collection.\n","isComplex":"\nisComplex( value:any )\n Tests if a value is a 64-bit or 128-bit complex number.\n","isComplex64":"\nisComplex64( value:any )\n Tests if a value is a 64-bit complex number.\n","isComplex64Array":"\nisComplex64Array( value:any )\n Tests if a value is a Complex64Array.\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing single-precision\n complex floating-point numbers.\n","isComplex64VectorLike":"\nisComplex64VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n","isComplex128":"\nisComplex128( value:any )\n Tests if a value is a 128-bit complex number.\n","isComplex128Array":"\nisComplex128Array( value:any )\n Tests if a value is a Complex128Array.\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing double-precision\n complex floating-point numbers.\n","isComplex128VectorLike":"\nisComplex128VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n","isComplexLike":"\nisComplexLike( value:any )\n Tests if a value is a complex number-like object.\n","isComplexTypedArray":"\nisComplexTypedArray( value:any )\n Tests if a value is a complex typed array.\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value:any )\n Tests if a value is complex-typed-array-like.\n","isComposite":"\nisComposite( value:any )\n Tests if a value is a composite number.\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value:any )\n Tests if a value is a number primitive which is a composite number.\n","isComposite.isObject":"\nisComposite.isObject( value:any )\n Tests if a value is a number object having a value which is a composite\n number.\n","isConfigurableProperty":"\nisConfigurableProperty( value:any, property:any )\n Tests if an object's own property is configurable.\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is configurable.\n","isCubeNumber":"\nisCubeNumber( value:any )\n Tests if a value is a cube number.\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a cube number.\n","isCubeNumber.isObject":"\nisCubeNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a cube number.\n","isDataProperty":"\nisDataProperty( value:any, property:any )\n Tests if an object's own property has a data descriptor.\n","isDataPropertyIn":"\nisDataPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property has a data descriptor.\n","isDataView":"\nisDataView( value:any )\n Tests if a value is a DataView.\n","isDateObject":"\nisDateObject( value:any )\n Tests if a value is a Date object.\n","isDateObjectArray":"\nisDateObjectArray( value:any )\n Tests if a value is an array-like object containing only Date objects.\n","isDigitString":"\nisDigitString( str:string )\n Tests whether a string contains only numeric digits.\n","isEmailAddress":"\nisEmailAddress( value:any )\n Tests if a value is an email address.\n","isEmptyArray":"\nisEmptyArray( value:any )\n Tests if a value is an empty array.\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value:any )\n Tests if a value is an empty array-like object.\n","isEmptyCollection":"\nisEmptyCollection( value:any )\n Tests if a value is an empty collection.\n","isEmptyObject":"\nisEmptyObject( value:any )\n Tests if a value is an empty object.\n","isEmptyString":"\nisEmptyString( value:any )\n Tests if a value is an empty string.\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value:any )\n Tests if a value is an empty string primitive.\n","isEmptyString.isObject":"\nisEmptyString.isObject( value:any )\n Tests if a value is an empty `String` object.\n","isEnumerableProperty":"\nisEnumerableProperty( value:any, property:any )\n Tests if an object's own property is enumerable.\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is enumerable.\n","isError":"\nisError( value:any )\n Tests if a value is an Error object.\n","isEvalError":"\nisEvalError( value:any )\n Tests if a value is an EvalError object.\n","isEven":"\nisEven( value:any )\n Tests if a value is an even number.\n","isEven.isPrimitive":"\nisEven.isPrimitive( value:any )\n Tests if a value is a number primitive that is an even number.\n","isEven.isObject":"\nisEven.isObject( value:any )\n Tests if a value is a number object that is an even number.\n","isFalsy":"\nisFalsy( value:any )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n","isFalsyArray":"\nisFalsyArray( value:any )\n Tests if a value is an array-like object containing only falsy values.\n","isFinite":"\nisFinite( value:any )\n Tests if a value is a finite number.\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a finite value.\n","isFinite.isObject":"\nisFinite.isObject( value:any )\n Tests if a value is a number object having a finite value.\n","isFiniteArray":"\nisFiniteArray( value:any )\n Tests if a value is an array-like object of finite numbers.\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n","isFiniteArray.objects":"\nisFiniteArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n","isFloat32Array":"\nisFloat32Array( value:any )\n Tests if a value is a Float32Array.\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing single-precision\n floating-point numbers.\n","isFloat32VectorLike":"\nisFloat32VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n","isFloat64Array":"\nisFloat64Array( value:any )\n Tests if a value is a Float64Array.\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing double-precision\n floating-point numbers.\n","isFloat64VectorLike":"\nisFloat64VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n","isFunction":"\nisFunction( value:any )\n Tests if a value is a function.\n","isFunctionArray":"\nisFunctionArray( value:any )\n Tests if a value is an array-like object containing only functions.\n","isGeneratorObject":"\nisGeneratorObject( value:any )\n Tests if a value is a generator object.\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value:any )\n Tests if a value is generator object-like.\n","isgzipBuffer":"\nisgzipBuffer( value:any )\n Tests if a value is a gzip buffer.\n","isHexString":"\nisHexString( str:string )\n Tests whether a string contains only hexadecimal digits.\n","isInfinite":"\nisInfinite( value:any )\n Tests if a value is an infinite number.\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value:any )\n Tests if a value is a number primitive having an infinite value.\n","isInfinite.isObject":"\nisInfinite.isObject( value:any )\n Tests if a value is a number object having an infinite value.\n","isInheritedProperty":"\nisInheritedProperty( value:any, property:any )\n Tests if an object has an inherited property.\n","isInt8Array":"\nisInt8Array( value:any )\n Tests if a value is an Int8Array.\n","isInt16Array":"\nisInt16Array( value:any )\n Tests if a value is an Int16Array.\n","isInt32Array":"\nisInt32Array( value:any )\n Tests if a value is an Int32Array.\n","isInteger":"\nisInteger( value:any )\n Tests if a value is an integer.\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having an integer value.\n","isInteger.isObject":"\nisInteger.isObject( value:any )\n Tests if a value is a number object having an integer value.\n","isIntegerArray":"\nisIntegerArray( value:any )\n Tests if a value is an array-like object of integer values.\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive integer\n values.\n","isIntegerArray.objects":"\nisIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n","isIterableLike":"\nisIterableLike( value:any )\n Tests if a value is iterable-like.\n","isIteratorLike":"\nisIteratorLike( value:any )\n Tests if a value is iterator-like.\n","isJSON":"\nisJSON( value:any )\n Tests if a value is a parseable JSON string.\n","isLeapYear":"\nisLeapYear( value:any )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n","isLocalhost":"\nisLocalhost( value:any )\n Tests whether a value is a localhost hostname.\n","isLowercase":"\nisLowercase( value:any )\n Tests if a value is a lowercase string.\n","isMatrixLike":"\nisMatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object.\n","isMethod":"\nisMethod( value:any, property:any )\n Tests if an object has a specified method name.\n","isMethodIn":"\nisMethodIn( value:any, property:any )\n Tests if an object has a specified method name, either own or inherited.\n","isMultiSlice":"\nisMultiSlice( value:any )\n Tests if a value is a MultiSlice object.\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value:any )\n Tests if a value is named typed tuple-like.\n","isnan":"\nisnan( value:any )\n Tests if a value is NaN.\n","isnan.isPrimitive":"\nisnan.isPrimitive( value:any )\n Tests if a value is a NaN number primitive.\n","isnan.isObject":"\nisnan.isObject( value:any )\n Tests if a value is a number object having a value of NaN.\n","isNaNArray":"\nisNaNArray( value:any )\n Tests if a value is an array-like object containing only NaN values.\n","isNaNArray.primitives":"\nisNaNArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n","isNaNArray.objects":"\nisNaNArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n","isNativeFunction":"\nisNativeFunction( value:any )\n Tests if a value is a native function.\n","isndarrayLike":"\nisndarrayLike( value:any )\n Tests if a value is ndarray-like.\n","isNegativeInteger":"\nisNegativeInteger( value:any )\n Tests if a value is a negative integer.\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a negative integer value.\n","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value:any )\n Tests if a value is a number object having a negative integer value.\n","isNegativeIntegerArray":"\nisNegativeIntegerArray( value:any )\n Tests if a value is an array-like object containing only negative integers.\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n","isNegativeNumber":"\nisNegativeNumber( value:any )\n Tests if a value is a negative number.\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a negative value.\n","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value:any )\n Tests if a value is a number object having a negative value.\n","isNegativeNumberArray":"\nisNegativeNumberArray( value:any )\n Tests if a value is an array-like object containing only negative numbers.\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n","isNegativeZero":"\nisNegativeZero( value:any )\n Tests if a value is negative zero.\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value:any )\n Tests if a value is a number primitive equal to negative zero.\n","isNegativeZero.isObject":"\nisNegativeZero.isObject( value:any )\n Tests if a value is a number object having a value equal to negative zero.\n","isNodeBuiltin":"\nisNodeBuiltin( str:string )\n Tests whether a string matches a Node.js built-in module name.\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value:any )\n Tests if a value is Node duplex stream-like.\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value:any )\n Tests if a value is Node readable stream-like.\n","isNodeREPL":"\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n","isNodeStreamLike":"\nisNodeStreamLike( value:any )\n Tests if a value is Node stream-like.\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value:any )\n Tests if a value is Node transform stream-like.\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value:any )\n Tests if a value is Node writable stream-like.\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value:any, property:any )\n Tests if an object's own property is non-configurable.\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is non-configurable.\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value:any, property:any )\n Tests if an object's own property is non-enumerable.\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is non-enumerable.\n","isNonNegativeFinite":"\nisNonNegativeFinite( value:any )\n Tests if a value is a nonnegative finite number.\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative finite value.\n","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value:any )\n Tests if a value is a number object having a nonnegative finite value.\n","isNonNegativeInteger":"\nisNonNegativeInteger( value:any )\n Tests if a value is a nonnegative integer.\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative integer value.\n","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value:any )\n Tests if a value is a number object having a nonnegative integer value.\n","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value:any )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n","isNonNegativeNumber":"\nisNonNegativeNumber( value:any )\n Tests if a value is a nonnegative number.\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative value.\n","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value:any )\n Tests if a value is a number object having a nonnegative value.\n","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value:any )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n","isNonPositiveInteger":"\nisNonPositiveInteger( value:any )\n Tests if a value is a nonpositive integer.\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive integer value.\n","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value:any )\n Tests if a value is a number object having a nonpositive integer value.\n","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value:any )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n","isNonPositiveNumber":"\nisNonPositiveNumber( value:any )\n Tests if a value is a nonpositive number.\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive value.\n","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value:any )\n Tests if a value is a number object having a nonpositive value.\n","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value:any )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value:any )\n Tests if a value is a non-symmetric matrix.\n","isNull":"\nisNull( value:any )\n Tests if a value is null.\n","isNullArray":"\nisNullArray( value:any )\n Tests if a value is an array-like object containing only null values.\n","isNumber":"\nisNumber( value:any )\n Tests if a value is a number.\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value:any )\n Tests if a value is a number primitive.\n","isNumber.isObject":"\nisNumber.isObject( value:any )\n Tests if a value is a `Number` object.\n","isNumberArray":"\nisNumberArray( value:any )\n Tests if a value is an array-like object containing only numbers.\n","isNumberArray.primitives":"\nisNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only number primitives.\n","isNumberArray.objects":"\nisNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only `Number` objects.\n","isNumericArray":"\nisNumericArray( value:any )\n Tests if a value is a numeric array.\n","isObject":"\nisObject( value:any )\n Tests if a value is an object; e.g., `{}`.\n","isObjectArray":"\nisObjectArray( value:any )\n Tests if a value is an array-like object containing only objects.\n","isObjectLike":"\nisObjectLike( value:any )\n Tests if a value is object-like.\n","isOdd":"\nisOdd( value:any )\n Tests if a value is an odd number.\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value:any )\n Tests if a value is a number primitive that is an odd number.\n","isOdd.isObject":"\nisOdd.isObject( value:any )\n Tests if a value is a number object that has an odd number value.\n","isoWeeksInYear":"\nisoWeeksInYear( [year:integer] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n","isPersymmetricMatrix":"\nisPersymmetricMatrix( value:any )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n","isPlainObject":"\nisPlainObject( value:any )\n Tests if a value is a plain object.\n","isPlainObjectArray":"\nisPlainObjectArray( value:any )\n Tests if a value is an array-like object containing only plain objects.\n","isPositiveInteger":"\nisPositiveInteger( value:any )\n Tests if a value is a positive integer.\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive integer value.\n","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value:any )\n Tests if a value is a number object having a positive integer value.\n","isPositiveIntegerArray":"\nisPositiveIntegerArray( value:any )\n Tests if a value is an array-like object containing only positive integers.\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n","isPositiveNumber":"\nisPositiveNumber( value:any )\n Tests if a value is a positive number.\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive value.\n","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value:any )\n Tests if a value is a number object having a positive value.\n","isPositiveNumberArray":"\nisPositiveNumberArray( value:any )\n Tests if a value is an array-like object containing only positive numbers.\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n","isPositiveZero":"\nisPositiveZero( value:any )\n Tests if a value is positive zero.\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value:any )\n Tests if a value is a number primitive equal to positive zero.\n","isPositiveZero.isObject":"\nisPositiveZero.isObject( value:any )\n Tests if a value is a number object having a value equal to positive zero.\n","isPrime":"\nisPrime( value:any )\n Tests if a value is a prime number.\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value:any )\n Tests if a value is a number primitive which is a prime number.\n","isPrime.isObject":"\nisPrime.isObject( value:any )\n Tests if a value is a number object having a value which is a prime number.\n","isPrimitive":"\nisPrimitive( value:any )\n Tests if a value is a JavaScript primitive.\n","isPrimitiveArray":"\nisPrimitiveArray( value:any )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n","isPRNGLike":"\nisPRNGLike( value:any )\n Tests if a value is PRNG-like.\n","isProbability":"\nisProbability( value:any )\n Tests if a value is a probability.\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value:any )\n Tests if a value is a number primitive which is a probability.\n","isProbability.isObject":"\nisProbability.isObject( value:any )\n Tests if a value is a number object having a value which is a probability.\n","isProbabilityArray":"\nisProbabilityArray( value:any )\n Tests if a value is an array-like object containing only probabilities.\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n","isProbabilityArray.objects":"\nisProbabilityArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n","isPropertyKey":"\nisPropertyKey( value:any )\n Tests whether a value is a property key.\n","isPrototypeOf":"\nisPrototypeOf( value:any, proto:Object|Function )\n Tests if an object's prototype chain contains a provided prototype.\n","isRangeError":"\nisRangeError( value:any )\n Tests if a value is a RangeError object.\n","isReadableProperty":"\nisReadableProperty( value:any, property:any )\n Tests if an object's own property is readable.\n","isReadablePropertyIn":"\nisReadablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is readable.\n","isReadOnlyProperty":"\nisReadOnlyProperty( value:any, property:any )\n Tests if an object's own property is read-only.\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is read-only.\n","isReadWriteProperty":"\nisReadWriteProperty( value:any, property:any )\n Tests if an object's own property is readable and writable.\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is readable and writable.\n","isReferenceError":"\nisReferenceError( value:any )\n Tests if a value is a ReferenceError object.\n","isRegExp":"\nisRegExp( value:any )\n Tests if a value is a regular expression.\n","isRegExpString":"\nisRegExpString( value:any )\n Tests if a value is a regular expression string.\n","isRelativePath":"\nisRelativePath( value:any )\n Tests if a value is a relative path.\n","isRelativePath.posix":"\nisRelativePath.posix( value:any )\n Tests if a value is a POSIX relative path.\n","isRelativePath.win32":"\nisRelativePath.win32( value:any )\n Tests if a value is a Windows relative path.\n","isSafeInteger":"\nisSafeInteger( value:any )\n Tests if a value is a safe integer.\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a safe integer value.\n","isSafeInteger.isObject":"\nisSafeInteger.isObject( value:any )\n Tests if a value is a `Number` object having a safe integer value.\n","isSafeIntegerArray":"\nisSafeIntegerArray( value:any )\n Tests if a value is an array-like object containing only safe integers.\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n","isSameArray":"\nisSameArray( v1:any, v2:any )\n Tests if two arguments are both generic arrays and have the same values.\n","isSameComplex64":"\nisSameComplex64( v1:any, v2:any )\n Tests if two arguments are both single-precision complex floating-point\n numbers and have the same value.\n","isSameComplex64Array":"\nisSameComplex64Array( v1:any, v2:any )\n Tests if two arguments are both Complex64Arrays and have the same values.\n","isSameComplex128":"\nisSameComplex128( v1:any, v2:any )\n Tests if two arguments are both double-precision complex floating-point\n numbers and have the same value.\n","isSameComplex128Array":"\nisSameComplex128Array( v1:any, v2:any )\n Tests if two arguments are both Complex128Arrays and have the same values.\n","isSameFloat32Array":"\nisSameFloat32Array( v1:any, v2:any )\n Tests if two arguments are both Float32Arrays and have the same values.\n","isSameFloat64Array":"\nisSameFloat64Array( v1:any, v2:any )\n Tests if two arguments are both Float64Arrays and have the same values.\n","isSameNativeClass":"\nisSameNativeClass( a:any, b:any )\n Tests if two arguments have the same native class.\n","isSameType":"\nisSameType( a:any, b:any )\n Tests if two arguments have the same type.\n","isSameValue":"\nisSameValue( a:any, b:any )\n Tests if two arguments are the same value.\n","isSameValueZero":"\nisSameValueZero( a:any, b:any )\n Tests if two arguments are the same value.\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value:any )\n Tests if a value is a SharedArrayBuffer.\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value:any )\n Tests if a value is a skew-centrosymmetric matrix.\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value:any )\n Tests if a value is a skew-persymmetric matrix.\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value:any )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n","isSlice":"\nisSlice( value:any )\n Tests if a value is a Slice object.\n","isSquareMatrix":"\nisSquareMatrix( value:any )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n","isSquareNumber":"\nisSquareNumber( value:any )\n Tests if a value is a square number.\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a square number.\n","isSquareNumber.isObject":"\nisSquareNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a square number.\n","isSquareTriangularNumber":"\nisSquareTriangularNumber( value:any )\n Tests if a value is a square triangular number.\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a square triangular number.\n","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a square\n triangular number.\n","isStrictEqual":"\nisStrictEqual( a:any, b:any )\n Tests if two arguments are strictly equal.\n","isString":"\nisString( value:any )\n Tests if a value is a string.\n","isString.isPrimitive":"\nisString.isPrimitive( value:any )\n Tests if a value is a string primitive.\n","isString.isObject":"\nisString.isObject( value:any )\n Tests if a value is a `String` object.\n","isStringArray":"\nisStringArray( value:any )\n Tests if a value is an array of strings.\n","isStringArray.primitives":"\nisStringArray.primitives( value:any )\n Tests if a value is an array containing only string primitives.\n","isStringArray.objects":"\nisStringArray.objects( value:any )\n Tests if a value is an array containing only `String` objects.\n","isSymbol":"\nisSymbol( value:any )\n Tests if a value is a symbol.\n","isSymbolArray":"\nisSymbolArray( value:any )\n Tests if a value is an array-like object containing only symbols.\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value:any )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n","isSymbolArray.objects":"\nisSymbolArray.objects( value:any )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n","isSymmetricMatrix":"\nisSymmetricMatrix( value:any )\n Tests if a value is a square matrix which equals its transpose.\n","isSyntaxError":"\nisSyntaxError( value:any )\n Tests if a value is a SyntaxError object.\n","isTriangularNumber":"\nisTriangularNumber( value:any )\n Tests if a value is a triangular number.\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a triangular number.\n","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a triangular\n number.\n","isTruthy":"\nisTruthy( value:any )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n","isTruthyArray":"\nisTruthyArray( value:any )\n Tests if a value is an array-like object containing only truthy values.\n","isTypedArray":"\nisTypedArray( value:any )\n Tests if a value is a typed array.\n","isTypedArrayLength":"\nisTypedArrayLength( value:any )\n Tests if a value is a valid typed array length.\n","isTypedArrayLike":"\nisTypedArrayLike( value:any )\n Tests if a value is typed-array-like.\n","isTypeError":"\nisTypeError( value:any )\n Tests if a value is a TypeError object.\n","isUint8Array":"\nisUint8Array( value:any )\n Tests if a value is a Uint8Array.\n","isUint8ClampedArray":"\nisUint8ClampedArray( value:any )\n Tests if a value is a Uint8ClampedArray.\n","isUint16Array":"\nisUint16Array( value:any )\n Tests if a value is a Uint16Array.\n","isUint32Array":"\nisUint32Array( value:any )\n Tests if a value is a Uint32Array.\n","isUNCPath":"\nisUNCPath( value:any )\n Tests if a value is a UNC path.\n","isUndefined":"\nisUndefined( value:any )\n Tests if a value is undefined.\n","isUndefinedOrNull":"\nisUndefinedOrNull( value:any )\n Tests if a value is undefined or null.\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value:any )\n Tests if a value is an array of probabilities that sum to one.\n","isUppercase":"\nisUppercase( value:any )\n Tests if a value is an uppercase string.\n","isURI":"\nisURI( value:any )\n Tests if a value is a URI.\n","isURIError":"\nisURIError( value:any )\n Tests if a value is a URIError object.\n","isVectorLike":"\nisVectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object.\n","isWhitespace":"\nisWhitespace( str:string )\n Tests whether a string contains only white space characters.\n","isWritableProperty":"\nisWritableProperty( value:any, property:any )\n Tests if an object's own property is writable.\n","isWritablePropertyIn":"\nisWritablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is writable.\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value:any, property:any )\n Tests if an object's own property is write-only.\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is write-only.\n","iterAbs":"\niterAbs( iterator:Object )\n Returns an iterator which iteratively computes the absolute value.\n","iterAbs2":"\niterAbs2( iterator:Object )\n Returns an iterator which iteratively computes the squared absolute value.\n","iterAcos":"\niterAcos( iterator:Object )\n Returns an iterator which iteratively computes the arccosine.\n","iterAcosh":"\niterAcosh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arccosine.\n","iterAcot":"\niterAcot( iterator:Object )\n Returns an iterator which iteratively computes the inverse cotangent.\n","iterAcoth":"\niterAcoth( iterator:Object )\n Returns an iterator which iteratively computes the inverse hyperbolic\n cotangent.\n","iterAcovercos":"\niterAcovercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse coversed cosine.\n","iterAcoversin":"\niterAcoversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse coversed sine.\n","iterAdd":"\niterAdd( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n","iterAdvance":"\niterAdvance( iterator:Object[, n:integer] )\n Advances an entire iterator.\n","iterAhavercos":"\niterAhavercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse half-value versed\n cosine.\n","iterAhaversin":"\niterAhaversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse half-value versed\n sine.\n","iterAny":"\niterAny( iterator:Object )\n Tests whether at least one iterated value is truthy.\n","iterAnyBy":"\niterAnyBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n","iterAsin":"\niterAsin( iterator:Object )\n Returns an iterator which iteratively computes the arcsine.\n","iterAsinh":"\niterAsinh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arcsine.\n","iterAtan":"\niterAtan( iterator:Object )\n Returns an iterator which iteratively computes the arctangent.\n","iterAtan2":"\niterAtan2( y:Object|number, x:Object|number )\n Returns an iterator which iteratively computes the angle in the plane (in\n radians) between the positive x-axis and the ray from (0,0) to the point\n (x,y).\n","iterAtanh":"\niterAtanh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arctangent.\n","iterator2array":"\niterator2array( iterator:Object[, out:ArrayLikeObject][, mapFcn:Function[, \n thisArg:any]] )\n Creates (or fills) an array from an iterator.\n","iterator2arrayview":"\niterator2arrayview( iterator:Object, dest:ArrayLikeObject[, begin:integer[, \n end:integer]][, mapFcn:Function[, thisArg:any]] )\n Fills an array-like object view with values returned from an iterator.\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator:Object, dest:ArrayLikeObject[, \n begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n","iteratorStream":"\niteratorStream( iterator:Object[, options:Object] )\n Creates a readable stream from an iterator.\n","iteratorStream.factory":"\niteratorStream.factory( [options:Object] )\n Returns a function for creating readable streams from iterators.\n","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator:Object[, options:Object] )\n Returns an \"objectMode\" readable stream from an iterator.\n","IteratorSymbol":"\nIteratorSymbol\n Iterator symbol.\n","iterAvercos":"\niterAvercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse versed cosine.\n","iterAversin":"\niterAversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse versed sine.\n","iterawgn":"\niterawgn( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n","iterawln":"\niterawln( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n","iterawun":"\niterawun( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options:Object] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n","iterBartlettPulse":"\niterBartlettPulse( [options:Object] )\n Returns an iterator which generates a Bartlett pulse waveform.\n","iterBesselj0":"\niterBesselj0( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order zero.\n","iterBesselj1":"\niterBesselj1( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order one.\n","iterBessely0":"\niterBessely0( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order zero.\n","iterBessely1":"\niterBessely1( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order one.\n","iterBeta":"\niterBeta( x:Object|number, y:Object|number )\n Returns an iterator which iteratively evaluates the beta function.\n","iterBetaln":"\niterBetaln( x:Object|number, y:Object|number )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n beta function.\n","iterBinet":"\niterBinet( iterator:Object )\n Returns an iterator which iteratively evaluates Binet's formula extended to\n real numbers.\n","iterCbrt":"\niterCbrt( iterator:Object )\n Returns an iterator which iteratively computes the cube root.\n","iterCeil":"\niterCeil( iterator:Object )\n Returns an iterator which rounds each iterated value toward positive\n infinity.\n","iterCeil2":"\niterCeil2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward positive infinity.\n","iterCeil10":"\niterCeil10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward positive infinity.\n","iterCompositesSeq":"\niterCompositesSeq( [options:Object] )\n Returns an iterator which generates a sequence of composite numbers.\n","iterConcat":"\niterConcat( iter0:Object, ...iterator:Object )\n Returns an iterator which iterates over the values of two or more iterators.\n","iterConstant":"\niterConstant( value:any[, options:Object] )\n Returns an iterator which always returns the same value.\n","iterContinuedFraction":"\niterContinuedFraction( iterator:Object[, options:Object] )\n Evaluates the terms of a continued fraction.\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x:number[, options:Object] )\n Returns an iterator which generates a list of all continued fraction terms\n which can be obtained given the precision of `x`.\n","iterCos":"\niterCos( iterator:Object )\n Returns an iterator which iteratively computes the cosine.\n","iterCosh":"\niterCosh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic cosine.\n","iterCosineWave":"\niterCosineWave( [options:Object] )\n Returns an iterator which generates a cosine wave.\n","iterCosm1":"\niterCosm1( iterator:Object )\n Returns an iterator which iteratively computes `cos(x) - 1`.\n","iterCospi":"\niterCospi( iterator:Object )\n Returns an iterator which computes the cosine of each iterated value times\n π.\n","iterCounter":"\niterCounter( iterator:Object )\n Returns an iterator which iteratively computes the number of iterated\n values.\n","iterCovercos":"\niterCovercos( iterator:Object )\n Returns an iterator which iteratively computes the coversed cosine.\n","iterCoversin":"\niterCoversin( iterator:Object )\n Returns an iterator which iteratively computes the coversed sine.\n","iterCubesSeq":"\niterCubesSeq( [options:Object] )\n Returns an iterator which generates a sequence of cubes.\n","itercugmean":"\nitercugmean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n","itercuhmean":"\nitercuhmean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n","itercumax":"\nitercumax( iterator:Object )\n Returns an iterator which iteratively computes a cumulative maximum value.\n","itercumaxabs":"\nitercumaxabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n","itercumean":"\nitercumean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n","itercumeanabs":"\nitercumeanabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n","itercumeanabs2":"\nitercumeanabs2( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n","itercumidrange":"\nitercumidrange( iterator:Object )\n Returns an iterator which iteratively computes a cumulative mid-range.\n","itercumin":"\nitercumin( iterator:Object )\n Returns an iterator which iteratively computes a cumulative minimum value.\n","itercuminabs":"\nitercuminabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n","itercuprod":"\nitercuprod( iterator:Object )\n Returns an iterator which iteratively computes a cumulative product.\n","itercurange":"\nitercurange( iterator:Object )\n Returns an iterator which iteratively computes a cumulative range.\n","itercusum":"\nitercusum( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum.\n","itercusumabs":"\nitercusumabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n","itercusumabs2":"\nitercusumabs2( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n","iterDatespace":"\niterDatespace( start:integer|string|Date, stop:integer|string|Date[, \n N:integer][, options:Object] )\n Returns an iterator which returns evenly spaced dates over a specified\n interval.\n","iterDedupe":"\niterDedupe( iterator:Object[, limit:integer] )\n Returns an iterator which removes consecutive duplicated values.\n","iterDedupeBy":"\niterDedupeBy( iterator:Object, [limit:integer,] fcn:Function )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n","iterDeg2rad":"\niterDeg2rad( iterator:Object )\n Returns an iterator which iteratively converts an angle from degrees to\n radians.\n","iterDigamma":"\niterDigamma( iterator:Object )\n Returns an iterator which iteratively evaluates the digamma function.\n","iterDiracComb":"\niterDiracComb( [options:Object] )\n Returns an iterator which generates a Dirac comb.\n","iterDiracDelta":"\niterDiracDelta( iterator:Object )\n Returns an iterator which iteratively evaluates the Dirac delta function.\n","iterDivide":"\niterDivide( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n","iterEllipe":"\niterEllipe( iterator:Object )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the second kind.\n","iterEllipk":"\niterEllipk( iterator:Object )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the first kind.\n","iterEmpty":"\niterEmpty()\n Returns an empty iterator.\n","iterErf":"\niterErf( iterator:Object )\n Returns an iterator which iteratively evaluates the error function.\n","iterErfc":"\niterErfc( iterator:Object )\n Returns an iterator which iteratively evaluates the complementary error\n function.\n","iterErfcinv":"\niterErfcinv( iterator:Object )\n Returns an iterator which iteratively evaluates the inverse complementary\n error function.\n","iterErfinv":"\niterErfinv( iterator:Object )\n Returns an iterator which iteratively evaluates the inverse error function.\n","iterEta":"\niterEta( iterator:Object )\n Returns an iterator which iteratively evaluates the Dirichlet eta function.\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved sequence of even\n integers.\n","iterEvery":"\niterEvery( iterator:Object )\n Tests whether all iterated values are truthy.\n","iterEveryBy":"\niterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n","iterExp":"\niterExp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural exponential\n function.\n","iterExp2":"\niterExp2( iterator:Object )\n Returns an iterator which iteratively evaluates the base `2` exponential\n function.\n","iterExp10":"\niterExp10( iterator:Object )\n Returns an iterator which iteratively evaluates the base `10` exponential\n function.\n","iterExpit":"\niterExpit( iterator:Object )\n Returns an iterator which iteratively evaluates the standard logistic\n function.\n","iterExpm1":"\niterExpm1( iterator:Object )\n Returns an iterator which iteratively computes `exp(x) - 1`.\n","iterExpm1rel":"\niterExpm1rel( iterator:Object )\n Returns an iterator which iteratively evaluates the relative error\n exponential.\n","iterFactorial":"\niterFactorial( iterator:Object )\n Returns an iterator which iteratively evaluates the factorial function.\n","iterFactorialln":"\niterFactorialln( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n factorial function.\n","iterFactorialsSeq":"\niterFactorialsSeq( [options:Object] )\n Returns an iterator which generates a sequence of factorials.\n","iterFibonacciSeq":"\niterFibonacciSeq( [options:Object] )\n Returns an iterator which generates a Fibonacci sequence.\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options:Object] )\n Returns an iterator which generates a sequence of fifth powers.\n","iterFill":"\niterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n","iterFilter":"\niterFilter( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n","iterFilterMap":"\niterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n","iterFirst":"\niterFirst( iterator:Object )\n Returns the first iterated value.\n","iterFlatTopPulse":"\niterFlatTopPulse( [options:Object] )\n Returns an iterator which generates a flat top pulse waveform.\n","iterFloor":"\niterFloor( iterator:Object )\n Returns an iterator which rounds each iterated value toward negative\n infinity.\n","iterFloor2":"\niterFloor2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward negative infinity.\n","iterFloor10":"\niterFloor10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward negative infinity.\n","iterFlow":"\niterFlow( methods:Object )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n","iterForEach":"\niterForEach( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options:Object] )\n Returns an iterator which generates a sequence of fourth powers.\n","iterFresnelc":"\niterFresnelc( iterator:Object )\n Returns an iterator which iteratively computes the Fresnel integral C(x).\n","iterFresnels":"\niterFresnels( iterator:Object )\n Returns an iterator which iteratively computes the Fresnel integral S(x).\n","iterGamma":"\niterGamma( iterator:Object )\n Returns an iterator which iteratively evaluates the gamma function.\n","iterGamma1pm1":"\niterGamma1pm1( iterator:Object )\n Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n cancellation errors for small `x`.\n","iterGammaln":"\niterGammaln( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n gamma function.\n","iterHacovercos":"\niterHacovercos( iterator:Object )\n Returns an iterator which iteratively computes the half-value coversed\n cosine.\n","iterHacoversin":"\niterHacoversin( iterator:Object )\n Returns an iterator which iteratively computes the half-value coversed sine.\n","iterHannPulse":"\niterHannPulse( [options:Object] )\n Returns an iterator which generates a Hann pulse waveform.\n","iterHavercos":"\niterHavercos( iterator:Object )\n Returns an iterator which iteratively computes the half-value versed cosine.\n","iterHaversin":"\niterHaversin( iterator:Object )\n Returns an iterator which iteratively computes the half-value versed sine.\n","iterHead":"\niterHead( iterator:Object, n:integer )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n","iterIncrspace":"\niterIncrspace( start:number, stop:number[, increment:number] )\n Returns an iterator which returns evenly spaced numbers according to a\n specified increment.\n","iterIntegersSeq":"\niterIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved integer sequence.\n","iterIntersection":"\niterIntersection( iter0:Object, ...iterator:Object )\n Returns an iterator which returns the intersection of two or more iterators.\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0:Object, ...iterator:Object, hashFcn:Function[, \n thisArg:any] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n","iterInv":"\niterInv( iterator:Object )\n Returns an iterator which iteratively computes the multiplicative inverse.\n","iterLanczosPulse":"\niterLanczosPulse( [options:Object] )\n Returns an iterator which generates a Lanczos pulse waveform.\n","iterLast":"\niterLast( iterator:Object )\n Consumes an entire iterator and returns the last iterated value.\n","iterLength":"\niterLength( iterator:Object )\n Consumes an entire iterator and returns the number of iterated values.\n","iterLinspace":"\niterLinspace( start:number, stop:number[, N:integer] )\n Returns an iterator which returns evenly spaced numbers over a specified\n interval.\n","iterLn":"\niterLn( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm.\n","iterLog":"\niterLog( x:Object|number, b:Object|number )\n Returns an iterator which iteratively computes the base `b` logarithm.\n","iterLog1mexp":"\niterLog1mexp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1-exp(-|x|)`.\n","iterLog1p":"\niterLog1p( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+x`.\n","iterLog1pexp":"\niterLog1pexp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+exp(x)`.\n","iterLog2":"\niterLog2( iterator:Object )\n Returns an iterator which iteratively evaluates the binary logarithm.\n","iterLog10":"\niterLog10( iterator:Object )\n Returns an iterator which iteratively evaluates the common logarithm\n (logarithm with base 10).\n","iterLogit":"\niterLogit( iterator:Object )\n Returns an iterator which iteratively evaluates the logit function.\n","iterLogspace":"\niterLogspace( start:number, stop:number[, N:integer][, options:Object] )\n Returns an iterator which returns evenly spaced numbers on a log scale.\n","iterLucasSeq":"\niterLucasSeq( [options:Object] )\n Returns an iterator which generates a Lucas sequence.\n","iterMap":"\niterMap( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which invokes a function for each iterated value.\n","iterMapN":"\niterMapN( iter0:Object, ...iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n","itermax":"\nitermax( iterator:Object )\n Computes the maximum value of all iterated values.\n","itermaxabs":"\nitermaxabs( iterator:Object )\n Computes the maximum absolute value of all iterated values.\n","itermean":"\nitermean( iterator:Object )\n Computes an arithmetic mean over all iterated values.\n","itermeanabs":"\nitermeanabs( iterator:Object )\n Computes an arithmetic mean of absolute values for all iterated values.\n","itermeanabs2":"\nitermeanabs2( iterator:Object )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n","itermidrange":"\nitermidrange( iterator:Object )\n Computes the mid-range of all iterated values.\n","itermin":"\nitermin( iterator:Object )\n Computes the minimum value of all iterated values.\n","iterminabs":"\niterminabs( iterator:Object )\n Computes the minimum absolute value of all iterated values.\n","itermmax":"\nitermmax( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving maximum value.\n","itermmaxabs":"\nitermmaxabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n","itermmean":"\nitermmean( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n","itermmeanabs":"\nitermmeanabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n","itermmeanabs2":"\nitermmeanabs2( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n","itermmidrange":"\nitermmidrange( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving mid-range.\n","itermmin":"\nitermmin( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving minimum value.\n","itermminabs":"\nitermminabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n","iterMod":"\niterMod( iter0:Object, ...iterator:Object )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n","itermprod":"\nitermprod( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving product.\n","itermrange":"\nitermrange( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving range.\n","itermsum":"\nitermsum( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum.\n","itermsumabs":"\nitermsumabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n","itermsumabs2":"\nitermsumabs2( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n","iterMultiply":"\niterMultiply( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options:Object] )\n Returns an iterator which generates a negaFibonacci sequence.\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options:Object] )\n Returns an iterator which generates a negaLucas sequence.\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of negative even integers.\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options:Object] )\n Returns an iterator which generates a negative integer sequence.\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of negative odd integers.\n","iterNone":"\niterNone( iterator:Object )\n Tests whether all iterated values are falsy.\n","iterNoneBy":"\niterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options:Object] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonnegative even integers.\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options:Object] )\n Returns an iterator which generates a nonnegative integer sequence.\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonpositive even integers.\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options:Object] )\n Returns an iterator which generates a nonpositive integer sequence.\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonsquares.\n","iterNth":"\niterNth( iterator:Object, n:integer )\n Returns the nth iterated value.\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved sequence of odd integers.\n","iterPeriodicSinc":"\niterPeriodicSinc( n:integer[, options:Object] )\n Returns an iterator which generates a periodic sinc waveform.\n","iterPipeline":"\niterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )\n Returns an iterator pipeline.\n","iterPop":"\niterPop( iterator:Object[, clbk:Function[, thisArg:any]] )\n Returns an iterator which skips the last value of a provided iterator.\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of positive even integers.\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options:Object] )\n Returns an iterator which generates a positive integer sequence.\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of positive odd integers.\n","iterPow":"\niterPow( base:Object|number, exponent:Object|number )\n Returns an iterator which iteratively evaluates the exponential function.\n","iterPrimesSeq":"\niterPrimesSeq( [options:Object] )\n Returns an iterator which generates a sequence of prime numbers.\n","iterprod":"\niterprod( iterator:Object )\n Computes the product of all iterated values.\n","iterPulse":"\niterPulse( [options:Object] )\n Returns an iterator which generates a pulse waveform.\n","iterPush":"\niterPush( iterator:Object, ...items:any )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n","iterRad2deg":"\niterRad2deg( iterator:Object )\n Returns an iterator which iteratively converts an angle from radians to\n degrees.\n","iterRamp":"\niterRamp( iterator:Object )\n Returns an iterator which iteratively evaluates the ramp function.\n","iterrange":"\niterrange( iterator:Object )\n Computes the range of all iterated values.\n","iterReject":"\niterReject( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n","iterReplicate":"\niterReplicate( iterator:Object, n:integer )\n Returns an iterator which replicates each iterated value `n` times.\n","iterReplicateBy":"\niterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n","iterRound":"\niterRound( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest integer.\n","iterRound2":"\niterRound2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two on a linear scale.\n","iterRound10":"\niterRound10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 on a linear scale.\n","iterRsqrt":"\niterRsqrt( iterator:Object )\n Returns an iterator which iteratively computes the reciprocal (inverse)\n square root.\n","iterSawtoothWave":"\niterSawtoothWave( [options:Object] )\n Returns an iterator which generates a sawtooth wave.\n","iterShift":"\niterShift( iterator:Object[, clbk:Function[, thisArg:any]] )\n Returns an iterator which skips the first value of a provided iterator.\n","iterSignum":"\niterSignum( iterator:Object )\n Returns an iterator which iteratively evaluates the signum function.\n","iterSin":"\niterSin( iterator:Object )\n Returns an iterator which iteratively computes the sine.\n","iterSinc":"\niterSinc( iterator:Object )\n Returns an iterator which iteratively computes the normalized cardinal sine.\n","iterSineWave":"\niterSineWave( [options:Object] )\n Returns an iterator which generates a sine wave.\n","iterSinh":"\niterSinh( iterator:Object )\n Returns an iterator which iteratively evaluates the hyperbolic sine.\n","iterSinpi":"\niterSinpi( iterator:Object )\n Returns an iterator which computes the sine of each iterated value times π.\n","iterSlice":"\niterSlice( iterator:Object[, begin:integer[, end:integer]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n","iterSome":"\niterSome( iterator:Object, n:number )\n Tests whether at least `n` iterated values are truthy.\n","iterSomeBy":"\niterSomeBy( iterator:Object, n:integer, predicate:Function[, thisArg:any ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n","iterSpence":"\niterSpence( iterator:Object )\n Returns an iterator which iteratively evaluates Spence's function.\n","iterSqrt":"\niterSqrt( iterator:Object )\n Returns an iterator which iteratively computes the principal square root.\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator:Object )\n Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n accurately for small `x`.\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options:Object] )\n Returns an iterator which generates a sequence of squared triangular\n numbers.\n","iterSquaresSeq":"\niterSquaresSeq( [options:Object] )\n Returns an iterator which generates a sequence of squares.\n","iterSquareWave":"\niterSquareWave( [options:Object] )\n Returns an iterator which generates a square wave.\n","iterstdev":"\niterstdev( iterator:Object[, mean:number] )\n Computes a correct sample standard deviation over all iterated values.\n","iterStep":"\niterStep( start:number, increment:number[, N:number] )\n Returns an iterator which returns a sequence of numbers according to a\n specified increment.\n","iterStrided":"\niterStrided( iterator:Object, stride:integer[, offset:integer[, \n eager:boolean]] )\n Returns an iterator which steps by a specified amount.\n","iterStridedBy":"\niterStridedBy( iterator:Object, fcn:Function[, offset:integer[, \n eager:boolean]][, thisArg:any] )\n Returns an iterator which steps according to a provided callback function.\n","iterSubtract":"\niterSubtract( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n","itersum":"\nitersum( iterator:Object )\n Computes the sum of all iterated values.\n","itersumabs":"\nitersumabs( iterator:Object )\n Computes the sum of absolute values for all iterated values.\n","itersumabs2":"\nitersumabs2( iterator:Object )\n Computes the sum of squared absolute values for all iterated values.\n","iterTan":"\niterTan( iterator:Object )\n Returns an iterator which iteratively evaluates the tangent.\n","iterTanh":"\niterTanh( iterator:Object )\n Returns an iterator which iteratively evaluates the hyperbolic tangent.\n","iterThunk":"\niterThunk( iterFcn:Function[, ...args:any] )\n Returns an iterator \"thunk\".\n","iterTriangleWave":"\niterTriangleWave( [options:Object] )\n Returns an iterator which generates a triangle wave.\n","iterTriangularSeq":"\niterTriangularSeq( [options:Object] )\n Returns an iterator which generates a sequence of triangular numbers.\n","iterTrigamma":"\niterTrigamma( iterator:Object )\n Returns an iterator which iteratively evaluates the trigamma function.\n","iterTrunc":"\niterTrunc( iterator:Object )\n Returns an iterator which rounds each iterated value toward zero.\n","iterTrunc2":"\niterTrunc2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward zero.\n","iterTrunc10":"\niterTrunc10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward zero.\n","iterUnion":"\niterUnion( iter0:Object, ...iterator:Object )\n Returns an iterator which returns the union of two or more iterators.\n","iterUnique":"\niterUnique( iterator:Object )\n Returns an iterator which returns unique values.\n","iterUniqueBy":"\niterUniqueBy( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which returns unique values according to a predicate\n function.\n","iterUniqueByHash":"\niterUniqueByHash( iterator:Object, hashFcn:Function[, thisArg:any] )\n Returns an iterator which returns unique values according to a hash\n function.\n","iterUnitspace":"\niterUnitspace( start:number[, stop:number] )\n Returns an iterator which returns numbers incremented by one.\n","iterUnshift":"\niterUnshift( iterator:Object, ...items:any )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n","itervariance":"\nitervariance( iterator:Object[, mean:number] )\n Computes an unbiased sample variance over all iterated values.\n","iterVercos":"\niterVercos( iterator:Object )\n Returns an iterator which iteratively computes the versed cosine.\n","iterVersin":"\niterVersin( iterator:Object )\n Returns an iterator which iteratively computes the versed sine.\n","iterZeta":"\niterZeta( iterator:Object )\n Returns an iterator which iteratively evaluates the Riemann zeta function.\n","joinStream":"\njoinStream( [options:Object] )\n Returns a transform stream which joins streamed data.\n","joinStream.factory":"\njoinStream.factory( [options:Object] )\n Returns a function for creating transform streams for joined streamed data.\n","joinStream.objectMode":"\njoinStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n","kde2d":"\nkde2d( x:Array, y:Array[, options:Object] )\n Two-dimensional kernel density estimation.\n","kebabcase":"\nkebabcase( str:string )\n Converts a string to kebab case.\n","keyBy":"\nkeyBy( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n","keyByRight":"\nkeyByRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n","keysIn":"\nkeysIn( obj:any )\n Returns an array of an object's own and inherited enumerable property\n names.\n","kruskalTest":"\nkruskalTest( ...x:Array[, options:Object] )\n Computes the Kruskal-Wallis test for equal medians.\n","kstest":"\nkstest( x:Array, y:Function|string[, ...params:number][, \n options:Object] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n","leveneTest":"\nleveneTest( x:Array[, ...y:Array[, options:Object]] )\n Computes Levene's test for equal variances.\n","LinkedList":"\nLinkedList()\n Linked list constructor.\n","linspace":"\nlinspace( start:number|ComplexLike, stop:number|ComplexLike, length:integer[, \n options:Object] )\n Generates a linearly spaced array over a specified interval.\n","linspace.assign":"\nlinspace.assign( start:number|ComplexLike, stop:number|ComplexLike, \n out:ArrayLikeObject[, options:Object] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n","LN_HALF":"\nLN_HALF\n Natural logarithm of `1/2`.\n","LN_PI":"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n","LN_TWO_PI":"\nLN_TWO_PI\n Natural logarithm of `2π`.\n","LN2":"\nLN2\n Natural logarithm of `2`.\n","LN10":"\nLN10\n Natural logarithm of `10`.\n","LOG2E":"\nLOG2E\n Base 2 logarithm of Euler's number.\n","LOG10E":"\nLOG10E\n Base 10 logarithm of Euler's number.\n","logspace":"\nlogspace( a:number, b:number[, length:integer] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n","lowercase":"\nlowercase( str:string )\n Converts a string to lowercase.\n","lowercaseKeys":"\nlowercaseKeys( obj:Object )\n Converts each object key to lowercase.\n","lowess":"\nlowess( x:Array, y:Array[, options:Object] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n","lpad":"\nlpad( str:string, len:integer[, pad:string] )\n Left pads a string such that the padded string has a length of at least\n `len`.\n","ltrim":"\nltrim( str:string )\n Trims whitespace from the beginning of a string.\n","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n","map":"\nmap( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array.\n","map.assign":"\nmap.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n","map2":"\nmap2( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n thisArg:any] )\n Applies a function to elements in two input arrays and assigns the results\n to a new array.\n","map2.assign":"\nmap2.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n","map2d":"\nmap2d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in an array of arrays and assigns\n the result to a nested element in a new array of arrays.\n","map2Right":"\nmap2Right( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n thisArg:any] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to a new array.\n","map2Right.assign":"\nmap2Right.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n","map3d":"\nmap3d( arr:ArrayLikeObject>, fcn:Function[, \n thisArg:any] )\n Applies a function to each nested element in a three-dimensional nested\n array and assigns the result to a nested element in a new three-dimensional\n nested array.\n","map4d":"\nmap4d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in a four-dimensional nested array\n and assigns the result to a nested element in a new four-dimensional nested\n array.\n","map5d":"\nmap5d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in a five-dimensional nested array\n and assigns the result to a nested element in a new five-dimensional nested\n array.\n","mapArguments":"\nmapArguments( fcn:Function, clbk:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function after\n transforming arguments according to a callback function.\n","mapFun":"\nmapFun( fcn:Function, n:integer[, thisArg:any] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n","mapFunAsync":"\nmapFunAsync( fcn:Function, n:integer, [options:Object,] done:Function )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n","mapKeys":"\nmapKeys( obj:Object, transform:Function )\n Maps keys from one object to a new object having the same values.\n","mapKeysAsync":"\nmapKeysAsync( obj:Object, [options:Object,] transform:Function, done:Function )\n Maps keys from one object to a new object having the same values.\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options:Object,] transform:Function )\n Returns a function which maps keys from one object to a new object having\n the same values.\n","mapReduce":"\nmapReduce( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n reducer:Function[, thisArg:any] )\n Performs a map-reduce operation for each element in an array and returns the\n accumulated result.\n","mapReduceRight":"\nmapReduceRight( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n reducer:Function[, thisArg:any] )\n Performs a map-reduce operation for each element in an array while iterating\n from right to left and returns the accumulated result.\n","mapRight":"\nmapRight( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array, iterating from right to left.\n","mapRight.assign":"\nmapRight.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n","mapValues":"\nmapValues( obj:Object, transform:Function )\n Maps values from one object to a new object having the same keys.\n","mapValuesAsync":"\nmapValuesAsync( obj:Object, [options:Object,] transform:Function, \n done:Function )\n Maps values from one object to a new object having the same keys.\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options:Object,] transform:Function )\n Returns a function which maps values from one object to a new object having\n the same keys.\n","maskArguments":"\nmaskArguments( fcn:Function, mask:ArrayLikeObject[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a specified mask.\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x:ndarray, shape:ArrayLikeObject )\n Broadcasts an ndarray to a specified shape if and only if the specified\n shape differs from the provided ndarray's shape.\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays:ndarray|ArrayLikeObject )\n Broadcasts ndarrays to a common shape.\n","memoize":"\nmemoize( fcn:Function[, hashFunction:Function] )\n Returns a memoized function.\n","merge":"\nmerge( target:Object, ...source:Object )\n Merges objects into a target object.\n","merge.factory":"\nmerge.factory( options:Object )\n Returns a function for merging and extending objects.\n","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n Number of milliseconds in a second.\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n Number of milliseconds in a week.\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options:Object] )\n Returns data for Charles Joseph Minard's cartographic depiction of\n Napoleon's Russian campaign of 1812.\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n Number of minutes in a day.\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n Number of minutes in a week.\n","minutesInMonth":"\nminutesInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of minutes in a month.\n","minutesInYear":"\nminutesInYear( [value:integer|Date] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n","MOBY_DICK":"\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n Number of months in a year.\n","moveProperty":"\nmoveProperty( source:Object, prop:string, target:Object )\n Moves a property from one object to another object.\n","MultiSlice":"\nMultiSlice( ...slice )\n Returns a multi-slice.\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n","namedtypedtuple":"\nnamedtypedtuple( fields:Array[, options:Object] )\n Returns a named typed tuple factory.\n","NAN":"\nNAN\n Double-precision floating-point NaN.\n","naryFunction":"\nnaryFunction( fcn:Function, arity:integer[, thisArg:any] )\n Returns a function that applies a specified number of arguments to a\n provided function.\n","nativeClass":"\nnativeClass( value:any )\n Returns a string value indicating a specification defined classification of\n an object.\n","ndarray":"\nndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string[, options:Object] )\n Returns an ndarray.\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","ndarray.prototype.data":"\nndarray.prototype.data\n Pointer to the underlying data buffer.\n","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n Underlying data type.\n","ndarray.prototype.flags":"\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","ndarray.prototype.length":"\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n Number of dimensions.\n","ndarray.prototype.offset":"\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","ndarray.prototype.order":"\nndarray.prototype.order\n Array order.\n","ndarray.prototype.shape":"\nndarray.prototype.shape\n Array shape.\n","ndarray.prototype.strides":"\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","ndarray.prototype.get":"\nndarray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","ndarray.prototype.iget":"\nndarray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","ndarray.prototype.set":"\nndarray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","ndarray.prototype.iset":"\nndarray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","ndarray.prototype.toString":"\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n","ndarray2array":"\nndarray2array( x:ndarray )\n Converts an ndarray to a generic array.\n","ndarrayCastingModes":"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x:ndarray )\n Returns the underlying data buffer of a provided ndarray.\n","ndarrayDataType":"\nndarrayDataType( x:ndarray )\n Returns the data type of a provided ndarray.\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind:string] )\n Returns a list of ndarray data types.\n","ndarrayDispatch":"\nndarrayDispatch( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns an ndarray function interface which performs multiple dispatch.\n","ndarrayFlag":"\nndarrayFlag( x:ndarray, name:string|symbol )\n Returns a specified flag for a provided ndarray.\n","ndarrayFlags":"\nndarrayFlags( x:ndarray )\n Returns the flags of a provided ndarray.\n","ndarrayIndexModes":"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n","ndarrayMinDataType":"\nndarrayMinDataType( value:any )\n Returns the minimum ndarray data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast and, for floating-point data types, can be downcast.\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype:any] )\n Returns the next larger ndarray data type of the same kind.\n","ndarrayOffset":"\nndarrayOffset( x:ndarray )\n Returns the index offset specifying the underlying buffer index of the first\n iterated ndarray element.\n","ndarrayOrder":"\nndarrayOrder( x:ndarray )\n Returns the layout order of a provided ndarray.\n","ndarrayOrders":"\nndarrayOrders()\n Returns a list of ndarray orders.\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1:any, dtype2:any] )\n Returns the ndarray data type with the smallest size and closest \"kind\" to\n which ndarray data types can be safely cast.\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same \"kind\".\n","ndarrayShape":"\nndarrayShape( x:ndarray )\n Returns the shape of a provided ndarray.\n","ndarrayStride":"\nndarrayStride( x:ndarray, dim:integer )\n Returns the stride along a specified dimension for a provided ndarray.\n","ndarrayStrides":"\nndarrayStrides( x:ndarray )\n Returns the strides of a provided ndarray.\n","ndat":"\nndat( x:ndarray[, ...indices:integer] )\n Returns an ndarray element.\n","ndempty":"\nndempty( shape:ArrayLikeObject|integer[, options:Object] )\n Returns an uninitialized ndarray having a specified shape and data type.\n","ndemptyLike":"\nndemptyLike( x:ndarray[, options:Object] )\n Returns an uninitialized ndarray having the same shape and data type as a\n provided input ndarray.\n","ndims":"\nndims( x:ndarray )\n Returns the number of ndarray dimensions.\n","nditerColumnEntries":"\nnditerColumnEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, column] pairs for each column in a\n matrix (or stack of matrices).\n","nditerColumns":"\nnditerColumns( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each column in a matrix (or stack of\n matrices).\n","nditerEntries":"\nnditerEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, value] pairs for each element in a\n provided ndarray.\n","nditerIndices":"\nnditerIndices( shape:Array[, options:Object] )\n Returns an iterator which returns indices for use indexing into an ndarray\n having a specified shape.\n","nditerMatrices":"\nnditerMatrices( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each matrix in a stack of matrices.\n","nditerMatrixEntries":"\nnditerMatrixEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, matrix] pairs for each matrix in a\n stack of matrices.\n","nditerRowEntries":"\nnditerRowEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, row] pairs for each row in a\n matrix (or stack of matrices).\n","nditerRows":"\nnditerRows( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each row in a matrix (or stack of\n matrices).\n","nditerValues":"\nnditerValues( x:ndarray[, options:Object] )\n Returns an iterator which returns individual elements from a provided\n ndarray.\n","ndslice":"\nndslice( x:ndarray, ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, \n options:Object] )\n Returns a read-only view of an input ndarray.\n","ndsliceAssign":"\nndsliceAssign( x:ndarray, y:ndarray, \n ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, options:Object] )\n Assigns element values from a broadcasted input ndarray to corresponding\n elements in an output ndarray view.\n","ndsliceDimension":"\nndsliceDimension( x:ndarray, dim:integer, slice:Slice|integer|null|undefined[, \n options:Object] )\n Returns a read-only view of an input ndarray when sliced along a specified\n dimension.\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x:ndarray, dim:integer, start:integer[, options:Object] )\n Returns a read-only shifted view of an input ndarray along a specified\n dimension.\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x:ndarray, dim:integer, stop:integer[, options:Object] )\n Returns a read-only truncated view of an input ndarray along a specified\n dimension.\n","ndsliceFrom":"\nndsliceFrom( x:ndarray, ...start:null|void|integer[, options:Object] )\n Returns a read-only shifted view of an input ndarray.\n","ndsliceTo":"\nndsliceTo( x:ndarray, ...stop:null|void|integer[, options:Object] )\n Returns a read-only truncated view of an input ndarray.\n","ndzeros":"\nndzeros( shape:ArrayLikeObject|integer[, options:Object] )\n Returns a zero-filled ndarray having a specified shape and data type.\n","ndzerosLike":"\nndzerosLike( x:ndarray[, options:Object] )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str:string[, fromIndex:integer] )\n Returns the next extended grapheme cluster break in a string after a\n specified position.\n","nextTick":"\nnextTick( clbk[, ...args] )\n Adds a callback to the \"next tick queue\".\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n","NINF":"\nNINF\n Double-precision floating-point negative infinity.\n","NODE_VERSION":"\nNODE_VERSION\n Node version.\n","none":"\nnone( collection:Array|TypedArray|Object )\n Tests whether all elements in a collection are falsy.\n","noneBy":"\nnoneBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n","noneByAsync":"\nnoneByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n","noneByAsync.factory":"\nnoneByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n","noneByRight":"\nnoneByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n","noneByRightAsync":"\nnoneByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n","nonEnumerableProperties":"\nnonEnumerableProperties( value:any )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value:any )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value:any )\n Returns an array of an object's own non-enumerable property names.\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value:any )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value:any )\n Returns an array of an object's own non-enumerable symbol properties.\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n","nonIndexKeys":"\nnonIndexKeys( obj:any )\n Returns an array of an object's own enumerable property names which are not\n integer indices.\n","noop":"\nnoop()\n A function which does nothing.\n","now":"\nnow()\n Returns the time in seconds since the epoch.\n","NUM_CPUS":"\nNUM_CPUS\n Number of CPUs.\n","num2words":"\nnum2words( value:integer[, options:Object] )\n Converts a number to a word representation.\n","Number":"\nNumber( value:number )\n Returns a Number object.\n","numel":"\nnumel( x:ndarray )\n Returns the number of elements in an ndarray.\n","numelDimension":"\nnumelDimension( x:ndarray, dim:integer )\n Returns the size (i.e., number of elements) of a specified dimension for a\n provided ndarray.\n","numGraphemeClusters":"\nnumGraphemeClusters( str:string )\n Returns the number of grapheme clusters in a string.\n","Object":"\nObject( value:any )\n Returns an object.\n","Object.assign":"\nObject.assign( target:Object, ...sources:Object )\n Assigns enumerable and own properties from source objects to a target\n object.\n","Object.create":"\nObject.create( prototype:Object, properties:Object )\n Creates a new object with a specified prototype object and properties.\n","Object.defineProperties":"\nObject.defineProperties( obj:Object, properties:Object )\n Defines properties for an object.\n","Object.defineProperty":"\nObject.defineProperty( obj:Object, key:string, descriptor:Object )\n Defines a property for an object.\n","Object.entries":"\nObject.entries( obj:Object )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n","Object.freeze":"\nObject.freeze( obj:Object )\n Freezes an object.\n","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj:Object, key:string )\n Returns an object's own property descriptor.\n","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj:Object )\n Returns an object's own property descriptors.\n","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj:Object )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj:Object )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj:Object )\n Returns an object's prototype.\n","Object.hasOwn":"\nObject.hasOwn( obj:Object, p:string )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n","Object.is":"\nObject.is( value1:any, value2:any )\n Returns a boolean indicating whether two values are the same value.\n","Object.isExtensible":"\nObject.isExtensible( obj:Object )\n Returns a boolean indicating whether an object is extensible.\n","Object.isFrozen":"\nObject.isFrozen( obj:Object )\n Returns a boolean indicating whether an object is frozen.\n","Object.isSealed":"\nObject.isSealed( obj:Object )\n Returns a boolean indicating whether an object is sealed.\n","Object.keys":"\nObject.keys( obj:Object )\n Returns an array of an object's own enumerable string-keyed property\n names.\n","Object.preventExtensions":"\nObject.preventExtensions( obj:Object )\n Prevents the addition of new properties to an object.\n","Object.seal":"\nObject.seal( obj:Object )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj:Object, proto:Object )\n Sets an object's prototype.\n","Object.values":"\nObject.values( obj:Object )\n Returns an array of an object's own enumerable property values.\n","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n","Object.prototype.toString":"\nObject.prototype.toString()\n Returns a string representing the object.\n","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p:string )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj:Object )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p:string )\n Returns a boolean indicating whether an object's property is enumerable.\n","Object.prototype.constructor":"\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n","objectEntries":"\nobjectEntries( obj:ObjectLike )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n","objectEntriesIn":"\nobjectEntriesIn( obj:ObjectLike )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n","objectFromEntries":"\nobjectFromEntries( entries:Array )\n Creates an object from an array of key-value pairs.\n","objectInverse":"\nobjectInverse( obj:ObjectLike[, options:Object] )\n Inverts an object, such that keys become values and values become keys.\n","objectInverseBy":"\nobjectInverseBy( obj:ObjectLike, [options:Object,] transform:Function )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n","objectKeys":"\nobjectKeys( value:any )\n Returns an array of an object's own enumerable property names.\n","objectValues":"\nobjectValues( obj:ObjectLike )\n Returns an array of an object's own enumerable property values.\n","objectValuesIn":"\nobjectValuesIn( obj:ObjectLike )\n Returns an array of an object's own and inherited enumerable property\n values.\n","omit":"\nomit( obj:Object, keys:string|Array )\n Returns a partial object copy excluding specified keys.\n","omitBy":"\nomitBy( obj:Object, predicate:Function )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n","open":"\nopen( path:string|Buffer[, flags:string|number[, mode:integer]], clbk:Function )\n Asynchronously opens a file.\n","open.sync":"\nopen.sync( path:string|Buffer[, flags:string|number[, mode:integer]] )\n Synchronously opens a file.\n","openURL":"\nopenURL( url:string )\n Opens a URL in a user's default browser.\n","ordinalize":"\nordinalize( value:string|integer[, options:Object] )\n Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n","pad":"\npad( str:string, len:integer[, options:Object] )\n Pads a `string` such that the padded `string` has length `len`.\n","padjust":"\npadjust( pvals:Array, method:string[, comparisons:integer] )\n Adjusts supplied p-values for multiple comparisons via a specified method.\n","papply":"\npapply( fcn:Function, ...args:any )\n Returns a function of smaller arity by partially applying arguments.\n","papplyRight":"\npapplyRight( fcn:Function, ...args:any )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n","parallel":"\nparallel( files:Array, [options:Object,] clbk:Function )\n Executes scripts in parallel.\n","parseJSON":"\nparseJSON( str:string[, reviver:Function] )\n Attempts to parse a string as JSON.\n","pascalcase":"\npascalcase( str:string )\n Converts a string to Pascal case.\n","PATH_DELIMITER":"\nPATH_DELIMITER\n Platform-specific path delimiter.\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n","PATH_SEP":"\nPATH_SEP\n Platform-specific path segment separator.\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n POSIX path segment separator.\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n Windows path segment separator.\n","pcorrtest":"\npcorrtest( x:Array, y:Array[, options:Object] )\n Computes a Pearson product-moment correlation test between paired samples.\n","percentEncode":"\npercentEncode( str:string )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","PHI":"\nPHI\n Golden ratio.\n","PI":"\nPI\n The mathematical constant `π`.\n","PI_SQUARED":"\nPI_SQUARED\n Square of the mathematical constant `π`.\n","pick":"\npick( obj:Object, keys:string|Array )\n Returns a partial object copy containing only specified keys.\n","pickArguments":"\npickArguments( fcn:Function, indices:Array[, thisArg:any] )\n Returns a function that applies specified arguments to a provided function.\n","pickBy":"\npickBy( obj:Object, predicate:Function )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n","PINF":"\nPINF\n Double-precision floating-point positive infinity.\n","pkg2alias":"\npkg2alias( pkg:string )\n Returns the alias associated with a specified package name.\n","pkg2related":"\npkg2related( pkg:string )\n Returns package names related to a specified package name.\n","pkg2standalone":"\npkg2standalone( pkg:string )\n Returns the standalone package name associated with a provided internal\n package name.\n","PLATFORM":"\nPLATFORM\n Platform on which the current process is running.\n","plot":"\nplot( [x:Array|Array, y:Array|Array,] [options:Object] )\n Returns a plot instance for creating 2-dimensional plots.\n","Plot":"\nPlot( [x:Array|Array, y:Array|Array,] [options:Object] )\n Returns a plot instance for creating 2-dimensional plots.\n","pluck":"\npluck( arr:Array, prop:string[, options:Object] )\n Extracts a property value from each element of an object array.\n","pop":"\npop( collection:Array|TypedArray|Object )\n Removes and returns the last element of a collection.\n","porterStemmer":"\nporterStemmer( word:string )\n Extracts the stem of a given word.\n","prepend":"\nprepend( collection1:Array|TypedArray|Object, \n collection2:Array|TypedArray|Object )\n Adds the elements of one collection to the beginning of another collection.\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str:string[, fromIndex:integer] )\n Returns the previous extended grapheme cluster break in a string before a\n specified position.\n","PRIMES_100K":"\nPRIMES_100K()\n Returns an array containing the first 100,000 prime numbers.\n","properties":"\nproperties( value:any )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n","propertiesIn":"\npropertiesIn( value:any )\n Returns an array of an object's own and inherited property names and\n symbols.\n","propertyDescriptor":"\npropertyDescriptor( value:any, property:string|symbol )\n Returns a property descriptor for an object's own property.\n","propertyDescriptorIn":"\npropertyDescriptorIn( value:any, property:string|symbol )\n Returns a property descriptor for an object's own or inherited property.\n","propertyDescriptors":"\npropertyDescriptors( value:any )\n Returns an object's own property descriptors.\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value:any )\n Returns an object's own and inherited property descriptors.\n","propertyNames":"\npropertyNames( value:any )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n","propertyNamesIn":"\npropertyNamesIn( value:any )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n","propertySymbols":"\npropertySymbols( value:any )\n Returns an array of an object's own symbol properties.\n","propertySymbolsIn":"\npropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited symbol properties.\n","Proxy":"\nProxy( target:Object, handlers:Object )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n","Proxy.revocable":"\nProxy.revocable( target:Object, handlers:Object )\n Returns a revocable proxy object.\n","push":"\npush( collection:Array|TypedArray|Object, ...items:any )\n Adds one or more elements to the end of a collection.\n","quarterOfYear":"\nquarterOfYear( [month:integer|string|Date] )\n Returns the quarter of the year.\n","random.array.arcsine":"\nrandom.array.arcsine( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an arcsine\n distribution.\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n Length of generator seed.\n","random.array.arcsine.state":"\nrandom.array.arcsine.state\n Generator state.\n","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n Length of generator state.\n","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n","random.array.bernoulli":"\nrandom.array.bernoulli( len:integer, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n Generator state.\n","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n Length of generator state.\n","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n","random.array.beta":"\nrandom.array.beta( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a beta\n distribution.\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n","random.array.beta.seed":"\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n Length of generator seed.\n","random.array.beta.state":"\nrandom.array.beta.state\n Generator state.\n","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n Length of generator state.\n","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n","random.array.betaprime":"\nrandom.array.betaprime( len:integer, alpha:number, beta:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a beta prime\n distribution.\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n Length of generator seed.\n","random.array.betaprime.state":"\nrandom.array.betaprime.state\n Generator state.\n","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n Length of generator state.\n","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n","random.array.binomial":"\nrandom.array.binomial( len:integer, n:number, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a binomial\n distribution.\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n:number, p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n:number, p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n","random.array.binomial.seed":"\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n Length of generator seed.\n","random.array.binomial.state":"\nrandom.array.binomial.state\n Generator state.\n","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n Length of generator state.\n","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n","random.array.cauchy":"\nrandom.array.cauchy( len:integer, x0:number, gamma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Cauchy\n distribution.\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0:number, gamma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0:number, gamma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n Length of generator seed.\n","random.array.cauchy.state":"\nrandom.array.cauchy.state\n Generator state.\n","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n Length of generator state.\n","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n","random.array.chi":"\nrandom.array.chi( len:integer, k:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a chi\n distribution.\n","random.array.chi.assign":"\nrandom.array.chi.assign( k:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n","random.array.chi.factory":"\nrandom.array.chi.factory( [k:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n","random.array.chi.seed":"\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n Length of generator seed.\n","random.array.chi.state":"\nrandom.array.chi.state\n Generator state.\n","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n Length of generator state.\n","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n","random.array.chisquare":"\nrandom.array.chisquare( len:integer, k:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a chi-square\n distribution.\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n Length of generator seed.\n","random.array.chisquare.state":"\nrandom.array.chisquare.state\n Generator state.\n","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n Length of generator state.\n","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n","random.array.cosine":"\nrandom.array.cosine( len:integer, mu:number, s:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a raised cosine\n distribution.\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu:number, s:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu:number, s:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n","random.array.cosine.seed":"\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n Length of generator seed.\n","random.array.cosine.state":"\nrandom.array.cosine.state\n Generator state.\n","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n Length of generator state.\n","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n","random.array.discreteUniform":"\nrandom.array.discreteUniform( len:integer, a:number, b:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a discrete\n uniform distribution.\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a:number, b:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n Generator state.\n","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n","random.array.erlang":"\nrandom.array.erlang( len:integer, k:number, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an Erlang\n distribution.\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k:number, lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k:number, lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n","random.array.erlang.seed":"\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n Length of generator seed.\n","random.array.erlang.state":"\nrandom.array.erlang.state\n Generator state.\n","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n Length of generator state.\n","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n","random.array.exponential":"\nrandom.array.exponential( len:integer, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an exponential\n distribution.\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n","random.array.exponential.seed":"\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n Length of generator seed.\n","random.array.exponential.state":"\nrandom.array.exponential.state\n Generator state.\n","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n Length of generator state.\n","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n","random.array.f":"\nrandom.array.f( len:integer, d1:number, d2:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an F\n distribution.\n","random.array.f.assign":"\nrandom.array.f.assign( d1:number, d2:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n","random.array.f.factory":"\nrandom.array.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n","random.array.f.PRNG":"\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n","random.array.f.seed":"\nrandom.array.f.seed\n Pseudorandom number generator seed.\n","random.array.f.seedLength":"\nrandom.array.f.seedLength\n Length of generator seed.\n","random.array.f.state":"\nrandom.array.f.state\n Generator state.\n","random.array.f.stateLength":"\nrandom.array.f.stateLength\n Length of generator state.\n","random.array.f.byteLength":"\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n","random.array.frechet":"\nrandom.array.frechet( len:integer, alpha:number, s:number, m:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha:number, s:number, m:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha:number, s:number, m:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n","random.array.frechet.seed":"\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n Length of generator seed.\n","random.array.frechet.state":"\nrandom.array.frechet.state\n Generator state.\n","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n Length of generator state.\n","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n","random.array.gamma":"\nrandom.array.gamma( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a gamma\n distribution.\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n","random.array.gamma.seed":"\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n Length of generator seed.\n","random.array.gamma.state":"\nrandom.array.gamma.state\n Generator state.\n","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n Length of generator state.\n","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n","random.array.geometric":"\nrandom.array.geometric( len:integer, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a geometric\n distribution.\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n","random.array.geometric.seed":"\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n Length of generator seed.\n","random.array.geometric.state":"\nrandom.array.geometric.state\n Generator state.\n","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n Length of generator state.\n","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n","random.array.gumbel":"\nrandom.array.gumbel( len:integer, mu:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Gumbel\n distribution.\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n Length of generator seed.\n","random.array.gumbel.state":"\nrandom.array.gumbel.state\n Generator state.\n","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n Length of generator state.\n","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n","random.array.hypergeometric":"\nrandom.array.hypergeometric( len:integer, N:number, K:number, n:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a hypergeometric\n distribution.\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N:number, K:number, n:number, \n out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N:number, K:number, n:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n Generator state.\n","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n","random.array.invgamma":"\nrandom.array.invgamma( len:integer, alpha:number, beta:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n Length of generator seed.\n","random.array.invgamma.state":"\nrandom.array.invgamma.state\n Generator state.\n","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n Length of generator state.\n","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n double bounded distribution.\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n Generator state.\n","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n","random.array.laplace":"\nrandom.array.laplace( len:integer, mu:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n","random.array.laplace.seed":"\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n Length of generator seed.\n","random.array.laplace.state":"\nrandom.array.laplace.state\n Generator state.\n","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n Length of generator state.\n","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n","random.array.levy":"\nrandom.array.levy( len:integer, mu:number, c:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Lévy\n distribution.\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu:number, c:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n","random.array.levy.factory":"\nrandom.array.levy.factory( [mu:number, c:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n","random.array.levy.seed":"\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n Length of generator seed.\n","random.array.levy.state":"\nrandom.array.levy.state\n Generator state.\n","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n Length of generator state.\n","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n","random.array.logistic":"\nrandom.array.logistic( len:integer, mu:number, s:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a logistic\n distribution.\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu:number, s:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu:number, s:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n","random.array.logistic.seed":"\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n Length of generator seed.\n","random.array.logistic.state":"\nrandom.array.logistic.state\n Generator state.\n","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n Length of generator state.\n","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n","random.array.lognormal":"\nrandom.array.lognormal( len:integer, mu:number, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a lognormal\n distribution.\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu:number, sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu:number, sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n Length of generator seed.\n","random.array.lognormal.state":"\nrandom.array.lognormal.state\n Generator state.\n","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n Length of generator state.\n","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n","random.array.minstd":"\nrandom.array.minstd( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n","random.array.minstd.seed":"\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n Length of generator seed.\n","random.array.minstd.state":"\nrandom.array.minstd.state\n Generator state.\n","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n Length of generator state.\n","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n Generator state.\n","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n","random.array.mt19937":"\nrandom.array.mt19937( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[0, 4294967295]`.\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n Length of generator seed.\n","random.array.mt19937.state":"\nrandom.array.mt19937.state\n Generator state.\n","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n Length of generator state.\n","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len:integer, r:number, p:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a negative\n binomial distribution.\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r:number, p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n Generator state.\n","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n","random.array.normal":"\nrandom.array.normal( len:integer, mu:number, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a normal\n distribution.\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu:number, sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n","random.array.normal.factory":"\nrandom.array.normal.factory( [mu:number, sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n","random.array.normal.seed":"\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n Length of generator seed.\n","random.array.normal.state":"\nrandom.array.normal.state\n Generator state.\n","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n Length of generator state.\n","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n","random.array.pareto1":"\nrandom.array.pareto1( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n I) distribution.\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n Length of generator seed.\n","random.array.pareto1.state":"\nrandom.array.pareto1.state\n Generator state.\n","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n Length of generator state.\n","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n","random.array.poisson":"\nrandom.array.poisson( len:integer, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Poisson\n distribution.\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n","random.array.poisson.seed":"\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n Length of generator seed.\n","random.array.poisson.state":"\nrandom.array.poisson.state\n Generator state.\n","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n Length of generator state.\n","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n","random.array.randu":"\nrandom.array.randu( len:integer[, options:Object] )\n Returns an array containing uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options:Object] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n","random.array.randu.seed":"\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n Length of generator seed.\n","random.array.randu.state":"\nrandom.array.randu.state\n Generator state.\n","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n Length of generator state.\n","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n","random.array.rayleigh":"\nrandom.array.rayleigh( len:integer, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n Generator state.\n","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n Length of generator state.\n","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n","random.array.t":"\nrandom.array.t( len:integer, v:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Student's t\n distribution.\n","random.array.t.assign":"\nrandom.array.t.assign( v:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n","random.array.t.factory":"\nrandom.array.t.factory( [v:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n","random.array.t.PRNG":"\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n","random.array.t.seed":"\nrandom.array.t.seed\n Pseudorandom number generator seed.\n","random.array.t.seedLength":"\nrandom.array.t.seedLength\n Length of generator seed.\n","random.array.t.state":"\nrandom.array.t.state\n Generator state.\n","random.array.t.stateLength":"\nrandom.array.t.stateLength\n Length of generator state.\n","random.array.t.byteLength":"\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n","random.array.triangular":"\nrandom.array.triangular( len:integer, a:number, b:number, c:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a triangular\n distribution.\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a:number, b:number, c:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n","random.array.triangular.seed":"\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n Length of generator seed.\n","random.array.triangular.state":"\nrandom.array.triangular.state\n Generator state.\n","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n Length of generator state.\n","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n","random.array.uniform":"\nrandom.array.uniform( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a continuous\n uniform distribution.\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n","random.array.uniform.seed":"\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n Length of generator seed.\n","random.array.uniform.state":"\nrandom.array.uniform.state\n Generator state.\n","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n Length of generator state.\n","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n","random.array.weibull":"\nrandom.array.weibull( len:integer, k:number, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Weibull\n distribution.\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k:number, lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k:number, lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n","random.array.weibull.seed":"\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n Length of generator seed.\n","random.array.weibull.state":"\nrandom.array.weibull.state\n Generator state.\n","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n Length of generator state.\n","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n","random.iterators.arcsine":"\nrandom.iterators.arcsine( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n","random.iterators.beta":"\nrandom.iterators.beta( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n","random.iterators.binomial":"\nrandom.iterators.binomial( n:integer, p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0:number, Ɣ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n","random.iterators.chi":"\nrandom.iterators.chi( k:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ:number, s:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a:integer, b:integer[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n","random.iterators.erlang":"\nrandom.iterators.erlang( k:integer, λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n","random.iterators.f":"\nrandom.iterators.f( d1:number, d2:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n","random.iterators.frechet":"\nrandom.iterators.frechet( α:number, s:number, m:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.iterators.gamma":"\nrandom.iterators.gamma( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n","random.iterators.geometric":"\nrandom.iterators.geometric( p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n","random.iterators.levy":"\nrandom.iterators.levy( μ:number, c:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ:number, s:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ:number, σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r:number, p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n","random.iterators.normal":"\nrandom.iterators.normal( μ:number, σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n","random.iterators.randi":"\nrandom.iterators.randi( [options:Object] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n","random.iterators.randn":"\nrandom.iterators.randn( [options:Object] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n","random.iterators.randu":"\nrandom.iterators.randu( [options:Object] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n","random.iterators.t":"\nrandom.iterators.t( v:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n","random.iterators.triangular":"\nrandom.iterators.triangular( a:number, b:number, c:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n","random.iterators.uniform":"\nrandom.iterators.uniform( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n","random.iterators.weibull":"\nrandom.iterators.weibull( k:number, λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n","random.streams.arcsine":"\nrandom.streams.arcsine( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n","random.streams.bernoulli":"\nrandom.streams.bernoulli( p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n","random.streams.beta":"\nrandom.streams.beta( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n","random.streams.betaprime":"\nrandom.streams.betaprime( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n","random.streams.binomial":"\nrandom.streams.binomial( n:integer, p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n:integer, p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n:integer, p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n","random.streams.cauchy":"\nrandom.streams.cauchy( x0:number, γ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0:number, γ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0:number, γ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n","random.streams.chi":"\nrandom.streams.chi( k:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n","random.streams.chisquare":"\nrandom.streams.chisquare( k:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n","random.streams.cosine":"\nrandom.streams.cosine( μ:number, s:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ:number, s:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ:number, s:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a:integer, b:integer[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a:integer, b:integer, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a:integer, b:integer[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n","random.streams.erlang":"\nrandom.streams.erlang( k:integer, λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k:number, λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k:number, λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n","random.streams.exponential":"\nrandom.streams.exponential( λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n","random.streams.f":"\nrandom.streams.f( d1:number, d2:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1:number, d2:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n","random.streams.frechet":"\nrandom.streams.frechet( α:number, s:number, m:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Fréchet distribution.\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α:number, s:number, m:number,]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α:number, s:number, m:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n","random.streams.gamma":"\nrandom.streams.gamma( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n","random.streams.geometric":"\nrandom.streams.geometric( p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n","random.streams.gumbel":"\nrandom.streams.gumbel( μ:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N:integer, K:integer, n:integer,]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n","random.streams.invgamma":"\nrandom.streams.invgamma( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.laplace":"\nrandom.streams.laplace( μ:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n","random.streams.levy":"\nrandom.streams.levy( μ:number, c:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ:number, c:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ:number, c:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n","random.streams.logistic":"\nrandom.streams.logistic( μ:number, s:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ:number, s:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ:number, s:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n","random.streams.lognormal":"\nrandom.streams.lognormal( μ:number, σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ:number, σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n","random.streams.minstd":"\nrandom.streams.minstd( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n","random.streams.mt19937":"\nrandom.streams.mt19937( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r:number, p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r:number, p:number, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r:integer, p:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n","random.streams.normal":"\nrandom.streams.normal( μ:number, σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ:number, σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n","random.streams.pareto1":"\nrandom.streams.pareto1( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n","random.streams.poisson":"\nrandom.streams.poisson( λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n","random.streams.randi":"\nrandom.streams.randi( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n","random.streams.randn":"\nrandom.streams.randn( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n","random.streams.randu":"\nrandom.streams.randu( [options:Object] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n","random.streams.t":"\nrandom.streams.t( v:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n","random.streams.triangular":"\nrandom.streams.triangular( a:number, b:number, c:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n triangular distribution.\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a:number, b:number, c:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n","random.streams.uniform":"\nrandom.streams.uniform( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n","random.streams.weibull":"\nrandom.streams.weibull( k:number, λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k:number, λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k:number, λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n","random.strided.arcsine":"\nrandom.strided.arcsine( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution.\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n","random.strided.bernoulli":"\nrandom.strided.bernoulli( N:integer, p:ArrayLikeObject, sp:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n Generator state.\n","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n","random.strided.beta":"\nrandom.strided.beta( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution.\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n","random.strided.betaprime":"\nrandom.strided.betaprime( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution.\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n","random.strided.chi":"\nrandom.strided.chi( N:integer, k:ArrayLikeObject, sk:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution.\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n","random.strided.chi.seed":"\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n Length of generator seed.\n","random.strided.chi.state":"\nrandom.strided.chi.state\n Generator state.\n","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n Length of generator state.\n","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n","random.strided.chisquare":"\nrandom.strided.chisquare( N:integer, k:ArrayLikeObject, sk:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution.\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n Generator state.\n","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n Length of generator state.\n","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n","random.strided.cosine":"\nrandom.strided.cosine( N:integer, mu:ArrayLikeObject, sm:integer, \n s:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution.\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, s:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution.\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N:integer, a:ArrayLikeObject, \n sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n","random.strided.exponential":"\nrandom.strided.exponential( N:integer, lambda:ArrayLikeObject, sl:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution.\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N:integer, lambda:ArrayLikeObject, \n sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n Length of generator seed.\n","random.strided.exponential.state":"\nrandom.strided.exponential.state\n Generator state.\n","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n Length of generator state.\n","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n","random.strided.gamma":"\nrandom.strided.gamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution.\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n","random.strided.geometric":"\nrandom.strided.geometric( N:integer, p:ArrayLikeObject, sp:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution.\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n Length of generator seed.\n","random.strided.geometric.state":"\nrandom.strided.geometric.state\n Generator state.\n","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n Length of generator state.\n","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n","random.strided.invgamma":"\nrandom.strided.invgamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n","random.strided.lognormal":"\nrandom.strided.lognormal( N:integer, mu:ArrayLikeObject, sm:integer, \n sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution.\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n","random.strided.minstd":"\nrandom.strided.minstd( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N:integer, out:ArrayLikeObject, \n so:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.mt19937":"\nrandom.strided.mt19937( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive).\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.normal":"\nrandom.strided.normal( N:integer, mu:ArrayLikeObject, sm:integer, \n sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution.\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n","random.strided.poisson":"\nrandom.strided.poisson( N:integer, lambda:ArrayLikeObject, sl:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution.\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, \n ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n Length of generator seed.\n","random.strided.poisson.state":"\nrandom.strided.poisson.state\n Generator state.\n","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n Length of generator state.\n","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n","random.strided.randu":"\nrandom.strided.randu( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n","random.strided.rayleigh":"\nrandom.strided.rayleigh( N:integer, sigma:ArrayLikeObject, ss:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N:integer, sigma:ArrayLikeObject, ss:integer, \n os:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n Generator state.\n","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n","random.strided.t":"\nrandom.strided.t( N:integer, v:ArrayLikeObject, sv:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution.\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N:integer, v:ArrayLikeObject, sv:integer, ov:integer, \n out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n","random.strided.t.factory":"\nrandom.strided.t.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n","random.strided.t.seed":"\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n Length of generator seed.\n","random.strided.t.state":"\nrandom.strided.t.state\n Generator state.\n","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n Length of generator state.\n","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n","random.strided.uniform":"\nrandom.strided.uniform( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution.\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n","ranks":"\nranks( arr:Array[, options:Object] )\n Computes the sample ranks for the values of an array-like object.\n","readDir":"\nreadDir( path:string|Buffer, clbk:Function )\n Asynchronously reads the contents of a directory.\n","readDir.sync":"\nreadDir.sync( path:string|Buffer )\n Synchronously reads the contents of a directory.\n","readFile":"\nreadFile( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n Asynchronously reads the entire contents of a file.\n","readFile.sync":"\nreadFile.sync( file:string|Buffer|integer[, options:Object|string] )\n Synchronously reads the entire contents of a file.\n","readFileList":"\nreadFileList( filepaths:Array[, options:Object|string], clbk:Function )\n Asynchronously reads the entire contents of each file in a file list.\n","readFileList.sync":"\nreadFileList.sync( filepaths:Array[, options:Object|string] )\n Synchronously reads the entire contents of each file in a file list.\n","readJSON":"\nreadJSON( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n Asynchronously reads a file as JSON.\n","readJSON.sync":"\nreadJSON.sync( file:string|Buffer|integer[, options:Object|string] )\n Synchronously reads a file as JSON.\n","readWASM":"\nreadWASM( file:string|Buffer|integer[, options:Object], clbk:Function )\n Asynchronously reads a file as WebAssembly.\n","readWASM.sync":"\nreadWASM.sync( file:string|Buffer|integer[, options:Object] )\n Synchronously reads a file as WebAssembly.\n","real":"\nreal( z:Complex128 )\n Returns the real component of a double-precision complex floating-point\n number.\n","realarray":"\nrealarray( [dtype:string] )\n Creates a typed array.\n\nrealarray( length:integer[, dtype:string] )\n Returns a typed array having a specified length.\n\nrealarray( typedarray:TypedArray[, dtype:string] )\n Creates a typed array from another typed array.\n\nrealarray( obj:Object[, dtype:string] )\n Creates a typed array from an array-like object or iterable.\n\nrealarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a typed array view of an ArrayBuffer.\n","realarrayCtors":"\nrealarrayCtors( dtype:string )\n Returns a typed array constructor.\n","realarrayDataTypes":"\nrealarrayDataTypes()\n Returns a list of typed array real-valued data types.\n","realf":"\nrealf( z:Complex64 )\n Returns the real component of a single-precision complex floating-point\n number.\n","realmax":"\nrealmax( dtype:string )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n","realmin":"\nrealmin( dtype:string )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n","reBasename":"\nreBasename( [platform:string] )\n Returns a regular expression to capture the last part of a path.\n","reBasename.REGEXP":"\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n","reBasenamePosix":"\nreBasenamePosix()\n Returns a regular expression to capture the last part of a POSIX path.\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n","reBasenameWindows":"\nreBasenameWindows()\n Returns a regular expression to capture the last part of a Windows path.\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n","reColorHexadecimal":"\nreColorHexadecimal( [mode:string] )\n Returns a regular expression to match a hexadecimal color.\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n","reDecimalNumber":"\nreDecimalNumber( [options:Object] )\n Returns a regular expression to match a decimal number.\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n","reDirname":"\nreDirname( [platform:string] )\n Returns a regular expression to capture a path dirname.\n","reDirname.REGEXP":"\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n","reDirnamePosix":"\nreDirnamePosix()\n Returns a regular expression to capture a POSIX path dirname.\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n","reDirnameWindows":"\nreDirnameWindows()\n Returns a regular expression to capture a Windows path dirname.\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n","reduce":"\nreduce( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n thisArg:any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","reduce2d":"\nreduce2d( arr:ArrayLikeObject, initial:ArrayLikeObject, \n reducer:Function[, thisArg:any] )\n Reduces the number of dimensions by one of a two-dimensional nested array by\n applying a function against an accumulator and each element along the\n innermost dimension and returning the accumulation results as a one-\n dimensional array.\n","reduceAsync":"\nreduceAsync( collection:Array|TypedArray|Object, initial:any, [options:Object,] \n reducer:Function, done:Function )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n","reduceAsync.factory":"\nreduceAsync.factory( [options:Object,] fcn:Function )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n","reduceRight":"\nreduceRight( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n thisArg:any] )\n Applies a function against an accumulator and each element in an array while\n iterating from right to left and returns the accumulated result.\n","reduceRightAsync":"\nreduceRightAsync( collection:Array|TypedArray|Object, initial:any, \n [options:Object,] reducer:Function, done:Function )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n","reEOL":"\nreEOL( [options:Object] )\n Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP":"\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n","reExtendedLengthPath":"\nreExtendedLengthPath()\n Returns a regular expression to test if a string is an extended-length path.\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n","reExtname":"\nreExtname( [platform:string] )\n Returns a regular expression to capture a filename extension.\n","reExtname.REGEXP":"\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n","reExtnamePosix":"\nreExtnamePosix\n Returns a regular expression to capture a POSIX filename extension.\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n","reExtnameWindows":"\nreExtnameWindows\n Returns a regular expression to capture a Windows filename extension.\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n","reFilename":"\nreFilename( [platform:string] )\n Regular expression to split a filename.\n","reFilename.REGEXP":"\nreFilename.REGEXP\n Regular expression to split a filename.\n","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n","reFilenamePosix":"\nreFilenamePosix()\n Returns a regular expression to split a POSIX filename.\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n","reFilenameWindows":"\nreFilenameWindows()\n Returns a regular expression to split a Windows filename.\n","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n","reFromString":"\nreFromString( str:string )\n Parses a regular expression string and returns a new regular expression.\n","reFunctionName":"\nreFunctionName()\n Return a regular expression to capture a function name.\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n","regexp2json":"\nregexp2json( re:RegExp )\n Returns a JSON representation of a regular expression.\n","reim":"\nreim( z:Complex128 )\n Returns the real and imaginary components of a double-precision complex\n floating-point number.\n","reimf":"\nreimf( z:Complex64 )\n Returns the real and imaginary components of a single-precision complex\n floating-point number.\n","rejectArguments":"\nrejectArguments( fcn:Function, predicate:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n","removeFirst":"\nremoveFirst( str:string[, n:integer][, options:Object] )\n Removes the first character(s) of a `string`.\n","removeLast":"\nremoveLast( str:string[, n:integer][, options:Object] )\n Removes the last character(s) of a `string`.\n","removePunctuation":"\nremovePunctuation( str:string )\n Removes punctuation characters from a `string`.\n","removeUTF8BOM":"\nremoveUTF8BOM( str:string )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n","removeWords":"\nremoveWords( str:string, words:Array[, ignoreCase:boolean] )\n Removes all occurrences of the given words from a `string`.\n","rename":"\nrename( oldPath:string|Buffer, newPath:string|Buffer, clbk:Function )\n Asynchronously renames a file.\n","rename.sync":"\nrename.sync( oldPath:string|Buffer, newPath:string|Buffer )\n Synchronously renames a file.\n","reNativeFunction":"\nreNativeFunction()\n Returns a regular expression to match a native function.\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n","reorderArguments":"\nreorderArguments( fcn:Function, indices:Array[, thisArg:any] )\n Returns a function that invokes a provided function with reordered\n arguments.\n","repeat":"\nrepeat( str:string, n:integer )\n Repeats a string `n` times and returns the concatenated result.\n","replace":"\nreplace( str:string, search:string|RegExp, newval:string|Function )\n Replaces search occurrences with a replacement string.\n","reRegExp":"\nreRegExp()\n Returns a regular expression to parse a regular expression string.\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n","rescape":"\nrescape( str:string )\n Escapes a regular expression string.\n","reSemVer":"\nreSemVer()\n Returns a regular expression to match a semantic version string.\n","reSemVer.REGEXP":"\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n","resolveParentPath":"\nresolveParentPath( path:string[, options:Object], clbk:Function )\n Asynchronously resolves a path by walking parent directories.\n","resolveParentPath.sync":"\nresolveParentPath.sync( path:string[, options:Object] )\n Synchronously resolves a path by walking parent directories.\n","resolveParentPathBy":"\nresolveParentPathBy( path:string[, options:Object], predicate:Function, \n clbk:Function )\n Asynchronously resolves a path according to a predicate function by walking\n parent directories.\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path:string[, options:Object], predicate:Function )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n","reUncPath":"\nreUncPath()\n Return a regular expression to parse a UNC path.\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n Returns a regular expression to match a UTF-16 surrogate pair.\n","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n Returns a regular expression to match an unpaired UTF-16 surrogate.\n","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n","reverseArguments":"\nreverseArguments( fcn:Function[, thisArg:any] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n","reverseString":"\nreverseString( str:string[, options:Object] )\n Reverses a string.\n","reviveBasePRNG":"\nreviveBasePRNG( key:string, value:any )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n","reviveBuffer":"\nreviveBuffer( key:string, value:any )\n Revives a JSON-serialized Buffer.\n","reviveComplex":"\nreviveComplex( key:string, value:any )\n Revives a JSON-serialized complex number.\n","reviveComplex64":"\nreviveComplex64( key:string, value:any )\n Revives a JSON-serialized 64-bit complex number.\n","reviveComplex128":"\nreviveComplex128( key:string, value:any )\n Revives a JSON-serialized 128-bit complex number.\n","reviveError":"\nreviveError( key:string, value:any )\n Revives a JSON-serialized error object.\n","reviveRegExp":"\nreviveRegExp( key:string, value:any )\n Revives a JSON-serialized regular expression.\n","reviveTypedArray":"\nreviveTypedArray( key:string, value:any )\n Revives a JSON-serialized typed array.\n","reWhitespace":"\nreWhitespace( [options:Object] )\n Returns a regular expression to match a white space character.\n","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n","rpad":"\nrpad( str:string, len:integer[, pad:string] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n","rtrim":"\nrtrim( str:string )\n Trims whitespace from the end of a string.\n","safeintmax":"\nsafeintmax( dtype:string )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n","safeintmin":"\nsafeintmin( dtype:string )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n","sample":"\nsample( x:ArrayLike[, options:Object] )\n Samples elements from an array-like object.\n","sample.factory":"\nsample.factory( [pool:ArrayLike, ][options:Object] )\n Returns a function to sample elements from an array-like object.\n","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n","scalar2array":"\nscalar2array( value:any[, dtype:string] )\n Returns a single-element array containing a provided scalar value.\n","scalar2ndarray":"\nscalar2ndarray( value:any[, options:Object] )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n","sdot":"\nsdot( x:ndarray, y:ndarray )\n Computes the dot product of two single-precision floating-point vectors.\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n Number of seconds in a day.\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n Number of seconds in a week.\n","secondsInMonth":"\nsecondsInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of seconds in a month.\n","secondsInYear":"\nsecondsInYear( [value:integer|Date] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n","seq2slice":"\nseq2slice( str:string, len:integer, strict:boolean )\n Converts a subsequence string to a Slice object.\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a configurable read-only property.\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj:Object, prop:string|symbol, \n getter:Function )\n Defines a configurable read-only accessor.\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj:Object, prop:string|symbol, \n getter:Function, setter:Function )\n Defines a configurable property having read-write accessors.\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n setter:Function )\n Defines a configurable write-only accessor.\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n Defines a configurable memoized read-only object property.\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n Defines a memoized read-only object property.\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj:Object, prop:string|symbol, value:any )\n Defines a non-enumerable property.\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a non-enumerable read-only property.\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj:Object, prop:string|symbol, \n getter:Function )\n Defines a non-enumerable read-only accessor.\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj:Object, prop:string|symbol, \n getter:Function, setter:Function )\n Defines a non-enumerable property having read-write accessors.\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n setter:Function )\n Defines a non-enumerable write-only accessor.\n","setReadOnly":"\nsetReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a read-only property.\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function )\n Defines a read-only accessor.\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj:Object, prop:string|symbol, getter:Function, \n setter:Function )\n Defines a property having read-write accessors.\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj:Object, prop:string|symbol, setter:Function )\n Defines a write-only accessor.\n","SharedArrayBuffer":"\nSharedArrayBuffer( size:integer )\n Returns a shared array buffer having a specified number of bytes.\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n","shift":"\nshift( collection:Array|TypedArray|Object )\n Removes and returns the first element of a collection.\n","shuffle":"\nshuffle( arr:ArrayLike[, options:Object] )\n Shuffles elements of an array-like object.\n","shuffle.factory":"\nshuffle.factory( [options:Object] )\n Returns a function to shuffle elements of array-like objects.\n","sizeOf":"\nsizeOf( dtype:string )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n","Slice":"\nSlice( [stop:integer|null|undefined] )\n Returns a Slice.\n\nSlice( start:integer|null|undefined, stop:integer|null|undefined[, \n step:integer|null|undefined] )\n Returns a Slice.\n","Slice.prototype.start":"\nSlice.prototype.start\n Read-only property returning the starting slice index.\n","Slice.prototype.stop":"\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n","Slice.prototype.step":"\nSlice.prototype.step\n Read-only property returning the index increment.\n","Slice.prototype.toString":"\nSlice.prototype.toString()\n Serializes a Slice as a string.\n","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n","snakecase":"\nsnakecase( str:string )\n Converts a string to snake case.\n","some":"\nsome( collection:Array|TypedArray|Object, n:number )\n Tests whether at least `n` elements in a collection are truthy.\n","someBy":"\nsomeBy( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n thisArg:any ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n","someByAsync":"\nsomeByAsync( collection:Array|TypedArray|Object, n:number, [options:Object,] \n predicate:Function, done:Function )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n","someByAsync.factory":"\nsomeByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n","someByRight":"\nsomeByRight( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n thisArg:any ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n","someByRightAsync":"\nsomeByRightAsync( collection:Array|TypedArray|Object, n:number, \n [options:Object,] predicate:Function, done:Function )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n","SOTU":"\nSOTU( [options:Object] )\n Returns State of the Union (SOTU) addresses.\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n","SparklineBase":"\nSparklineBase( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a Sparkline instance.\n","sparsearray2iterator":"\nsparsearray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, \n thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n","splitStream":"\nsplitStream( [options:Object] )\n Returns a transform stream which splits streamed data.\n","splitStream.factory":"\nsplitStream.factory( [options:Object] )\n Returns a function for creating transform streams for splitting streamed\n data.\n","splitStream.objectMode":"\nsplitStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n","SQRT_EPS":"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n","SQRT_HALF":"\nSQRT_HALF\n Square root of `1/2`.\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n","SQRT_PHI":"\nSQRT_PHI\n Square root of the golden ratio.\n","SQRT_PI":"\nSQRT_PI\n Square root of the mathematical constant `π`.\n","SQRT_THREE":"\nSQRT_THREE\n Square root of `3`.\n","SQRT_TWO":"\nSQRT_TWO\n Square root of `2`.\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n Returns US birth data from 2000 to 2014, as provided by the Social Security\n Administration.\n","sswap":"\nsswap( x:ndarray, y:ndarray )\n Interchanges two single-precision floating-point vectors.\n","Stack":"\nStack()\n Stack constructor.\n","standalone2pkg":"\nstandalone2pkg( pkg:string )\n Returns the internal package name associated with a provided standalone\n package name.\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n Returns a string array containing two or three letter abbreviations for each\n card in a standard 52-card deck.\n","startcase":"\nstartcase( str:string )\n Capitalizes the first letter of each word in an input string.\n","startsWith":"\nstartsWith( str:string, search:string[, position:integer] )\n Tests if a string starts with the characters of another string.\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n Returns a list of English stop words.\n","strided.abs":"\nstrided.abs( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n offsetY:integer )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.abs2":"\nstrided.abs2( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.abs2By":"\nstrided.abs2By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n","strided.absBy":"\nstrided.absBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y`.\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n","strided.add":"\nstrided.add( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.add.ndarray":"\nstrided.add.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.cbrt":"\nstrided.cbrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y`.\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n","strided.ceil":"\nstrided.ceil( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y`.\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.deg2rad":"\nstrided.deg2rad( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y`.\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.dataTypes":"\nstrided.dataTypes()\n Returns a list of strided array data types.\n","strided.dispatch":"\nstrided.dispatch( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns a strided array function interface which performs multiple dispatch.\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns a strided array function interface which accepts a callback function\n and performs multiple dispatch.\n","strided.floor":"\nstrided.floor( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y`.\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.inv":"\nstrided.inv( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n offsetY:integer )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.mul":"\nstrided.mul( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.ramp":"\nstrided.ramp( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.rsqrt":"\nstrided.rsqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.sqrt":"\nstrided.sqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.sub":"\nstrided.sub( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.trunc":"\nstrided.trunc( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y`.\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n","stridedarray2iterator":"\nstridedarray2iterator( N:integer, src:ArrayLikeObject, stride:integer, \n offset:integer[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n","stridedArrayStream":"\nstridedArrayStream( N:integer, buffer:ArrayLikeObject, stride:integer, \n offset:integer[, options:Object] )\n Creates a readable stream from a strided array-like object.\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects.\n","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N:integer, buffer:ArrayLikeObject, \n stride:integer, offset:integer[, options:Object] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n","string2buffer":"\nstring2buffer( str:string[, encoding:string] )\n Allocates a buffer containing a provided string.\n","sub2ind":"\nsub2ind( shape:ArrayLike, ...subscript:integer[, options:Object] )\n Converts subscripts to a linear index.\n","substringAfter":"\nsubstringAfter( str:string, search:string[, fromIndex:integer] )\n Returns the part of a string after a specified substring.\n","substringAfterLast":"\nsubstringAfterLast( str:string, search:string[, fromIndex:integer] )\n Returns the part of a string after the last occurrence of a specified\n substring.\n","substringBefore":"\nsubstringBefore( str:string, search:string )\n Returns the part of a string before a specified substring.\n","substringBeforeLast":"\nsubstringBeforeLast( str:string, search:string )\n Returns the part of a string before the last occurrence of a specified\n substring.\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n","Symbol":"\nSymbol( [description:string] )\n Returns a symbol.\n","tabulate":"\ntabulate( collection:Array|TypedArray|Object )\n Generates a frequency table.\n","tabulateBy":"\ntabulateBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Generates a frequency table according to an indicator function.\n","tabulateByAsync":"\ntabulateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Generates a frequency table according to an indicator function.\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which generates a frequency table according to an\n indicator function.\n","thunk":"\nthunk( fcn:Function[, ...args:any] )\n Returns a thunk.\n","tic":"\ntic()\n Returns a high-resolution time.\n","timeit":"\ntimeit( code:string, [options:Object,] clbk:Function )\n Times a snippet.\n","tmpdir":"\ntmpdir()\n Returns the directory for storing temporary files.\n","toc":"\ntoc( time:Array )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n","tokenize":"\ntokenize( str:string[, keepWhitespace:boolean] )\n Tokenizes a string.\n","transformStream":"\ntransformStream( [options:Object] )\n Returns a transform stream.\n","transformStream.factory":"\ntransformStream.factory( [options:Object] )\n Returns a function for creating transform streams.\n","transformStream.objectMode":"\ntransformStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream.\n","transformStream.ctor":"\ntransformStream.ctor( [options:Object] )\n Returns a custom transform stream constructor.\n","trim":"\ntrim( str:string )\n Trims whitespace from the beginning and end of a `string`.\n","truncate":"\ntruncate( str:string, len:integer[, ending:string] )\n Truncates a string to a specified length.\n","truncateMiddle":"\ntruncateMiddle( str:string, len:integer[, seq:string] )\n Truncates a string in the middle to a specified length.\n","trycatch":"\ntrycatch( x:Function, y:any )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n","trycatchAsync":"\ntrycatchAsync( x:Function, y:any, done:Function )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n","tryFunction":"\ntryFunction( fcn:Function[, thisArg:any] )\n Wraps a function in a try/catch block.\n","tryRequire":"\ntryRequire( id:string )\n Wraps `require` in a `try/catch` block.\n","trythen":"\ntrythen( x:Function, y:Function )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n","trythenAsync":"\ntrythenAsync( x:Function, y:Function, done:Function )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n","ttest":"\nttest( x:Array[, y:Array][, options:Object] )\n Computes a one-sample or paired Student's t test.\n","ttest2":"\nttest2( x:Array, y:Array[, options:Object] )\n Computes a two-sample Student's t test.\n","TWO_PI":"\nTWO_PI\n The mathematical constant `π` times `2`.\n","typedarray":"\ntypedarray( [dtype:string] )\n Creates a typed array.\n\ntypedarray( length:integer[, dtype:string] )\n Returns a typed array having a specified length.\n\ntypedarray( typedarray:TypedArray[, dtype:string] )\n Creates a typed array from another typed array.\n\ntypedarray( obj:Object[, dtype:string] )\n Creates a typed array from an array-like object or iterable.\n\ntypedarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a typed array view of an ArrayBuffer.\n","typedarray2json":"\ntypedarray2json( arr:TypedArray )\n Returns a JSON representation of a typed array.\n","typedarrayCtors":"\ntypedarrayCtors( dtype:string )\n Returns a typed array constructor.\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n","typedarraypool":"\ntypedarraypool( [dtype:string] )\n Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool( length:integer[, dtype:string] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\ntypedarraypool( typedarray:TypedArray[, dtype:string] )\n Creates a pooled typed array from another typed array.\n\ntypedarraypool( obj:Object[, dtype:string] )\n Creates a pooled typed array from an array-like object.\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype:string] )\n Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool.malloc( length:integer[, dtype:string] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\ntypedarraypool.malloc( typedarray:TypedArray[, dtype:string] )\n Creates a pooled typed array from another typed array.\n\ntypedarraypool.malloc( obj:Object[, dtype:string] )\n Creates a pooled typed array from an array-like object.\n","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype:string] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\ntypedarraypool.calloc( length:integer[, dtype:string] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n","typedarraypool.free":"\ntypedarraypool.free( buf:TypedArray|ArrayBuffer )\n Frees a typed array or typed array buffer for use in a future allocation.\n","typedarraypool.clear":"\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n","typedarraypool.factory":"\ntypedarraypool.factory( [options:Object] )\n Creates a typed array pool.\n","typemax":"\ntypemax( dtype:string )\n Returns the maximum value of a specified numeric type.\n","typemin":"\ntypemin( dtype:string )\n Returns the minimum value of a specified numeric type.\n","typeOf":"\ntypeOf( value:any )\n Determines a value's type.\n","UINT8_MAX":"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n","Uint8Array":"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\nUint8Array( length:integer )\n Returns a typed array having a specified length.\n\nUint8Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint8Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint8Array.from":"\nUint8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint8Array.of":"\nUint8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8Array.name":"\nUint8Array.name\n Typed array constructor name.\n","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n Serializes an array as a string.\n","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Uint8ClampedArray":"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\nUint8ClampedArray( length:integer )\n Returns a typed array having a specified length.\n\nUint8ClampedArray( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint8ClampedArray( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint8ClampedArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n Typed array constructor name.\n","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement:number[, \n fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement:number[, \n fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n","UINT16_MAX":"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n","Uint16Array":"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\nUint16Array( length:integer )\n Returns a typed array having a specified length.\n\nUint16Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint16Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint16Array.from":"\nUint16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint16Array.of":"\nUint16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint16Array.name":"\nUint16Array.name\n Typed array constructor name.\n","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n Serializes an array as a string.\n","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","UINT32_MAX":"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n","Uint32Array":"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\nUint32Array( length:integer )\n Returns a typed array having a specified length.\n\nUint32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint32Array.from":"\nUint32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint32Array.of":"\nUint32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint32Array.name":"\nUint32Array.name\n Typed array constructor name.\n","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n Serializes an array as a string.\n","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","umask":"\numask( [mask:integer|string,] [options:Object] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n","uncapitalize":"\nuncapitalize( str:string )\n Lowercases the first character of a string.\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj:Object )\n Converts the first letter of each object key to lowercase.\n","uncurry":"\nuncurry( fcn:Function[, arity:integer, ][thisArg:any] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n","uncurryRight":"\nuncurryRight( fcn:Function[, arity:integer, ][thisArg:any] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n","UNICODE_MAX":"\nUNICODE_MAX\n Maximum Unicode code point.\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline column chart instance.\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline line chart instance.\n","UnicodeSparkline":"\nUnicodeSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a Unicode sparkline instance.\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline tristate chart instance.\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline up/down chart instance.\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline win/loss chart instance.\n","unlink":"\nunlink( path:string|Buffer|integer, clbk:Function )\n Asynchronously removes a directory entry.\n","unlink.sync":"\nunlink.sync( path:string|Buffer|integer )\n Synchronously removes a directory entry.\n","unshift":"\nunshift( collection:Array|TypedArray|Object, ...items:any )\n Adds one or more elements to the beginning of a collection.\n","until":"\nuntil( predicate:Function, fcn:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","untilAsync":"\nuntilAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","untilEach":"\nuntilEach( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n","untilEachRight":"\nuntilEachRight( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","unzip":"\nunzip( arr:Array[, idx:Array] )\n Unzips a zipped array (i.e., a nested array of tuples).\n","uppercase":"\nuppercase( str:string )\n Converts a string to uppercase.\n","uppercaseKeys":"\nuppercaseKeys( obj:Object )\n Converts each object key to uppercase.\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str:string )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n","vartest":"\nvartest( x:Array, y:Array[, options:Object] )\n Computes a two-sample F-test for equal variances.\n","waterfall":"\nwaterfall( fcns:Array, clbk:Function[, thisArg:any] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n","waterfall.factory":"\nwaterfall.factory( fcns:Array, clbk:Function[, thisArg:any] )\n Returns a reusable waterfall function.\n","whileAsync":"\nwhileAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","whileEach":"\nwhileEach( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection.\n","whileEachRight":"\nwhileEachRight( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","whilst":"\nwhilst( predicate:Function, fcn:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","wilcoxon":"\nwilcoxon( x:Array|TypedArray[, y:Array|TypedArray][, options:Object] )\n Computes a one-sample or paired Wilcoxon signed rank test.\n","writableProperties":"\nwritableProperties( value:any )\n Returns an array of an object's own writable property names and symbols.\n","writablePropertiesIn":"\nwritablePropertiesIn( value:any )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n","writablePropertyNames":"\nwritablePropertyNames( value:any )\n Returns an array of an object's own writable property names.\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value:any )\n Returns an array of an object's own and inherited writable property names.\n","writablePropertySymbols":"\nwritablePropertySymbols( value:any )\n Returns an array of an object's own writable symbol properties.\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited writable symbol\n properties.\n","writeFile":"\nwriteFile( file:string|Buffer|integer, data:string|Buffer[, \n options:Object|string], clbk:Function )\n Asynchronously writes data to a file.\n","writeFile.sync":"\nwriteFile.sync( file:string|Buffer|integer, data:string|Buffer[, \n options:Object|string] )\n Synchronously writes data to a file.\n","zip":"\nzip( ...arr:Array[, options:Object] )\n Generates array tuples from input arrays.\n","ztest":"\nztest( x:Array, sigma:number[, options:Object] )\n Computes a one-sample z-test.\n","ztest2":"\nztest2( x:Array, y:Array, sigmax:number, sigmay:number[, \n options:Object] )\n Computes a two-sample z-test.\n"} \ No newline at end of file diff --git a/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/README.md b/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/README.md deleted file mode 100644 index 0314025fec2e..000000000000 --- a/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/README.md +++ /dev/null @@ -1,95 +0,0 @@ - - -# lastGraphemeCluster - -> Return the last `n` grapheme clusters (i.e., user-perceived characters) of a string. - -
- -## Usage - -```javascript -var lastGraphemeCluster = require( '@stdlib/string/base/last-grapheme-cluster' ); -``` - -#### lastGraphemeCluster( str, n ) - -Returns the last `n` grapheme clusters (i.e., user-perceived characters) of a string. - -```javascript -var out = lastGraphemeCluster( 'Hello World', 1 ); -// returns 'd' - -out = lastGraphemeCluster( 'Evening', 3 ); -// returns 'ing' - -out = lastGraphemeCluster( 'foo bar', 10 ); -// returns 'foo bar' -``` - -
- - - -
- -## Examples - - - -```javascript -var lastGraphemeCluster = require( '@stdlib/string/base/last-grapheme-cluster' ); - -var str = lastGraphemeCluster( 'Hello World!', 1 ); -// returns '!' - -str = lastGraphemeCluster( 'JavaScript', 6 ); -// returns 'Script' - -str = lastGraphemeCluster( 'stdlib', 10 ); -// returns 'stdlib' - -str = lastGraphemeCluster( '🐶🐮🐷🐰🐸', 2 ); -// returns '🐰🐸' - -str = lastGraphemeCluster( '六书/六書', 2 ); -// returns '六書' -``` - -
- - - - - -
- -
- - - - - -
- -
- - diff --git a/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/benchmark/benchmark.js b/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/benchmark/benchmark.js deleted file mode 100644 index 677642f35e65..000000000000 --- a/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/benchmark/benchmark.js +++ /dev/null @@ -1,58 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var bench = require( '@stdlib/bench' ); -var isString = require( '@stdlib/assert/is-string' ).isPrimitive; -var pkg = require( './../package.json' ).name; -var last = require( './../lib' ); - - -// MAIN // - -bench( pkg, function benchmark( b ) { - var values; - var out; - var i; - - values = [ - 'beep boop', - 'foo bar', - '六書', - 'xyz abc', - '🐶🐮🐷🐰🐸', - '🌷🌷🌷🌷🌷' - ]; - - b.tic(); - for ( i = 0; i < b.iterations; i++ ) { - out = last( values[ i%values.length ], 1 ); - if ( typeof out !== 'string' ) { - b.fail( 'should return a string' ); - } - } - b.toc(); - if ( !isString( out ) ) { - b.fail( 'should return a string' ); - } - b.pass( 'benchmark finished' ); - b.end(); -}); diff --git a/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/docs/repl.txt b/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/docs/repl.txt deleted file mode 100644 index 50e902a51c40..000000000000 --- a/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/docs/repl.txt +++ /dev/null @@ -1,30 +0,0 @@ - -{{alias}}( str, n ) - Returns the last `n` grapheme clusters (i.e., user-perceived characters) of - a string. - - Parameters - ---------- - str: string - Input string. - - n: integer - Number of grapheme clusters to return. - - Returns - ------- - out: string - Output string. - - Examples - -------- - > var out = {{alias}}( 'beep', 1 ) - 'p' - > out = {{alias}}( 'Boop', 2 ) - 'op' - > out = {{alias}}( 'JavaScript', 6 ) - 'Script' - - See Also - -------- - diff --git a/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/docs/types/index.d.ts b/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/docs/types/index.d.ts deleted file mode 100644 index 2009262f6545..000000000000 --- a/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/docs/types/index.d.ts +++ /dev/null @@ -1,53 +0,0 @@ -/* -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -// TypeScript Version: 4.1 - -/** -* Returns the last `n` grapheme clusters (i.e., user-perceived characters) of a string. -* -* @param str - input string -* @param n - number of grapheme clusters to return -* @returns output string -* -* @example -* var out = last( 'Hello World', 1 ); -* // returns 'd' -* -* @example -* var out = last( 'Evening', 3 ); -* // returns 'ing' -* -* @example -* var out = last( 'JavaScript', 6 ); -* // returns 'Script' -* -* @example -* var out = last( '🐶🐮🐷🐰🐸', 2 ); -* // returns '🐰🐸' -* -* @example -* var out = last( 'foo bar', 5 ); -* // returns 'o bar' -*/ -declare function last( str: string, n: number ): string; - - -// EXPORTS // - -export = last; diff --git a/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/docs/types/test.ts b/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/docs/types/test.ts deleted file mode 100644 index 310a416d4bc1..000000000000 --- a/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/docs/types/test.ts +++ /dev/null @@ -1,57 +0,0 @@ -/* -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -import last = require( './index' ); - - -// TESTS // - -// The function returns a string... -{ - last( 'abc', 1 ); // $ExpectType string -} - -// The compiler throws an error if the function is provided a value other than a string... -{ - last( true, 1 ); // $ExpectError - last( false, 1 ); // $ExpectError - last( null, 1 ); // $ExpectError - last( undefined, 1 ); // $ExpectError - last( 5, 1 ); // $ExpectError - last( [], 1 ); // $ExpectError - last( {}, 1 ); // $ExpectError - last( ( x: number ): number => x, 1 ); // $ExpectError -} - -// The compiler throws an error if the function is provided a second argument that is not a number... -{ - last( 'abc', true ); // $ExpectError - last( 'abc', false ); // $ExpectError - last( 'abc', null ); // $ExpectError - last( 'abc', 'abc' ); // $ExpectError - last( 'abc', [] ); // $ExpectError - last( 'abc', {} ); // $ExpectError - last( 'abc', ( x: number ): number => x ); // $ExpectError -} - -// The compiler throws an error if the function is provided an unsupported number of arguments... -{ - last(); // $ExpectError - last( 'abc' ); // $ExpectError - last( 'abc', 1, 2 ); // $ExpectError -} diff --git a/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/examples/index.js b/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/examples/index.js deleted file mode 100644 index db262395aca5..000000000000 --- a/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/examples/index.js +++ /dev/null @@ -1,36 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -var lastGraphemeCluster = require( './../lib' ); - -console.log( lastGraphemeCluster( 'Hello World!', 1 ) ); -// => '!' - -console.log( lastGraphemeCluster( 'JavaScript', 6 ) ); -// => 'Script' - -console.log( lastGraphemeCluster( 'stdlib', 10 ) ); -// => 'stdlib' - -console.log( lastGraphemeCluster( '🐶🐮🐷🐰🐸', 2 ) ); -// => '🐰🐸' - -console.log( lastGraphemeCluster( '六书/六書', 2 ) ); -// => '六書' diff --git a/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/lib/main.js b/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/lib/main.js deleted file mode 100644 index 02ac01944877..000000000000 --- a/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/lib/main.js +++ /dev/null @@ -1,105 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var nextGraphemeClusterBreak = require( '@stdlib/string/next-grapheme-cluster-break' ); -var CircularBuffer = require( '@stdlib/utils/circular-buffer' ); -var zeros = require( '@stdlib/array/base/zeros' ); - - -// MAIN // - -/** -* Returns the last `n` grapheme clusters (i.e., user-perceived characters) of a string. -* -* @param {string} str - input string -* @param {NonNegativeInteger} n - number of grapheme clusters to return -* @returns {string} output string -* -* @example -* var out = last( 'Hello World', 1 ); -* // returns 'd' -* -* @example -* var out = last( 'Evening', 3 ); -* // returns 'ing' -* -* @example -* var out = last( 'JavaScript', 6 ); -* // returns 'Script' -* -* @example -* var out = last( '六书/六書', 1 ); -* // returns '書' -* -* @example -* var out = last( '🐶🐮🐷🐰🐸', 2 ); -* // returns '🐰🐸' -*/ -function last( str, n ) { - var count; - var cbuf; - var buf; - var i; - - if ( n === 0 || str === '' ) { - return ''; - } - // Resolve the first cluster break: - i = nextGraphemeClusterBreak( str, 0 ); - - // If we received a sentinel value, return the input string, as there are no more cluster breaks to iterate over... - if ( i === -1 ) { - return str; - } - // Initialize a buffer for keeping track of cluster break indices: - buf = zeros( n ); - - // Wrap the buffer to create a circular buffer serving as a FIFO stack where we can keep at most `n` indices as we iterate from left-to-right: - cbuf = new CircularBuffer( buf ); - - // Add the first character index: - cbuf.push( 0 ); - - // Add the index of the first grapheme cluster break to our buffer: - cbuf.push( i ); - - // Slide a window over the string from left-to-right... - count = 0; - while ( true ) { - count += 1; - i = nextGraphemeClusterBreak( str, i ); - if ( i === -1 ) { - break; - } - cbuf.push( i ); - } - // Resolve the leftmost index: - i = buf[ (count+1)%n ]; // count+1 as count%n corresponds to the index of the "newest" element in the circular buffer and count+1 is the next element to replace (i.e., the "oldest" index) - - // Return the last `n` grapheme clusters: - return str.substring( i ); -} - - -// EXPORTS // - -module.exports = last; diff --git a/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/test/test.js b/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/test/test.js deleted file mode 100644 index 328eb89376bb..000000000000 --- a/lib/node_modules/@stdlib/string/base/last-grapheme-cluster/test/test.js +++ /dev/null @@ -1,129 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var last = require( './../lib' ); - - -// TESTS // - -tape( 'main export is a function', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof last, 'function', 'main export is a function' ); - t.end(); -}); - -tape( 'the function returns an empty string if provided an empty string', function test( t ) { - t.strictEqual( last( '', 1 ), '', 'returns expected value' ); - t.strictEqual( last( '', 2 ), '', 'returns expected value' ); - t.strictEqual( last( '', 3 ), '', 'returns expected value' ); - t.end(); -}); - -tape( 'the function returns an empty string if provided zero as the second argument', function test( t ) { - t.strictEqual( last( 'hello world', 0 ), '', 'returns expected value' ); - t.end(); -}); - -tape( 'the function returns the last grapheme cluster of a provided string (ascii)', function test( t ) { - var out; - - out = last( 'hello world', 1 ); - t.strictEqual( out, 'd', 'returns expected value' ); - - out = last( 'h', 1 ); - t.strictEqual( out, 'h', 'returns expected value' ); - - out = last( '!!!', 1 ); - t.strictEqual( out, '!', 'returns expected value' ); - - out = last( 'JavaScript', 1 ); - t.strictEqual( out, 't', 'returns expected value' ); - - t.end(); -}); - -tape( 'the function returns the last grapheme cluster of a provided string (Unicode)', function test( t ) { - var out; - - out = last( 'अनुच्छेद', 1 ); - t.strictEqual( out, 'द', 'returns expected value' ); - - out = last( '六书/六書', 1 ); - t.strictEqual( out, '書', 'returns expected value' ); - - out = last( '書', 1 ); - t.strictEqual( out, '書', 'returns expected value' ); - - t.end(); -}); - -tape( 'the function returns the last grapheme cluster of a provided string (emoji)', function test( t ) { - var out; - - out = last( '🌷', 1 ); - t.strictEqual( out, '🌷', 'returns expected value' ); - - out = last( '🏝️🌷', 1 ); - t.strictEqual( out, '🌷', 'returns expected value' ); - - t.end(); -}); - -tape( 'the function supports returning the last `n` grapheme clusters of a provided string', function test( t ) { - var out; - - out = last( 'hello world', 1 ); - t.strictEqual( out, 'd', 'returns expected value' ); - - out = last( 'hello world', 7 ); - t.strictEqual( out, 'o world', 'returns expected value' ); - - out = last( 'JavaScript', 15 ); - t.strictEqual( out, 'JavaScript', 'returns expected value' ); - - out = last( '!!!', 1 ); - t.strictEqual( out, '!', 'returns expected value' ); - - out = last( '!!!', 2 ); - t.strictEqual( out, '!!', 'returns expected value' ); - - out = last( 'अनुच्छेद', 1 ); - t.strictEqual( out, 'द', 'returns expected value' ); - - out = last( 'अनुच्छेद+o', 3 ); - t.strictEqual( out, 'द+o', 'returns expected value' ); - - out = last( '六书/六書', 2 ); - t.strictEqual( out, '六書', 'returns expected value' ); - - out = last( '六书/六書()!', 4 ); - t.strictEqual( out, '書()!', 'returns expected value' ); - - out = last( '六书/六書', 10 ); - t.strictEqual( out, '六书/六書', 'returns expected value' ); - - out = last( '🌷🌷🌷🌷🌷', 2 ); - t.strictEqual( out, '🌷🌷', 'returns expected value' ); - - t.end(); -}); diff --git a/lib/node_modules/@stdlib/utils/any-in-by/README.md b/lib/node_modules/@stdlib/utils/any-in-by/README.md index 61ae4e2da7df..a774899a3be1 100644 --- a/lib/node_modules/@stdlib/utils/any-in-by/README.md +++ b/lib/node_modules/@stdlib/utils/any-in-by/README.md @@ -137,6 +137,7 @@ var mean = context.sum / context.count; + diff --git a/lib/node_modules/@stdlib/utils/any-own-by/package.json b/lib/node_modules/@stdlib/utils/any-own-by/package.json index a007e3b22ed7..8fdc7bf41d92 100644 --- a/lib/node_modules/@stdlib/utils/any-own-by/package.json +++ b/lib/node_modules/@stdlib/utils/any-own-by/package.json @@ -1,70 +1,71 @@ { - "name": "@stdlib/utils/any-own-by", - "version": "0.0.0", - "description": "Test whether whether any 'own' property of a provided object satisfies a predicate function.", - "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { + "name": "@stdlib/utils/any-own-by", + "version": "0.0.0", + "description": "Test whether whether any 'own' property of a provided object satisfies a predicate function.", + "license": "Apache-2.0", + "author": { "name": "The Stdlib Authors", "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "directories": { - "doc": "./docs", - "example": "./examples", - "lib": "./lib", - "test": "./test" - }, - "types": "./docs/types", - "scripts": {}, - "homepage": "https://github.com/stdlib-js/stdlib", - "repository": { - "type": "git", - "url": "git://github.com/stdlib-js/stdlib.git" - }, - "bugs": { - "url": "https://github.com/stdlib-js/stdlib/issues" - }, - "dependencies": {}, - "devDependencies": {}, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], - "keywords": [ - "stdlib", - "stdutils", - "stdutil", - "utilities", - "utility", - "utils", - "util", - "test", - "predicate", - "any", - "iterate", - "object", - "property", - "properties", - "props", - "keys", - "obj", - "validate" - ] -} + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdutils", + "stdutil", + "utilities", + "utility", + "utils", + "util", + "test", + "predicate", + "any", + "iterate", + "object", + "property", + "properties", + "props", + "keys", + "obj", + "validate" + ] + } \ No newline at end of file diff --git a/tools/make/lib/install/addons.mk b/tools/make/lib/install/addons.mk index 9aaee2253556..8f7015d89301 100644 --- a/tools/make/lib/install/addons.mk +++ b/tools/make/lib/install/addons.mk @@ -55,35 +55,12 @@ install_node_addons_list_addons_flags := "--pattern $(node_addons_pattern)" # # ## Notes # -# - When `FAST_FAIL` is `0`, if unable to install a native add-on, the recipe prints an error message and proceeds to try installing the next add-on. -# -# @param {integer} [FAST_FAIL] - flag indicating whether to immediately exit if unable to install a native add-on (default: 1) +# - If unable to install a native add-on, the target prints an error message and proceeds to try installing the next add-on. # # @example # make install-node-addons -# -# @example -# FAST_FAIL=0 make install-node-addons -# -# @example -# FAST_FAIL=1 make install-node-addons #/ install-node-addons: $(NODE_MODULES) clean-node-addons -ifeq ($(FAIL_FAST), true) - $(QUIET) $(MAKE) LIST_PKGS_ADDONS_FLAGS=$(install_node_addons_list_addons_flags) -f $(this_file) list-pkgs-addons | while read -r pkg; do \ - if echo "$$pkg" | grep -v '^\/.*\|^[a-zA-Z]:.*' >/dev/null; then \ - continue; \ - fi; \ - echo ''; \ - echo "Building add-on: $$pkg"; \ - cd $$pkg && \ - MAKEFLAGS= \ - NODE_PATH="$(NODE_PATH)" \ - GYP_DEFINES="$(NODE_GYP_DEFINES)" \ - $(NODE_GYP) $(NODE_GYP_FLAGS) rebuild \ - || { echo "Error: failed to build add-on: $$pkg"; exit 1; } \ - done -else $(QUIET) $(MAKE) LIST_PKGS_ADDONS_FLAGS=$(install_node_addons_list_addons_flags) -f $(this_file) list-pkgs-addons | while read -r pkg; do \ if echo "$$pkg" | grep -v '^\/.*\|^[a-zA-Z]:.*' >/dev/null; then \ continue; \ @@ -97,41 +74,16 @@ else $(NODE_GYP) $(NODE_GYP_FLAGS) rebuild \ || { echo "Error: failed to build add-on: $$pkg"; exit 0; } \ done -endif .PHONY: install-node-addons #/ # Removes all compiled and generated files for Node.js native add-ons. # -# ## Notes -# -# - When `FAST_FAIL` is `0`, if unable to clean a native add-on, the recipe prints an error message and proceeds to try cleaning the next add-on. -# -# @param {integer} [FAST_FAIL] - flag indicating whether to immediately exit if unable to clean a native add-on (default: 1) -# # @example # make clean-node-addons -# -# @example -# FAST_FAIL=0 make clean-node-addons -# -# @example -# FAST_FAIL=1 make clean-node-addons #/ -clean-node-addons: $(NODE_MODULES) -ifeq ($(FAIL_FAST), true) - $(QUIET) $(MAKE) LIST_PKGS_ADDONS_FLAGS=$(install_node_addons_list_addons_flags) -f $(this_file) list-pkgs-addons | while read -r pkg; do \ - if echo "$$pkg" | grep -v '^\/.*\|^[a-zA-Z]:.*' >/dev/null; then \ - continue; \ - fi; \ - echo ''; \ - echo "Cleaning add-on: $$pkg"; \ - cd $$pkg/src && $(MAKE) clean && \ - cd $$pkg && $(NODE_GYP) clean \ - || { echo "Error: failed to clean add-on: $$pkg"; exit 1; } \ - done -else +clean-node-addons: $(QUIET) $(MAKE) LIST_PKGS_ADDONS_FLAGS=$(install_node_addons_list_addons_flags) -f $(this_file) list-pkgs-addons | while read -r pkg; do \ if echo "$$pkg" | grep -v '^\/.*\|^[a-zA-Z]:.*' >/dev/null; then \ continue; \ @@ -142,6 +94,5 @@ else cd $$pkg && $(NODE_GYP) clean \ || { echo "Error: failed to clean add-on: $$pkg"; exit 0; } \ done -endif .PHONY: clean-node-addons